id	sid	tid	token	lemma	pos
ajst-15595	1	1	academic	academic	ADJ
ajst-15595	1	2	journal	journal	NOUN
ajst-15595	1	3	of	of	ADP
ajst-15595	1	4	science	science	NOUN
ajst-15595	1	5	and	and	CCONJ
ajst-15595	1	6	technology	technology	NOUN
ajst-15595	1	7	issn	issn	NOUN
ajst-15595	1	8	:	:	PUNCT
ajst-15595	1	9	2771	2771	NUM
ajst-15595	1	10	-	-	SYM
ajst-15595	1	11	3032	3032	NUM
ajst-15595	1	12	|	|	NOUN
ajst-15595	1	13	vol	vol	NOUN
ajst-15595	1	14	.	.	PROPN
ajst-15595	1	15	8	8	NUM
ajst-15595	1	16	,	,	PUNCT
ajst-15595	1	17	no	no	INTJ
ajst-15595	1	18	.	.	NOUN
ajst-15595	1	19	3	3	NUM
ajst-15595	1	20	,	,	PUNCT
ajst-15595	1	21	2023	2023	NUM
ajst-15595	1	22	172	172	NUM
ajst-15595	1	23	quantile	quantile	ADJ
ajst-15595	1	24	regression	regression	NOUN
ajst-15595	1	25	model	model	NOUN
ajst-15595	1	26	and	and	CCONJ
ajst-15595	1	27	its	its	PRON
ajst-15595	1	28	application	application	NOUN
ajst-15595	1	29	research	research	NOUN
ajst-15595	1	30	mengfan	mengfan	NOUN
ajst-15595	1	31	xu1	xu1	PROPN
ajst-15595	1	32	,	,	PUNCT
ajst-15595	1	33	*	*	PROPN
ajst-15595	1	34	1department	1department	NUM
ajst-15595	1	35	of	of	ADP
ajst-15595	1	36	statistics	statistic	NOUN
ajst-15595	1	37	and	and	CCONJ
ajst-15595	1	38	applied	applied	ADJ
ajst-15595	1	39	mathematics	mathematic	NOUN
ajst-15595	1	40	,	,	PUNCT
ajst-15595	1	41	anhui	anhui	PROPN
ajst-15595	1	42	university	university	PROPN
ajst-15595	1	43	of	of	ADP
ajst-15595	1	44	finance	finance	NOUN
ajst-15595	1	45	and	and	CCONJ
ajst-15595	1	46	economics	economic	NOUN
ajst-15595	1	47	,	,	PUNCT
ajst-15595	1	48	bengbu	bengbu	NOUN
ajst-15595	1	49	233000	233000	NUM
ajst-15595	1	50	,	,	PUNCT
ajst-15595	1	51	china	china	PROPN
ajst-15595	1	52	*	*	PUNCT
ajst-15595	1	53	corresponding	correspond	VERB
ajst-15595	1	54	author	author	NOUN
ajst-15595	1	55	:	:	PUNCT
ajst-15595	2	1	mengfan	mengfan	PROPN
ajst-15595	2	2	xu	xu	PROPN
ajst-15595	2	3	(	(	PUNCT
ajst-15595	2	4	email	email	NOUN
ajst-15595	2	5	:	:	PUNCT
ajst-15595	2	6	1181797479@qq.com	1181797479@qq.com	NUM
ajst-15595	2	7	)	)	PUNCT
ajst-15595	2	8	abstract	abstract	NOUN
ajst-15595	2	9	:	:	PUNCT
ajst-15595	2	10	quantile	quantile	ADJ
ajst-15595	2	11	regression	regression	NOUN
ajst-15595	2	12	is	be	AUX
ajst-15595	2	13	a	a	DET
ajst-15595	2	14	regression	regression	NOUN
ajst-15595	2	15	analysis	analysis	NOUN
ajst-15595	2	16	method	method	NOUN
ajst-15595	2	17	that	that	PRON
ajst-15595	2	18	estimates	estimate	VERB
ajst-15595	2	19	the	the	DET
ajst-15595	2	20	parameters	parameter	NOUN
ajst-15595	2	21	of	of	ADP
ajst-15595	2	22	a	a	DET
ajst-15595	2	23	model	model	NOUN
ajst-15595	2	24	by	by	ADP
ajst-15595	2	25	minimizing	minimize	VERB
ajst-15595	2	26	the	the	DET
ajst-15595	2	27	weighted	weighted	ADJ
ajst-15595	2	28	sum	sum	NOUN
ajst-15595	2	29	of	of	ADP
ajst-15595	2	30	absolute	absolute	ADJ
ajst-15595	2	31	residuals	residual	NOUN
ajst-15595	2	32	.	.	PUNCT
ajst-15595	3	1	it	it	PRON
ajst-15595	3	2	was	be	AUX
ajst-15595	3	3	introduced	introduce	VERB
ajst-15595	3	4	by	by	ADP
ajst-15595	3	5	roger	roger	PROPN
ajst-15595	3	6	koenker	koenker	PROPN
ajst-15595	3	7	in	in	ADP
ajst-15595	3	8	1978	1978	NUM
ajst-15595	3	9	.	.	PUNCT
ajst-15595	4	1	as	as	ADP
ajst-15595	4	2	a	a	DET
ajst-15595	4	3	complementary	complementary	ADJ
ajst-15595	4	4	and	and	CCONJ
ajst-15595	4	5	extended	extended	ADJ
ajst-15595	4	6	approach	approach	NOUN
ajst-15595	4	7	to	to	ADP
ajst-15595	4	8	the	the	DET
ajst-15595	4	9	traditional	traditional	ADJ
ajst-15595	4	10	regression	regression	NOUN
ajst-15595	4	11	method	method	NOUN
ajst-15595	4	12	,	,	PUNCT
ajst-15595	4	13	namely	namely	ADV
ajst-15595	4	14	least	least	ADJ
ajst-15595	4	15	squares	square	NOUN
ajst-15595	4	16	method	method	NOUN
ajst-15595	4	17	,	,	PUNCT
ajst-15595	4	18	quantile	quantile	ADJ
ajst-15595	4	19	regression	regression	NOUN
ajst-15595	4	20	addresses	address	VERB
ajst-15595	4	21	the	the	DET
ajst-15595	4	22	limitations	limitation	NOUN
ajst-15595	4	23	of	of	ADP
ajst-15595	4	24	least	least	ADJ
ajst-15595	4	25	squares	square	NOUN
ajst-15595	4	26	method	method	NOUN
ajst-15595	4	27	in	in	ADP
ajst-15595	4	28	the	the	DET
ajst-15595	4	29	presence	presence	NOUN
ajst-15595	4	30	of	of	ADP
ajst-15595	4	31	heteroscedasticity	heteroscedasticity	NOUN
ajst-15595	4	32	and	and	CCONJ
ajst-15595	4	33	ensures	ensure	VERB
ajst-15595	4	34	the	the	DET
ajst-15595	4	35	robustness	robustness	NOUN
ajst-15595	4	36	of	of	ADP
ajst-15595	4	37	quantile	quantile	ADJ
ajst-15595	4	38	regression	regression	NOUN
ajst-15595	4	39	through	through	ADP
ajst-15595	4	40	its	its	PRON
ajst-15595	4	41	robustness	robustness	NOUN
ajst-15595	4	42	to	to	ADP
ajst-15595	4	43	outliers	outlier	NOUN
ajst-15595	4	44	,	,	PUNCT
ajst-15595	4	45	which	which	PRON
ajst-15595	4	46	compensates	compensate	VERB
ajst-15595	4	47	for	for	ADP
ajst-15595	4	48	the	the	DET
ajst-15595	4	49	weakness	weakness	NOUN
ajst-15595	4	50	of	of	ADP
ajst-15595	4	51	least	least	ADJ
ajst-15595	4	52	squares	square	NOUN
ajst-15595	4	53	method	method	NOUN
ajst-15595	4	54	in	in	ADP
ajst-15595	4	55	dealing	deal	VERB
ajst-15595	4	56	with	with	ADP
ajst-15595	4	57	outlier	outlier	ADJ
ajst-15595	4	58	data	datum	NOUN
ajst-15595	4	59	.	.	PUNCT
ajst-15595	5	1	in	in	ADP
ajst-15595	5	2	practical	practical	ADJ
ajst-15595	5	3	applications	application	NOUN
ajst-15595	5	4	,	,	PUNCT
ajst-15595	5	5	quantile	quantile	ADJ
ajst-15595	5	6	regression	regression	NOUN
ajst-15595	5	7	can	can	AUX
ajst-15595	5	8	provide	provide	VERB
ajst-15595	5	9	a	a	DET
ajst-15595	5	10	more	more	ADV
ajst-15595	5	11	comprehensive	comprehensive	ADJ
ajst-15595	5	12	reflection	reflection	NOUN
ajst-15595	5	13	of	of	ADP
ajst-15595	5	14	data	datum	NOUN
ajst-15595	5	15	information	information	NOUN
ajst-15595	5	16	and	and	CCONJ
ajst-15595	5	17	capture	capture	VERB
ajst-15595	5	18	the	the	DET
ajst-15595	5	19	tails	tail	NOUN
ajst-15595	5	20	of	of	ADP
ajst-15595	5	21	the	the	DET
ajst-15595	5	22	distribution	distribution	NOUN
ajst-15595	5	23	of	of	ADP
ajst-15595	5	24	the	the	DET
ajst-15595	5	25	dependent	dependent	ADJ
ajst-15595	5	26	variable	variable	NOUN
ajst-15595	5	27	,	,	PUNCT
ajst-15595	5	28	thus	thus	ADV
ajst-15595	5	29	overcoming	overcome	VERB
ajst-15595	5	30	the	the	DET
ajst-15595	5	31	limitation	limitation	NOUN
ajst-15595	5	32	of	of	ADP
ajst-15595	5	33	least	least	ADJ
ajst-15595	5	34	squares	square	NOUN
ajst-15595	5	35	method	method	NOUN
ajst-15595	5	36	that	that	PRON
ajst-15595	5	37	can	can	AUX
ajst-15595	5	38	only	only	ADV
ajst-15595	5	39	estimate	estimate	VERB
ajst-15595	5	40	the	the	DET
ajst-15595	5	41	central	central	ADJ
ajst-15595	5	42	tendency	tendency	NOUN
ajst-15595	5	43	of	of	ADP
ajst-15595	5	44	the	the	DET
ajst-15595	5	45	dependent	dependent	ADJ
ajst-15595	5	46	variable	variable	ADJ
ajst-15595	5	47	distribution	distribution	NOUN
ajst-15595	5	48	.	.	PUNCT
ajst-15595	6	1	moreover	moreover	ADV
ajst-15595	6	2	,	,	PUNCT
ajst-15595	6	3	quantile	quantile	ADJ
ajst-15595	6	4	regression	regression	NOUN
ajst-15595	6	5	provides	provide	VERB
ajst-15595	6	6	more	more	ADJ
ajst-15595	6	7	reasonable	reasonable	ADJ
ajst-15595	6	8	interpretations	interpretation	NOUN
ajst-15595	6	9	and	and	CCONJ
ajst-15595	6	10	prevents	prevent	VERB
ajst-15595	6	11	biased	biased	ADJ
ajst-15595	6	12	or	or	CCONJ
ajst-15595	6	13	even	even	ADV
ajst-15595	6	14	erroneous	erroneous	ADJ
ajst-15595	6	15	estimations	estimation	NOUN
ajst-15595	6	16	that	that	PRON
ajst-15595	6	17	can	can	AUX
ajst-15595	6	18	occur	occur	VERB
ajst-15595	6	19	when	when	SCONJ
ajst-15595	6	20	using	use	VERB
ajst-15595	6	21	least	least	ADJ
ajst-15595	6	22	squares	square	NOUN
ajst-15595	6	23	method	method	NOUN
ajst-15595	6	24	.	.	PUNCT
ajst-15595	7	1	overall	overall	ADJ
ajst-15595	7	2	,	,	PUNCT
ajst-15595	7	3	quantile	quantile	ADJ
ajst-15595	7	4	regression	regression	NOUN
ajst-15595	7	5	offers	offer	VERB
ajst-15595	7	6	a	a	DET
ajst-15595	7	7	novel	novel	ADJ
ajst-15595	7	8	regression	regression	NOUN
ajst-15595	7	9	method	method	NOUN
ajst-15595	7	10	that	that	PRON
ajst-15595	7	11	addresses	address	VERB
ajst-15595	7	12	many	many	ADJ
ajst-15595	7	13	shortcomings	shortcoming	NOUN
ajst-15595	7	14	of	of	ADP
ajst-15595	7	15	least	least	ADJ
ajst-15595	7	16	squares	square	NOUN
ajst-15595	7	17	method	method	NOUN
ajst-15595	7	18	.	.	PUNCT
ajst-15595	8	1	by	by	ADP
ajst-15595	8	2	combining	combine	VERB
ajst-15595	8	3	quantile	quantile	ADJ
ajst-15595	8	4	regression	regression	NOUN
ajst-15595	8	5	with	with	ADP
ajst-15595	8	6	least	least	ADJ
ajst-15595	8	7	squares	square	NOUN
ajst-15595	8	8	method	method	NOUN
ajst-15595	8	9	,	,	PUNCT
ajst-15595	8	10	we	we	PRON
ajst-15595	8	11	can	can	AUX
ajst-15595	8	12	understand	understand	VERB
ajst-15595	8	13	both	both	CCONJ
ajst-15595	8	14	the	the	DET
ajst-15595	8	15	central	central	ADJ
ajst-15595	8	16	tendency	tendency	NOUN
ajst-15595	8	17	and	and	CCONJ
ajst-15595	8	18	tail	tail	NOUN
ajst-15595	8	19	behavior	behavior	NOUN
ajst-15595	8	20	of	of	ADP
ajst-15595	8	21	the	the	DET
ajst-15595	8	22	dependent	dependent	ADJ
ajst-15595	8	23	variable	variable	ADJ
ajst-15595	8	24	distribution	distribution	NOUN
ajst-15595	8	25	.	.	PUNCT
ajst-15595	9	1	the	the	DET
ajst-15595	9	2	fitting	fitting	ADJ
ajst-15595	9	3	results	result	NOUN
ajst-15595	9	4	obtained	obtain	VERB
ajst-15595	9	5	from	from	ADP
ajst-15595	9	6	quantile	quantile	ADJ
ajst-15595	9	7	regression	regression	NOUN
ajst-15595	9	8	can	can	AUX
ajst-15595	9	9	also	also	ADV
ajst-15595	9	10	provide	provide	VERB
ajst-15595	9	11	insights	insight	NOUN
ajst-15595	9	12	into	into	ADP
ajst-15595	9	13	the	the	DET
ajst-15595	9	14	suitability	suitability	NOUN
ajst-15595	9	15	of	of	ADP
ajst-15595	9	16	least	least	ADJ
ajst-15595	9	17	squares	square	NOUN
ajst-15595	9	18	estimation	estimation	NOUN
ajst-15595	9	19	.	.	PUNCT
ajst-15595	10	1	briefly	briefly	ADV
ajst-15595	10	2	,	,	PUNCT
ajst-15595	10	3	the	the	DET
ajst-15595	10	4	combination	combination	NOUN
ajst-15595	10	5	of	of	ADP
ajst-15595	10	6	both	both	DET
ajst-15595	10	7	methods	method	NOUN
ajst-15595	10	8	yields	yield	VERB
ajst-15595	10	9	better	well	ADJ
ajst-15595	10	10	results	result	NOUN
ajst-15595	10	11	in	in	ADP
ajst-15595	10	12	statistical	statistical	ADJ
ajst-15595	10	13	problems	problem	NOUN
ajst-15595	10	14	.	.	PUNCT
ajst-15595	11	1	this	this	DET
ajst-15595	11	2	paper	paper	NOUN
ajst-15595	11	3	introduces	introduce	VERB
ajst-15595	11	4	the	the	DET
ajst-15595	11	5	principles	principle	NOUN
ajst-15595	11	6	of	of	ADP
ajst-15595	11	7	quantile	quantile	ADJ
ajst-15595	11	8	regression	regression	NOUN
ajst-15595	11	9	and	and	CCONJ
ajst-15595	11	10	further	far	ADV
ajst-15595	11	11	discusses	discuss	VERB
ajst-15595	11	12	its	its	PRON
ajst-15595	11	13	scope	scope	NOUN
ajst-15595	11	14	and	and	CCONJ
ajst-15595	11	15	application	application	NOUN
ajst-15595	11	16	,	,	PUNCT
ajst-15595	11	17	aiming	aim	VERB
ajst-15595	11	18	to	to	PART
ajst-15595	11	19	provide	provide	VERB
ajst-15595	11	20	a	a	DET
ajst-15595	11	21	preliminary	preliminary	ADJ
ajst-15595	11	22	summary	summary	NOUN
ajst-15595	11	23	for	for	ADP
ajst-15595	11	24	a	a	DET
ajst-15595	11	25	better	well	ADJ
ajst-15595	11	26	understanding	understanding	NOUN
ajst-15595	11	27	of	of	ADP
ajst-15595	11	28	quantile	quantile	ADJ
ajst-15595	11	29	regression	regression	NOUN
ajst-15595	11	30	.	.	PUNCT
ajst-15595	12	1	keywords	keyword	NOUN
ajst-15595	12	2	:	:	PUNCT
ajst-15595	12	3	quantile	quantile	ADJ
ajst-15595	12	4	regression	regression	NOUN
ajst-15595	12	5	,	,	PUNCT
ajst-15595	12	6	panel	panel	NOUN
ajst-15595	12	7	data	datum	NOUN
ajst-15595	12	8	model	model	NOUN
ajst-15595	12	9	,	,	PUNCT
ajst-15595	12	10	penalized	penalize	VERB
ajst-15595	12	11	quantile	quantile	ADJ
ajst-15595	12	12	regression	regression	NOUN
ajst-15595	12	13	estimation	estimation	NOUN
ajst-15595	12	14	.	.	PUNCT
ajst-15595	13	1	1	1	X
ajst-15595	13	2	.	.	X
ajst-15595	13	3	introduction	introduction	NOUN
ajst-15595	13	4	traditional	traditional	ADJ
ajst-15595	13	5	panel	panel	NOUN
ajst-15595	13	6	data	datum	NOUN
ajst-15595	13	7	models	model	NOUN
ajst-15595	13	8	are	be	AUX
ajst-15595	13	9	mostly	mostly	ADV
ajst-15595	13	10	based	base	VERB
ajst-15595	13	11	on	on	ADP
ajst-15595	13	12	the	the	DET
ajst-15595	13	13	basic	basic	ADJ
ajst-15595	13	14	assumptions	assumption	NOUN
ajst-15595	13	15	of	of	ADP
ajst-15595	13	16	mean	mean	ADJ
ajst-15595	13	17	regression	regression	NOUN
ajst-15595	13	18	,	,	PUNCT
ajst-15595	13	19	where	where	SCONJ
ajst-15595	13	20	the	the	DET
ajst-15595	13	21	regression	regression	NOUN
ajst-15595	13	22	results	result	VERB
ajst-15595	13	23	only	only	ADV
ajst-15595	13	24	reflect	reflect	VERB
ajst-15595	13	25	the	the	DET
ajst-15595	13	26	structural	structural	ADJ
ajst-15595	13	27	relationship	relationship	NOUN
ajst-15595	13	28	between	between	ADP
ajst-15595	13	29	data	datum	NOUN
ajst-15595	13	30	near	near	ADP
ajst-15595	13	31	the	the	DET
ajst-15595	13	32	mean	mean	NOUN
ajst-15595	13	33	.	.	PUNCT
ajst-15595	14	1	they	they	PRON
ajst-15595	14	2	are	be	AUX
ajst-15595	14	3	not	not	PART
ajst-15595	14	4	accurate	accurate	ADJ
ajst-15595	14	5	in	in	ADP
ajst-15595	14	6	characterizing	characterize	VERB
ajst-15595	14	7	the	the	DET
ajst-15595	14	8	relationship	relationship	NOUN
ajst-15595	14	9	between	between	ADP
ajst-15595	14	10	variables	variable	NOUN
ajst-15595	14	11	in	in	ADP
ajst-15595	14	12	the	the	DET
ajst-15595	14	13	upper	upper	ADJ
ajst-15595	14	14	and	and	CCONJ
ajst-15595	14	15	lower	low	ADJ
ajst-15595	14	16	tails	tail	NOUN
ajst-15595	14	17	.	.	PUNCT
ajst-15595	15	1	moreover	moreover	ADV
ajst-15595	15	2	,	,	PUNCT
ajst-15595	15	3	traditional	traditional	ADJ
ajst-15595	15	4	panel	panel	NOUN
ajst-15595	15	5	data	datum	NOUN
ajst-15595	15	6	models	model	NOUN
ajst-15595	15	7	assume	assume	VERB
ajst-15595	15	8	that	that	SCONJ
ajst-15595	15	9	the	the	DET
ajst-15595	15	10	error	error	NOUN
ajst-15595	15	11	term	term	NOUN
ajst-15595	15	12	follows	follow	VERB
ajst-15595	15	13	a	a	DET
ajst-15595	15	14	normal	normal	ADJ
ajst-15595	15	15	distribution	distribution	NOUN
ajst-15595	15	16	.	.	PUNCT
ajst-15595	16	1	when	when	SCONJ
ajst-15595	16	2	the	the	DET
ajst-15595	16	3	sample	sample	NOUN
ajst-15595	16	4	data	data	NOUN
ajst-15595	16	5	does	do	AUX
ajst-15595	16	6	not	not	PART
ajst-15595	16	7	satisfy	satisfy	VERB
ajst-15595	16	8	the	the	DET
ajst-15595	16	9	classical	classical	ADJ
ajst-15595	16	10	assumptions	assumption	NOUN
ajst-15595	16	11	,	,	PUNCT
ajst-15595	16	12	such	such	ADJ
ajst-15595	16	13	as	as	ADP
ajst-15595	16	14	having	have	VERB
ajst-15595	16	15	heavy	heavy	ADJ
ajst-15595	16	16	tails	tail	NOUN
ajst-15595	16	17	or	or	CCONJ
ajst-15595	16	18	outliers	outlier	NOUN
ajst-15595	16	19	,	,	PUNCT
ajst-15595	16	20	the	the	DET
ajst-15595	16	21	estimation	estimation	NOUN
ajst-15595	16	22	results	result	NOUN
ajst-15595	16	23	are	be	AUX
ajst-15595	16	24	often	often	ADV
ajst-15595	16	25	not	not	PART
ajst-15595	16	26	robust	robust	ADJ
ajst-15595	16	27	and	and	CCONJ
ajst-15595	16	28	efficient	efficient	ADJ
ajst-15595	16	29	.	.	PUNCT
ajst-15595	17	1	due	due	ADP
ajst-15595	17	2	to	to	ADP
ajst-15595	17	3	the	the	DET
ajst-15595	17	4	limitations	limitation	NOUN
ajst-15595	17	5	of	of	ADP
ajst-15595	17	6	mean	mean	ADJ
ajst-15595	17	7	regression	regression	NOUN
ajst-15595	17	8	,	,	PUNCT
ajst-15595	17	9	some	some	DET
ajst-15595	17	10	scholars	scholar	NOUN
ajst-15595	17	11	have	have	AUX
ajst-15595	17	12	turned	turn	VERB
ajst-15595	17	13	to	to	ADP
ajst-15595	17	14	the	the	DET
ajst-15595	17	15	study	study	NOUN
ajst-15595	17	16	of	of	ADP
ajst-15595	17	17	quantile	quantile	NOUN
ajst-15595	17	18	regression.compared	regression.compare	VERB
ajst-15595	17	19	to	to	PART
ajst-15595	17	20	mean	mean	VERB
ajst-15595	17	21	regression	regression	NOUN
ajst-15595	17	22	models	model	NOUN
ajst-15595	17	23	,	,	PUNCT
ajst-15595	17	24	quantile	quantile	ADJ
ajst-15595	17	25	regression	regression	NOUN
ajst-15595	17	26	can	can	AUX
ajst-15595	17	27	more	more	ADV
ajst-15595	17	28	comprehensively	comprehensively	ADV
ajst-15595	17	29	reflect	reflect	VERB
ajst-15595	17	30	the	the	DET
ajst-15595	17	31	information	information	NOUN
ajst-15595	17	32	in	in	ADP
ajst-15595	17	33	the	the	DET
ajst-15595	17	34	data	datum	NOUN
ajst-15595	17	35	and	and	CCONJ
ajst-15595	17	36	is	be	AUX
ajst-15595	17	37	not	not	PART
ajst-15595	17	38	affected	affect	VERB
ajst-15595	17	39	by	by	ADP
ajst-15595	17	40	contaminated	contaminate	VERB
ajst-15595	17	41	data	datum	NOUN
ajst-15595	17	42	.	.	PUNCT
ajst-15595	18	1	currently	currently	ADV
ajst-15595	18	2	,	,	PUNCT
ajst-15595	18	3	the	the	DET
ajst-15595	18	4	most	most	ADV
ajst-15595	18	5	researched	research	VERB
ajst-15595	18	6	quantile	quantile	ADJ
ajst-15595	18	7	regression	regression	NOUN
ajst-15595	18	8	model	model	NOUN
ajst-15595	18	9	is	be	AUX
ajst-15595	18	10	linear	linear	PROPN
ajst-15595	18	11	quantile	quantile	ADJ
ajst-15595	18	12	regression	regression	NOUN
ajst-15595	18	13	,	,	PUNCT
ajst-15595	18	14	which	which	PRON
ajst-15595	18	15	assumes	assume	VERB
ajst-15595	18	16	a	a	DET
ajst-15595	18	17	linear	linear	ADJ
ajst-15595	18	18	relationship	relationship	NOUN
ajst-15595	18	19	between	between	ADP
ajst-15595	18	20	the	the	DET
ajst-15595	18	21	variables	variable	NOUN
ajst-15595	18	22	and	and	CCONJ
ajst-15595	18	23	provides	provide	VERB
ajst-15595	18	24	a	a	DET
ajst-15595	18	25	comprehensive	comprehensive	ADJ
ajst-15595	18	26	analysis	analysis	NOUN
ajst-15595	18	27	of	of	ADP
ajst-15595	18	28	the	the	DET
ajst-15595	18	29	data	datum	NOUN
ajst-15595	18	30	from	from	ADP
ajst-15595	18	31	various	various	ADJ
ajst-15595	18	32	quantiles	quantile	NOUN
ajst-15595	18	33	.	.	PUNCT
ajst-15595	19	1	however	however	ADV
ajst-15595	19	2	,	,	PUNCT
ajst-15595	19	3	as	as	SCONJ
ajst-15595	19	4	the	the	DET
ajst-15595	19	5	complexity	complexity	NOUN
ajst-15595	19	6	of	of	ADP
ajst-15595	19	7	modern	modern	ADJ
ajst-15595	19	8	data	datum	NOUN
ajst-15595	19	9	increases	increase	NOUN
ajst-15595	19	10	,	,	PUNCT
ajst-15595	19	11	the	the	DET
ajst-15595	19	12	advantages	advantage	NOUN
ajst-15595	19	13	and	and	CCONJ
ajst-15595	19	14	limitations	limitation	NOUN
ajst-15595	19	15	of	of	ADP
ajst-15595	19	16	parametric	parametric	ADJ
ajst-15595	19	17	quantile	quantile	ADJ
ajst-15595	19	18	regression	regression	NOUN
ajst-15595	19	19	models	model	NOUN
ajst-15595	19	20	become	become	VERB
ajst-15595	19	21	more	more	ADV
ajst-15595	19	22	apparent	apparent	ADJ
ajst-15595	19	23	.	.	PUNCT
ajst-15595	20	1	parametric	parametric	ADJ
ajst-15595	20	2	quantile	quantile	ADJ
ajst-15595	20	3	regression	regression	NOUN
ajst-15595	20	4	relies	rely	VERB
ajst-15595	20	5	on	on	ADP
ajst-15595	20	6	the	the	DET
ajst-15595	20	7	establishment	establishment	NOUN
ajst-15595	20	8	of	of	ADP
ajst-15595	20	9	a	a	DET
ajst-15595	20	10	parameter	parameter	NOUN
ajst-15595	20	11	model	model	NOUN
ajst-15595	20	12	and	and	CCONJ
ajst-15595	20	13	is	be	AUX
ajst-15595	20	14	limited	limit	VERB
ajst-15595	20	15	by	by	ADP
ajst-15595	20	16	the	the	DET
ajst-15595	20	17	given	give	VERB
ajst-15595	20	18	model	model	NOUN
ajst-15595	20	19	assumptions	assumption	NOUN
ajst-15595	20	20	,	,	PUNCT
ajst-15595	20	21	lacking	lack	VERB
ajst-15595	20	22	flexibility	flexibility	NOUN
ajst-15595	20	23	and	and	CCONJ
ajst-15595	20	24	adaptability	adaptability	NOUN
ajst-15595	20	25	to	to	ADP
ajst-15595	20	26	the	the	DET
ajst-15595	20	27	data	datum	NOUN
ajst-15595	20	28	.	.	PUNCT
ajst-15595	21	1	therefore	therefore	ADV
ajst-15595	21	2	,	,	PUNCT
ajst-15595	21	3	the	the	DET
ajst-15595	21	4	application	application	NOUN
ajst-15595	21	5	of	of	ADP
ajst-15595	21	6	nonparametric	nonparametric	NOUN
ajst-15595	21	7	quantile	quantile	ADJ
ajst-15595	21	8	regression	regression	NOUN
ajst-15595	21	9	and	and	CCONJ
ajst-15595	21	10	bayesian	bayesian	NOUN
ajst-15595	21	11	perspectives	perspective	NOUN
ajst-15595	21	12	in	in	ADP
ajst-15595	21	13	quantile	quantile	ADJ
ajst-15595	21	14	regression	regression	NOUN
ajst-15595	21	15	has	have	AUX
ajst-15595	21	16	gradually	gradually	ADV
ajst-15595	21	17	extended	extend	VERB
ajst-15595	21	18	and	and	CCONJ
ajst-15595	21	19	deepened	deepen	VERB
ajst-15595	21	20	the	the	DET
ajst-15595	21	21	original	original	ADJ
ajst-15595	21	22	regression	regression	NOUN
ajst-15595	21	23	forms	form	NOUN
ajst-15595	21	24	to	to	PART
ajst-15595	21	25	find	find	VERB
ajst-15595	21	26	the	the	DET
ajst-15595	21	27	best	good	ADJ
ajst-15595	21	28	approaches	approach	NOUN
ajst-15595	21	29	to	to	PART
ajst-15595	21	30	handle	handle	VERB
ajst-15595	21	31	complex	complex	ADJ
ajst-15595	21	32	data	datum	NOUN
ajst-15595	21	33	.	.	PUNCT
ajst-15595	22	1	since	since	SCONJ
ajst-15595	22	2	koenker	koenker	NOUN
ajst-15595	22	3	and	and	CCONJ
ajst-15595	22	4	bassett	bassett	PROPN
ajst-15595	22	5	(	(	PUNCT
ajst-15595	22	6	1978	1978	NUM
ajst-15595	22	7	)	)	PUNCT
ajst-15595	22	8	introduced	introduce	VERB
ajst-15595	22	9	the	the	DET
ajst-15595	22	10	theory	theory	NOUN
ajst-15595	22	11	of	of	ADP
ajst-15595	22	12	linear	linear	PROPN
ajst-15595	22	13	quantile	quantile	ADJ
ajst-15595	22	14	regression	regression	NOUN
ajst-15595	22	15	,	,	PUNCT
ajst-15595	22	16	quantile	quantile	ADJ
ajst-15595	22	17	regression	regression	NOUN
ajst-15595	22	18	(	(	PUNCT
ajst-15595	22	19	qr	qr	NOUN
ajst-15595	22	20	)	)	PUNCT
ajst-15595	22	21	has	have	AUX
ajst-15595	22	22	become	become	VERB
ajst-15595	22	23	a	a	DET
ajst-15595	22	24	rapidly	rapidly	ADV
ajst-15595	22	25	developing	develop	VERB
ajst-15595	22	26	and	and	CCONJ
ajst-15595	22	27	widely	widely	ADV
ajst-15595	22	28	applied	apply	VERB
ajst-15595	22	29	regression	regression	NOUN
ajst-15595	22	30	model	model	NOUN
ajst-15595	22	31	method	method	NOUN
ajst-15595	22	32	in	in	ADP
ajst-15595	22	33	recent	recent	ADJ
ajst-15595	22	34	decades	decade	NOUN
ajst-15595	22	35	.	.	PUNCT
ajst-15595	23	1	it	it	PRON
ajst-15595	23	2	not	not	PART
ajst-15595	23	3	only	only	ADV
ajst-15595	23	4	deepens	deepen	VERB
ajst-15595	23	5	the	the	DET
ajst-15595	23	6	understanding	understanding	NOUN
ajst-15595	23	7	of	of	ADP
ajst-15595	23	8	traditional	traditional	ADJ
ajst-15595	23	9	regression	regression	NOUN
ajst-15595	23	10	models	model	NOUN
ajst-15595	23	11	but	but	CCONJ
ajst-15595	23	12	also	also	ADV
ajst-15595	23	13	expands	expand	VERB
ajst-15595	23	14	the	the	DET
ajst-15595	23	15	types	type	NOUN
ajst-15595	23	16	and	and	CCONJ
ajst-15595	23	17	applications	application	NOUN
ajst-15595	23	18	of	of	ADP
ajst-15595	23	19	regression	regression	NOUN
ajst-15595	23	20	models	model	NOUN
ajst-15595	23	21	,	,	PUNCT
ajst-15595	23	22	making	make	VERB
ajst-15595	23	23	the	the	DET
ajst-15595	23	24	fitting	fitting	NOUN
ajst-15595	23	25	of	of	ADP
ajst-15595	23	26	statistical	statistical	ADJ
ajst-15595	23	27	data	datum	NOUN
ajst-15595	23	28	more	more	ADV
ajst-15595	23	29	accurate	accurate	ADJ
ajst-15595	23	30	and	and	CCONJ
ajst-15595	23	31	detailed[1	detailed[1	PROPN
ajst-15595	23	32	]	]	PUNCT
ajst-15595	23	33	.	.	PUNCT
ajst-15595	24	1	quantile	quantile	ADJ
ajst-15595	24	2	regression	regression	NOUN
ajst-15595	24	3	models	model	NOUN
ajst-15595	24	4	are	be	AUX
ajst-15595	24	5	developed	develop	VERB
ajst-15595	24	6	based	base	VERB
ajst-15595	24	7	on	on	ADP
ajst-15595	24	8	robust	robust	ADJ
ajst-15595	24	9	estimation	estimation	NOUN
ajst-15595	24	10	models	model	NOUN
ajst-15595	24	11	,	,	PUNCT
ajst-15595	24	12	including	include	VERB
ajst-15595	24	13	m	m	PROPN
ajst-15595	24	14	-	-	PUNCT
ajst-15595	24	15	estimation	estimation	NOUN
ajst-15595	24	16	theory	theory	NOUN
ajst-15595	24	17	based	base	VERB
ajst-15595	24	18	on	on	ADP
ajst-15595	24	19	general	general	ADJ
ajst-15595	24	20	convex	convex	NOUN
ajst-15595	24	21	loss	loss	NOUN
ajst-15595	24	22	functions	function	NOUN
ajst-15595	24	23	,	,	PUNCT
ajst-15595	24	24	r	r	NOUN
ajst-15595	24	25	-	-	PUNCT
ajst-15595	24	26	estimation	estimation	NOUN
ajst-15595	24	27	theory	theory	NOUN
ajst-15595	24	28	based	base	VERB
ajst-15595	24	29	on	on	ADP
ajst-15595	24	30	sample	sample	NOUN
ajst-15595	24	31	rank	rank	NOUN
ajst-15595	24	32	statistics	statistic	NOUN
ajst-15595	24	33	,	,	PUNCT
ajst-15595	24	34	and	and	CCONJ
ajst-15595	24	35	l	l	NOUN
ajst-15595	24	36	-	-	NOUN
ajst-15595	24	37	estimation	estimation	NOUN
ajst-15595	24	38	theory	theory	NOUN
ajst-15595	24	39	based	base	VERB
ajst-15595	24	40	on	on	ADP
ajst-15595	24	41	sample	sample	NOUN
ajst-15595	24	42	order	order	NOUN
ajst-15595	24	43	statistics	statistic	NOUN
ajst-15595	24	44	.	.	PUNCT
ajst-15595	25	1	quantile	quantile	ADJ
ajst-15595	25	2	regression	regression	NOUN
ajst-15595	25	3	emphasizes	emphasize	VERB
ajst-15595	25	4	estimating	estimate	VERB
ajst-15595	25	5	the	the	DET
ajst-15595	25	6	quantiles	quantile	NOUN
ajst-15595	25	7	of	of	ADP
ajst-15595	25	8	the	the	DET
ajst-15595	25	9	dependent	dependent	ADJ
ajst-15595	25	10	variable	variable	NOUN
ajst-15595	25	11	using	use	VERB
ajst-15595	25	12	quantiles	quantile	NOUN
ajst-15595	25	13	of	of	ADP
ajst-15595	25	14	the	the	DET
ajst-15595	25	15	explanatory	explanatory	ADJ
ajst-15595	25	16	variable	variable	NOUN
ajst-15595	25	17	.	.	PUNCT
ajst-15595	26	1	this	this	PRON
ajst-15595	26	2	is	be	AUX
ajst-15595	26	3	achieved	achieve	VERB
ajst-15595	26	4	by	by	ADP
ajst-15595	26	5	establishing	establish	VERB
ajst-15595	26	6	quantile	quantile	ADJ
ajst-15595	26	7	estimation	estimation	NOUN
ajst-15595	26	8	equations	equation	NOUN
ajst-15595	26	9	and	and	CCONJ
ajst-15595	26	10	using	use	VERB
ajst-15595	26	11	linear	linear	ADJ
ajst-15595	26	12	programming	programming	NOUN
ajst-15595	26	13	or	or	CCONJ
ajst-15595	26	14	nonparametric	nonparametric	NOUN
ajst-15595	26	15	estimation	estimation	NOUN
ajst-15595	26	16	methods	method	NOUN
ajst-15595	26	17	to	to	PART
ajst-15595	26	18	estimate	estimate	VERB
ajst-15595	26	19	the	the	DET
ajst-15595	26	20	coefficients	coefficient	NOUN
ajst-15595	26	21	or	or	CCONJ
ajst-15595	26	22	unknown	unknown	ADJ
ajst-15595	26	23	parameters	parameter	NOUN
ajst-15595	26	24	corresponding	correspond	VERB
ajst-15595	26	25	to	to	ADP
ajst-15595	26	26	different	different	ADJ
ajst-15595	26	27	quantiles	quantile	NOUN
ajst-15595	26	28	.	.	PUNCT
ajst-15595	27	1	quantile	quantile	ADJ
ajst-15595	27	2	regression	regression	NOUN
ajst-15595	27	3	is	be	AUX
ajst-15595	27	4	an	an	DET
ajst-15595	27	5	extension	extension	NOUN
ajst-15595	27	6	of	of	ADP
ajst-15595	27	7	median	median	ADJ
ajst-15595	27	8	regression	regression	NOUN
ajst-15595	27	9	and	and	CCONJ
ajst-15595	27	10	mean	mean	VERB
ajst-15595	27	11	regression	regression	NOUN
ajst-15595	27	12	.	.	PUNCT
ajst-15595	28	1	specific	specific	ADJ
ajst-15595	28	2	quantile	quantile	ADJ
ajst-15595	28	3	regression	regression	NOUN
ajst-15595	28	4	models	model	NOUN
ajst-15595	28	5	include	include	VERB
ajst-15595	28	6	quartile	quartile	ADJ
ajst-15595	28	7	regression	regression	NOUN
ajst-15595	28	8	,	,	PUNCT
ajst-15595	28	9	decile	decile	NOUN
ajst-15595	28	10	regression	regression	NOUN
ajst-15595	28	11	,	,	PUNCT
ajst-15595	28	12	percentile	percentile	ADJ
ajst-15595	28	13	regression	regression	NOUN
ajst-15595	28	14	,	,	PUNCT
ajst-15595	28	15	logit	logit	VERB
ajst-15595	28	16	quantile	quantile	ADJ
ajst-15595	28	17	regression	regression	NOUN
ajst-15595	28	18	,	,	PUNCT
ajst-15595	28	19	scrutiny	scrutiny	NOUN
ajst-15595	28	20	quantile	quantile	ADJ
ajst-15595	28	21	regression	regression	NOUN
ajst-15595	28	22	,	,	PUNCT
ajst-15595	28	23	and	and	CCONJ
ajst-15595	28	24	other	other	ADJ
ajst-15595	28	25	models	model	NOUN
ajst-15595	28	26	.	.	PUNCT
ajst-15595	29	1	these	these	DET
ajst-15595	29	2	models	model	NOUN
ajst-15595	29	3	not	not	PART
ajst-15595	29	4	only	only	ADV
ajst-15595	29	5	overcome	overcome	VERB
ajst-15595	29	6	the	the	DET
ajst-15595	29	7	limitations	limitation	NOUN
ajst-15595	29	8	of	of	ADP
ajst-15595	29	9	error	error	NOUN
ajst-15595	29	10	restrictions	restriction	NOUN
ajst-15595	29	11	and	and	CCONJ
ajst-15595	29	12	outlier	outlier	NOUN
ajst-15595	29	13	interference	interference	NOUN
ajst-15595	29	14	but	but	CCONJ
ajst-15595	29	15	also	also	ADV
ajst-15595	29	16	solve	solve	VERB
ajst-15595	29	17	the	the	DET
ajst-15595	29	18	problem	problem	NOUN
ajst-15595	29	19	of	of	ADP
ajst-15595	29	20	modeling	model	VERB
ajst-15595	29	21	data	datum	NOUN
ajst-15595	29	22	from	from	ADP
ajst-15595	29	23	multiple	multiple	ADJ
ajst-15595	29	24	perspectives	perspective	NOUN
ajst-15595	29	25	.	.	PUNCT
ajst-15595	30	1	recent	recent	ADJ
ajst-15595	30	2	developments	development	NOUN
ajst-15595	30	3	in	in	ADP
ajst-15595	30	4	quantile	quantile	ADJ
ajst-15595	30	5	regression	regression	NOUN
ajst-15595	30	6	research	research	NOUN
ajst-15595	30	7	mainly	mainly	ADV
ajst-15595	30	8	focus	focus	VERB
ajst-15595	30	9	on	on	ADP
ajst-15595	30	10	the	the	DET
ajst-15595	30	11	technical	technical	ADJ
ajst-15595	30	12	methods	method	NOUN
ajst-15595	30	13	and	and	CCONJ
ajst-15595	30	14	applications	application	NOUN
ajst-15595	30	15	of	of	ADP
ajst-15595	30	16	quantile	quantile	ADJ
ajst-15595	30	17	regression	regression	NOUN
ajst-15595	30	18	.	.	PUNCT
ajst-15595	31	1	foreign	foreign	ADJ
ajst-15595	31	2	scholars	scholar	NOUN
ajst-15595	31	3	such	such	ADJ
ajst-15595	31	4	as	as	ADP
ajst-15595	31	5	koenker	koenker	NOUN
ajst-15595	31	6	and	and	CCONJ
ajst-15595	31	7	zhijie	zhijie	PROPN
ajst-15595	31	8	xiao	xiao	PROPN
ajst-15595	31	9	have	have	AUX
ajst-15595	31	10	addressed	address	VERB
ajst-15595	31	11	specific	specific	ADJ
ajst-15595	31	12	inference	inference	NOUN
ajst-15595	31	13	problems	problem	NOUN
ajst-15595	31	14	in	in	ADP
ajst-15595	31	15	quantile	quantile	ADJ
ajst-15595	31	16	regression	regression	NOUN
ajst-15595	31	17	.	.	PUNCT
ajst-15595	32	1	kim	kim	PROPN
ajst-15595	32	2	and	and	CCONJ
ajst-15595	32	3	muller	muller	PROPN
ajst-15595	32	4	have	have	AUX
ajst-15595	32	5	studied	study	VERB
ajst-15595	32	6	the	the	DET
ajst-15595	32	7	asymptotic	asymptotic	ADJ
ajst-15595	32	8	properties	property	NOUN
ajst-15595	32	9	of	of	ADP
ajst-15595	32	10	two	two	NUM
ajst-15595	32	11	-	-	PUNCT
ajst-15595	32	12	step	step	NOUN
ajst-15595	32	13	quantile	quantile	ADJ
ajst-15595	32	14	regression	regression	NOUN
ajst-15595	32	15	.	.	PUNCT
ajst-15595	33	1	tasche	tasche	PROPN
ajst-15595	33	2	has	have	AUX
ajst-15595	33	3	examined	examine	VERB
ajst-15595	33	4	the	the	DET
ajst-15595	33	5	unbiasedness	unbiasedness	NOUN
ajst-15595	33	6	of	of	ADP
ajst-15595	33	7	least	least	ADJ
ajst-15595	33	8	quantile	quantile	ADJ
ajst-15595	33	9	regression	regression	NOUN
ajst-15595	33	10	.	.	PUNCT
ajst-15595	34	1	chernozhukov	chernozhukov	PROPN
ajst-15595	34	2	and	and	CCONJ
ajst-15595	34	3	han	han	PROPN
ajst-15595	34	4	hong	hong	PROPN
ajst-15595	34	5	have	have	AUX
ajst-15595	34	6	proposed	propose	VERB
ajst-15595	34	7	a	a	DET
ajst-15595	34	8	three	three	NUM
ajst-15595	34	9	-	-	PUNCT
ajst-15595	34	10	step	step	NOUN
ajst-15595	34	11	evaluation	evaluation	NOUN
ajst-15595	34	12	method	method	NOUN
ajst-15595	34	13	for	for	ADP
ajst-15595	34	14	scrutiny	scrutiny	NOUN
ajst-15595	34	15	quantile	quantile	ADJ
ajst-15595	34	16	regression	regression	NOUN
ajst-15595	34	17	.	.	PUNCT
ajst-15595	35	1	wu	wu	PROPN
ajst-15595	35	2	jiannan	jiannan	PROPN
ajst-15595	35	3	,	,	PUNCT
ajst-15595	35	4	bret	bret	PROPN
ajst-15595	35	5	-	-	PUNCT
ajst-15595	35	6	schneider	schneider	PROPN
ajst-15595	35	7	et	et	PROPN
ajst-15595	35	8	al	al	PROPN
ajst-15595	35	9	.	.	PROPN
ajst-15595	35	10	have	have	AUX
ajst-15595	35	11	compared	compare	VERB
ajst-15595	35	12	the	the	DET
ajst-15595	35	13	advantages	advantage	NOUN
ajst-15595	35	14	and	and	CCONJ
ajst-15595	35	15	disadvantages	disadvantage	NOUN
ajst-15595	35	16	of	of	ADP
ajst-15595	35	17	significant	significant	ADJ
ajst-15595	35	18	weight	weight	NOUN
ajst-15595	35	19	analysis	analysis	NOUN
ajst-15595	35	20	methods	method	NOUN
ajst-15595	35	21	and	and	CCONJ
ajst-15595	35	22	quantile	quantile	ADJ
ajst-15595	35	23	regression	regression	NOUN
ajst-15595	35	24	using	use	VERB
ajst-15595	35	25	monte	monte	PROPN
ajst-15595	35	26	carlo	carlo	PROPN
ajst-15595	35	27	methods	method	NOUN
ajst-15595	35	28	with	with	ADP
ajst-15595	35	29	100	100	NUM
ajst-15595	35	30	random	random	ADJ
ajst-15595	35	31	data	datum	NOUN
ajst-15595	35	32	sets	set	NOUN
ajst-15595	35	33	.	.	PUNCT
ajst-15595	36	1	koenker	koenker	NOUN
ajst-15595	36	2	(	(	PUNCT
ajst-15595	36	3	2004	2004	NUM
ajst-15595	36	4	)	)	PUNCT
ajst-15595	36	5	first	first	ADV
ajst-15595	36	6	applied	apply	VERB
ajst-15595	36	7	quantile	quantile	ADJ
ajst-15595	36	8	173	173	NUM
ajst-15595	36	9	regression	regression	NOUN
ajst-15595	36	10	methods	method	NOUN
ajst-15595	36	11	to	to	ADP
ajst-15595	36	12	panel	panel	NOUN
ajst-15595	36	13	data	datum	NOUN
ajst-15595	36	14	models	model	NOUN
ajst-15595	36	15	and	and	CCONJ
ajst-15595	36	16	proposed	propose	VERB
ajst-15595	36	17	panel	panel	NOUN
ajst-15595	36	18	data	datum	NOUN
ajst-15595	36	19	quantile	quantile	ADJ
ajst-15595	36	20	regression	regression	NOUN
ajst-15595	36	21	methods	method	NOUN
ajst-15595	36	22	,	,	PUNCT
ajst-15595	36	23	which	which	PRON
ajst-15595	36	24	are	be	AUX
ajst-15595	36	25	powerful	powerful	ADJ
ajst-15595	36	26	complements	complement	NOUN
ajst-15595	36	27	and	and	CCONJ
ajst-15595	36	28	extensions	extension	NOUN
ajst-15595	36	29	to	to	ADP
ajst-15595	36	30	traditional	traditional	ADJ
ajst-15595	36	31	panel	panel	NOUN
ajst-15595	36	32	data	data	VERB
ajst-15595	36	33	analysis	analysis	NOUN
ajst-15595	36	34	methods[2	methods[2	PROPN
ajst-15595	36	35	]	]	PUNCT
ajst-15595	36	36	.	.	PUNCT
ajst-15595	37	1	they	they	PRON
ajst-15595	37	2	can	can	AUX
ajst-15595	37	3	fully	fully	ADV
ajst-15595	37	4	utilize	utilize	VERB
ajst-15595	37	5	the	the	DET
ajst-15595	37	6	characteristics	characteristic	NOUN
ajst-15595	37	7	of	of	ADP
ajst-15595	37	8	large	large	ADJ
ajst-15595	37	9	sample	sample	NOUN
ajst-15595	37	10	panel	panel	NOUN
ajst-15595	37	11	data	datum	NOUN
ajst-15595	37	12	,	,	PUNCT
ajst-15595	37	13	accurately	accurately	ADV
ajst-15595	37	14	describe	describe	VERB
ajst-15595	37	15	the	the	DET
ajst-15595	37	16	impact	impact	NOUN
ajst-15595	37	17	of	of	ADP
ajst-15595	37	18	explanatory	explanatory	ADJ
ajst-15595	37	19	variables	variable	NOUN
ajst-15595	37	20	on	on	ADP
ajst-15595	37	21	the	the	DET
ajst-15595	37	22	conditional	conditional	ADJ
ajst-15595	37	23	distribution	distribution	NOUN
ajst-15595	37	24	of	of	ADP
ajst-15595	37	25	the	the	DET
ajst-15595	37	26	dependent	dependent	ADJ
ajst-15595	37	27	variable	variable	NOUN
ajst-15595	37	28	,	,	PUNCT
ajst-15595	37	29	relax	relax	VERB
ajst-15595	37	30	the	the	DET
ajst-15595	37	31	assumptions	assumption	NOUN
ajst-15595	37	32	of	of	ADP
ajst-15595	37	33	error	error	NOUN
ajst-15595	37	34	distribution	distribution	NOUN
ajst-15595	37	35	,	,	PUNCT
ajst-15595	37	36	and	and	CCONJ
ajst-15595	37	37	improve	improve	VERB
ajst-15595	37	38	the	the	DET
ajst-15595	37	39	interpretability	interpretability	NOUN
ajst-15595	37	40	,	,	PUNCT
ajst-15595	37	41	robustness	robustness	NOUN
ajst-15595	37	42	,	,	PUNCT
ajst-15595	37	43	and	and	CCONJ
ajst-15595	37	44	efficiency	efficiency	NOUN
ajst-15595	37	45	of	of	ADP
ajst-15595	37	46	the	the	DET
ajst-15595	37	47	model	model	NOUN
ajst-15595	37	48	's	's	PART
ajst-15595	37	49	estimators	estimator	NOUN
ajst-15595	37	50	.	.	PUNCT
ajst-15595	38	1	research	research	NOUN
ajst-15595	38	2	has	have	AUX
ajst-15595	38	3	found	find	VERB
ajst-15595	38	4	that	that	SCONJ
ajst-15595	38	5	under	under	ADP
ajst-15595	38	6	nonnormal	nonnormal	ADJ
ajst-15595	38	7	assumptions	assumption	NOUN
ajst-15595	38	8	,	,	PUNCT
ajst-15595	38	9	quantile	quantile	ADJ
ajst-15595	38	10	regression	regression	NOUN
ajst-15595	38	11	models	model	NOUN
ajst-15595	38	12	are	be	AUX
ajst-15595	38	13	more	more	ADV
ajst-15595	38	14	stable	stable	ADJ
ajst-15595	38	15	than	than	ADP
ajst-15595	38	16	traditional	traditional	ADJ
ajst-15595	38	17	mean	mean	ADJ
ajst-15595	38	18	regression	regression	NOUN
ajst-15595	38	19	.	.	PUNCT
ajst-15595	39	1	carloslamarche	carloslamarche	NOUN
ajst-15595	39	2	further	far	ADV
ajst-15595	39	3	explores	explore	VERB
ajst-15595	39	4	the	the	DET
ajst-15595	39	5	pqr	pqr	PROPN
ajst-15595	39	6	estimation	estimation	NOUN
ajst-15595	39	7	method	method	NOUN
ajst-15595	39	8	and	and	CCONJ
ajst-15595	39	9	combines	combine	VERB
ajst-15595	39	10	it	it	PRON
ajst-15595	39	11	with	with	ADP
ajst-15595	39	12	empirical	empirical	ADJ
ajst-15595	39	13	analysis	analysis	NOUN
ajst-15595	39	14	using	use	VERB
ajst-15595	39	15	real	real	ADJ
ajst-15595	39	16	data	datum	NOUN
ajst-15595	39	17	.	.	PUNCT
ajst-15595	40	1	cai	cai	PROPN
ajst-15595	40	2	(	(	PUNCT
ajst-15595	40	3	2010	2010	NUM
ajst-15595	40	4	)	)	PUNCT
ajst-15595	40	5	discusses	discuss	VERB
ajst-15595	40	6	the	the	DET
ajst-15595	40	7	analysis	analysis	NOUN
ajst-15595	40	8	of	of	ADP
ajst-15595	40	9	nonparametric	nonparametric	PROPN
ajst-15595	40	10	spline	spline	PROPN
ajst-15595	40	11	quantile	quantile	ADJ
ajst-15595	40	12	regression	regression	NOUN
ajst-15595	40	13	for	for	ADP
ajst-15595	40	14	ordinary	ordinary	ADJ
ajst-15595	40	15	bivariate	bivariate	ADJ
ajst-15595	40	16	data	datum	NOUN
ajst-15595	40	17	from	from	ADP
ajst-15595	40	18	a	a	DET
ajst-15595	40	19	bayesian	bayesian	NOUN
ajst-15595	40	20	perspective	perspective	NOUN
ajst-15595	40	21	,	,	PUNCT
ajst-15595	40	22	estimates	estimate	VERB
ajst-15595	40	23	the	the	DET
ajst-15595	40	24	mean	mean	NOUN
ajst-15595	40	25	of	of	ADP
ajst-15595	40	26	the	the	DET
ajst-15595	40	27	parameters	parameter	NOUN
ajst-15595	40	28	using	use	VERB
ajst-15595	40	29	monte	monte	PROPN
ajst-15595	40	30	carlo	carlo	PROPN
ajst-15595	40	31	markov	markov	PROPN
ajst-15595	40	32	chain	chain	NOUN
ajst-15595	40	33	,	,	PUNCT
ajst-15595	40	34	and	and	CCONJ
ajst-15595	40	35	studies	study	VERB
ajst-15595	40	36	the	the	DET
ajst-15595	40	37	optimal	optimal	ADJ
ajst-15595	40	38	selection	selection	NOUN
ajst-15595	40	39	of	of	ADP
ajst-15595	40	40	the	the	DET
ajst-15595	40	41	proposed	propose	VERB
ajst-15595	40	42	distribution[3	distribution[3	PROPN
ajst-15595	40	43	]	]	PUNCT
ajst-15595	40	44	.	.	PUNCT
ajst-15595	41	1	the	the	DET
ajst-15595	41	2	conclusion	conclusion	NOUN
ajst-15595	41	3	is	be	AUX
ajst-15595	41	4	that	that	SCONJ
ajst-15595	41	5	bayesian	bayesian	NOUN
ajst-15595	41	6	nonparametric	nonparametric	NOUN
ajst-15595	41	7	quantile	quantile	ADJ
ajst-15595	41	8	regression	regression	NOUN
ajst-15595	41	9	is	be	AUX
ajst-15595	41	10	more	more	ADV
ajst-15595	41	11	flexible	flexible	ADJ
ajst-15595	41	12	than	than	ADP
ajst-15595	41	13	parametric	parametric	ADJ
ajst-15595	41	14	quantile	quantile	ADJ
ajst-15595	41	15	regression	regression	NOUN
ajst-15595	41	16	,	,	PUNCT
ajst-15595	41	17	as	as	SCONJ
ajst-15595	41	18	it	it	PRON
ajst-15595	41	19	combines	combine	VERB
ajst-15595	41	20	nonparametric	nonparametric	NOUN
ajst-15595	41	21	with	with	ADP
ajst-15595	41	22	quantile	quantile	ADJ
ajst-15595	41	23	regression	regression	NOUN
ajst-15595	41	24	and	and	CCONJ
ajst-15595	41	25	applies	apply	VERB
ajst-15595	41	26	it	it	PRON
ajst-15595	41	27	to	to	ADP
ajst-15595	41	28	ordinary	ordinary	ADJ
ajst-15595	41	29	data	datum	NOUN
ajst-15595	41	30	.	.	PUNCT
ajst-15595	42	1	later	later	ADV
ajst-15595	42	2	,	,	PUNCT
ajst-15595	42	3	scholars	scholar	NOUN
ajst-15595	42	4	extended	extend	VERB
ajst-15595	42	5	this	this	PRON
ajst-15595	42	6	from	from	ADP
ajst-15595	42	7	ordinary	ordinary	ADJ
ajst-15595	42	8	data	datum	NOUN
ajst-15595	42	9	to	to	ADP
ajst-15595	42	10	panel	panel	NOUN
ajst-15595	42	11	data	datum	NOUN
ajst-15595	42	12	,	,	PUNCT
ajst-15595	42	13	fully	fully	ADV
ajst-15595	42	14	utilizing	utilize	VERB
ajst-15595	42	15	the	the	DET
ajst-15595	42	16	sample	sample	NOUN
ajst-15595	42	17	information	information	NOUN
ajst-15595	42	18	and	and	CCONJ
ajst-15595	42	19	combining	combine	VERB
ajst-15595	42	20	bayesian	bayesian	NOUN
ajst-15595	42	21	methods	method	NOUN
ajst-15595	42	22	with	with	ADP
ajst-15595	42	23	quantile	quantile	ADJ
ajst-15595	42	24	regression	regression	NOUN
ajst-15595	42	25	to	to	PART
ajst-15595	42	26	handle	handle	VERB
ajst-15595	42	27	panel	panel	NOUN
ajst-15595	42	28	data	datum	NOUN
ajst-15595	42	29	,	,	PUNCT
ajst-15595	42	30	resulting	result	VERB
ajst-15595	42	31	in	in	ADP
ajst-15595	42	32	beneficial	beneficial	ADJ
ajst-15595	42	33	conclusions	conclusion	NOUN
ajst-15595	42	34	.	.	PUNCT
ajst-15595	43	1	yeh	yeh	PROPN
ajst-15595	43	2	et	et	PROPN
ajst-15595	43	3	al	al	PROPN
ajst-15595	43	4	.	.	PROPN
ajst-15595	44	1	(	(	PUNCT
ajst-15595	44	2	2011	2011	NUM
ajst-15595	44	3	)	)	PUNCT
ajst-15595	44	4	also	also	ADV
ajst-15595	44	5	provide	provide	VERB
ajst-15595	44	6	empirical	empirical	ADJ
ajst-15595	44	7	likelihood	likelihood	NOUN
ajst-15595	44	8	estimates	estimate	NOUN
ajst-15595	44	9	for	for	ADP
ajst-15595	44	10	panel	panel	NOUN
ajst-15595	44	11	quantile	quantile	ADJ
ajst-15595	44	12	regression	regression	NOUN
ajst-15595	44	13	models	model	NOUN
ajst-15595	44	14	.	.	PUNCT
ajst-15595	45	1	before	before	ADP
ajst-15595	45	2	this	this	PRON
ajst-15595	45	3	,	,	PUNCT
ajst-15595	45	4	many	many	ADJ
ajst-15595	45	5	scholars	scholar	NOUN
ajst-15595	45	6	introduced	introduce	VERB
ajst-15595	45	7	empirical	empirical	ADJ
ajst-15595	45	8	likelihood	likelihood	NOUN
ajst-15595	45	9	functions	function	NOUN
ajst-15595	45	10	,	,	PUNCT
ajst-15595	45	11	but	but	CCONJ
ajst-15595	46	1	yeh	yeh	PROPN
ajst-15595	46	2	et	et	PROPN
ajst-15595	46	3	al	al	PROPN
ajst-15595	46	4	.	.	PROPN
ajst-15595	46	5	argue	argue	VERB
ajst-15595	46	6	that	that	SCONJ
ajst-15595	46	7	for	for	ADP
ajst-15595	46	8	panel	panel	NOUN
ajst-15595	46	9	data	datum	NOUN
ajst-15595	46	10	quantile	quantile	ADJ
ajst-15595	46	11	regression	regression	NOUN
ajst-15595	46	12	models	model	NOUN
ajst-15595	46	13	,	,	PUNCT
ajst-15595	46	14	considering	consider	VERB
ajst-15595	46	15	the	the	DET
ajst-15595	46	16	correlation	correlation	NOUN
ajst-15595	46	17	within	within	ADP
ajst-15595	46	18	each	each	DET
ajst-15595	46	19	cross	cross	NOUN
ajst-15595	46	20	-	-	NOUN
ajst-15595	46	21	section	section	NOUN
ajst-15595	46	22	,	,	PUNCT
ajst-15595	46	23	the	the	DET
ajst-15595	46	24	likelihood	likelihood	NOUN
ajst-15595	46	25	ratio	ratio	NOUN
ajst-15595	46	26	mentioned	mention	VERB
ajst-15595	46	27	in	in	ADP
ajst-15595	46	28	the	the	DET
ajst-15595	46	29	literature	literature	NOUN
ajst-15595	46	30	is	be	AUX
ajst-15595	46	31	no	no	ADV
ajst-15595	46	32	longer	long	ADV
ajst-15595	46	33	applicable	applicable	ADJ
ajst-15595	46	34	to	to	ADP
ajst-15595	46	35	this	this	DET
ajst-15595	46	36	model	model	NOUN
ajst-15595	46	37	,	,	PUNCT
ajst-15595	46	38	which	which	PRON
ajst-15595	46	39	diminishes	diminish	VERB
ajst-15595	46	40	the	the	DET
ajst-15595	46	41	charm	charm	NOUN
ajst-15595	46	42	of	of	ADP
ajst-15595	46	43	the	the	DET
ajst-15595	46	44	empirical	empirical	ADJ
ajst-15595	46	45	likelihood	likelihood	NOUN
ajst-15595	46	46	as	as	ADP
ajst-15595	46	47	a	a	DET
ajst-15595	46	48	statistical	statistical	ADJ
ajst-15595	46	49	quantity[4	quantity[4	NOUN
ajst-15595	46	50	]	]	PUNCT
ajst-15595	46	51	.	.	PUNCT
ajst-15595	47	1	in	in	ADP
ajst-15595	47	2	this	this	DET
ajst-15595	47	3	study	study	NOUN
ajst-15595	47	4	,	,	PUNCT
ajst-15595	47	5	to	to	PART
ajst-15595	47	6	adapt	adapt	VERB
ajst-15595	47	7	to	to	ADP
ajst-15595	47	8	the	the	DET
ajst-15595	47	9	correlation	correlation	NOUN
ajst-15595	47	10	within	within	ADP
ajst-15595	47	11	cross	cross	NOUN
ajst-15595	47	12	-	-	NOUN
ajst-15595	47	13	sections	section	NOUN
ajst-15595	47	14	and	and	CCONJ
ajst-15595	47	15	obtain	obtain	VERB
ajst-15595	47	16	more	more	ADV
ajst-15595	47	17	accurate	accurate	ADJ
ajst-15595	47	18	estimates	estimate	NOUN
ajst-15595	47	19	,	,	PUNCT
ajst-15595	47	20	the	the	DET
ajst-15595	47	21	authors	author	NOUN
ajst-15595	47	22	replaced	replace	VERB
ajst-15595	47	23	the	the	DET
ajst-15595	47	24	quantile	quantile	ADJ
ajst-15595	47	25	score	score	NOUN
ajst-15595	47	26	function	function	NOUN
ajst-15595	47	27	with	with	ADP
ajst-15595	47	28	smooth	smooth	ADJ
ajst-15595	47	29	empirical	empirical	ADJ
ajst-15595	47	30	likelihood	likelihood	NOUN
ajst-15595	47	31	estimates	estimate	NOUN
ajst-15595	47	32	,	,	PUNCT
ajst-15595	47	33	thus	thus	ADV
ajst-15595	47	34	obtaining	obtain	VERB
ajst-15595	47	35	empirical	empirical	ADJ
ajst-15595	47	36	loglikelihood	loglikelihood	NOUN
ajst-15595	47	37	and	and	CCONJ
ajst-15595	47	38	maximum	maximum	ADJ
ajst-15595	47	39	empirical	empirical	ADJ
ajst-15595	47	40	likelihood	likelihood	NOUN
ajst-15595	47	41	functions	function	NOUN
ajst-15595	47	42	for	for	ADP
ajst-15595	47	43	further	further	ADJ
ajst-15595	47	44	research	research	NOUN
ajst-15595	47	45	.	.	PUNCT
ajst-15595	48	1	antonio	antonio	PROPN
ajst-15595	48	2	and	and	CCONJ
ajst-15595	48	3	galvao	galvao	PROPN
ajst-15595	48	4	(	(	PUNCT
ajst-15595	48	5	2011	2011	NUM
ajst-15595	48	6	)	)	PUNCT
ajst-15595	48	7	studied	study	VERB
ajst-15595	48	8	fixedeffects	fixedeffect	NOUN
ajst-15595	48	9	dynamic	dynamic	ADJ
ajst-15595	48	10	panel	panel	NOUN
ajst-15595	48	11	models	model	NOUN
ajst-15595	48	12	and	and	CCONJ
ajst-15595	48	13	found	find	VERB
ajst-15595	48	14	that	that	SCONJ
ajst-15595	48	15	in	in	ADP
ajst-15595	48	16	general	general	ADJ
ajst-15595	48	17	,	,	PUNCT
ajst-15595	48	18	the	the	DET
ajst-15595	48	19	time	time	NOUN
ajst-15595	48	20	dimension	dimension	PROPN
ajst-15595	48	21	t	t	PROPN
ajst-15595	48	22	is	be	AUX
ajst-15595	48	23	smaller	small	ADJ
ajst-15595	48	24	than	than	ADP
ajst-15595	48	25	the	the	DET
ajst-15595	48	26	individual	individual	ADJ
ajst-15595	48	27	dimension	dimension	NOUN
ajst-15595	48	28	n	n	CCONJ
ajst-15595	48	29	,	,	PUNCT
ajst-15595	48	30	making	make	VERB
ajst-15595	48	31	it	it	PRON
ajst-15595	48	32	difficult	difficult	ADJ
ajst-15595	48	33	to	to	PART
ajst-15595	48	34	estimate	estimate	VERB
ajst-15595	48	35	individual	individual	ADJ
ajst-15595	48	36	fixed	fix	VERB
ajst-15595	48	37	effects[5	effects[5	NOUN
ajst-15595	48	38	]	]	PUNCT
ajst-15595	48	39	.	.	PUNCT
ajst-15595	49	1	in	in	ADP
ajst-15595	49	2	the	the	DET
ajst-15595	49	3	least	least	ADJ
ajst-15595	49	4	squares	square	NOUN
ajst-15595	49	5	estimation	estimation	NOUN
ajst-15595	49	6	of	of	ADP
ajst-15595	49	7	dynamic	dynamic	ADJ
ajst-15595	49	8	panel	panel	NOUN
ajst-15595	49	9	data	datum	NOUN
ajst-15595	49	10	quantile	quantile	ADJ
ajst-15595	49	11	regression	regression	NOUN
ajst-15595	49	12	models	model	NOUN
ajst-15595	49	13	,	,	PUNCT
ajst-15595	49	14	the	the	DET
ajst-15595	49	15	unobserved	unobserved	ADJ
ajst-15595	49	16	initial	initial	ADJ
ajst-15595	49	17	values	value	NOUN
ajst-15595	49	18	cause	cause	VERB
ajst-15595	49	19	biases	bias	NOUN
ajst-15595	49	20	in	in	ADP
ajst-15595	49	21	the	the	DET
ajst-15595	49	22	dynamic	dynamic	ADJ
ajst-15595	49	23	process	process	NOUN
ajst-15595	49	24	of	of	ADP
ajst-15595	49	25	quantile	quantile	ADJ
ajst-15595	49	26	regression	regression	NOUN
ajst-15595	49	27	fixed	fix	VERB
ajst-15595	49	28	effects	effect	NOUN
ajst-15595	49	29	estimation	estimation	NOUN
ajst-15595	49	30	.	.	PUNCT
ajst-15595	50	1	therefore	therefore	ADV
ajst-15595	50	2	,	,	PUNCT
ajst-15595	50	3	the	the	DET
ajst-15595	50	4	authors	author	NOUN
ajst-15595	50	5	used	use	VERB
ajst-15595	50	6	instrumental	instrumental	ADJ
ajst-15595	50	7	variable	variable	ADJ
ajst-15595	50	8	methods	method	NOUN
ajst-15595	50	9	to	to	PART
ajst-15595	50	10	estimate	estimate	VERB
ajst-15595	50	11	the	the	DET
ajst-15595	50	12	dynamic	dynamic	ADJ
ajst-15595	50	13	panel	panel	NOUN
ajst-15595	50	14	data	datum	NOUN
ajst-15595	50	15	quantile	quantile	PROPN
ajst-15595	50	16	regression	regression	NOUN
ajst-15595	50	17	model	model	NOUN
ajst-15595	50	18	.	.	PUNCT
ajst-15595	51	1	koenker	koenker	NOUN
ajst-15595	51	2	(	(	PUNCT
ajst-15595	51	3	2011	2011	NUM
ajst-15595	51	4	)	)	PUNCT
ajst-15595	51	5	first	first	ADV
ajst-15595	51	6	considered	consider	VERB
ajst-15595	51	7	quantile	quantile	ADJ
ajst-15595	51	8	regression	regression	NOUN
ajst-15595	51	9	methods	method	NOUN
ajst-15595	51	10	for	for	ADP
ajst-15595	51	11	additive	additive	ADJ
ajst-15595	51	12	models	model	NOUN
ajst-15595	51	13	and	and	CCONJ
ajst-15595	51	14	used	use	VERB
ajst-15595	51	15	piecewise	piecewise	NOUN
ajst-15595	51	16	linear	linear	NOUN
ajst-15595	51	17	bases	basis	NOUN
ajst-15595	51	18	to	to	PART
ajst-15595	51	19	find	find	VERB
ajst-15595	51	20	the	the	DET
ajst-15595	51	21	smoothing	smooth	VERB
ajst-15595	51	22	parameters	parameter	NOUN
ajst-15595	51	23	that	that	PRON
ajst-15595	51	24	minimize	minimize	VERB
ajst-15595	51	25	the	the	DET
ajst-15595	51	26	model	model	NOUN
ajst-15595	51	27	's	's	PART
ajst-15595	51	28	sic	sic	ADJ
ajst-15595	51	29	value[6	value[6	NOUN
ajst-15595	51	30	]	]	PUNCT
ajst-15595	51	31	.	.	PUNCT
ajst-15595	52	1	they	they	PRON
ajst-15595	52	2	then	then	ADV
ajst-15595	52	3	constructed	construct	VERB
ajst-15595	52	4	a	a	DET
ajst-15595	52	5	confidence	confidence	NOUN
ajst-15595	52	6	band	band	NOUN
ajst-15595	52	7	for	for	ADP
ajst-15595	52	8	the	the	DET
ajst-15595	52	9	nonparametric	nonparametric	NOUN
ajst-15595	52	10	function	function	NOUN
ajst-15595	52	11	using	use	VERB
ajst-15595	52	12	the	the	DET
ajst-15595	52	13	sandwich	sandwich	NOUN
ajst-15595	52	14	method	method	NOUN
ajst-15595	52	15	.	.	PUNCT
ajst-15595	53	1	waldmann	waldmann	NOUN
ajst-15595	53	2	(	(	PUNCT
ajst-15595	53	3	2013	2013	NUM
ajst-15595	53	4	)	)	PUNCT
ajst-15595	53	5	studied	study	VERB
ajst-15595	53	6	additive	additive	ADJ
ajst-15595	53	7	quantile	quantile	ADJ
ajst-15595	53	8	regression	regression	NOUN
ajst-15595	53	9	models	model	NOUN
ajst-15595	53	10	from	from	ADP
ajst-15595	53	11	a	a	DET
ajst-15595	53	12	bayesian	bayesian	NOUN
ajst-15595	53	13	perspective	perspective	NOUN
ajst-15595	53	14	by	by	ADP
ajst-15595	53	15	transforming	transform	VERB
ajst-15595	53	16	the	the	DET
ajst-15595	53	17	asymmetric	asymmetric	ADJ
ajst-15595	53	18	laplace	laplace	NOUN
ajst-15595	53	19	distribution	distribution	NOUN
ajst-15595	53	20	using	use	VERB
ajst-15595	53	21	a	a	DET
ajst-15595	53	22	scale	scale	NOUN
ajst-15595	53	23	-	-	PUNCT
ajst-15595	53	24	mixture	mixture	NOUN
ajst-15595	53	25	gaussian	gaussian	ADJ
ajst-15595	53	26	distribution	distribution	NOUN
ajst-15595	53	27	to	to	PART
ajst-15595	53	28	establish	establish	VERB
ajst-15595	53	29	a	a	DET
ajst-15595	53	30	bayesian	bayesian	NOUN
ajst-15595	53	31	hierarchical	hierarchical	ADJ
ajst-15595	53	32	quantile	quantile	ADJ
ajst-15595	53	33	regression	regression	NOUN
ajst-15595	53	34	model	model	NOUN
ajst-15595	53	35	.	.	PUNCT
ajst-15595	54	1	finally	finally	ADV
ajst-15595	54	2	,	,	PUNCT
ajst-15595	54	3	they	they	PRON
ajst-15595	54	4	used	use	VERB
ajst-15595	54	5	the	the	DET
ajst-15595	54	6	markov	markov	NOUN
ajst-15595	54	7	chain	chain	NOUN
ajst-15595	54	8	monte	monte	PROPN
ajst-15595	54	9	carlo	carlo	PROPN
ajst-15595	54	10	(	(	PUNCT
ajst-15595	54	11	mcmc	mcmc	PROPN
ajst-15595	54	12	)	)	PUNCT
ajst-15595	54	13	algorithm	algorithm	NOUN
ajst-15595	54	14	to	to	PART
ajst-15595	54	15	quickly	quickly	ADV
ajst-15595	54	16	solve	solve	VERB
ajst-15595	54	17	the	the	DET
ajst-15595	54	18	problems	problem	NOUN
ajst-15595	54	19	of	of	ADP
ajst-15595	54	20	nonparametric	nonparametric	NOUN
ajst-15595	54	21	function	function	NOUN
ajst-15595	54	22	estimation	estimation	NOUN
ajst-15595	54	23	and	and	CCONJ
ajst-15595	54	24	construction	construction	NOUN
ajst-15595	54	25	of	of	ADP
ajst-15595	54	26	confidence	confidence	NOUN
ajst-15595	54	27	bands[7	bands[7	ADP
ajst-15595	54	28	]	]	PUNCT
ajst-15595	54	29	.	.	PUNCT
ajst-15595	55	1	kengo	kengo	PROPN
ajst-15595	55	2	and	and	CCONJ
ajst-15595	55	3	antonio	antonio	PROPN
ajst-15595	55	4	(	(	PUNCT
ajst-15595	55	5	2012	2012	NUM
ajst-15595	55	6	)	)	PUNCT
ajst-15595	55	7	studied	study	VERB
ajst-15595	55	8	panel	panel	NOUN
ajst-15595	55	9	data	data	NOUN
ajst-15595	55	10	models	model	NOUN
ajst-15595	55	11	with	with	ADP
ajst-15595	55	12	individual	individual	ADJ
ajst-15595	55	13	fixed	fix	VERB
ajst-15595	55	14	effects	effect	NOUN
ajst-15595	55	15	and	and	CCONJ
ajst-15595	55	16	established	establish	VERB
ajst-15595	55	17	the	the	DET
ajst-15595	55	18	consistency	consistency	NOUN
ajst-15595	55	19	and	and	CCONJ
ajst-15595	55	20	asymptotic	asymptotic	ADJ
ajst-15595	55	21	normality	normality	NOUN
ajst-15595	55	22	of	of	ADP
ajst-15595	55	23	quantile	quantile	ADJ
ajst-15595	55	24	regression	regression	NOUN
ajst-15595	55	25	estimators	estimator	NOUN
ajst-15595	55	26	as	as	SCONJ
ajst-15595	55	27	the	the	DET
ajst-15595	55	28	number	number	NOUN
ajst-15595	55	29	of	of	ADP
ajst-15595	55	30	individuals	individual	NOUN
ajst-15595	55	31	and	and	CCONJ
ajst-15595	55	32	time	time	NOUN
ajst-15595	55	33	periods	period	NOUN
ajst-15595	55	34	tends	tend	VERB
ajst-15595	55	35	to	to	ADP
ajst-15595	55	36	infinity[8	infinity[8	NOUN
ajst-15595	55	37	]	]	PUNCT
ajst-15595	55	38	.	.	PUNCT
ajst-15595	56	1	considering	consider	VERB
ajst-15595	56	2	the	the	DET
ajst-15595	56	3	nonsmoothness	nonsmoothness	NOUN
ajst-15595	56	4	of	of	ADP
ajst-15595	56	5	the	the	DET
ajst-15595	56	6	true	true	ADJ
ajst-15595	56	7	function	function	NOUN
ajst-15595	56	8	,	,	PUNCT
ajst-15595	56	9	the	the	DET
ajst-15595	56	10	authors	author	NOUN
ajst-15595	56	11	imposed	impose	VERB
ajst-15595	56	12	strong	strong	ADJ
ajst-15595	56	13	restrictions	restriction	NOUN
ajst-15595	56	14	on	on	ADP
ajst-15595	56	15	time	time	NOUN
ajst-15595	56	16	to	to	PART
ajst-15595	56	17	prove	prove	VERB
ajst-15595	56	18	asymptotic	asymptotic	ADJ
ajst-15595	56	19	normality	normality	NOUN
ajst-15595	56	20	.	.	PUNCT
ajst-15595	57	1	aghamohammadi	aghamohammadi	NOUN
ajst-15595	57	2	and	and	CCONJ
ajst-15595	57	3	mohammadi	mohammadi	NOUN
ajst-15595	57	4	(	(	PUNCT
ajst-15595	57	5	2015	2015	NUM
ajst-15595	57	6	)	)	PUNCT
ajst-15595	57	7	analyzed	analyze	VERB
ajst-15595	57	8	longitudinal	longitudinal	ADJ
ajst-15595	57	9	data	data	NOUN
ajst-15595	57	10	models	model	NOUN
ajst-15595	57	11	with	with	ADP
ajst-15595	57	12	random	random	ADJ
ajst-15595	57	13	effects	effect	NOUN
ajst-15595	57	14	from	from	ADP
ajst-15595	57	15	a	a	DET
ajst-15595	57	16	bayesian	bayesian	NOUN
ajst-15595	57	17	perspective	perspective	NOUN
ajst-15595	57	18	using	use	VERB
ajst-15595	57	19	penalized	penalize	VERB
ajst-15595	57	20	quantile	quantile	ADJ
ajst-15595	57	21	regression	regression	NOUN
ajst-15595	57	22	methods[9	methods[9	PROPN
ajst-15595	57	23	]	]	PUNCT
ajst-15595	57	24	.	.	PUNCT
ajst-15595	58	1	galvao	galvao	PROPN
ajst-15595	58	2	and	and	CCONJ
ajst-15595	58	3	kato	kato	PROPN
ajst-15595	58	4	(	(	PUNCT
ajst-15595	58	5	2016	2016	NUM
ajst-15595	58	6	)	)	PUNCT
ajst-15595	58	7	applied	apply	VERB
ajst-15595	58	8	smooth	smooth	ADJ
ajst-15595	58	9	quantile	quantile	ADJ
ajst-15595	58	10	regression	regression	NOUN
ajst-15595	58	11	methods	method	NOUN
ajst-15595	58	12	to	to	ADP
ajst-15595	58	13	panel	panel	NOUN
ajst-15595	58	14	data	datum	NOUN
ajst-15595	58	15	with	with	ADP
ajst-15595	58	16	fixed	fix	VERB
ajst-15595	58	17	effects	effect	NOUN
ajst-15595	58	18	,	,	PUNCT
ajst-15595	58	19	smoothed	smooth	VERB
ajst-15595	58	20	the	the	DET
ajst-15595	58	21	indicator	indicator	NOUN
ajst-15595	58	22	function	function	NOUN
ajst-15595	58	23	using	use	VERB
ajst-15595	58	24	kernel	kernel	PROPN
ajst-15595	58	25	estimation	estimation	NOUN
ajst-15595	58	26	,	,	PUNCT
ajst-15595	58	27	and	and	CCONJ
ajst-15595	58	28	concluded	conclude	VERB
ajst-15595	58	29	that	that	SCONJ
ajst-15595	58	30	the	the	DET
ajst-15595	58	31	fixed	fix	VERB
ajst-15595	58	32	effects	effect	NOUN
ajst-15595	58	33	estimator	estimator	NOUN
ajst-15595	58	34	has	have	VERB
ajst-15595	58	35	a	a	DET
ajst-15595	58	36	limiting	limit	VERB
ajst-15595	58	37	normal	normal	ADJ
ajst-15595	58	38	distribution	distribution	NOUN
ajst-15595	58	39	.	.	PUNCT
ajst-15595	59	1	they	they	PRON
ajst-15595	59	2	also	also	ADV
ajst-15595	59	3	proposed	propose	VERB
ajst-15595	59	4	a	a	DET
ajst-15595	59	5	first	first	ADJ
ajst-15595	59	6	-	-	PUNCT
ajst-15595	59	7	order	order	NOUN
ajst-15595	59	8	bias	bias	NOUN
ajst-15595	59	9	-	-	PUNCT
ajst-15595	59	10	corrected	correct	VERB
ajst-15595	59	11	estimator	estimator	NOUN
ajst-15595	59	12	to	to	PART
ajst-15595	59	13	reduce	reduce	VERB
ajst-15595	59	14	bias	bias	NOUN
ajst-15595	59	15	,	,	PUNCT
ajst-15595	59	16	although	although	SCONJ
ajst-15595	59	17	the	the	DET
ajst-15595	59	18	bias	bias	NOUN
ajst-15595	59	19	correction	correction	NOUN
ajst-15595	59	20	increased	increase	VERB
ajst-15595	59	21	the	the	DET
ajst-15595	59	22	variability	variability	NOUN
ajst-15595	59	23	of	of	ADP
ajst-15595	59	24	small	small	ADJ
ajst-15595	59	25	samples[10	samples[10	NOUN
ajst-15595	59	26	]	]	PUNCT
ajst-15595	59	27	.	.	PUNCT
ajst-15595	60	1	domestic	domestic	ADJ
ajst-15595	60	2	scholars	scholar	NOUN
ajst-15595	60	3	luo	luo	PROPN
ajst-15595	60	4	youxi	youxi	PROPN
ajst-15595	60	5	and	and	CCONJ
ajst-15595	60	6	tian	tian	PROPN
ajst-15595	60	7	maozai	maozai	PROPN
ajst-15595	60	8	studied	study	VERB
ajst-15595	60	9	the	the	DET
ajst-15595	60	10	quantile	quantile	ADJ
ajst-15595	60	11	regression	regression	NOUN
ajst-15595	60	12	method	method	NOUN
ajst-15595	60	13	for	for	ADP
ajst-15595	60	14	panel	panel	NOUN
ajst-15595	60	15	data	datum	NOUN
ajst-15595	60	16	and	and	CCONJ
ajst-15595	60	17	considered	consider	VERB
ajst-15595	60	18	three	three	NUM
ajst-15595	60	19	methods	method	NOUN
ajst-15595	60	20	for	for	ADP
ajst-15595	60	21	handling	handle	VERB
ajst-15595	60	22	fixed	fix	VERB
ajst-15595	60	23	effects	effect	NOUN
ajst-15595	60	24	.	.	PUNCT
ajst-15595	61	1	through	through	ADP
ajst-15595	61	2	monte	monte	PROPN
ajst-15595	61	3	carlo	carlo	PROPN
ajst-15595	61	4	simulation	simulation	PROPN
ajst-15595	61	5	,	,	PUNCT
ajst-15595	61	6	they	they	PRON
ajst-15595	61	7	showed	show	VERB
ajst-15595	61	8	that	that	SCONJ
ajst-15595	61	9	the	the	DET
ajst-15595	61	10	panel	panel	NOUN
ajst-15595	61	11	data	datum	NOUN
ajst-15595	61	12	quantile	quantile	PROPN
ajst-15595	61	13	regression	regression	NOUN
ajst-15595	61	14	model	model	NOUN
ajst-15595	61	15	is	be	AUX
ajst-15595	61	16	more	more	ADV
ajst-15595	61	17	stable	stable	ADJ
ajst-15595	61	18	and	and	CCONJ
ajst-15595	61	19	effective	effective	ADJ
ajst-15595	61	20	than	than	SCONJ
ajst-15595	61	21	mean	mean	VERB
ajst-15595	61	22	regression	regression	NOUN
ajst-15595	61	23	when	when	SCONJ
ajst-15595	61	24	the	the	DET
ajst-15595	61	25	error	error	NOUN
ajst-15595	61	26	does	do	AUX
ajst-15595	61	27	not	not	PART
ajst-15595	61	28	follow	follow	VERB
ajst-15595	61	29	a	a	DET
ajst-15595	61	30	normal	normal	ADJ
ajst-15595	61	31	distribution	distribution	NOUN
ajst-15595	61	32	.	.	PUNCT
ajst-15595	62	1	zhang	zhang	PROPN
ajst-15595	62	2	yuanjie	yuanjie	PROPN
ajst-15595	62	3	and	and	CCONJ
ajst-15595	62	4	tian	tian	PROPN
ajst-15595	62	5	maozai	maozai	PROPN
ajst-15595	62	6	discussed	discuss	VERB
ajst-15595	62	7	the	the	DET
ajst-15595	62	8	panel	panel	NOUN
ajst-15595	62	9	data	datum	NOUN
ajst-15595	62	10	quantile	quantile	ADJ
ajst-15595	62	11	regression	regression	NOUN
ajst-15595	62	12	model	model	NOUN
ajst-15595	62	13	with	with	ADP
ajst-15595	62	14	only	only	ADV
ajst-15595	62	15	fixed	fix	VERB
ajst-15595	62	16	effects	effect	NOUN
ajst-15595	62	17	and	and	CCONJ
ajst-15595	62	18	established	establish	VERB
ajst-15595	62	19	a	a	DET
ajst-15595	62	20	linear	linear	ADJ
ajst-15595	62	21	quantile	quantile	ADJ
ajst-15595	62	22	regression	regression	NOUN
ajst-15595	62	23	model	model	NOUN
ajst-15595	62	24	.	.	PUNCT
ajst-15595	63	1	to	to	PART
ajst-15595	63	2	eliminate	eliminate	VERB
ajst-15595	63	3	fixed	fix	VERB
ajst-15595	63	4	effects	effect	NOUN
ajst-15595	63	5	,	,	PUNCT
ajst-15595	63	6	they	they	PRON
ajst-15595	63	7	used	use	VERB
ajst-15595	63	8	the	the	DET
ajst-15595	63	9	k	k	ADJ
ajst-15595	63	10	-	-	PUNCT
ajst-15595	63	11	step	step	NOUN
ajst-15595	63	12	differencing	differencing	NOUN
ajst-15595	63	13	method	method	NOUN
ajst-15595	63	14	for	for	ADP
ajst-15595	63	15	the	the	DET
ajst-15595	63	16	same	same	ADJ
ajst-15595	63	17	individuals	individual	NOUN
ajst-15595	63	18	before	before	ADP
ajst-15595	63	19	conducting	conduct	VERB
ajst-15595	63	20	the	the	DET
ajst-15595	63	21	quantile	quantile	ADJ
ajst-15595	63	22	regression	regression	NOUN
ajst-15595	63	23	.	.	PUNCT
ajst-15595	64	1	monte	monte	PROPN
ajst-15595	64	2	carlo	carlo	PROPN
ajst-15595	64	3	simulation	simulation	PROPN
ajst-15595	64	4	showed	show	VERB
ajst-15595	64	5	that	that	SCONJ
ajst-15595	64	6	this	this	DET
ajst-15595	64	7	two	two	NUM
ajst-15595	64	8	-	-	PUNCT
ajst-15595	64	9	stage	stage	NOUN
ajst-15595	64	10	method	method	NOUN
ajst-15595	64	11	has	have	VERB
ajst-15595	64	12	good	good	ADJ
ajst-15595	64	13	accuracy	accuracy	NOUN
ajst-15595	64	14	and	and	CCONJ
ajst-15595	64	15	stability	stability	NOUN
ajst-15595	64	16	,	,	PUNCT
ajst-15595	64	17	but	but	CCONJ
ajst-15595	64	18	it	it	PRON
ajst-15595	64	19	is	be	AUX
ajst-15595	64	20	only	only	ADV
ajst-15595	64	21	suitable	suitable	ADJ
ajst-15595	64	22	for	for	ADP
ajst-15595	64	23	linear	linear	ADJ
ajst-15595	64	24	models	model	NOUN
ajst-15595	64	25	,	,	PUNCT
ajst-15595	64	26	and	and	CCONJ
ajst-15595	64	27	further	further	ADJ
ajst-15595	64	28	improvements	improvement	NOUN
ajst-15595	64	29	are	be	AUX
ajst-15595	64	30	needed	need	VERB
ajst-15595	64	31	for	for	ADP
ajst-15595	64	32	nonlinear	nonlinear	ADJ
ajst-15595	64	33	models.wang	models.wang	PROPN
ajst-15595	64	34	na	na	PART
ajst-15595	64	35	studied	study	VERB
ajst-15595	64	36	the	the	DET
ajst-15595	64	37	panel	panel	NOUN
ajst-15595	64	38	data	datum	NOUN
ajst-15595	64	39	quantile	quantile	ADJ
ajst-15595	64	40	regression	regression	NOUN
ajst-15595	64	41	model	model	NOUN
ajst-15595	64	42	and	and	CCONJ
ajst-15595	64	43	considered	consider	VERB
ajst-15595	64	44	the	the	DET
ajst-15595	64	45	estimation	estimation	NOUN
ajst-15595	64	46	of	of	ADP
ajst-15595	64	47	individual	individual	ADJ
ajst-15595	64	48	effects	effect	NOUN
ajst-15595	64	49	in	in	ADP
ajst-15595	64	50	panel	panel	NOUN
ajst-15595	64	51	data	datum	NOUN
ajst-15595	64	52	.	.	PUNCT
ajst-15595	65	1	they	they	PRON
ajst-15595	65	2	proposed	propose	VERB
ajst-15595	65	3	a	a	DET
ajst-15595	65	4	pattern	pattern	NOUN
ajst-15595	65	5	recognition	recognition	NOUN
ajst-15595	65	6	method	method	NOUN
ajst-15595	65	7	to	to	PART
ajst-15595	65	8	simultaneously	simultaneously	ADV
ajst-15595	65	9	estimate	estimate	VERB
ajst-15595	65	10	the	the	DET
ajst-15595	65	11	coefficients	coefficient	NOUN
ajst-15595	65	12	of	of	ADP
ajst-15595	65	13	the	the	DET
ajst-15595	65	14	independent	independent	ADJ
ajst-15595	65	15	variables	variable	NOUN
ajst-15595	65	16	and	and	CCONJ
ajst-15595	65	17	the	the	DET
ajst-15595	65	18	individual	individual	ADJ
ajst-15595	65	19	fixed	fix	VERB
ajst-15595	65	20	effects	effect	NOUN
ajst-15595	65	21	.	.	PUNCT
ajst-15595	66	1	they	they	PRON
ajst-15595	66	2	introduced	introduce	VERB
ajst-15595	66	3	a	a	DET
ajst-15595	66	4	copula	copula	NOUN
ajst-15595	66	5	structure	structure	NOUN
ajst-15595	66	6	and	and	CCONJ
ajst-15595	66	7	proposed	propose	VERB
ajst-15595	66	8	a	a	DET
ajst-15595	66	9	maximum	maximum	ADJ
ajst-15595	66	10	likelihood	likelihood	NOUN
ajst-15595	66	11	estimation	estimation	NOUN
ajst-15595	66	12	method	method	NOUN
ajst-15595	66	13	for	for	ADP
ajst-15595	66	14	panel	panel	NOUN
ajst-15595	66	15	data	datum	NOUN
ajst-15595	66	16	quantile	quantile	ADJ
ajst-15595	66	17	regression	regression	NOUN
ajst-15595	66	18	with	with	ADP
ajst-15595	66	19	random	random	ADJ
ajst-15595	66	20	effects	effect	NOUN
ajst-15595	66	21	.	.	PUNCT
ajst-15595	67	1	xu	xu	PROPN
ajst-15595	67	2	jie	jie	PROPN
ajst-15595	67	3	extended	extend	VERB
ajst-15595	67	4	the	the	DET
ajst-15595	67	5	research	research	NOUN
ajst-15595	67	6	to	to	ADP
ajst-15595	67	7	composite	composite	ADJ
ajst-15595	67	8	quantile	quantile	ADJ
ajst-15595	67	9	regression	regression	NOUN
ajst-15595	67	10	method	method	NOUN
ajst-15595	67	11	on	on	ADP
ajst-15595	67	12	individual	individual	ADJ
ajst-15595	67	13	fixed	fix	VERB
ajst-15595	67	14	effects	effect	NOUN
ajst-15595	67	15	panel	panel	NOUN
ajst-15595	67	16	models	model	NOUN
ajst-15595	67	17	to	to	PART
ajst-15595	67	18	achieve	achieve	VERB
ajst-15595	67	19	more	more	ADV
ajst-15595	67	20	efficient	efficient	ADJ
ajst-15595	67	21	estimation	estimation	NOUN
ajst-15595	67	22	of	of	ADP
ajst-15595	67	23	regression	regression	NOUN
ajst-15595	67	24	coefficients	coefficient	NOUN
ajst-15595	67	25	by	by	ADP
ajst-15595	67	26	integrating	integrate	VERB
ajst-15595	67	27	multiple	multiple	ADJ
ajst-15595	67	28	quantiles	quantile	NOUN
ajst-15595	67	29	.	.	PUNCT
ajst-15595	68	1	this	this	DET
ajst-15595	68	2	method	method	NOUN
ajst-15595	68	3	retains	retain	VERB
ajst-15595	68	4	the	the	DET
ajst-15595	68	5	robustness	robustness	NOUN
ajst-15595	68	6	of	of	ADP
ajst-15595	68	7	quantile	quantile	ADJ
ajst-15595	68	8	regression	regression	NOUN
ajst-15595	68	9	and	and	CCONJ
ajst-15595	68	10	improves	improve	VERB
ajst-15595	68	11	estimation	estimation	NOUN
ajst-15595	68	12	efficiency	efficiency	NOUN
ajst-15595	68	13	through	through	ADP
ajst-15595	68	14	composition	composition	NOUN
ajst-15595	68	15	.	.	PUNCT
ajst-15595	69	1	by	by	ADP
ajst-15595	69	2	introducing	introduce	VERB
ajst-15595	69	3	a	a	DET
ajst-15595	69	4	specific	specific	ADJ
ajst-15595	69	5	idempotent	idempotent	ADJ
ajst-15595	69	6	matrix	matrix	NOUN
ajst-15595	69	7	to	to	PART
ajst-15595	69	8	eliminate	eliminate	VERB
ajst-15595	69	9	the	the	DET
ajst-15595	69	10	individual	individual	ADJ
ajst-15595	69	11	effect	effect	NOUN
ajst-15595	69	12	term	term	NOUN
ajst-15595	69	13	,	,	PUNCT
ajst-15595	69	14	it	it	PRON
ajst-15595	69	15	avoids	avoid	VERB
ajst-15595	69	16	the	the	DET
ajst-15595	69	17	problem	problem	NOUN
ajst-15595	69	18	of	of	ADP
ajst-15595	69	19	parameter	parameter	NOUN
ajst-15595	69	20	curse	curse	NOUN
ajst-15595	69	21	and	and	CCONJ
ajst-15595	69	22	transforms	transform	VERB
ajst-15595	69	23	the	the	DET
ajst-15595	69	24	panel	panel	NOUN
ajst-15595	69	25	data	datum	NOUN
ajst-15595	69	26	model	model	NOUN
ajst-15595	69	27	into	into	ADP
ajst-15595	69	28	a	a	DET
ajst-15595	69	29	linear	linear	ADJ
ajst-15595	69	30	model	model	NOUN
ajst-15595	69	31	.	.	PUNCT
ajst-15595	70	1	then	then	ADV
ajst-15595	70	2	,	,	PUNCT
ajst-15595	70	3	the	the	DET
ajst-15595	70	4	composite	composite	ADJ
ajst-15595	70	5	quantile	quantile	ADJ
ajst-15595	70	6	regression	regression	NOUN
ajst-15595	70	7	method	method	NOUN
ajst-15595	70	8	is	be	AUX
ajst-15595	70	9	used	use	VERB
ajst-15595	70	10	to	to	PART
ajst-15595	70	11	construct	construct	VERB
ajst-15595	70	12	the	the	DET
ajst-15595	70	13	objective	objective	ADJ
ajst-15595	70	14	function	function	NOUN
ajst-15595	70	15	of	of	ADP
ajst-15595	70	16	regression	regression	NOUN
ajst-15595	70	17	coefficients	coefficient	NOUN
ajst-15595	70	18	.	.	PUNCT
ajst-15595	71	1	the	the	DET
ajst-15595	71	2	results	result	NOUN
ajst-15595	71	3	show	show	VERB
ajst-15595	71	4	that	that	SCONJ
ajst-15595	71	5	,	,	PUNCT
ajst-15595	71	6	compared	compare	VERB
ajst-15595	71	7	to	to	ADP
ajst-15595	71	8	quantile	quantile	ADJ
ajst-15595	71	9	regression	regression	NOUN
ajst-15595	71	10	,	,	PUNCT
ajst-15595	71	11	composite	composite	ADJ
ajst-15595	71	12	quantile	quantile	ADJ
ajst-15595	71	13	regression	regression	NOUN
ajst-15595	71	14	has	have	VERB
ajst-15595	71	15	better	well	ADJ
ajst-15595	71	16	stability	stability	NOUN
ajst-15595	71	17	under	under	ADP
ajst-15595	71	18	non	non	ADJ
ajst-15595	71	19	-	-	ADJ
ajst-15595	71	20	normal	normal	ADJ
ajst-15595	71	21	conditions	condition	NOUN
ajst-15595	71	22	.	.	PUNCT
ajst-15595	72	1	this	this	DET
ajst-15595	72	2	method	method	NOUN
ajst-15595	72	3	has	have	AUX
ajst-15595	72	4	greatly	greatly	ADV
ajst-15595	72	5	promoted	promote	VERB
ajst-15595	72	6	the	the	DET
ajst-15595	72	7	development	development	NOUN
ajst-15595	72	8	of	of	ADP
ajst-15595	72	9	quantile	quantile	ADJ
ajst-15595	72	10	regression	regression	NOUN
ajst-15595	72	11	,	,	PUNCT
ajst-15595	72	12	but	but	CCONJ
ajst-15595	72	13	it	it	PRON
ajst-15595	72	14	is	be	AUX
ajst-15595	72	15	limited	limit	VERB
ajst-15595	72	16	to	to	ADP
ajst-15595	72	17	linear	linear	ADJ
ajst-15595	72	18	models	model	NOUN
ajst-15595	72	19	and	and	CCONJ
ajst-15595	72	20	further	further	ADJ
ajst-15595	72	21	research	research	NOUN
ajst-15595	72	22	is	be	AUX
ajst-15595	72	23	needed	need	VERB
ajst-15595	72	24	for	for	ADP
ajst-15595	72	25	panel	panel	NOUN
ajst-15595	72	26	data	datum	NOUN
ajst-15595	72	27	with	with	ADP
ajst-15595	72	28	non	non	ADJ
ajst-15595	72	29	-	-	ADJ
ajst-15595	72	30	linear	linear	ADJ
ajst-15595	72	31	relationships.kong	relationships.kong	NOUN
ajst-15595	72	32	hang	hang	PROPN
ajst-15595	72	33	compared	compare	VERB
ajst-15595	72	34	the	the	DET
ajst-15595	72	35	classical	classical	ADJ
ajst-15595	72	36	kernel	kernel	NOUN
ajst-15595	72	37	estimation	estimation	PROPN
ajst-15595	72	38	,	,	PUNCT
ajst-15595	72	39	polynomial	polynomial	ADJ
ajst-15595	72	40	estimation	estimation	NOUN
ajst-15595	72	41	,	,	PUNCT
ajst-15595	72	42	and	and	CCONJ
ajst-15595	72	43	k	k	X
ajst-15595	72	44	-	-	PUNCT
ajst-15595	72	45	nearest	near	ADJ
ajst-15595	72	46	neighbor	neighbor	NOUN
ajst-15595	72	47	estimation	estimation	NOUN
ajst-15595	72	48	methods	method	NOUN
ajst-15595	72	49	with	with	ADP
ajst-15595	72	50	a	a	DET
ajst-15595	72	51	bayesian	bayesian	NOUN
ajst-15595	72	52	nonparametric	nonparametric	NOUN
ajst-15595	72	53	quantile	quantile	PROPN
ajst-15595	72	54	regression	regression	NOUN
ajst-15595	72	55	model	model	NOUN
ajst-15595	72	56	.	.	PUNCT
ajst-15595	73	1	they	they	PRON
ajst-15595	73	2	obtained	obtain	VERB
ajst-15595	73	3	useful	useful	ADJ
ajst-15595	73	4	conclusions	conclusion	NOUN
ajst-15595	73	5	:	:	PUNCT
ajst-15595	73	6	quantile	quantile	ADJ
ajst-15595	73	7	regression	regression	NOUN
ajst-15595	73	8	can	can	AUX
ajst-15595	73	9	set	set	VERB
ajst-15595	73	10	quantile	quantile	ADJ
ajst-15595	73	11	points	point	NOUN
ajst-15595	73	12	according	accord	VERB
ajst-15595	73	13	to	to	ADP
ajst-15595	73	14	needs	need	NOUN
ajst-15595	73	15	,	,	PUNCT
ajst-15595	73	16	and	and	CCONJ
ajst-15595	73	17	determine	determine	VERB
ajst-15595	73	18	the	the	DET
ajst-15595	73	19	optimal	optimal	ADJ
ajst-15595	73	20	quantile	quantile	ADJ
ajst-15595	73	21	points	point	NOUN
ajst-15595	73	22	through	through	ADP
ajst-15595	73	23	model	model	NOUN
ajst-15595	73	24	evaluation	evaluation	NOUN
ajst-15595	73	25	;	;	PUNCT
ajst-15595	73	26	they	they	PRON
ajst-15595	73	27	also	also	ADV
ajst-15595	73	28	proposed	propose	VERB
ajst-15595	73	29	a	a	DET
ajst-15595	73	30	new	new	ADJ
ajst-15595	73	31	simplified	simplified	ADJ
ajst-15595	73	32	bayesian	bayesian	NOUN
ajst-15595	73	33	method	method	NOUN
ajst-15595	73	34	,	,	PUNCT
ajst-15595	73	35	which	which	PRON
ajst-15595	73	36	greatly	greatly	ADV
ajst-15595	73	37	improves	improve	VERB
ajst-15595	73	38	computational	computational	ADJ
ajst-15595	73	39	efficiency	efficiency	NOUN
ajst-15595	73	40	by	by	ADP
ajst-15595	73	41	reducing	reduce	VERB
ajst-15595	73	42	the	the	DET
ajst-15595	73	43	likelihood	likelihood	NOUN
ajst-15595	73	44	function	function	NOUN
ajst-15595	73	45	from	from	ADP
ajst-15595	73	46	.through	.through	NOUN
ajst-15595	73	47	gibbs	gibbs	PROPN
ajst-15595	73	48	sampling	sample	VERB
ajst-15595	73	49	for	for	ADP
ajst-15595	73	50	model	model	NOUN
ajst-15595	73	51	calibration	calibration	NOUN
ajst-15595	73	52	,	,	PUNCT
ajst-15595	73	53	the	the	DET
ajst-15595	73	54	accuracy	accuracy	NOUN
ajst-15595	73	55	is	be	AUX
ajst-15595	73	56	improved	improve	VERB
ajst-15595	73	57	.	.	PUNCT
ajst-15595	74	1	he	he	PRON
ajst-15595	74	2	jing	je	VERB
ajst-15595	74	3	et	et	PROPN
ajst-15595	74	4	al	al	PROPN
ajst-15595	74	5	.	.	PROPN
ajst-15595	75	1	also	also	ADV
ajst-15595	75	2	studied	study	VERB
ajst-15595	75	3	crossquantile	crossquantile	NOUN
ajst-15595	75	4	regression	regression	NOUN
ajst-15595	75	5	curve	curve	NOUN
ajst-15595	75	6	models	model	NOUN
ajst-15595	75	7	of	of	ADP
ajst-15595	75	8	additive	additive	ADJ
ajst-15595	75	9	models	model	NOUN
ajst-15595	75	10	and	and	CCONJ
ajst-15595	75	11	applied	apply	VERB
ajst-15595	75	12	them	they	PRON
ajst-15595	75	13	to	to	ADP
ajst-15595	75	14	housing	housing	NOUN
ajst-15595	75	15	price	price	NOUN
ajst-15595	75	16	research	research	NOUN
ajst-15595	75	17	.	.	PUNCT
ajst-15595	76	1	they	they	PRON
ajst-15595	76	2	analyzed	analyze	VERB
ajst-15595	76	3	the	the	DET
ajst-15595	76	4	impact	impact	NOUN
ajst-15595	76	5	of	of	ADP
ajst-15595	76	6	various	various	ADJ
ajst-15595	76	7	variables	variable	NOUN
ajst-15595	76	8	on	on	ADP
ajst-15595	76	9	housing	housing	NOUN
ajst-15595	76	10	prices	price	NOUN
ajst-15595	76	11	under	under	ADP
ajst-15595	76	12	different	different	ADJ
ajst-15595	76	13	quantiles	quantile	NOUN
ajst-15595	76	14	.	.	PUNCT
ajst-15595	77	1	however	however	ADV
ajst-15595	77	2	,	,	PUNCT
ajst-15595	77	3	the	the	DET
ajst-15595	77	4	above	above	ADJ
ajst-15595	77	5	methods	method	NOUN
ajst-15595	77	6	rely	rely	VERB
ajst-15595	77	7	heavily	heavily	ADV
ajst-15595	77	8	on	on	ADP
ajst-15595	77	9	the	the	DET
ajst-15595	77	10	large	large	ADJ
ajst-15595	77	11	sample	sample	NOUN
ajst-15595	77	12	properties	property	NOUN
ajst-15595	77	13	of	of	ADP
ajst-15595	77	14	estimates	estimate	NOUN
ajst-15595	77	15	in	in	ADP
ajst-15595	77	16	the	the	DET
ajst-15595	77	17	model	model	NOUN
ajst-15595	77	18	testing	testing	NOUN
ajst-15595	77	19	and	and	CCONJ
ajst-15595	77	20	174	174	NUM
ajst-15595	77	21	confidence	confidence	NOUN
ajst-15595	77	22	interval	interval	NOUN
ajst-15595	77	23	construction	construction	NOUN
ajst-15595	77	24	processes	process	NOUN
ajst-15595	77	25	.	.	PUNCT
ajst-15595	78	1	in	in	ADP
ajst-15595	78	2	addition	addition	NOUN
ajst-15595	78	3	,	,	PUNCT
ajst-15595	78	4	in	in	ADP
ajst-15595	78	5	the	the	DET
ajst-15595	78	6	analysis	analysis	NOUN
ajst-15595	78	7	of	of	ADP
ajst-15595	78	8	panel	panel	NOUN
ajst-15595	78	9	data	datum	NOUN
ajst-15595	78	10	quantile	quantile	ADJ
ajst-15595	78	11	regression	regression	NOUN
ajst-15595	78	12	models	model	NOUN
ajst-15595	78	13	,	,	PUNCT
ajst-15595	78	14	scholars	scholar	NOUN
ajst-15595	78	15	have	have	AUX
ajst-15595	78	16	also	also	ADV
ajst-15595	78	17	devoted	devote	VERB
ajst-15595	78	18	themselves	themselves	PRON
ajst-15595	78	19	to	to	ADP
ajst-15595	78	20	variable	variable	ADJ
ajst-15595	78	21	selection	selection	NOUN
ajst-15595	78	22	.	.	PUNCT
ajst-15595	79	1	by	by	ADP
ajst-15595	79	2	applying	apply	VERB
ajst-15595	79	3	penalties	penalty	NOUN
ajst-15595	79	4	to	to	ADP
ajst-15595	79	5	variables	variable	NOUN
ajst-15595	79	6	to	to	PART
ajst-15595	79	7	select	select	VERB
ajst-15595	79	8	them	they	PRON
ajst-15595	79	9	and	and	CCONJ
ajst-15595	79	10	considering	consider	VERB
ajst-15595	79	11	the	the	DET
ajst-15595	79	12	influence	influence	NOUN
ajst-15595	79	13	of	of	ADP
ajst-15595	79	14	random	random	ADJ
ajst-15595	79	15	effects	effect	NOUN
ajst-15595	79	16	on	on	ADP
ajst-15595	79	17	covariates	covariate	NOUN
ajst-15595	79	18	,	,	PUNCT
ajst-15595	79	19	they	they	PRON
ajst-15595	79	20	used	use	VERB
ajst-15595	79	21	a	a	DET
ajst-15595	79	22	bayesian	bayesian	NOUN
ajst-15595	79	23	hierarchical	hierarchical	ADJ
ajst-15595	79	24	model	model	NOUN
ajst-15595	79	25	and	and	CCONJ
ajst-15595	79	26	used	use	VERB
ajst-15595	79	27	lasso	lasso	NOUN
ajst-15595	79	28	and	and	CCONJ
ajst-15595	79	29	adaptive	adaptive	ADJ
ajst-15595	79	30	lasso	lasso	NOUN
ajst-15595	79	31	penalties	penalty	NOUN
ajst-15595	79	32	in	in	ADP
ajst-15595	79	33	the	the	DET
ajst-15595	79	34	quantile	quantile	ADJ
ajst-15595	79	35	regression	regression	NOUN
ajst-15595	79	36	test	test	NOUN
ajst-15595	79	37	function	function	NOUN
ajst-15595	79	38	to	to	PART
ajst-15595	79	39	reduce	reduce	VERB
ajst-15595	79	40	this	this	DET
ajst-15595	79	41	influence	influence	NOUN
ajst-15595	79	42	.	.	PUNCT
ajst-15595	80	1	this	this	DET
ajst-15595	80	2	method	method	NOUN
ajst-15595	80	3	directly	directly	ADV
ajst-15595	80	4	assumes	assume	VERB
ajst-15595	80	5	a	a	DET
ajst-15595	80	6	linear	linear	ADJ
ajst-15595	80	7	model	model	NOUN
ajst-15595	80	8	and	and	CCONJ
ajst-15595	80	9	has	have	VERB
ajst-15595	80	10	good	good	ADJ
ajst-15595	80	11	performance	performance	NOUN
ajst-15595	80	12	in	in	ADP
ajst-15595	80	13	dealing	deal	VERB
ajst-15595	80	14	with	with	ADP
ajst-15595	80	15	data	datum	NOUN
ajst-15595	80	16	with	with	ADP
ajst-15595	80	17	linear	linear	ADJ
ajst-15595	80	18	relationships	relationship	NOUN
ajst-15595	80	19	proposed	propose	VERB
ajst-15595	80	20	a	a	DET
ajst-15595	80	21	double	double	ADJ
ajst-15595	80	22	-	-	PUNCT
ajst-15595	80	23	regularized	regularize	VERB
ajst-15595	80	24	quantile	quantile	ADJ
ajst-15595	80	25	regression	regression	NOUN
ajst-15595	80	26	method	method	NOUN
ajst-15595	80	27	for	for	ADP
ajst-15595	80	28	high	high	ADJ
ajst-15595	80	29	-	-	PUNCT
ajst-15595	80	30	dimensional	dimensional	ADJ
ajst-15595	80	31	mixed	mixed	ADJ
ajst-15595	80	32	effects	effect	NOUN
ajst-15595	80	33	models	model	NOUN
ajst-15595	80	34	.	.	PUNCT
ajst-15595	81	1	by	by	ADP
ajst-15595	81	2	simultaneously	simultaneously	ADV
ajst-15595	81	3	applying	apply	VERB
ajst-15595	81	4	l1	l1	PROPN
ajst-15595	81	5	regularization	regularization	NOUN
ajst-15595	81	6	penalties	penalty	NOUN
ajst-15595	81	7	to	to	ADP
ajst-15595	81	8	both	both	CCONJ
ajst-15595	81	9	random	random	ADJ
ajst-15595	81	10	and	and	CCONJ
ajst-15595	81	11	fixed	fix	VERB
ajst-15595	81	12	effects	effect	NOUN
ajst-15595	81	13	coefficients	coefficient	NOUN
ajst-15595	81	14	,	,	PUNCT
ajst-15595	81	15	important	important	ADJ
ajst-15595	81	16	explanatory	explanatory	ADJ
ajst-15595	81	17	variables	variable	NOUN
ajst-15595	81	18	can	can	AUX
ajst-15595	81	19	be	be	AUX
ajst-15595	81	20	selected	select	VERB
ajst-15595	81	21	,	,	PUNCT
ajst-15595	81	22	and	and	CCONJ
ajst-15595	81	23	bias	bias	NOUN
ajst-15595	81	24	caused	cause	VERB
ajst-15595	81	25	by	by	ADP
ajst-15595	81	26	individual	individual	ADJ
ajst-15595	81	27	random	random	ADJ
ajst-15595	81	28	fluctuations	fluctuation	NOUN
ajst-15595	81	29	can	can	AUX
ajst-15595	81	30	be	be	AUX
ajst-15595	81	31	eliminated	eliminate	VERB
ajst-15595	81	32	.	.	PUNCT
ajst-15595	82	1	luo	luo	PROPN
ajst-15595	82	2	youxi	youxi	PROPN
ajst-15595	82	3	and	and	CCONJ
ajst-15595	82	4	li	li	PROPN
ajst-15595	82	5	hanfang	hanfang	PROPN
ajst-15595	82	6	studied	study	VERB
ajst-15595	82	7	longitudinal	longitudinal	ADJ
ajst-15595	82	8	data	datum	NOUN
ajst-15595	82	9	models	model	NOUN
ajst-15595	82	10	with	with	ADP
ajst-15595	82	11	multiple	multiple	ADJ
ajst-15595	82	12	random	random	ADJ
ajst-15595	82	13	effects	effect	NOUN
ajst-15595	82	14	and	and	CCONJ
ajst-15595	82	15	proposed	propose	VERB
ajst-15595	82	16	two	two	NUM
ajst-15595	82	17	new	new	ADJ
ajst-15595	82	18	penalty	penalty	NOUN
ajst-15595	82	19	quantile	quantile	NOUN
ajst-15595	82	20	regression	regression	NOUN
ajst-15595	82	21	methods	method	NOUN
ajst-15595	82	22	.	.	PUNCT
ajst-15595	83	1	by	by	ADP
ajst-15595	83	2	applying	apply	VERB
ajst-15595	83	3	lasso	lasso	NOUN
ajst-15595	83	4	and	and	CCONJ
ajst-15595	83	5	adaptive	adaptive	ADJ
ajst-15595	83	6	lasso	lasso	NOUN
ajst-15595	83	7	penalties	penalty	NOUN
ajst-15595	83	8	to	to	ADP
ajst-15595	83	9	the	the	DET
ajst-15595	83	10	quantile	quantile	ADJ
ajst-15595	83	11	regression	regression	NOUN
ajst-15595	83	12	coefficients	coefficient	NOUN
ajst-15595	83	13	,	,	PUNCT
ajst-15595	83	14	both	both	DET
ajst-15595	83	15	methods	method	NOUN
ajst-15595	83	16	can	can	AUX
ajst-15595	83	17	automatically	automatically	ADV
ajst-15595	83	18	select	select	VERB
ajst-15595	83	19	independent	independent	ADJ
ajst-15595	83	20	variables	variable	NOUN
ajst-15595	83	21	in	in	ADP
ajst-15595	83	22	the	the	DET
ajst-15595	83	23	model	model	NOUN
ajst-15595	83	24	.	.	PUNCT
ajst-15595	84	1	the	the	DET
ajst-15595	84	2	proposed	propose	VERB
ajst-15595	84	3	methods	method	NOUN
ajst-15595	84	4	not	not	PART
ajst-15595	84	5	only	only	ADV
ajst-15595	84	6	accurately	accurately	ADV
ajst-15595	84	7	estimate	estimate	VERB
ajst-15595	84	8	and	and	CCONJ
ajst-15595	84	9	select	select	VERB
ajst-15595	84	10	quantile	quantile	ADJ
ajst-15595	84	11	regression	regression	NOUN
ajst-15595	84	12	coefficients	coefficient	NOUN
ajst-15595	84	13	but	but	CCONJ
ajst-15595	84	14	also	also	ADV
ajst-15595	84	15	have	have	VERB
ajst-15595	84	16	strong	strong	ADJ
ajst-15595	84	17	robustness	robustness	NOUN
ajst-15595	84	18	to	to	ADP
ajst-15595	84	19	random	random	ADJ
ajst-15595	84	20	error	error	NOUN
ajst-15595	84	21	distributions	distribution	NOUN
ajst-15595	84	22	.	.	PUNCT
ajst-15595	85	1	furthermore	furthermore	ADV
ajst-15595	85	2	,	,	PUNCT
ajst-15595	85	3	there	there	PRON
ajst-15595	85	4	are	be	VERB
ajst-15595	85	5	studies	study	NOUN
ajst-15595	85	6	on	on	ADP
ajst-15595	85	7	the	the	DET
ajst-15595	85	8	application	application	NOUN
ajst-15595	85	9	of	of	ADP
ajst-15595	85	10	quantile	quantile	ADJ
ajst-15595	85	11	regression	regression	NOUN
ajst-15595	85	12	methods	method	NOUN
ajst-15595	85	13	.	.	PUNCT
ajst-15595	86	1	in	in	ADP
ajst-15595	86	2	this	this	DET
ajst-15595	86	3	regard	regard	NOUN
ajst-15595	86	4	,	,	PUNCT
ajst-15595	86	5	barnes	barne	NOUN
ajst-15595	86	6	and	and	CCONJ
ajst-15595	86	7	w.	w.	PROPN
ajst-15595	86	8	hughes	hughes	PROPN
ajst-15595	86	9	(	(	PUNCT
ajst-15595	86	10	2002	2002	NUM
ajst-15595	86	11	)	)	PUNCT
ajst-15595	86	12	used	use	VERB
ajst-15595	86	13	quantile	quantile	ADJ
ajst-15595	86	14	regression	regression	NOUN
ajst-15595	86	15	to	to	PART
ajst-15595	86	16	analyze	analyze	VERB
ajst-15595	86	17	the	the	DET
ajst-15595	86	18	return	return	NOUN
ajst-15595	86	19	of	of	ADP
ajst-15595	86	20	cross	cross	ADJ
ajst-15595	86	21	-	-	ADJ
ajst-15595	86	22	sector	sector	ADJ
ajst-15595	86	23	public	public	ADJ
ajst-15595	86	24	bond	bond	NOUN
ajst-15595	86	25	markets	market	NOUN
ajst-15595	86	26	.	.	PUNCT
ajst-15595	87	1	buhai	buhai	PROPN
ajst-15595	87	2	(	(	PUNCT
ajst-15595	87	3	2004	2004	NUM
ajst-15595	87	4	)	)	PUNCT
ajst-15595	87	5	studied	study	VERB
ajst-15595	87	6	its	its	PRON
ajst-15595	87	7	application	application	NOUN
ajst-15595	87	8	in	in	ADP
ajst-15595	87	9	duration	duration	NOUN
ajst-15595	87	10	models	model	NOUN
ajst-15595	87	11	and	and	CCONJ
ajst-15595	87	12	cyclic	cyclic	ADJ
ajst-15595	87	13	structure	structure	NOUN
ajst-15595	87	14	equation	equation	NOUN
ajst-15595	87	15	models	model	NOUN
ajst-15595	87	16	.	.	PUNCT
ajst-15595	88	1	xu	xu	PROPN
ajst-15595	88	2	and	and	CCONJ
ajst-15595	88	3	lin	lin	PROPN
ajst-15595	88	4	(	(	PUNCT
ajst-15595	88	5	2016	2016	NUM
ajst-15595	88	6	)	)	PUNCT
ajst-15595	88	7	studied	study	VERB
ajst-15595	88	8	the	the	DET
ajst-15595	88	9	carbon	carbon	NOUN
ajst-15595	88	10	dioxide	dioxide	NOUN
ajst-15595	88	11	emissions	emission	NOUN
ajst-15595	88	12	at	at	ADP
ajst-15595	88	13	the	the	DET
ajst-15595	88	14	provincial	provincial	ADJ
ajst-15595	88	15	level	level	NOUN
ajst-15595	88	16	in	in	ADP
ajst-15595	88	17	china	china	PROPN
ajst-15595	88	18	and	and	CCONJ
ajst-15595	88	19	attempted	attempt	VERB
ajst-15595	88	20	to	to	PART
ajst-15595	88	21	identify	identify	VERB
ajst-15595	88	22	differences	difference	NOUN
ajst-15595	88	23	among	among	ADP
ajst-15595	88	24	different	different	ADJ
ajst-15595	88	25	quantiles[11	quantiles[11	NOUN
ajst-15595	88	26	]	]	PUNCT
ajst-15595	88	27	.	.	PUNCT
ajst-15595	89	1	these	these	DET
ajst-15595	89	2	studies	study	NOUN
ajst-15595	89	3	applying	apply	VERB
ajst-15595	89	4	quantile	quantile	ADJ
ajst-15595	89	5	regression	regression	NOUN
ajst-15595	89	6	to	to	ADP
ajst-15595	89	7	real	real	ADJ
ajst-15595	89	8	data	datum	NOUN
ajst-15595	89	9	have	have	AUX
ajst-15595	89	10	yielded	yield	VERB
ajst-15595	89	11	valuable	valuable	ADJ
ajst-15595	89	12	conclusions	conclusion	NOUN
ajst-15595	89	13	.	.	PUNCT
ajst-15595	90	1	roca	roca	NOUN
ajst-15595	90	2	-	-	PUNCT
ajst-15595	90	3	pardiñas	pardiñas	NOUN
ajst-15595	90	4	and	and	CCONJ
ajst-15595	90	5	ordóñez	ordóñez	NOUN
ajst-15595	90	6	(	(	PUNCT
ajst-15595	90	7	2019	2019	NUM
ajst-15595	90	8	)	)	PUNCT
ajst-15595	90	9	studied	study	VERB
ajst-15595	90	10	sulfur	sulfur	NOUN
ajst-15595	90	11	dioxide	dioxide	NOUN
ajst-15595	90	12	pollution	pollution	NOUN
ajst-15595	90	13	using	use	VERB
ajst-15595	90	14	a	a	DET
ajst-15595	90	15	semiparametric	semiparametric	ADJ
ajst-15595	90	16	additive	additive	NOUN
ajst-15595	90	17	quantile	quantile	ADJ
ajst-15595	90	18	regression	regression	NOUN
ajst-15595	90	19	model	model	NOUN
ajst-15595	90	20	,	,	PUNCT
ajst-15595	90	21	and	and	CCONJ
ajst-15595	90	22	solved	solve	VERB
ajst-15595	90	23	the	the	DET
ajst-15595	90	24	model	model	NOUN
ajst-15595	90	25	using	use	VERB
ajst-15595	90	26	the	the	DET
ajst-15595	90	27	two	two	NUM
ajst-15595	90	28	-	-	PUNCT
ajst-15595	90	29	stage	stage	NOUN
ajst-15595	90	30	backfitting	backfitting	NOUN
ajst-15595	90	31	algorithm[12	algorithm[12	NOUN
ajst-15595	90	32	]	]	PUNCT
ajst-15595	90	33	.	.	PUNCT
ajst-15595	91	1	the	the	DET
ajst-15595	91	2	model	model	NOUN
ajst-15595	91	3	was	be	AUX
ajst-15595	91	4	tested	test	VERB
ajst-15595	91	5	with	with	ADP
ajst-15595	91	6	simulated	simulate	VERB
ajst-15595	91	7	and	and	CCONJ
ajst-15595	91	8	real	real	ADJ
ajst-15595	91	9	data	datum	NOUN
ajst-15595	91	10	,	,	PUNCT
ajst-15595	91	11	confirming	confirm	VERB
ajst-15595	91	12	its	its	PRON
ajst-15595	91	13	effectiveness	effectiveness	NOUN
ajst-15595	91	14	.	.	PUNCT
ajst-15595	92	1	however	however	ADV
ajst-15595	92	2	,	,	PUNCT
ajst-15595	92	3	this	this	DET
ajst-15595	92	4	algorithm	algorithm	NOUN
ajst-15595	92	5	is	be	AUX
ajst-15595	92	6	dependent	dependent	ADJ
ajst-15595	92	7	on	on	ADP
ajst-15595	92	8	initial	initial	ADJ
ajst-15595	92	9	values	value	NOUN
ajst-15595	92	10	and	and	CCONJ
ajst-15595	92	11	has	have	VERB
ajst-15595	92	12	high	high	ADJ
ajst-15595	92	13	computational	computational	ADJ
ajst-15595	92	14	complexity	complexity	NOUN
ajst-15595	92	15	.	.	PUNCT
ajst-15595	93	1	to	to	PART
ajst-15595	93	2	avoid	avoid	VERB
ajst-15595	93	3	relying	rely	VERB
ajst-15595	93	4	on	on	ADP
ajst-15595	93	5	large	large	ADJ
ajst-15595	93	6	sample	sample	NOUN
ajst-15595	93	7	properties	property	NOUN
ajst-15595	93	8	and	and	CCONJ
ajst-15595	93	9	complex	complex	ADJ
ajst-15595	93	10	iterative	iterative	ADJ
ajst-15595	93	11	algorithms	algorithm	NOUN
ajst-15595	93	12	,	,	PUNCT
ajst-15595	93	13	fredj	fredj	NOUN
ajst-15595	93	14	and	and	CCONJ
ajst-15595	93	15	nabila	nabila	PROPN
ajst-15595	93	16	(	(	PUNCT
ajst-15595	93	17	2017	2017	NUM
ajst-15595	93	18	)	)	PUNCT
ajst-15595	93	19	studied	study	VERB
ajst-15595	93	20	the	the	DET
ajst-15595	93	21	impact	impact	NOUN
ajst-15595	93	22	of	of	ADP
ajst-15595	93	23	geographical	geographical	ADJ
ajst-15595	93	24	environment	environment	NOUN
ajst-15595	93	25	on	on	ADP
ajst-15595	93	26	islamic	islamic	ADJ
ajst-15595	93	27	banking	banking	NOUN
ajst-15595	93	28	performance[13	performance[13	NOUN
ajst-15595	93	29	]	]	PUNCT
ajst-15595	93	30	,	,	PUNCT
ajst-15595	93	31	and	and	CCONJ
ajst-15595	93	32	chang	chang	PROPN
ajst-15595	93	33	et	et	PROPN
ajst-15595	93	34	al	al	PROPN
ajst-15595	93	35	.	.	PROPN
ajst-15595	94	1	(	(	PUNCT
ajst-15595	94	2	2018	2018	NUM
ajst-15595	94	3	)	)	PUNCT
ajst-15595	94	4	examined	examine	VERB
ajst-15595	94	5	whether	whether	SCONJ
ajst-15595	94	6	governmental	governmental	ADJ
ajst-15595	94	7	ideology	ideology	NOUN
ajst-15595	94	8	affects	affect	VERB
ajst-15595	94	9	environmental	environmental	ADJ
ajst-15595	94	10	pollution[14	pollution[14	PROPN
ajst-15595	94	11	]	]	PUNCT
ajst-15595	94	12	.	.	PUNCT
ajst-15595	95	1	ž	ž	INTJ
ajst-15595	95	2	šarić	šarić	NOUN
ajst-15595	95	3	et	et	PROPN
ajst-15595	95	4	al	al	PROPN
ajst-15595	95	5	.	.	PROPN
ajst-15595	96	1	(	(	PUNCT
ajst-15595	96	2	2018	2018	NUM
ajst-15595	96	3	)	)	PUNCT
ajst-15595	96	4	used	use	VERB
ajst-15595	96	5	quantile	quantile	ADJ
ajst-15595	96	6	regression	regression	NOUN
ajst-15595	96	7	to	to	PART
ajst-15595	96	8	study	study	VERB
ajst-15595	96	9	the	the	DET
ajst-15595	96	10	relationship	relationship	NOUN
ajst-15595	96	11	between	between	ADP
ajst-15595	96	12	road	road	NOUN
ajst-15595	96	13	signs	sign	NOUN
ajst-15595	96	14	placed	place	VERB
ajst-15595	96	15	on	on	ADP
ajst-15595	96	16	state	state	NOUN
ajst-15595	96	17	roads	road	NOUN
ajst-15595	96	18	in	in	ADP
ajst-15595	96	19	13	13	NUM
ajst-15595	96	20	states	state	NOUN
ajst-15595	96	21	over	over	ADP
ajst-15595	96	22	four	four	NUM
ajst-15595	96	23	years	year	NOUN
ajst-15595	96	24	and	and	CCONJ
ajst-15595	96	25	accident	accident	NOUN
ajst-15595	96	26	rates[15	rates[15	VERB
ajst-15595	96	27	]	]	PUNCT
ajst-15595	96	28	.	.	PUNCT
ajst-15595	97	1	the	the	DET
ajst-15595	97	2	results	result	NOUN
ajst-15595	97	3	indicated	indicate	VERB
ajst-15595	97	4	that	that	SCONJ
ajst-15595	97	5	low	low	ADJ
ajst-15595	97	6	sign	sign	NOUN
ajst-15595	97	7	visibility	visibility	NOUN
ajst-15595	97	8	,	,	PUNCT
ajst-15595	97	9	fewer	few	ADJ
ajst-15595	97	10	mandatory	mandatory	ADJ
ajst-15595	97	11	signs	sign	NOUN
ajst-15595	97	12	,	,	PUNCT
ajst-15595	97	13	and	and	CCONJ
ajst-15595	97	14	an	an	DET
ajst-15595	97	15	increase	increase	NOUN
ajst-15595	97	16	in	in	ADP
ajst-15595	97	17	ineffective	ineffective	ADJ
ajst-15595	97	18	signs	sign	NOUN
ajst-15595	97	19	all	all	DET
ajst-15595	97	20	increased	increase	VERB
ajst-15595	97	21	accident	accident	NOUN
ajst-15595	97	22	rates	rate	NOUN
ajst-15595	97	23	.	.	PUNCT
ajst-15595	98	1	this	this	PRON
ajst-15595	98	2	has	have	VERB
ajst-15595	98	3	important	important	ADJ
ajst-15595	98	4	decision	decision	NOUN
ajst-15595	98	5	-	-	PUNCT
ajst-15595	98	6	making	make	VERB
ajst-15595	98	7	implications	implication	NOUN
ajst-15595	98	8	for	for	ADP
ajst-15595	98	9	reducing	reduce	VERB
ajst-15595	98	10	traffic	traffic	NOUN
ajst-15595	98	11	accidents.there	accidents.there	ADV
ajst-15595	98	12	are	be	AUX
ajst-15595	98	13	also	also	ADV
ajst-15595	98	14	many	many	ADJ
ajst-15595	98	15	domestic	domestic	ADJ
ajst-15595	98	16	scholars	scholar	NOUN
ajst-15595	98	17	who	who	PRON
ajst-15595	98	18	have	have	AUX
ajst-15595	98	19	applied	apply	VERB
ajst-15595	98	20	quantile	quantile	ADJ
ajst-15595	98	21	regression	regression	NOUN
ajst-15595	98	22	estimation	estimation	NOUN
ajst-15595	98	23	methods	method	NOUN
ajst-15595	98	24	to	to	ADP
ajst-15595	98	25	medical	medical	ADJ
ajst-15595	98	26	and	and	CCONJ
ajst-15595	98	27	health	health	NOUN
ajst-15595	98	28	research	research	NOUN
ajst-15595	98	29	,	,	PUNCT
ajst-15595	98	30	public	public	ADJ
ajst-15595	98	31	management	management	NOUN
ajst-15595	98	32	research	research	NOUN
ajst-15595	98	33	,	,	PUNCT
ajst-15595	98	34	and	and	CCONJ
ajst-15595	98	35	other	other	ADJ
ajst-15595	98	36	statistical	statistical	ADJ
ajst-15595	98	37	data	datum	NOUN
ajst-15595	98	38	research	research	NOUN
ajst-15595	98	39	with	with	ADP
ajst-15595	98	40	extreme	extreme	ADJ
ajst-15595	98	41	distribution	distribution	NOUN
ajst-15595	98	42	characteristics	characteristic	NOUN
ajst-15595	98	43	.	.	PUNCT
ajst-15595	99	1	with	with	ADP
ajst-15595	99	2	the	the	DET
ajst-15595	99	3	matured	mature	VERB
ajst-15595	99	4	and	and	CCONJ
ajst-15595	99	5	widespread	widespread	ADJ
ajst-15595	99	6	theoretical	theoretical	ADJ
ajst-15595	99	7	development	development	NOUN
ajst-15595	99	8	of	of	ADP
ajst-15595	99	9	quantile	quantile	ADJ
ajst-15595	99	10	regression	regression	NOUN
ajst-15595	99	11	methods	method	NOUN
ajst-15595	99	12	,	,	PUNCT
ajst-15595	99	13	their	their	PRON
ajst-15595	99	14	applications	application	NOUN
ajst-15595	99	15	in	in	ADP
ajst-15595	99	16	various	various	ADJ
ajst-15595	99	17	fields	field	NOUN
ajst-15595	99	18	such	such	ADJ
ajst-15595	99	19	as	as	ADP
ajst-15595	99	20	economics	economic	NOUN
ajst-15595	99	21	,	,	PUNCT
ajst-15595	99	22	finance	finance	NOUN
ajst-15595	99	23	,	,	PUNCT
ajst-15595	99	24	environmental	environmental	ADJ
ajst-15595	99	25	studies	study	NOUN
ajst-15595	99	26	,	,	PUNCT
ajst-15595	99	27	and	and	CCONJ
ajst-15595	99	28	management	management	NOUN
ajst-15595	99	29	are	be	AUX
ajst-15595	99	30	becoming	become	VERB
ajst-15595	99	31	increasingly	increasingly	ADV
ajst-15595	99	32	widespread	widespread	ADJ
ajst-15595	99	33	.	.	PUNCT
ajst-15595	100	1	the	the	DET
ajst-15595	100	2	most	most	ADV
ajst-15595	100	3	common	common	ADJ
ajst-15595	100	4	application	application	NOUN
ajst-15595	100	5	in	in	ADP
ajst-15595	100	6	economic	economic	ADJ
ajst-15595	100	7	research	research	NOUN
ajst-15595	100	8	is	be	AUX
ajst-15595	100	9	the	the	DET
ajst-15595	100	10	study	study	NOUN
ajst-15595	100	11	of	of	ADP
ajst-15595	100	12	factors	factor	NOUN
ajst-15595	100	13	influencing	influence	VERB
ajst-15595	100	14	income	income	NOUN
ajst-15595	100	15	levels	level	NOUN
ajst-15595	100	16	.	.	PUNCT
ajst-15595	101	1	liu	liu	PROPN
ajst-15595	101	2	shengqiao	shengqiao	PROPN
ajst-15595	101	3	(	(	PUNCT
ajst-15595	101	4	used	use	VERB
ajst-15595	101	5	the	the	DET
ajst-15595	101	6	quantile	quantile	ADJ
ajst-15595	101	7	regression	regression	NOUN
ajst-15595	101	8	model	model	NOUN
ajst-15595	101	9	to	to	PART
ajst-15595	101	10	analyze	analyze	VERB
ajst-15595	101	11	the	the	DET
ajst-15595	101	12	role	role	NOUN
ajst-15595	101	13	of	of	ADP
ajst-15595	101	14	education	education	NOUN
ajst-15595	101	15	and	and	CCONJ
ajst-15595	101	16	experience	experience	NOUN
ajst-15595	101	17	factors	factor	NOUN
ajst-15595	101	18	in	in	ADP
ajst-15595	101	19	chinese	chinese	ADJ
ajst-15595	101	20	residents	resident	NOUN
ajst-15595	101	21	'	'	PART
ajst-15595	101	22	income	income	NOUN
ajst-15595	101	23	and	and	CCONJ
ajst-15595	101	24	found	find	VERB
ajst-15595	101	25	that	that	SCONJ
ajst-15595	101	26	both	both	CCONJ
ajst-15595	101	27	education	education	NOUN
ajst-15595	101	28	and	and	CCONJ
ajst-15595	101	29	experience	experience	NOUN
ajst-15595	101	30	promote	promote	VERB
ajst-15595	101	31	income	income	NOUN
ajst-15595	101	32	growth	growth	NOUN
ajst-15595	101	33	.	.	PUNCT
ajst-15595	102	1	the	the	DET
ajst-15595	102	2	regression	regression	NOUN
ajst-15595	102	3	coefficient	coefficient	NOUN
ajst-15595	102	4	for	for	ADP
ajst-15595	102	5	education	education	NOUN
ajst-15595	102	6	changes	change	NOUN
ajst-15595	102	7	inversely	inversely	ADV
ajst-15595	102	8	with	with	ADP
ajst-15595	102	9	income	income	NOUN
ajst-15595	102	10	level	level	NOUN
ajst-15595	102	11	,	,	PUNCT
ajst-15595	102	12	with	with	ADP
ajst-15595	102	13	a	a	DET
ajst-15595	102	14	decrease	decrease	NOUN
ajst-15595	102	15	in	in	ADP
ajst-15595	102	16	education	education	NOUN
ajst-15595	102	17	return	return	NOUN
ajst-15595	102	18	rate	rate	NOUN
ajst-15595	102	19	as	as	ADP
ajst-15595	102	20	income	income	NOUN
ajst-15595	102	21	level	level	NOUN
ajst-15595	102	22	increases	increase	NOUN
ajst-15595	102	23	,	,	PUNCT
ajst-15595	102	24	while	while	SCONJ
ajst-15595	102	25	the	the	DET
ajst-15595	102	26	regression	regression	NOUN
ajst-15595	102	27	coefficient	coefficient	NOUN
ajst-15595	102	28	for	for	ADP
ajst-15595	102	29	experience	experience	NOUN
ajst-15595	102	30	follows	follow	VERB
ajst-15595	102	31	the	the	DET
ajst-15595	102	32	same	same	ADJ
ajst-15595	102	33	trend	trend	NOUN
ajst-15595	102	34	as	as	ADP
ajst-15595	102	35	income	income	NOUN
ajst-15595	102	36	level	level	NOUN
ajst-15595	102	37	.	.	PUNCT
ajst-15595	103	1	wei	wei	PROPN
ajst-15595	103	2	xiahai	xiahai	PROPN
ajst-15595	103	3	and	and	CCONJ
ajst-15595	103	4	yu	yu	PROPN
ajst-15595	103	5	lingfeng	lingfeng	PROPN
ajst-15595	103	6	used	use	VERB
ajst-15595	103	7	this	this	DET
ajst-15595	103	8	model	model	NOUN
ajst-15595	103	9	to	to	PART
ajst-15595	103	10	empirically	empirically	ADV
ajst-15595	103	11	analyze	analyze	VERB
ajst-15595	103	12	the	the	DET
ajst-15595	103	13	income	income	NOUN
ajst-15595	103	14	difference	difference	NOUN
ajst-15595	103	15	between	between	ADP
ajst-15595	103	16	regular	regular	ADJ
ajst-15595	103	17	and	and	CCONJ
ajst-15595	103	18	nonregular	nonregular	ADJ
ajst-15595	103	19	employment	employment	NOUN
ajst-15595	103	20	within	within	ADP
ajst-15595	103	21	urban	urban	ADJ
ajst-15595	103	22	areas	area	NOUN
ajst-15595	103	23	.	.	PUNCT
ajst-15595	104	1	the	the	DET
ajst-15595	104	2	results	result	NOUN
ajst-15595	104	3	showed	show	VERB
ajst-15595	104	4	that	that	SCONJ
ajst-15595	104	5	the	the	DET
ajst-15595	104	6	return	return	NOUN
ajst-15595	104	7	rate	rate	NOUN
ajst-15595	104	8	of	of	ADP
ajst-15595	104	9	education	education	NOUN
ajst-15595	104	10	exhibits	exhibit	VERB
ajst-15595	104	11	an	an	DET
ajst-15595	104	12	increasing	increase	VERB
ajst-15595	104	13	-	-	PUNCT
ajst-15595	104	14	thendecreasing	thendecrease	VERB
ajst-15595	104	15	pattern	pattern	NOUN
ajst-15595	104	16	under	under	ADP
ajst-15595	104	17	both	both	DET
ajst-15595	104	18	scenarios	scenario	NOUN
ajst-15595	104	19	as	as	SCONJ
ajst-15595	104	20	wage	wage	NOUN
ajst-15595	104	21	levels	level	NOUN
ajst-15595	104	22	increase	increase	VERB
ajst-15595	104	23	.	.	PUNCT
ajst-15595	105	1	on	on	ADP
ajst-15595	105	2	the	the	DET
ajst-15595	105	3	other	other	ADJ
ajst-15595	105	4	hand	hand	NOUN
ajst-15595	105	5	,	,	PUNCT
ajst-15595	105	6	the	the	DET
ajst-15595	105	7	wage	wage	NOUN
ajst-15595	105	8	-	-	PUNCT
ajst-15595	105	9	efficiency	efficiency	NOUN
ajst-15595	105	10	line	line	NOUN
ajst-15595	105	11	varies	vary	VERB
ajst-15595	105	12	significantly	significantly	ADV
ajst-15595	105	13	among	among	ADP
ajst-15595	105	14	different	different	ADJ
ajst-15595	105	15	samples	sample	NOUN
ajst-15595	105	16	,	,	PUNCT
ajst-15595	105	17	exhibiting	exhibit	VERB
ajst-15595	105	18	a	a	DET
ajst-15595	105	19	linear	linear	ADJ
ajst-15595	105	20	relationship	relationship	NOUN
ajst-15595	105	21	and	and	CCONJ
ajst-15595	105	22	monotonically	monotonically	ADV
ajst-15595	105	23	increasing	increase	VERB
ajst-15595	105	24	trend	trend	NOUN
ajst-15595	105	25	in	in	ADP
ajst-15595	105	26	regular	regular	ADJ
ajst-15595	105	27	employment	employment	NOUN
ajst-15595	105	28	but	but	CCONJ
ajst-15595	105	29	a	a	DET
ajst-15595	105	30	u	u	NOUN
ajst-15595	105	31	-	-	ADJ
ajst-15595	105	32	shaped	shape	VERB
ajst-15595	105	33	relationship	relationship	NOUN
ajst-15595	105	34	in	in	ADP
ajst-15595	105	35	non	non	ADJ
ajst-15595	105	36	-	-	ADJ
ajst-15595	105	37	regular	regular	ADJ
ajst-15595	105	38	employment	employment	NOUN
ajst-15595	105	39	.	.	PUNCT
ajst-15595	106	1	jiang	jiang	PROPN
ajst-15595	106	2	liqing	liqe	VERB
ajst-15595	106	3	and	and	CCONJ
ajst-15595	106	4	qian	qian	PROPN
ajst-15595	106	5	wenrong	wenrong	PROPN
ajst-15595	106	6	studied	study	VERB
ajst-15595	106	7	the	the	DET
ajst-15595	106	8	wage	wage	NOUN
ajst-15595	106	9	gap	gap	NOUN
ajst-15595	106	10	between	between	ADP
ajst-15595	106	11	public	public	ADJ
ajst-15595	106	12	and	and	CCONJ
ajst-15595	106	13	non	non	ADJ
ajst-15595	106	14	-	-	ADJ
ajst-15595	106	15	public	public	ADJ
ajst-15595	106	16	sectors	sector	NOUN
ajst-15595	106	17	and	and	CCONJ
ajst-15595	106	18	found	find	VERB
ajst-15595	106	19	that	that	SCONJ
ajst-15595	106	20	the	the	DET
ajst-15595	106	21	wage	wage	NOUN
ajst-15595	106	22	difference	difference	NOUN
ajst-15595	106	23	does	do	AUX
ajst-15595	106	24	exist	exist	VERB
ajst-15595	106	25	,	,	PUNCT
ajst-15595	106	26	with	with	ADP
ajst-15595	106	27	public	public	ADJ
ajst-15595	106	28	sector	sector	NOUN
ajst-15595	106	29	wages	wage	NOUN
ajst-15595	106	30	being	be	AUX
ajst-15595	106	31	significantly	significantly	ADV
ajst-15595	106	32	higher	high	ADJ
ajst-15595	106	33	.	.	PUNCT
ajst-15595	107	1	however	however	ADV
ajst-15595	107	2	,	,	PUNCT
ajst-15595	107	3	as	as	ADP
ajst-15595	107	4	the	the	DET
ajst-15595	107	5	quantile	quantile	ADJ
ajst-15595	107	6	increases	increase	NOUN
ajst-15595	107	7	,	,	PUNCT
ajst-15595	107	8	the	the	DET
ajst-15595	107	9	income	income	NOUN
ajst-15595	107	10	difference	difference	NOUN
ajst-15595	107	11	between	between	ADP
ajst-15595	107	12	the	the	DET
ajst-15595	107	13	two	two	NUM
ajst-15595	107	14	sectors	sector	NOUN
ajst-15595	107	15	tends	tend	VERB
ajst-15595	107	16	to	to	PART
ajst-15595	107	17	reduce	reduce	VERB
ajst-15595	107	18	.	.	PUNCT
ajst-15595	108	1	kou	kou	PROPN
ajst-15595	108	2	enhui	enhui	PROPN
ajst-15595	108	3	and	and	CCONJ
ajst-15595	108	4	liu	liu	PROPN
ajst-15595	108	5	baihui	baihui	PROPN
ajst-15595	108	6	estimated	estimate	VERB
ajst-15595	108	7	the	the	DET
ajst-15595	108	8	wage	wage	NOUN
ajst-15595	108	9	function	function	NOUN
ajst-15595	108	10	of	of	ADP
ajst-15595	108	11	migrant	migrant	ADJ
ajst-15595	108	12	workers	worker	NOUN
ajst-15595	108	13	and	and	CCONJ
ajst-15595	108	14	analyzed	analyze	VERB
ajst-15595	108	15	the	the	DET
ajst-15595	108	16	wage	wage	NOUN
ajst-15595	108	17	gap	gap	NOUN
ajst-15595	108	18	between	between	ADP
ajst-15595	108	19	shortterm	shortterm	PROPN
ajst-15595	108	20	and	and	CCONJ
ajst-15595	108	21	long	long	ADJ
ajst-15595	108	22	-	-	PUNCT
ajst-15595	108	23	term	term	NOUN
ajst-15595	108	24	migrant	migrant	ADJ
ajst-15595	108	25	workers	worker	NOUN
ajst-15595	108	26	using	use	VERB
ajst-15595	108	27	the	the	DET
ajst-15595	108	28	mm	mm	PROPN
ajst-15595	108	29	method	method	NOUN
ajst-15595	108	30	.	.	PUNCT
ajst-15595	109	1	the	the	DET
ajst-15595	109	2	results	result	NOUN
ajst-15595	109	3	showed	show	VERB
ajst-15595	109	4	that	that	SCONJ
ajst-15595	109	5	the	the	DET
ajst-15595	109	6	main	main	ADJ
ajst-15595	109	7	factors	factor	NOUN
ajst-15595	109	8	influencing	influence	VERB
ajst-15595	109	9	migrant	migrant	ADJ
ajst-15595	109	10	workers	worker	NOUN
ajst-15595	109	11	'	'	PART
ajst-15595	109	12	wages	wage	NOUN
ajst-15595	109	13	are	be	AUX
ajst-15595	109	14	regional	regional	ADJ
ajst-15595	109	15	factors	factor	NOUN
ajst-15595	109	16	and	and	CCONJ
ajst-15595	109	17	education	education	NOUN
ajst-15595	109	18	factors	factor	NOUN
ajst-15595	109	19	.	.	PUNCT
ajst-15595	110	1	at	at	ADP
ajst-15595	110	2	low	low	ADJ
ajst-15595	110	3	quantiles	quantile	NOUN
ajst-15595	110	4	of	of	ADP
ajst-15595	110	5	the	the	DET
ajst-15595	110	6	wage	wage	NOUN
ajst-15595	110	7	variable	variable	NOUN
ajst-15595	110	8	,	,	PUNCT
ajst-15595	110	9	there	there	PRON
ajst-15595	110	10	is	be	VERB
ajst-15595	110	11	a	a	DET
ajst-15595	110	12	significant	significant	ADJ
ajst-15595	110	13	difference	difference	NOUN
ajst-15595	110	14	in	in	ADP
ajst-15595	110	15	wage	wage	NOUN
ajst-15595	110	16	income	income	NOUN
ajst-15595	110	17	between	between	ADP
ajst-15595	110	18	short	short	ADJ
ajst-15595	110	19	-	-	PUNCT
ajst-15595	110	20	term	term	NOUN
ajst-15595	110	21	contract	contract	NOUN
ajst-15595	110	22	workers	worker	NOUN
ajst-15595	110	23	and	and	CCONJ
ajst-15595	110	24	long	long	ADJ
ajst-15595	110	25	-	-	PUNCT
ajst-15595	110	26	term	term	NOUN
ajst-15595	110	27	contract	contract	NOUN
ajst-15595	110	28	workers	worker	NOUN
ajst-15595	110	29	.	.	PUNCT
ajst-15595	111	1	guo	guo	PROPN
ajst-15595	111	2	yifu	yifu	PROPN
ajst-15595	111	3	discussed	discuss	VERB
ajst-15595	111	4	the	the	DET
ajst-15595	111	5	main	main	ADJ
ajst-15595	111	6	factors	factor	NOUN
ajst-15595	111	7	affecting	affect	VERB
ajst-15595	111	8	the	the	DET
ajst-15595	111	9	income	income	NOUN
ajst-15595	111	10	levels	level	NOUN
ajst-15595	111	11	of	of	ADP
ajst-15595	111	12	urban	urban	ADJ
ajst-15595	111	13	and	and	CCONJ
ajst-15595	111	14	rural	rural	ADJ
ajst-15595	111	15	residents	resident	NOUN
ajst-15595	111	16	and	and	CCONJ
ajst-15595	111	17	their	their	PRON
ajst-15595	111	18	relative	relative	ADJ
ajst-15595	111	19	impacts	impact	NOUN
ajst-15595	111	20	on	on	ADP
ajst-15595	111	21	the	the	DET
ajst-15595	111	22	urban	urban	ADJ
ajst-15595	111	23	-	-	PUNCT
ajst-15595	111	24	rural	rural	ADJ
ajst-15595	111	25	income	income	NOUN
ajst-15595	111	26	gap	gap	NOUN
ajst-15595	111	27	based	base	VERB
ajst-15595	111	28	on	on	ADP
ajst-15595	111	29	endowment	endowment	NOUN
ajst-15595	111	30	composition	composition	NOUN
ajst-15595	111	31	and	and	CCONJ
ajst-15595	111	32	individual	individual	ADJ
ajst-15595	111	33	return	return	NOUN
ajst-15595	111	34	rates	rate	NOUN
ajst-15595	111	35	of	of	ADP
ajst-15595	111	36	urban	urban	ADJ
ajst-15595	111	37	and	and	CCONJ
ajst-15595	111	38	rural	rural	ADJ
ajst-15595	111	39	residents	resident	NOUN
ajst-15595	111	40	.	.	PUNCT
ajst-15595	112	1	wu	wu	PROPN
ajst-15595	112	2	yanke	yanke	PROPN
ajst-15595	112	3	and	and	CCONJ
ajst-15595	112	4	tian	tian	PROPN
ajst-15595	112	5	mao	mao	PROPN
ajst-15595	112	6	first	first	ADV
ajst-15595	112	7	used	use	VERB
ajst-15595	112	8	factor	factor	NOUN
ajst-15595	112	9	analysis	analysis	NOUN
ajst-15595	112	10	to	to	PART
ajst-15595	112	11	measure	measure	VERB
ajst-15595	112	12	household	household	NOUN
ajst-15595	112	13	socioeconomic	socioeconomic	ADJ
ajst-15595	112	14	status	status	NOUN
ajst-15595	112	15	based	base	VERB
ajst-15595	112	16	on	on	ADP
ajst-15595	112	17	variables	variable	NOUN
ajst-15595	112	18	representing	represent	VERB
ajst-15595	112	19	the	the	DET
ajst-15595	112	20	highest	high	ADJ
ajst-15595	112	21	education	education	NOUN
ajst-15595	112	22	level	level	NOUN
ajst-15595	112	23	of	of	ADP
ajst-15595	112	24	fathers	father	NOUN
ajst-15595	112	25	and	and	CCONJ
ajst-15595	112	26	mothers	mother	NOUN
ajst-15595	112	27	,	,	PUNCT
ajst-15595	112	28	and	and	CCONJ
ajst-15595	112	29	family	family	NOUN
ajst-15595	112	30	social	social	ADJ
ajst-15595	112	31	class	class	NOUN
ajst-15595	112	32	.	.	PUNCT
ajst-15595	113	1	then	then	ADV
ajst-15595	113	2	,	,	PUNCT
ajst-15595	113	3	using	use	VERB
ajst-15595	113	4	the	the	DET
ajst-15595	113	5	ffl	ffl	PROPN
ajst-15595	113	6	unconditional	unconditional	ADJ
ajst-15595	113	7	quantile	quantile	ADJ
ajst-15595	113	8	regression	regression	NOUN
ajst-15595	113	9	method	method	NOUN
ajst-15595	113	10	according	accord	VERB
ajst-15595	113	11	to	to	ADP
ajst-15595	113	12	different	different	ADJ
ajst-15595	113	13	family	family	NOUN
ajst-15595	113	14	socioeconomic	socioeconomic	ADJ
ajst-15595	113	15	statuses	status	NOUN
ajst-15595	113	16	,	,	PUNCT
ajst-15595	113	17	they	they	PRON
ajst-15595	113	18	conducted	conduct	VERB
ajst-15595	113	19	unconditional	unconditional	ADJ
ajst-15595	113	20	quantile	quantile	ADJ
ajst-15595	113	21	regression	regression	NOUN
ajst-15595	113	22	analysis	analysis	NOUN
ajst-15595	113	23	of	of	ADP
ajst-15595	113	24	education	education	NOUN
ajst-15595	113	25	return	return	NOUN
ajst-15595	113	26	rates	rate	NOUN
ajst-15595	113	27	.	.	PUNCT
ajst-15595	114	1	quantile	quantile	ADJ
ajst-15595	114	2	regression	regression	NOUN
ajst-15595	114	3	models	model	NOUN
ajst-15595	114	4	can	can	AUX
ajst-15595	114	5	also	also	ADV
ajst-15595	114	6	be	be	AUX
ajst-15595	114	7	used	use	VERB
ajst-15595	114	8	to	to	PART
ajst-15595	114	9	analyze	analyze	VERB
ajst-15595	114	10	the	the	DET
ajst-15595	114	11	main	main	ADJ
ajst-15595	114	12	factors	factor	NOUN
ajst-15595	114	13	influencing	influence	VERB
ajst-15595	114	14	consumption	consumption	NOUN
ajst-15595	114	15	levels	level	NOUN
ajst-15595	114	16	.	.	PUNCT
ajst-15595	115	1	chen	chen	PROPN
ajst-15595	115	2	juan	juan	PROPN
ajst-15595	115	3	,	,	PUNCT
ajst-15595	115	4	lin	lin	PROPN
ajst-15595	115	5	long	long	ADV
ajst-15595	115	6	,	,	PUNCT
ajst-15595	115	7	etc	etc	X
ajst-15595	115	8	.	.	X
ajst-15595	115	9	added	add	VERB
ajst-15595	115	10	household	household	NOUN
ajst-15595	115	11	income	income	NOUN
ajst-15595	115	12	and	and	CCONJ
ajst-15595	115	13	government	government	NOUN
ajst-15595	115	14	expenditure	expenditure	NOUN
ajst-15595	115	15	factors	factor	NOUN
ajst-15595	115	16	to	to	ADP
ajst-15595	115	17	the	the	DET
ajst-15595	115	18	consumer	consumer	NOUN
ajst-15595	115	19	utility	utility	NOUN
ajst-15595	115	20	function	function	NOUN
ajst-15595	115	21	to	to	PART
ajst-15595	115	22	explore	explore	VERB
ajst-15595	115	23	the	the	DET
ajst-15595	115	24	inherent	inherent	ADJ
ajst-15595	115	25	relationship	relationship	NOUN
ajst-15595	115	26	among	among	ADP
ajst-15595	115	27	consumption	consumption	NOUN
ajst-15595	115	28	,	,	PUNCT
ajst-15595	115	29	production	production	NOUN
ajst-15595	115	30	,	,	PUNCT
ajst-15595	115	31	and	and	CCONJ
ajst-15595	115	32	government	government	NOUN
ajst-15595	115	33	behavior	behavior	NOUN
ajst-15595	115	34	.	.	PUNCT
ajst-15595	116	1	the	the	DET
ajst-15595	116	2	empirical	empirical	ADJ
ajst-15595	116	3	results	result	NOUN
ajst-15595	116	4	show	show	VERB
ajst-15595	116	5	that	that	SCONJ
ajst-15595	116	6	as	as	ADP
ajst-15595	116	7	the	the	DET
ajst-15595	116	8	consumption	consumption	NOUN
ajst-15595	116	9	level	level	NOUN
ajst-15595	116	10	changes	change	NOUN
ajst-15595	116	11	,	,	PUNCT
ajst-15595	116	12	the	the	DET
ajst-15595	116	13	influence	influence	NOUN
ajst-15595	116	14	of	of	ADP
ajst-15595	116	15	various	various	ADJ
ajst-15595	116	16	factors	factor	NOUN
ajst-15595	116	17	on	on	ADP
ajst-15595	116	18	consumption	consumption	NOUN
ajst-15595	116	19	also	also	ADV
ajst-15595	116	20	varies	vary	VERB
ajst-15595	116	21	.	.	PUNCT
ajst-15595	117	1	the	the	DET
ajst-15595	117	2	impact	impact	NOUN
ajst-15595	117	3	is	be	AUX
ajst-15595	117	4	also	also	ADV
ajst-15595	117	5	significantly	significantly	ADV
ajst-15595	117	6	different	different	ADJ
ajst-15595	117	7	between	between	ADP
ajst-15595	117	8	urban	urban	ADJ
ajst-15595	117	9	and	and	CCONJ
ajst-15595	117	10	rural	rural	ADJ
ajst-15595	117	11	areas	area	NOUN
ajst-15595	117	12	.	.	PUNCT
ajst-15595	118	1	zhao	zhao	PROPN
ajst-15595	118	2	xindong	xindong	PROPN
ajst-15595	118	3	and	and	CCONJ
ajst-15595	118	4	li	li	PROPN
ajst-15595	118	5	lin	lin	PROPN
ajst-15595	118	6	used	use	VERB
ajst-15595	118	7	2007	2007	NUM
ajst-15595	118	8	china	china	PROPN
ajst-15595	118	9	household	household	PROPN
ajst-15595	118	10	income	income	NOUN
ajst-15595	118	11	project	project	NOUN
ajst-15595	118	12	survey	survey	NOUN
ajst-15595	118	13	data	datum	NOUN
ajst-15595	118	14	to	to	PART
ajst-15595	118	15	simultaneously	simultaneously	ADV
ajst-15595	118	16	consider	consider	VERB
ajst-15595	118	17	the	the	DET
ajst-15595	118	18	linear	linear	ADJ
ajst-15595	118	19	and	and	CCONJ
ajst-15595	118	20	nonlinear	nonlinear	ADJ
ajst-15595	118	21	effects	effect	NOUN
ajst-15595	118	22	of	of	ADP
ajst-15595	118	23	household	household	NOUN
ajst-15595	118	24	economic	economic	ADJ
ajst-15595	118	25	factors	factor	NOUN
ajst-15595	118	26	and	and	CCONJ
ajst-15595	118	27	household	household	NOUN
ajst-15595	118	28	population	population	NOUN
ajst-15595	118	29	characteristics	characteristic	NOUN
ajst-15595	118	30	on	on	ADP
ajst-15595	118	31	consumption	consumption	NOUN
ajst-15595	118	32	levels	level	NOUN
ajst-15595	118	33	.	.	PUNCT
ajst-15595	119	1	they	they	PRON
ajst-15595	119	2	constructed	construct	VERB
ajst-15595	119	3	an	an	DET
ajst-15595	119	4	additive	additive	ADJ
ajst-15595	119	5	semiparametric	semiparametric	NOUN
ajst-15595	119	6	quantile	quantile	ADJ
ajst-15595	119	7	regression	regression	NOUN
ajst-15595	119	8	model	model	NOUN
ajst-15595	119	9	and	and	CCONJ
ajst-15595	119	10	analyzed	analyze	VERB
ajst-15595	119	11	the	the	DET
ajst-15595	119	12	contributions	contribution	NOUN
ajst-15595	119	13	of	of	ADP
ajst-15595	119	14	household	household	NOUN
ajst-15595	119	15	economic	economic	ADJ
ajst-15595	119	16	factors	factor	NOUN
ajst-15595	119	17	and	and	CCONJ
ajst-15595	119	18	household	household	NOUN
ajst-15595	119	19	population	population	NOUN
ajst-15595	119	20	characteristics	characteristic	NOUN
ajst-15595	119	21	to	to	ADP
ajst-15595	119	22	consumption	consumption	NOUN
ajst-15595	119	23	levels	level	NOUN
ajst-15595	119	24	,	,	PUNCT
ajst-15595	119	25	as	as	ADV
ajst-15595	119	26	well	well	ADV
ajst-15595	119	27	as	as	ADP
ajst-15595	119	28	the	the	DET
ajst-15595	119	29	changes	change	NOUN
ajst-15595	119	30	in	in	ADP
ajst-15595	119	31	their	their	PRON
ajst-15595	119	32	effects	effect	NOUN
ajst-15595	119	33	at	at	ADP
ajst-15595	119	34	different	different	ADJ
ajst-15595	119	35	consumption	consumption	NOUN
ajst-15595	119	36	levels.in	levels.in	X
ajst-15595	119	37	other	other	ADJ
ajst-15595	119	38	economic	economic	ADJ
ajst-15595	119	39	research	research	NOUN
ajst-15595	119	40	fields	field	NOUN
ajst-15595	119	41	,	,	PUNCT
ajst-15595	119	42	quantile	quantile	ADJ
ajst-15595	119	43	regression	regression	NOUN
ajst-15595	119	44	methods	method	NOUN
ajst-15595	119	45	can	can	AUX
ajst-15595	119	46	be	be	AUX
ajst-15595	119	47	applied	apply	VERB
ajst-15595	119	48	to	to	ADP
ajst-15595	119	49	total	total	ADJ
ajst-15595	119	50	factor	factor	NOUN
ajst-15595	119	51	productivity	productivity	NOUN
ajst-15595	119	52	analysis	analysis	NOUN
ajst-15595	119	53	,	,	PUNCT
ajst-15595	119	54	exchange	exchange	NOUN
ajst-15595	119	55	rate	rate	NOUN
ajst-15595	119	56	fluctuations	fluctuation	NOUN
ajst-15595	119	57	,	,	PUNCT
ajst-15595	119	58	network	network	NOUN
ajst-15595	119	59	commodity	commodity	NOUN
ajst-15595	119	60	pricing	pricing	NOUN
ajst-15595	119	61	,	,	PUNCT
ajst-15595	119	62	and	and	CCONJ
ajst-15595	119	63	others	other	NOUN
ajst-15595	119	64	.	.	PUNCT
ajst-15595	120	1	mei	mei	PROPN
ajst-15595	120	2	bo	bo	PROPN
ajst-15595	120	3	and	and	CCONJ
ajst-15595	120	4	tian	tian	PROPN
ajst-15595	120	5	maozai	maozai	PROPN
ajst-15595	120	6	constructed	construct	VERB
ajst-15595	120	7	a	a	DET
ajst-15595	120	8	spatio	spatio	NOUN
ajst-15595	120	9	-	-	PUNCT
ajst-15595	120	10	temporal	temporal	ADJ
ajst-15595	120	11	quantile	quantile	ADJ
ajst-15595	120	12	regression	regression	NOUN
ajst-15595	120	13	model	model	NOUN
ajst-15595	120	14	based	base	VERB
ajst-15595	120	15	on	on	ADP
ajst-15595	120	16	spatio	spatio	PROPN
ajst-15595	120	17	-	-	PUNCT
ajst-15595	120	18	temporal	temporal	ADJ
ajst-15595	120	19	models	model	NOUN
ajst-15595	120	20	and	and	CCONJ
ajst-15595	120	21	the	the	DET
ajst-15595	120	22	ald	ald	PROPN
ajst-15595	120	23	distribution	distribution	NOUN
ajst-15595	120	24	.	.	PUNCT
ajst-15595	121	1	they	they	PRON
ajst-15595	121	2	used	use	VERB
ajst-15595	121	3	thin	thin	ADJ
ajst-15595	121	4	plate	plate	NOUN
ajst-15595	121	5	regression	regression	NOUN
ajst-15595	121	6	splines	spline	NOUN
ajst-15595	121	7	to	to	PART
ajst-15595	121	8	expand	expand	VERB
ajst-15595	121	9	the	the	DET
ajst-15595	121	10	spatial	spatial	ADJ
ajst-15595	121	11	domain	domain	NOUN
ajst-15595	121	12	and	and	CCONJ
ajst-15595	121	13	proposed	propose	VERB
ajst-15595	121	14	a	a	DET
ajst-15595	121	15	hierarchical	hierarchical	ADJ
ajst-15595	121	16	bayesian	bayesian	NOUN
ajst-15595	121	17	quantile	quantile	ADJ
ajst-15595	121	18	regression	regression	NOUN
ajst-15595	121	19	model	model	NOUN
ajst-15595	121	20	based	base	VERB
ajst-15595	121	21	on	on	ADP
ajst-15595	121	22	the	the	DET
ajst-15595	121	23	relationship	relationship	NOUN
ajst-15595	121	24	between	between	ADP
ajst-15595	121	25	the	the	DET
ajst-15595	121	26	mixed	mixed	ADJ
ajst-15595	121	27	model	model	NOUN
ajst-15595	121	28	and	and	CCONJ
ajst-15595	121	29	splines	spline	NOUN
ajst-15595	121	30	.	.	PUNCT
ajst-15595	122	1	using	use	VERB
ajst-15595	122	2	this	this	DET
ajst-15595	122	3	model	model	NOUN
ajst-15595	122	4	,	,	PUNCT
ajst-15595	122	5	they	they	PRON
ajst-15595	122	6	studied	study	VERB
ajst-15595	122	7	175	175	NUM
ajst-15595	122	8	the	the	DET
ajst-15595	122	9	major	major	ADJ
ajst-15595	122	10	factors	factor	NOUN
ajst-15595	122	11	influencing	influence	VERB
ajst-15595	122	12	pm2.5	pm2.5	DET
ajst-15595	122	13	concentrations	concentration	NOUN
ajst-15595	122	14	in	in	ADP
ajst-15595	122	15	beijing	beijing	PROPN
ajst-15595	122	16	and	and	CCONJ
ajst-15595	122	17	explained	explain	VERB
ajst-15595	122	18	the	the	DET
ajst-15595	122	19	spatial	spatial	ADJ
ajst-15595	122	20	distribution	distribution	NOUN
ajst-15595	122	21	characteristics	characteristic	NOUN
ajst-15595	122	22	of	of	ADP
ajst-15595	122	23	the	the	DET
ajst-15595	122	24	impact	impact	NOUN
ajst-15595	122	25	of	of	ADP
ajst-15595	122	26	meteorological	meteorological	ADJ
ajst-15595	122	27	conditions	condition	NOUN
ajst-15595	122	28	on	on	ADP
ajst-15595	122	29	pm2.5	pm2.5	DET
ajst-15595	122	30	concentrations	concentration	NOUN
ajst-15595	122	31	.	.	PUNCT
ajst-15595	123	1	li	li	PROPN
ajst-15595	123	2	zedou	zedou	AUX
ajst-15595	123	3	et	et	PROPN
ajst-15595	123	4	al	al	PROPN
ajst-15595	123	5	.	.	PROPN
ajst-15595	123	6	applied	apply	VERB
ajst-15595	123	7	quantile	quantile	ADJ
ajst-15595	123	8	regression	regression	NOUN
ajst-15595	123	9	using	use	VERB
ajst-15595	123	10	representative	representative	ADJ
ajst-15595	123	11	data	datum	NOUN
ajst-15595	123	12	on	on	ADP
ajst-15595	123	13	indicators	indicator	NOUN
ajst-15595	123	14	of	of	ADP
ajst-15595	123	15	national	national	ADJ
ajst-15595	123	16	image	image	NOUN
ajst-15595	123	17	and	and	CCONJ
ajst-15595	123	18	empirically	empirically	ADV
ajst-15595	123	19	studied	study	VERB
ajst-15595	123	20	the	the	DET
ajst-15595	123	21	major	major	ADJ
ajst-15595	123	22	factors	factor	NOUN
ajst-15595	123	23	influencing	influence	VERB
ajst-15595	123	24	national	national	ADJ
ajst-15595	123	25	image	image	NOUN
ajst-15595	123	26	.	.	PUNCT
ajst-15595	124	1	the	the	DET
ajst-15595	124	2	estimation	estimation	NOUN
ajst-15595	124	3	and	and	CCONJ
ajst-15595	124	4	analysis	analysis	NOUN
ajst-15595	124	5	of	of	ADP
ajst-15595	124	6	education	education	NOUN
ajst-15595	124	7	return	return	NOUN
ajst-15595	124	8	rates	rate	NOUN
ajst-15595	124	9	,	,	PUNCT
ajst-15595	124	10	labor	labor	NOUN
ajst-15595	124	11	discrimination	discrimination	NOUN
ajst-15595	124	12	factors	factor	NOUN
ajst-15595	124	13	,	,	PUNCT
ajst-15595	124	14	and	and	CCONJ
ajst-15595	124	15	more	more	ADJ
ajst-15595	124	16	have	have	AUX
ajst-15595	124	17	been	be	AUX
ajst-15595	124	18	conducted	conduct	VERB
ajst-15595	124	19	.	.	PUNCT
ajst-15595	125	1	it	it	PRON
ajst-15595	125	2	can	can	AUX
ajst-15595	125	3	be	be	AUX
ajst-15595	125	4	seen	see	VERB
ajst-15595	125	5	that	that	SCONJ
ajst-15595	125	6	the	the	DET
ajst-15595	125	7	theoretical	theoretical	ADJ
ajst-15595	125	8	development	development	NOUN
ajst-15595	125	9	of	of	ADP
ajst-15595	125	10	quantile	quantile	ADJ
ajst-15595	125	11	regression	regression	NOUN
ajst-15595	125	12	has	have	AUX
ajst-15595	125	13	become	become	VERB
ajst-15595	125	14	more	more	ADV
ajst-15595	125	15	mature	mature	ADJ
ajst-15595	125	16	,	,	PUNCT
ajst-15595	125	17	and	and	CCONJ
ajst-15595	125	18	there	there	PRON
ajst-15595	125	19	is	be	VERB
ajst-15595	125	20	an	an	DET
ajst-15595	125	21	increasing	increase	VERB
ajst-15595	125	22	demand	demand	NOUN
ajst-15595	125	23	for	for	ADP
ajst-15595	125	24	the	the	DET
ajst-15595	125	25	application	application	NOUN
ajst-15595	125	26	of	of	ADP
ajst-15595	125	27	quantile	quantile	ADJ
ajst-15595	125	28	regression	regression	NOUN
ajst-15595	125	29	models	model	NOUN
ajst-15595	125	30	to	to	PART
ajst-15595	125	31	solve	solve	VERB
ajst-15595	125	32	practical	practical	ADJ
ajst-15595	125	33	problems	problem	NOUN
ajst-15595	125	34	in	in	ADP
ajst-15595	125	35	life	life	NOUN
ajst-15595	125	36	.	.	PUNCT
ajst-15595	126	1	however	however	ADV
ajst-15595	126	2	,	,	PUNCT
ajst-15595	126	3	the	the	DET
ajst-15595	126	4	biggest	big	ADJ
ajst-15595	126	5	limitation	limitation	NOUN
ajst-15595	126	6	of	of	ADP
ajst-15595	126	7	quantile	quantile	ADJ
ajst-15595	126	8	regression	regression	NOUN
ajst-15595	126	9	in	in	ADP
ajst-15595	126	10	panel	panel	NOUN
ajst-15595	126	11	data	datum	NOUN
ajst-15595	126	12	research	research	NOUN
ajst-15595	126	13	is	be	AUX
ajst-15595	126	14	its	its	PRON
ajst-15595	126	15	reliance	reliance	NOUN
ajst-15595	126	16	on	on	ADP
ajst-15595	126	17	parametric	parametric	ADJ
ajst-15595	126	18	models	model	NOUN
ajst-15595	126	19	.	.	PUNCT
ajst-15595	127	1	parametric	parametric	ADJ
ajst-15595	127	2	models	model	NOUN
ajst-15595	127	3	are	be	AUX
ajst-15595	127	4	models	model	NOUN
ajst-15595	127	5	formulated	formulate	VERB
ajst-15595	127	6	by	by	ADP
ajst-15595	127	7	researchers	researcher	NOUN
ajst-15595	127	8	based	base	VERB
ajst-15595	127	9	on	on	ADP
ajst-15595	127	10	a	a	DET
ajst-15595	127	11	rough	rough	ADJ
ajst-15595	127	12	analysis	analysis	NOUN
ajst-15595	127	13	of	of	ADP
ajst-15595	127	14	data	datum	NOUN
ajst-15595	127	15	using	use	VERB
ajst-15595	127	16	structured	structured	ADJ
ajst-15595	127	17	expressions	expression	NOUN
ajst-15595	127	18	and	and	CCONJ
ajst-15595	127	19	parameter	parameter	NOUN
ajst-15595	127	20	sets	set	NOUN
ajst-15595	127	21	.	.	PUNCT
ajst-15595	128	1	when	when	SCONJ
ajst-15595	128	2	modeling	modeling	NOUN
ajst-15595	128	3	,	,	PUNCT
ajst-15595	128	4	certain	certain	ADJ
ajst-15595	128	5	prior	prior	ADJ
ajst-15595	128	6	assumptions	assumption	NOUN
ajst-15595	128	7	need	need	VERB
ajst-15595	128	8	to	to	PART
ajst-15595	128	9	be	be	AUX
ajst-15595	128	10	made	make	VERB
ajst-15595	128	11	about	about	ADP
ajst-15595	128	12	the	the	DET
ajst-15595	128	13	data	datum	NOUN
ajst-15595	128	14	,	,	PUNCT
ajst-15595	128	15	which	which	PRON
ajst-15595	128	16	may	may	AUX
ajst-15595	128	17	not	not	PART
ajst-15595	128	18	fully	fully	ADV
ajst-15595	128	19	fit	fit	VERB
ajst-15595	128	20	the	the	DET
ajst-15595	128	21	pre	pre	ADJ
ajst-15595	128	22	-	-	ADJ
ajst-15595	128	23	given	give	VERB
ajst-15595	128	24	model	model	NOUN
ajst-15595	128	25	and	and	CCONJ
ajst-15595	128	26	may	may	AUX
ajst-15595	128	27	not	not	PART
ajst-15595	128	28	satisfy	satisfy	VERB
ajst-15595	128	29	the	the	DET
ajst-15595	128	30	researcher	researcher	NOUN
ajst-15595	128	31	's	's	PART
ajst-15595	128	32	predetermined	predetermine	VERB
ajst-15595	128	33	assumptions	assumption	NOUN
ajst-15595	128	34	.	.	PUNCT
ajst-15595	129	1	parametric	parametric	ADJ
ajst-15595	129	2	models	model	NOUN
ajst-15595	129	3	have	have	VERB
ajst-15595	129	4	relatively	relatively	ADV
ajst-15595	129	5	poor	poor	ADJ
ajst-15595	129	6	flexibility	flexibility	NOUN
ajst-15595	129	7	and	and	CCONJ
ajst-15595	129	8	strong	strong	ADJ
ajst-15595	129	9	data	datum	NOUN
ajst-15595	129	10	requirements	requirement	NOUN
ajst-15595	129	11	.	.	PUNCT
ajst-15595	130	1	2	2	X
ajst-15595	130	2	.	.	X
ajst-15595	130	3	principle	principle	NOUN
ajst-15595	130	4	of	of	ADP
ajst-15595	130	5	quantile	quantile	ADJ
ajst-15595	130	6	regression	regression	NOUN
ajst-15595	130	7	model	model	NOUN
ajst-15595	130	8	2.1	2.1	NUM
ajst-15595	130	9	.	.	PUNCT
ajst-15595	131	1	the	the	DET
ajst-15595	131	2	basic	basic	ADJ
ajst-15595	131	3	principle	principle	NOUN
ajst-15595	131	4	of	of	ADP
ajst-15595	131	5	quantile	quantile	ADJ
ajst-15595	131	6	regression	regression	NOUN
ajst-15595	131	7	the	the	DET
ajst-15595	131	8	general	general	ADJ
ajst-15595	131	9	linear	linear	PROPN
ajst-15595	131	10	regression	regression	NOUN
ajst-15595	131	11	model	model	NOUN
ajst-15595	131	12	can	can	AUX
ajst-15595	131	13	be	be	AUX
ajst-15595	131	14	set	set	VERB
ajst-15595	131	15	as	as	SCONJ
ajst-15595	131	16	follows	follow	VERB
ajst-15595	131	17	:	:	PUNCT
ajst-15595	131	18	0	0	NUM
ajst-15595	131	19	1	1	NUM
ajst-15595	131	20	1	1	NUM
ajst-15595	131	21	2	2	NUM
ajst-15595	131	22	2	2	NUM
ajst-15595	131	23			ADV
ajst-15595	131	24			PROPN
ajst-15595	131	25			PUNCT
ajst-15595	131	26			PUNCT
ajst-15595	132	1			PROPN
ajst-15595	132	2	k	k	PROPN
ajst-15595	132	3	ky	ky	PROPN
ajst-15595	132	4	a	a	DET
ajst-15595	132	5	a	a	DET
ajst-15595	132	6	x	x	SYM
ajst-15595	132	7	a	a	DET
ajst-15595	132	8	x	x	SYM
ajst-15595	132	9	a	a	X
ajst-15595	132	10	x	x	X
ajst-15595	132	11	u	u	NOUN
ajst-15595	132	12	under	under	ADP
ajst-15595	132	13	the	the	DET
ajst-15595	132	14	premise	premise	NOUN
ajst-15595	132	15	of	of	ADP
ajst-15595	132	16	satisfying	satisfy	VERB
ajst-15595	132	17	the	the	DET
ajst-15595	132	18	gauss	gauss	ADJ
ajst-15595	132	19	-	-	PUNCT
ajst-15595	132	20	markov	markov	NOUN
ajst-15595	132	21	hypothesis	hypothesis	NOUN
ajst-15595	132	22	,	,	PUNCT
ajst-15595	132	23	it	it	PRON
ajst-15595	132	24	can	can	AUX
ajst-15595	132	25	be	be	AUX
ajst-15595	132	26	expressed	express	VERB
ajst-15595	132	27	as	as	SCONJ
ajst-15595	132	28	follows	follow	VERB
ajst-15595	132	29	:	:	PUNCT
ajst-15595	132	30			NOUN
ajst-15595	132	31			PUNCT
ajst-15595	132	32	0	0	NUM
ajst-15595	132	33	1	1	NUM
ajst-15595	132	34	1	1	NUM
ajst-15595	132	35	2	2	NUM
ajst-15595	132	36	2	2	NUM
ajst-15595	132	37	k	k	NOUN
ajst-15595	132	38	ke	ke	NOUN
ajst-15595	132	39	y	y	PROPN
ajst-15595	132	40	x	x	PROPN
ajst-15595	133	1	a	a	DET
ajst-15595	133	2	a	a	X
ajst-15595	133	3	x	x	SYM
ajst-15595	133	4	a	a	DET
ajst-15595	133	5	x	x	X
ajst-15595	133	6	a	a	DET
ajst-15595	133	7	x	x	PROPN
ajst-15595	133	8			PROPN
ajst-15595	133	9			PUNCT
ajst-15595	133	10			PUNCT
ajst-15595	133	11			ADJ
ajst-15595	133	12	where	where	SCONJ
ajst-15595	133	13	,	,	PUNCT
ajst-15595	133	14	0	0	NUM
ajst-15595	133	15	1	1	NUM
ajst-15595	133	16	,	,	PUNCT
ajst-15595	133	17	,	,	PUNCT
ajst-15595	133	18	,	,	PUNCT
ajst-15595	133	19	ka	ka	PROPN
ajst-15595	133	20	a	a	DET
ajst-15595	133	21	a	a	NOUN
ajst-15595	133	22	is	be	AUX
ajst-15595	133	23	the	the	DET
ajst-15595	133	24	coefficient	coefficient	NOUN
ajst-15595	133	25	of	of	ADP
ajst-15595	133	26	explanatory	explanatory	ADJ
ajst-15595	133	27	variable	variable	NOUN
ajst-15595	133	28	to	to	PART
ajst-15595	133	29	be	be	AUX
ajst-15595	133	30	estimated	estimate	VERB
ajst-15595	133	31	.	.	PUNCT
ajst-15595	134	1	the	the	DET
ajst-15595	134	2	above	above	ADJ
ajst-15595	134	3	model	model	NOUN
ajst-15595	134	4	is	be	AUX
ajst-15595	134	5	the	the	DET
ajst-15595	134	6	expression	expression	NOUN
ajst-15595	134	7	of	of	ADP
ajst-15595	134	8	the	the	DET
ajst-15595	134	9	mean	mean	ADJ
ajst-15595	134	10	reversion	reversion	NOUN
ajst-15595	134	11	model	model	NOUN
ajst-15595	134	12	,	,	PUNCT
ajst-15595	134	13	which	which	PRON
ajst-15595	134	14	is	be	AUX
ajst-15595	134	15	the	the	DET
ajst-15595	134	16	result	result	NOUN
ajst-15595	134	17	of	of	ADP
ajst-15595	134	18	taking	take	VERB
ajst-15595	134	19	the	the	DET
ajst-15595	134	20	mathematical	mathematical	ADJ
ajst-15595	134	21	expectation	expectation	NOUN
ajst-15595	134	22	on	on	ADP
ajst-15595	134	23	both	both	DET
ajst-15595	134	24	sides	side	NOUN
ajst-15595	134	25	of	of	ADP
ajst-15595	134	26	the	the	DET
ajst-15595	134	27	equation	equation	NOUN
ajst-15595	134	28	.	.	PUNCT
ajst-15595	135	1	similar	similar	ADJ
ajst-15595	135	2	to	to	ADP
ajst-15595	135	3	the	the	DET
ajst-15595	135	4	mean	mean	ADJ
ajst-15595	135	5	regression	regression	NOUN
ajst-15595	135	6	model	model	NOUN
ajst-15595	135	7	,	,	PUNCT
ajst-15595	135	8	the	the	DET
ajst-15595	135	9	median	median	ADJ
ajst-15595	135	10	regression	regression	NOUN
ajst-15595	135	11	model	model	NOUN
ajst-15595	135	12	can	can	AUX
ajst-15595	135	13	also	also	ADV
ajst-15595	135	14	be	be	AUX
ajst-15595	135	15	set	set	VERB
ajst-15595	135	16	as	as	SCONJ
ajst-15595	135	17	follows	follow	VERB
ajst-15595	135	18	:	:	PUNCT
ajst-15595	135	19			NOUN
ajst-15595	135	20			SYM
ajst-15595	135	21			NOUN
ajst-15595	136	1	0	0	NOUN
ajst-15595	136	2	1	1	NUM
ajst-15595	136	3	1	1	NUM
ajst-15595	136	4	2	2	NUM
ajst-15595	136	5	2	2	NUM
ajst-15595	136	6	k	k	NOUN
ajst-15595	136	7	km	km	NOUN
ajst-15595	136	8	y	y	PROPN
ajst-15595	136	9	x	x	PROPN
ajst-15595	136	10	a	a	DET
ajst-15595	136	11	a	a	X
ajst-15595	136	12	x	x	SYM
ajst-15595	136	13	a	a	DET
ajst-15595	136	14	x	x	SYM
ajst-15595	136	15	a	a	DET
ajst-15595	136	16	x	x	NOUN
ajst-15595	136	17	m	m	VERB
ajst-15595	136	18	u	u	X
ajst-15595	136	19			PROPN
ajst-15595	136	20			PUNCT
ajst-15595	136	21			PUNCT
ajst-15595	136	22			PUNCT
ajst-15595	136	23			ADJ
ajst-15595	136	24	where	where	SCONJ
ajst-15595	136	25	,	,	PUNCT
ajst-15595	136	26			PROPN
ajst-15595	136	27	m	m	X
ajst-15595	136	28	y	y	NOUN
ajst-15595	136	29	x	x	PROPN
ajst-15595	136	30	is	be	AUX
ajst-15595	136	31	the	the	DET
ajst-15595	136	32	conditional	conditional	ADJ
ajst-15595	136	33	median	median	NOUN
ajst-15595	136	34	about	about	ADP
ajst-15595	136	35	x	x	PROPN
ajst-15595	136	36	,	,	PUNCT
ajst-15595	136	37	and	and	CCONJ
ajst-15595	136	38			ADJ
ajst-15595	136	39	m	m	NOUN
ajst-15595	136	40	u	u	NOUN
ajst-15595	136	41	is	be	AUX
ajst-15595	136	42	the	the	DET
ajst-15595	136	43	median	median	NOUN
ajst-15595	136	44	of	of	ADP
ajst-15595	136	45	the	the	DET
ajst-15595	136	46	random	random	ADJ
ajst-15595	136	47	disturbance	disturbance	NOUN
ajst-15595	136	48	term	term	NOUN
ajst-15595	136	49	.	.	PUNCT
ajst-15595	137	1	the	the	DET
ajst-15595	137	2	quantile	quantile	ADJ
ajst-15595	137	3	regression	regression	NOUN
ajst-15595	137	4	model	model	NOUN
ajst-15595	137	5	is	be	AUX
ajst-15595	137	6	as	as	SCONJ
ajst-15595	137	7	follows	follow	VERB
ajst-15595	137	8	:	:	PUNCT
ajst-15595	138	1			NOUN
ajst-15595	138	2			SYM
ajst-15595	138	3			NOUN
ajst-15595	139	1	0	0	NOUN
ajst-15595	139	2	1	1	NUM
ajst-15595	139	3	1	1	NUM
ajst-15595	139	4	2	2	NUM
ajst-15595	139	5	2y	2y	NOUN
ajst-15595	139	6	k	k	PROPN
ajst-15595	139	7	k	k	PROPN
ajst-15595	139	8	uq	uq	PROPN
ajst-15595	139	9	x	x	PROPN
ajst-15595	139	10	a	a	DET
ajst-15595	139	11	a	a	DET
ajst-15595	139	12	x	x	SYM
ajst-15595	139	13	a	a	DET
ajst-15595	139	14	x	x	SYM
ajst-15595	139	15	a	a	DET
ajst-15595	139	16	x	x	X
ajst-15595	139	17	q	q	PROPN
ajst-15595	139	18			VERB
ajst-15595	139	19			ADV
ajst-15595	139	20			PUNCT
ajst-15595	139	21			PUNCT
ajst-15595	139	22			PUNCT
ajst-15595	139	23			ADJ
ajst-15595	139	24	for	for	ADP
ajst-15595	139	25	the	the	DET
ajst-15595	139	26	mean	mean	ADJ
ajst-15595	139	27	regression	regression	NOUN
ajst-15595	139	28	model	model	NOUN
ajst-15595	139	29	,	,	PUNCT
ajst-15595	139	30	the	the	DET
ajst-15595	139	31	least	least	ADJ
ajst-15595	139	32	squares	square	NOUN
ajst-15595	139	33	method	method	NOUN
ajst-15595	139	34	(	(	PUNCT
ajst-15595	139	35	ols	ol	NOUN
ajst-15595	139	36	)	)	PUNCT
ajst-15595	139	37	can	can	AUX
ajst-15595	139	38	be	be	AUX
ajst-15595	139	39	used	use	VERB
ajst-15595	139	40	to	to	PART
ajst-15595	139	41	estimate	estimate	VERB
ajst-15595	139	42	the	the	DET
ajst-15595	139	43	unknown	unknown	ADJ
ajst-15595	139	44	parameters	parameter	NOUN
ajst-15595	139	45	.	.	PUNCT
ajst-15595	140	1	for	for	ADP
ajst-15595	140	2	the	the	DET
ajst-15595	140	3	median	median	ADJ
ajst-15595	140	4	regression	regression	NOUN
ajst-15595	140	5	model	model	NOUN
ajst-15595	140	6	,	,	PUNCT
ajst-15595	140	7	the	the	DET
ajst-15595	140	8	least	least	ADJ
ajst-15595	140	9	square	square	ADJ
ajst-15595	140	10	method	method	NOUN
ajst-15595	140	11	(	(	PUNCT
ajst-15595	140	12	lad	lad	NOUN
ajst-15595	140	13	)	)	PUNCT
ajst-15595	140	14	can	can	AUX
ajst-15595	140	15	be	be	AUX
ajst-15595	140	16	used	use	VERB
ajst-15595	140	17	;	;	PUNCT
ajst-15595	140	18	for	for	ADP
ajst-15595	140	19	quantile	quantile	ADJ
ajst-15595	140	20	regression	regression	NOUN
ajst-15595	140	21	model	model	NOUN
ajst-15595	140	22	,	,	PUNCT
ajst-15595	140	23	the	the	DET
ajst-15595	140	24	linear	linear	ADJ
ajst-15595	140	25	programming	programming	NOUN
ajst-15595	140	26	method	method	NOUN
ajst-15595	140	27	(	(	PUNCT
ajst-15595	140	28	lp	lp	NOUN
ajst-15595	140	29	)	)	PUNCT
ajst-15595	140	30	can	can	AUX
ajst-15595	140	31	be	be	AUX
ajst-15595	140	32	used	use	VERB
ajst-15595	140	33	to	to	PART
ajst-15595	140	34	estimate	estimate	VERB
ajst-15595	140	35	the	the	DET
ajst-15595	140	36	minimum	minimum	NOUN
ajst-15595	140	37	weighted	weight	VERB
ajst-15595	140	38	absolute	absolute	ADJ
ajst-15595	140	39	deviation	deviation	NOUN
ajst-15595	140	40	,	,	PUNCT
ajst-15595	140	41	and	and	CCONJ
ajst-15595	140	42	the	the	DET
ajst-15595	140	43	regression	regression	NOUN
ajst-15595	140	44	coefficient	coefficient	NOUN
ajst-15595	140	45	of	of	ADP
ajst-15595	140	46	explanatory	explanatory	ADJ
ajst-15595	140	47	variables	variable	NOUN
ajst-15595	140	48	can	can	AUX
ajst-15595	140	49	be	be	AUX
ajst-15595	140	50	obtained	obtain	VERB
ajst-15595	140	51	.	.	PUNCT
ajst-15595	141	1	they	they	PRON
ajst-15595	141	2	can	can	AUX
ajst-15595	141	3	be	be	AUX
ajst-15595	141	4	expressed	express	VERB
ajst-15595	141	5	as	as	SCONJ
ajst-15595	141	6	follows	follow	VERB
ajst-15595	141	7	:	:	PUNCT
ajst-15595	141	8	ols	ol	NOUN
ajst-15595	141	9	approach	approach	NOUN
ajst-15595	141	10	:	:	PUNCT
ajst-15595	141	11			NOUN
ajst-15595	142	1	2	2	NOUN
ajst-15595	142	2	0	0	NUM
ajst-15595	142	3	1	1	NUM
ajst-15595	142	4	1	1	NUM
ajst-15595	142	5	2	2	NUM
ajst-15595	142	6	2min	2min	NOUN
ajst-15595	142	7	k	k	PROPN
ajst-15595	142	8	ke	ke	NOUN
ajst-15595	142	9	y	y	PROPN
ajst-15595	142	10	a	a	DET
ajst-15595	142	11	a	a	DET
ajst-15595	142	12	x	x	SYM
ajst-15595	142	13	a	a	DET
ajst-15595	142	14	x	x	X
ajst-15595	142	15	a	a	DET
ajst-15595	142	16	x	x	PROPN
ajst-15595	142	17			PROPN
ajst-15595	142	18			PROPN
ajst-15595	142	19			PROPN
ajst-15595	142	20			NOUN
ajst-15595	142	21	be	be	AUX
ajst-15595	142	22	solved	solve	VERB
ajst-15595	142	23	:	:	PUNCT
ajst-15595	142	24			NOUN
ajst-15595	142	25			PUNCT
ajst-15595	142	26	0	0	NUM
ajst-15595	142	27	1	1	NUM
ajst-15595	142	28	1	1	NUM
ajst-15595	142	29	2	2	NUM
ajst-15595	142	30	2	2	NUM
ajst-15595	142	31	ˆ	ˆ	NOUN
ajst-15595	142	32	ˆ	ˆ	NOUN
ajst-15595	142	33	ˆ	ˆ	NOUN
ajst-15595	142	34	ˆ	ˆ	ADV
ajst-15595	142	35	ˆk	ˆk	PROPN
ajst-15595	142	36	ke	ke	NOUN
ajst-15595	142	37	y	y	PROPN
ajst-15595	142	38	x	x	PROPN
ajst-15595	143	1	a	a	DET
ajst-15595	143	2	a	a	X
ajst-15595	143	3	x	x	SYM
ajst-15595	143	4	a	a	PRON
ajst-15595	143	5	x	x	X
ajst-15595	143	6	a	a	DET
ajst-15595	143	7	x	x	PROPN
ajst-15595	143	8			PROPN
ajst-15595	143	9			PUNCT
ajst-15595	143	10			PUNCT
ajst-15595	143	11			ADJ
ajst-15595	143	12	lad	lad	NOUN
ajst-15595	143	13	approach	approach	NOUN
ajst-15595	143	14	:	:	PUNCT
ajst-15595	143	15	0	0	NUM
ajst-15595	143	16	1	1	NUM
ajst-15595	143	17	1	1	NUM
ajst-15595	143	18	2	2	NUM
ajst-15595	143	19	2min	2min	NOUN
ajst-15595	143	20	k	k	PROPN
ajst-15595	143	21	ke	ke	NOUN
ajst-15595	143	22	y	y	PROPN
ajst-15595	143	23	a	a	PRON
ajst-15595	143	24	a	a	PRON
ajst-15595	143	25	x	x	SYM
ajst-15595	143	26	a	a	PRON
ajst-15595	143	27	x	x	X
ajst-15595	143	28	a	a	DET
ajst-15595	143	29	x	x	PROPN
ajst-15595	143	30			PROPN
ajst-15595	143	31			PROPN
ajst-15595	143	32			PROPN
ajst-15595	143	33			NOUN
ajst-15595	143	34	be	be	AUX
ajst-15595	143	35	solved	solve	VERB
ajst-15595	143	36	：	：	PUNCT
ajst-15595	143	37			NOUN
ajst-15595	143	38			PROPN
ajst-15595	143	39	0	0	NUM
ajst-15595	143	40	1	1	NUM
ajst-15595	143	41	1	1	NUM
ajst-15595	143	42	2	2	NUM
ajst-15595	143	43	2	2	NUM
ajst-15595	143	44	ˆ	ˆ	NOUN
ajst-15595	143	45	ˆ	ˆ	NOUN
ajst-15595	143	46	ˆ	ˆ	NOUN
ajst-15595	143	47	ˆ	ˆ	ADV
ajst-15595	143	48	ˆk	ˆk	ADP
ajst-15595	143	49	km	km	PROPN
ajst-15595	143	50	y	y	PROPN
ajst-15595	143	51	x	x	PROPN
ajst-15595	143	52	a	a	PRON
ajst-15595	143	53	a	a	X
ajst-15595	143	54	x	x	SYM
ajst-15595	143	55	a	a	PRON
ajst-15595	143	56	x	x	X
ajst-15595	143	57	a	a	DET
ajst-15595	143	58	x	x	PROPN
ajst-15595	143	59			PROPN
ajst-15595	143	60			PUNCT
ajst-15595	143	61			PUNCT
ajst-15595	143	62			PROPN
ajst-15595	143	63	qr	qr	NOUN
ajst-15595	143	64	approach	approach	NOUN
ajst-15595	143	65	:	:	PUNCT
ajst-15595	143	66			NOUN
ajst-15595	143	67	0	0	NOUN
ajst-15595	143	68	1	1	NUM
ajst-15595	143	69	1	1	NUM
ajst-15595	143	70	2	2	NUM
ajst-15595	143	71	2min	2min	NOUN
ajst-15595	143	72	k	k	PROPN
ajst-15595	143	73	ke	ke	NOUN
ajst-15595	143	74	y	y	PROPN
ajst-15595	143	75	a	a	DET
ajst-15595	143	76	a	a	DET
ajst-15595	143	77	x	x	SYM
ajst-15595	143	78	a	a	DET
ajst-15595	143	79	x	x	X
ajst-15595	143	80	a	a	DET
ajst-15595	143	81	x	x	PROPN
ajst-15595	143	82			PROPN
ajst-15595	143	83			PROPN
ajst-15595	143	84			PROPN
ajst-15595	143	85			PROPN
ajst-15595	143	86			NOUN
ajst-15595	143	87	be	be	AUX
ajst-15595	143	88	solved	solve	VERB
ajst-15595	143	89	:	:	PUNCT
ajst-15595	143	90			NOUN
ajst-15595	143	91			PUNCT
ajst-15595	143	92	0	0	NUM
ajst-15595	143	93	1	1	NUM
ajst-15595	143	94	1	1	NUM
ajst-15595	143	95	2	2	NUM
ajst-15595	143	96	2	2	NUM
ajst-15595	143	97	ˆ	ˆ	NOUN
ajst-15595	143	98	ˆ	ˆ	NOUN
ajst-15595	143	99	ˆ	ˆ	NOUN
ajst-15595	143	100	ˆ	ˆ	ADV
ajst-15595	143	101	ˆy	ˆy	ADP
ajst-15595	143	102	k	k	PROPN
ajst-15595	143	103	kq	kq	PROPN
ajst-15595	143	104	x	x	PROPN
ajst-15595	143	105	a	a	DET
ajst-15595	143	106	a	a	NOUN
ajst-15595	143	107	x	x	SYM
ajst-15595	143	108	a	a	PRON
ajst-15595	143	109	x	x	SYM
ajst-15595	143	110	a	a	DET
ajst-15595	143	111	x	x	PROPN
ajst-15595	143	112			PROPN
ajst-15595	143	113			ADV
ajst-15595	143	114			PUNCT
ajst-15595	143	115			PUNCT
ajst-15595	143	116			ADJ
ajst-15595	143	117	where	where	SCONJ
ajst-15595	143	118	,	,	PUNCT
ajst-15595	143	119			NOUN
ajst-15595	144	1			SYM
ajst-15595	144	2			NOUN
ajst-15595	144	3			NOUN
ajst-15595	144	4			PUNCT
ajst-15595	144	5			PROPN
ajst-15595	145	1	0	0	INTJ
ajst-15595	145	2	,	,	PUNCT
ajst-15595	145	3	0,1	0,1	X
ajst-15595	145	4			NOUN
ajst-15595	145	5			VERB
ajst-15595	145	6			NOUN
ajst-15595	145	7			PROPN
ajst-15595	145	8	t	t	PROPN
ajst-15595	145	9	t	t	PROPN
ajst-15595	145	10	i	i	PRON
ajst-15595	145	11	t	t	PROPN
ajst-15595	145	12	.	.	PUNCT
ajst-15595	146	1	2.2	2.2	NUM
ajst-15595	146	2	.	.	PUNCT
ajst-15595	147	1	panel	panel	NOUN
ajst-15595	147	2	data	datum	NOUN
ajst-15595	147	3	model	model	NOUN
ajst-15595	147	4	and	and	CCONJ
ajst-15595	147	5	quantile	quantile	ADJ
ajst-15595	147	6	regression	regression	NOUN
ajst-15595	147	7	method	method	NOUN
ajst-15595	147	8	considering	consider	VERB
ajst-15595	147	9	the	the	DET
ajst-15595	147	10	general	general	ADJ
ajst-15595	147	11	panel	panel	NOUN
ajst-15595	147	12	data	datum	NOUN
ajst-15595	147	13	model	model	PROPN
ajst-15595	147	14	,	,	PUNCT
ajst-15595	147	15	the	the	DET
ajst-15595	147	16	expression	expression	NOUN
ajst-15595	147	17	is	be	AUX
ajst-15595	147	18	as	as	SCONJ
ajst-15595	147	19	follows	follow	VERB
ajst-15595	147	20	:	:	PUNCT
ajst-15595	147	21	'	'	PUNCT
ajst-15595	147	22	,	,	PUNCT
ajst-15595	147	23	1	1	NUM
ajst-15595	147	24	,	,	PUNCT
ajst-15595	147	25	2	2	NUM
ajst-15595	147	26	,	,	PUNCT
ajst-15595	147	27	,	,	PUNCT
ajst-15595	147	28	.	.	PUNCT
ajst-15595	148	1	1	1	NUM
ajst-15595	148	2	,	,	PUNCT
ajst-15595	148	3	2	2	NUM
ajst-15595	148	4	,	,	PUNCT
ajst-15595	148	5	,	,	PUNCT
ajst-15595	148	6	.it	.it	PUNCT
ajst-15595	149	1	it	it	PRON
ajst-15595	150	1	i	i	PRON
ajst-15595	150	2	ity	ity	VERB
ajst-15595	150	3	x	x	PUNCT
ajst-15595	150	4	u	u	VERB
ajst-15595	150	5	i	i	NOUN
ajst-15595	150	6	n	n	VERB
ajst-15595	150	7	t	t	NOUN
ajst-15595	150	8	t	t	PRON
ajst-15595	150	9			NOUN
ajst-15595	150	10			ADV
ajst-15595	150	11			PUNCT
ajst-15595	150	12			PROPN
ajst-15595	150	13			ADJ
ajst-15595	150	14			NOUN
ajst-15595	150	15	where	where	SCONJ
ajst-15595	150	16	,	,	PUNCT
ajst-15595	150	17	i	i	PRON
ajst-15595	150	18	represents	represent	VERB
ajst-15595	150	19	different	different	ADJ
ajst-15595	150	20	sample	sample	NOUN
ajst-15595	150	21	individuals	individual	NOUN
ajst-15595	150	22	,	,	PUNCT
ajst-15595	150	23	t	t	PROPN
ajst-15595	150	24	represents	represent	VERB
ajst-15595	150	25	different	different	ADJ
ajst-15595	150	26	sample	sample	NOUN
ajst-15595	150	27	observation	observation	NOUN
ajst-15595	150	28	time	time	NOUN
ajst-15595	150	29	points	point	NOUN
ajst-15595	150	30	,	,	PUNCT
ajst-15595	150	31	u	u	PRON
ajst-15595	150	32	represents	represent	VERB
ajst-15595	150	33	the	the	DET
ajst-15595	150	34	random	random	ADJ
ajst-15595	150	35	error	error	NOUN
ajst-15595	150	36	term	term	NOUN
ajst-15595	150	37	,	,	PUNCT
ajst-15595	150	38	β	β	NOUN
ajst-15595	150	39	represents	represent	VERB
ajst-15595	150	40	the	the	DET
ajst-15595	150	41	coefficient	coefficient	NOUN
ajst-15595	150	42	vector	vector	NOUN
ajst-15595	150	43	of	of	ADP
ajst-15595	150	44	the	the	DET
ajst-15595	150	45	explanatory	explanatory	ADJ
ajst-15595	150	46	variable	variable	NOUN
ajst-15595	150	47	,	,	PUNCT
ajst-15595	150	48	and	and	CCONJ
ajst-15595	150	49	i	i	PRON
ajst-15595	150	50	represents	represent	VERB
ajst-15595	150	51	the	the	DET
ajst-15595	150	52	unobservable	unobservable	ADJ
ajst-15595	150	53	random	random	ADJ
ajst-15595	150	54	effect	effect	NOUN
ajst-15595	150	55	of	of	ADP
ajst-15595	150	56	the	the	DET
ajst-15595	150	57	i	i	PROPN
ajst-15595	150	58	th	th	X
ajst-15595	150	59	sample	sample	NOUN
ajst-15595	150	60	.	.	PUNCT
ajst-15595	151	1			NOUN
ajst-15595	151	2			PROPN
ajst-15595	151	3	'	'	PART
ajst-15595	151	4	1	1	NUM
ajst-15595	151	5	21	21	NUM
ajst-15595	151	6	,	,	PUNCT
ajst-15595	151	7	,	,	PUNCT
ajst-15595	151	8	,	,	PUNCT
ajst-15595	151	9	,	,	PUNCT
ajst-15595	151	10			NUM
ajst-15595	151	11	it	it	NUM
ajst-15595	151	12	it	it	PRON
ajst-15595	151	13	it	it	PRON
ajst-15595	151	14	itpx	itpx	VERB
ajst-15595	151	15	x	x	PUNCT
ajst-15595	151	16	x	x	SYM
ajst-15595	151	17	x	x	X
ajst-15595	151	18	,	,	PUNCT
ajst-15595	151	19	in	in	ADP
ajst-15595	151	20	the	the	DET
ajst-15595	151	21	fixed	fix	VERB
ajst-15595	151	22	effect	effect	NOUN
ajst-15595	151	23	case	case	NOUN
ajst-15595	151	24	,	,	PUNCT
ajst-15595	151	25	the	the	DET
ajst-15595	151	26	estimator	estimator	NOUN
ajst-15595	151	27	of	of	ADP
ajst-15595	151	28	beta	beta	NOUN
ajst-15595	151	29	is	be	AUX
ajst-15595	151	30	2	2	NUM
ajst-15595	151	31	,	,	PUNCT
ajst-15595	151	32	min	min	NOUN
ajst-15595	151	33			NOUN
ajst-15595	152	1			PROPN
ajst-15595	152	2			PROPN
ajst-15595	152	3			CCONJ
ajst-15595	152	4	y	y	NOUN
ajst-15595	152	5	x	x	X
ajst-15595	152	6	z	z	NOUN
ajst-15595	152	7			NOUN
ajst-15595	152	8			SYM
ajst-15595	152	9			NOUN
ajst-15595	153	1	1	1	ADJ
ajst-15595	153	2	1ˆ	1ˆ	NOUN
ajst-15595	153	3	,	,	PUNCT
ajst-15595	153	4	,	,	PUNCT
ajst-15595	153	5			PROPN
ajst-15595	153	6			PROPN
ajst-15595	153	7			VERB
ajst-15595	153	8			ADV
ajst-15595	153	9			ADJ
ajst-15595	153	10			ADP
ajst-15595	154	1			NUM
ajst-15595	154	2			NOUN
ajst-15595	154	3	xmx	xmx	NOUN
ajst-15595	154	4	xmy	xmy	NOUN
ajst-15595	154	5	m	m	VERB
ajst-15595	154	6	i	i	PRON
ajst-15595	154	7	p	p	X
ajst-15595	154	8	p	p	PROPN
ajst-15595	154	9	z	z	NOUN
ajst-15595	154	10	z	z	NOUN
ajst-15595	154	11	z	z	NOUN
ajst-15595	154	12	z	z	NOUN
ajst-15595	154	13	assumptions	assumption	NOUN
ajst-15595	154	14	:	:	PUNCT
ajst-15595	154	15	u	u	NOUN
ajst-15595	154	16	~	~	PUNCT
ajst-15595	154	17	n(0,r	n(0,r	NUM
ajst-15595	154	18	)	)	PUNCT
ajst-15595	154	19	,	,	PUNCT
ajst-15595	154	20	~n(0,w	~n(0,w	NUM
ajst-15595	154	21	)	)	PUNCT
ajst-15595	154	22	v=	v=	NOUN
ajst-15595	154	23	z+u，	z+u，	NOUN
ajst-15595	154	24			X
ajst-15595	154	25	then	then	ADV
ajst-15595	154	26			NOUN
ajst-15595	154	27			SYM
ajst-15595	154	28			NOUN
ajst-15595	155	1	e	e	INTJ
ajst-15595	155	2	vv	vv	ADP
ajst-15595	155	3	zwz	zwz	NOUN
ajst-15595	155	4	r	r	NOUN
ajst-15595	155	5	v	v	NOUN
ajst-15595	155	6			PROPN
ajst-15595	155	7			ADJ
ajst-15595	155	8			NUM
ajst-15595	155	9	gls	gl	VERB
ajst-15595	155	10	estimation	estimation	NOUN
ajst-15595	155	11	method	method	NOUN
ajst-15595	155	12	and	and	CCONJ
ajst-15595	155	13	penalty	penalty	NOUN
ajst-15595	155	14	least	least	ADJ
ajst-15595	155	15	square	square	ADJ
ajst-15595	155	16	method	method	NOUN
ajst-15595	155	17	(	(	PUNCT
ajst-15595	155	18	pls	pls	INTJ
ajst-15595	155	19	)	)	PUNCT
ajst-15595	155	20	reflecting	reflect	VERB
ajst-15595	155	21	individual	individual	ADJ
ajst-15595	155	22	influence	influence	NOUN
ajst-15595	155	23	can	can	AUX
ajst-15595	155	24	be	be	AUX
ajst-15595	155	25	used	use	VERB
ajst-15595	155	26	to	to	PART
ajst-15595	155	27	estimate	estimate	VERB
ajst-15595	155	28	regression	regression	NOUN
ajst-15595	155	29	coefficient	coefficient	NOUN
ajst-15595	155	30	β	β	PROPN
ajst-15595	155	31	for	for	ADP
ajst-15595	155	32	panel	panel	NOUN
ajst-15595	155	33	data	datum	NOUN
ajst-15595	155	34	model	model	NOUN
ajst-15595	155	35	in	in	ADP
ajst-15595	155	36	this	this	DET
ajst-15595	155	37	case	case	NOUN
ajst-15595	155	38	,	,	PUNCT
ajst-15595	155	39	respectively	respectively	ADV
ajst-15595	155	40	expressed	express	VERB
ajst-15595	155	41	as	as	SCONJ
ajst-15595	155	42	follows	follow	VERB
ajst-15595	155	43	:	:	PUNCT
ajst-15595	155	44	gls	gls	NOUN
ajst-15595	155	45	method	method	NOUN
ajst-15595	155	46	:	:	PUNCT
ajst-15595	155	47	1	1	NUM
ajst-15595	155	48	2	2	NUM
ajst-15595	155	49	min	min	NOUN
ajst-15595	155	50	v	v	ADP
ajst-15595	155	51	y	y	PROPN
ajst-15595	155	52	x	x	PROPN
ajst-15595	155	53			NOUN
ajst-15595	155	54			PROPN
ajst-15595	155	55			NOUN
ajst-15595	155	56	pls	pls	INTJ
ajst-15595	155	57	method	method	NOUN
ajst-15595	155	58	:	:	PUNCT
ajst-15595	155	59	1	1	NUM
ajst-15595	155	60	1	1	NUM
ajst-15595	155	61	2	2	NUM
ajst-15595	155	62	2	2	NUM
ajst-15595	155	63	,	,	PUNCT
ajst-15595	156	1	min	min	NOUN
ajst-15595	156	2	r	r	NOUN
ajst-15595	156	3	w	w	PROPN
ajst-15595	156	4	y	y	PROPN
ajst-15595	156	5	x	x	SYM
ajst-15595	156	6			NUM
ajst-15595	156	7			PROPN
ajst-15595	156	8			PROPN
ajst-15595	156	9			X
ajst-15595	156	10			PROPN
ajst-15595	156	11			VERB
ajst-15595	156	12	the	the	DET
ajst-15595	156	13	common	common	ADJ
ajst-15595	156	14	solution	solution	NOUN
ajst-15595	156	15	of	of	ADP
ajst-15595	156	16	both	both	PRON
ajst-15595	156	17	is	be	AUX
ajst-15595	156	18	:	:	PUNCT
ajst-15595	156	19			NOUN
ajst-15595	156	20			PROPN
ajst-15595	156	21	11	11	NUM
ajst-15595	156	22	1ˆ	1ˆ	NOUN
ajst-15595	156	23	x	x	SYM
ajst-15595	156	24	v	v	NOUN
ajst-15595	156	25	x	x	SYM
ajst-15595	156	26	x	x	SYM
ajst-15595	156	27	v	v	NOUN
ajst-15595	156	28	y	y	PROPN
ajst-15595	156	29			PROPN
ajst-15595	156	30			PROPN
ajst-15595	156	31			PROPN
ajst-15595	156	32	.	.	PUNCT
ajst-15595	157	1	quantile	quantile	ADJ
ajst-15595	157	2	regression	regression	NOUN
ajst-15595	157	3	method	method	NOUN
ajst-15595	157	4	can	can	AUX
ajst-15595	157	5	also	also	ADV
ajst-15595	157	6	be	be	AUX
ajst-15595	157	7	used	use	VERB
ajst-15595	157	8	to	to	PART
ajst-15595	157	9	estimate	estimate	VERB
ajst-15595	157	10	the	the	DET
ajst-15595	157	11	parameters	parameter	NOUN
ajst-15595	157	12	of	of	ADP
ajst-15595	157	13	the	the	DET
ajst-15595	157	14	panel	panel	NOUN
ajst-15595	157	15	data	datum	NOUN
ajst-15595	157	16	model	model	NOUN
ajst-15595	157	17	.	.	PUNCT
ajst-15595	158	1	for	for	ADP
ajst-15595	158	2	that	that	PRON
ajst-15595	158	3	.	.	PUNCT
ajst-15595	159	1	the	the	DET
ajst-15595	159	2	quantile	quantile	ADJ
ajst-15595	159	3	equation	equation	NOUN
ajst-15595	159	4	under	under	ADP
ajst-15595	159	5	the	the	DET
ajst-15595	159	6	following	follow	VERB
ajst-15595	159	7	conditions	condition	NOUN
ajst-15595	159	8	is	be	AUX
ajst-15595	159	9	established	establish	VERB
ajst-15595	159	10	:	:	PUNCT
ajst-15595	159	11			NOUN
ajst-15595	159	12			PROPN
ajst-15595	159	13			NOUN
ajst-15595	159	14			PROPN
ajst-15595	159	15	'	'	NOUN
ajst-15595	159	16	,	,	PUNCT
ajst-15595	159	17	ity	ity	PROPN
ajst-15595	159	18	j	j	PROPN
ajst-15595	159	19	it	it	PRON
ajst-15595	160	1	i	i	PRON
ajst-15595	160	2	it	it	PRON
ajst-15595	161	1	j	j	INTJ
ajst-15595	161	2	iq	iq	INTJ
ajst-15595	161	3	x	x	PROPN
ajst-15595	161	4	x	x	PROPN
ajst-15595	161	5			NUM
ajst-15595	161	6			PROPN
ajst-15595	161	7			NOUN
ajst-15595	161	8			NOUN
ajst-15595	161	9			PUNCT
ajst-15595	161	10	,	,	PUNCT
ajst-15595	161	11	1,2	1,2	NUM
ajst-15595	161	12	,	,	PUNCT
ajst-15595	161	13	...	...	PUNCT
ajst-15595	161	14	,	,	PUNCT
ajst-15595	161	15	;	;	PUNCT
ajst-15595	161	16	1,2,	1,2,	NUM
ajst-15595	161	17	...	...	PUNCT
ajst-15595	161	18	,i	,i	PUNCT
ajst-15595	161	19	n	n	PRON
ajst-15595	161	20	t	t	NOUN
ajst-15595	161	21	t	t	PROPN
ajst-15595	161	22			PROPN
ajst-15595	161	23	the	the	DET
ajst-15595	161	24	quantile	quantile	ADJ
ajst-15595	161	25	equation	equation	NOUN
ajst-15595	161	26	above	above	ADV
ajst-15595	161	27	assumes	assume	VERB
ajst-15595	161	28	that	that	SCONJ
ajst-15595	161	29	the	the	DET
ajst-15595	161	30	individual	individual	ADJ
ajst-15595	161	31	effects	effect	NOUN
ajst-15595	161	32	are	be	AUX
ajst-15595	161	33	fixed	fix	VERB
ajst-15595	161	34	.	.	PUNCT
ajst-15595	162	1	for	for	ADP
ajst-15595	162	2	this	this	DET
ajst-15595	162	3	equation	equation	NOUN
ajst-15595	162	4	,	,	PUNCT
ajst-15595	162	5	koenker	koenker	NOUN
ajst-15595	162	6	(	(	PUNCT
ajst-15595	162	7	2004	2004	NUM
ajst-15595	162	8	)	)	PUNCT
ajst-15595	162	9	pointed	point	VERB
ajst-15595	162	10	out	out	ADP
ajst-15595	162	11	that	that	SCONJ
ajst-15595	162	12	when	when	SCONJ
ajst-15595	162	13	the	the	DET
ajst-15595	162	14	number	number	NOUN
ajst-15595	162	15	of	of	ADP
ajst-15595	162	16	individuals	individual	NOUN
ajst-15595	162	17	n	n	CCONJ
ajst-15595	162	18	is	be	AUX
ajst-15595	162	19	large	large	ADJ
ajst-15595	162	20	and	and	CCONJ
ajst-15595	162	21	the	the	DET
ajst-15595	162	22	number	number	NOUN
ajst-15595	162	23	of	of	ADP
ajst-15595	162	24	observations	observation	NOUN
ajst-15595	162	25	contained	contain	VERB
ajst-15595	162	26	by	by	ADP
ajst-15595	162	27	each	each	DET
ajst-15595	162	28	individual	individual	NOUN
ajst-15595	162	29	is	be	AUX
ajst-15595	162	30	relatively	relatively	ADV
ajst-15595	162	31	small	small	ADJ
ajst-15595	162	32	,	,	PUNCT
ajst-15595	162	33	appropriate	appropriate	ADJ
ajst-15595	162	34	contraction	contraction	NOUN
ajst-15595	162	35	control	control	NOUN
ajst-15595	162	36	of	of	ADP
ajst-15595	162	37	the	the	DET
ajst-15595	162	38	individual	individual	ADJ
ajst-15595	162	39	effect	effect	NOUN
ajst-15595	162	40	can	can	AUX
ajst-15595	162	41	effectively	effectively	ADV
ajst-15595	162	42	reduce	reduce	VERB
ajst-15595	162	43	the	the	DET
ajst-15595	162	44	variance	variance	NOUN
ajst-15595	162	45	i	i	PRON
ajst-15595	162	46			ADJ
ajst-15595	162	47	due	due	ADP
ajst-15595	162	48	to	to	ADP
ajst-15595	162	49	estimation	estimation	NOUN
ajst-15595	162	50	.	.	PUNCT
ajst-15595	163	1	for	for	ADP
ajst-15595	163	2	the	the	DET
ajst-15595	163	3	linear	linear	PROPN
ajst-15595	163	4	quantile	quantile	ADJ
ajst-15595	163	5	loss	loss	NOUN
ajst-15595	163	6	function	function	NOUN
ajst-15595	163	7	(	(	PUNCT
ajst-15595	163	8	)	)	PUNCT
ajst-15595	163	9	t	t	PROPN
ajst-15595	163	10			NOUN
ajst-15595	163	11			NOUN
ajst-15595	163	12	,	,	PUNCT
ajst-15595	163	13	in	in	ADP
ajst-15595	163	14	order	order	NOUN
ajst-15595	163	15	to	to	PART
ajst-15595	163	16	maintain	maintain	VERB
ajst-15595	163	17	the	the	DET
ajst-15595	163	18	linear	linear	ADJ
ajst-15595	163	19	characteristics	characteristic	NOUN
ajst-15595	163	20	of	of	ADP
ajst-15595	163	21	the	the	DET
ajst-15595	163	22	objective	objective	ADJ
ajst-15595	163	23	function	function	NOUN
ajst-15595	163	24	,	,	PUNCT
ajst-15595	163	25	i	i	PRON
ajst-15595	163	26	l	l	VERB
ajst-15595	163	27	a	a	DET
ajst-15595	163	28	linear	linear	ADJ
ajst-15595	163	29	penalty	penalty	NOUN
ajst-15595	163	30	term	term	NOUN
ajst-15595	163	31	can	can	AUX
ajst-15595	163	32	be	be	AUX
ajst-15595	163	33	considered	consider	VERB
ajst-15595	163	34	,	,	PUNCT
ajst-15595	163	35	that	that	PRON
ajst-15595	163	36	is	is	ADV
ajst-15595	163	37	1	1	NUM
ajst-15595	163	38	(	(	PUNCT
ajst-15595	163	39	)	)	PUNCT
ajst-15595	164	1	|	|	ADV
ajst-15595	164	2	|	|	ADV
ajst-15595	164	3	n	n	INTJ
ajst-15595	165	1	i	i	PRON
ajst-15595	166	1	i	i	PRON
ajst-15595	166	2	p	p	ADJ
ajst-15595	166	3			X
ajst-15595	166	4			X
ajst-15595	166	5			NOUN
ajst-15595	166	6			NOUN
ajst-15595	166	7			VERB
ajst-15595	166	8	a	a	DET
ajst-15595	166	9	penalty	penalty	NOUN
ajst-15595	166	10	quantile	quantile	NOUN
ajst-15595	166	11	regression	regression	NOUN
ajst-15595	166	12	(	(	PUNCT
ajst-15595	166	13	pqr	pqr	NOUN
ajst-15595	166	14	)	)	PUNCT
ajst-15595	166	15	method	method	NOUN
ajst-15595	166	16	is	be	AUX
ajst-15595	166	17	proposed	propose	VERB
ajst-15595	166	18	for	for	ADP
ajst-15595	166	19	estimation	estimation	NOUN
ajst-15595	166	20	.	.	PUNCT
ajst-15595	167	1	the	the	DET
ajst-15595	167	2	details	detail	NOUN
ajst-15595	167	3	are	be	AUX
ajst-15595	167	4	as	as	SCONJ
ajst-15595	167	5	follows	follow	VERB
ajst-15595	167	6	:	:	PUNCT
ajst-15595	168	1			PROPN
ajst-15595	168	2			ADJ
ajst-15595	168	3			X
ajst-15595	168	4			PROPN
ajst-15595	168	5			NOUN
ajst-15595	168	6			PROPN
ajst-15595	168	7			PROPN
ajst-15595	168	8			PROPN
ajst-15595	168	9			X
ajst-15595	169	1			PROPN
ajst-15595	169	2	'	'	PART
ajst-15595	169	3	1	1	NUM
ajst-15595	169	4	,	,	PUNCT
ajst-15595	169	5	1	1	NUM
ajst-15595	169	6	1	1	NUM
ajst-15595	169	7	1	1	NUM
ajst-15595	169	8	1	1	NUM
ajst-15595	169	9	1	1	NUM
ajst-15595	169	10	ˆ	ˆ	NOUN
ajst-15595	169	11	ˆ	ˆ	PROPN
ajst-15595	169	12	,	,	PUNCT
ajst-15595	169	13	,	,	PUNCT
ajst-15595	169	14	arg	arg	PROPN
ajst-15595	169	15	min	min	PROPN
ajst-15595	169	16	j	j	PROPN
ajst-15595	169	17	j	j	PROPN
ajst-15595	169	18	t	t	PROPN
ajst-15595	169	19	n	n	PROPN
ajst-15595	169	20	nj	nj	PROPN
ajst-15595	170	1	n	n	ADV
ajst-15595	170	2	j	j	NOUN
ajst-15595	171	1	i	i	PRON
ajst-15595	171	2	j	j	VERB
ajst-15595	171	3	it	it	PRON
ajst-15595	172	1	it	it	PRON
ajst-15595	172	2	j	j	INTJ
ajst-15595	173	1	i	i	PRON
ajst-15595	173	2	iij	iij	VERB
ajst-15595	174	1	j	j	PROPN
ajst-15595	174	2	t	t	PROPN
ajst-15595	175	1	i	i	PRON
ajst-15595	176	1	i	i	INTJ
ajst-15595	176	2	w	w	VERB
ajst-15595	176	3	y	y	PROPN
ajst-15595	176	4	x	x	PUNCT
ajst-15595	177	1			PROPN
ajst-15595	177	2			PROPN
ajst-15595	177	3			PROPN
ajst-15595	177	4			ADJ
ajst-15595	177	5			NOUN
ajst-15595	177	6			X
ajst-15595	177	7			ADP
ajst-15595	177	8			PROPN
ajst-15595	177	9			NOUN
ajst-15595	177	10			NOUN
ajst-15595	177	11			VERB
ajst-15595	177	12			X
ajst-15595	177	13			NUM
ajst-15595	177	14			NUM
ajst-15595	177	15			NUM
ajst-15595	177	16			NUM
ajst-15595	178	1			NUM
ajst-15595	178	2			PROPN
ajst-15595	178	3			PROPN
ajst-15595	178	4			PROPN
ajst-15595	178	5			NOUN
ajst-15595	178	6			X
ajst-15595	178	7	where	where	SCONJ
ajst-15595	178	8	,	,	PUNCT
ajst-15595	178	9	wj	wj	PROPN
ajst-15595	178	10	is	be	AUX
ajst-15595	178	11	the	the	DET
ajst-15595	178	12	weight	weight	NOUN
ajst-15595	178	13	corresponding	correspond	VERB
ajst-15595	178	14	to	to	ADP
ajst-15595	178	15	each	each	DET
ajst-15595	178	16	quantile	quantile	NOUN
ajst-15595	178	17	and	and	CCONJ
ajst-15595	178	18	λ	λ	PROPN
ajst-15595	178	19	is	be	AUX
ajst-15595	178	20	the	the	DET
ajst-15595	178	21	adjustment	adjustment	NOUN
ajst-15595	178	22	coefficient	coefficient	NOUN
ajst-15595	178	23	.	.	PUNCT
ajst-15595	179	1	if	if	SCONJ
ajst-15595	179	2	λ=0	λ=0	PROPN
ajst-15595	179	3	,	,	PUNCT
ajst-15595	179	4	it	it	PRON
ajst-15595	179	5	is	be	AUX
ajst-15595	179	6	a	a	DET
ajst-15595	179	7	fixed	fixed	ADJ
ajst-15595	179	8	effect	effect	NOUN
ajst-15595	179	9	quantile	quantile	ADJ
ajst-15595	179	10	regression	regression	NOUN
ajst-15595	179	11	estimator	estimator	NOUN
ajst-15595	179	12	(	(	PUNCT
ajst-15595	179	13	feqr	feqr	PROPN
ajst-15595	179	14	)	)	PUNCT
ajst-15595	179	15	.	.	PUNCT
ajst-15595	180	1	if	if	SCONJ
ajst-15595	180	2	λ>0	λ>0	NOUN
ajst-15595	180	3	,	,	PUNCT
ajst-15595	180	4	it	it	PRON
ajst-15595	180	5	is	be	AUX
ajst-15595	180	6	a	a	DET
ajst-15595	180	7	penalty	penalty	NOUN
ajst-15595	180	8	quantile	quantile	NOUN
ajst-15595	180	9	regression	regression	NOUN
ajst-15595	180	10	estimator	estimator	NOUN
ajst-15595	180	11	(	(	PUNCT
ajst-15595	180	12	pqr	pqr	PROPN
ajst-15595	180	13	)	)	PUNCT
ajst-15595	180	14	.	.	PUNCT
ajst-15595	181	1	in	in	ADP
ajst-15595	181	2	addition	addition	NOUN
ajst-15595	181	3	,	,	PUNCT
ajst-15595	181	4	koenker	koenker	NOUN
ajst-15595	181	5	176	176	NUM
ajst-15595	181	6	also	also	ADV
ajst-15595	181	7	investigated	investigate	VERB
ajst-15595	181	8	the	the	DET
ajst-15595	181	9	asymptotic	asymptotic	ADJ
ajst-15595	181	10	properties	property	NOUN
ajst-15595	181	11	of	of	ADP
ajst-15595	181	12	quantile	quantile	ADJ
ajst-15595	181	13	regression	regression	NOUN
ajst-15595	181	14	and	and	CCONJ
ajst-15595	181	15	penalty	penalty	NOUN
ajst-15595	181	16	quantile	quantile	NOUN
ajst-15595	181	17	regression	regression	NOUN
ajst-15595	181	18	estimators	estimator	NOUN
ajst-15595	181	19	in	in	ADP
ajst-15595	181	20	detail	detail	NOUN
ajst-15595	181	21	.	.	PUNCT
ajst-15595	182	1	on	on	ADP
ajst-15595	182	2	this	this	DET
ajst-15595	182	3	basis	basis	NOUN
ajst-15595	182	4	,	,	PUNCT
ajst-15595	182	5	monte	monte	PROPN
ajst-15595	182	6	carlo	carlo	PROPN
ajst-15595	182	7	simulation	simulation	PROPN
ajst-15595	182	8	method	method	NOUN
ajst-15595	182	9	is	be	AUX
ajst-15595	182	10	used	use	VERB
ajst-15595	182	11	to	to	PART
ajst-15595	182	12	compare	compare	VERB
ajst-15595	182	13	and	and	CCONJ
ajst-15595	182	14	analyze	analyze	VERB
ajst-15595	182	15	the	the	DET
ajst-15595	182	16	effect	effect	NOUN
ajst-15595	182	17	of	of	ADP
ajst-15595	182	18	different	different	ADJ
ajst-15595	182	19	regression	regression	NOUN
ajst-15595	182	20	estimation	estimation	NOUN
ajst-15595	182	21	methods	method	NOUN
ajst-15595	182	22	under	under	ADP
ajst-15595	182	23	small	small	ADJ
ajst-15595	182	24	sample	sample	NOUN
ajst-15595	182	25	settings	setting	NOUN
ajst-15595	182	26	.	.	PUNCT
ajst-15595	183	1	3	3	X
ajst-15595	183	2	.	.	X
ajst-15595	183	3	conclusion	conclusion	NOUN
ajst-15595	183	4	on	on	ADP
ajst-15595	183	5	the	the	DET
ajst-15595	183	6	basis	basis	NOUN
ajst-15595	183	7	of	of	ADP
ajst-15595	183	8	the	the	DET
ajst-15595	183	9	comprehensive	comprehensive	ADJ
ajst-15595	183	10	analysis	analysis	NOUN
ajst-15595	183	11	of	of	ADP
ajst-15595	183	12	the	the	DET
ajst-15595	183	13	meaning	meaning	NOUN
ajst-15595	183	14	and	and	CCONJ
ajst-15595	183	15	basic	basic	ADJ
ajst-15595	183	16	principle	principle	NOUN
ajst-15595	183	17	of	of	ADP
ajst-15595	183	18	quantile	quantile	ADJ
ajst-15595	183	19	regression	regression	NOUN
ajst-15595	183	20	method	method	NOUN
ajst-15595	183	21	,	,	PUNCT
ajst-15595	183	22	the	the	DET
ajst-15595	183	23	application	application	NOUN
ajst-15595	183	24	of	of	ADP
ajst-15595	183	25	quantile	quantile	ADJ
ajst-15595	183	26	regression	regression	NOUN
ajst-15595	183	27	method	method	NOUN
ajst-15595	183	28	in	in	ADP
ajst-15595	183	29	panel	panel	NOUN
ajst-15595	183	30	data	datum	NOUN
ajst-15595	183	31	model	model	NOUN
ajst-15595	183	32	is	be	AUX
ajst-15595	183	33	deeply	deeply	ADV
ajst-15595	183	34	analyzed	analyze	VERB
ajst-15595	183	35	,	,	PUNCT
ajst-15595	183	36	and	and	CCONJ
ajst-15595	183	37	the	the	DET
ajst-15595	183	38	estimation	estimation	NOUN
ajst-15595	183	39	effect	effect	NOUN
ajst-15595	183	40	of	of	ADP
ajst-15595	183	41	different	different	ADJ
ajst-15595	183	42	regression	regression	NOUN
ajst-15595	183	43	estimation	estimation	NOUN
ajst-15595	183	44	methods	method	NOUN
ajst-15595	183	45	in	in	ADP
ajst-15595	183	46	panel	panel	NOUN
ajst-15595	183	47	data	datum	NOUN
ajst-15595	183	48	model	model	NOUN
ajst-15595	183	49	is	be	AUX
ajst-15595	183	50	compared	compare	VERB
ajst-15595	183	51	and	and	CCONJ
ajst-15595	183	52	analyzed	analyze	VERB
ajst-15595	183	53	.	.	PUNCT
ajst-15595	184	1	in	in	ADP
ajst-15595	184	2	general	general	ADJ
ajst-15595	184	3	,	,	PUNCT
ajst-15595	184	4	quantile	quantile	ADJ
ajst-15595	184	5	estimation	estimation	NOUN
ajst-15595	184	6	methods	method	NOUN
ajst-15595	184	7	have	have	VERB
ajst-15595	184	8	certain	certain	ADJ
ajst-15595	184	9	advantages	advantage	NOUN
ajst-15595	184	10	in	in	ADP
ajst-15595	184	11	estimating	estimate	VERB
ajst-15595	184	12	error	error	NOUN
ajst-15595	184	13	terms	term	NOUN
ajst-15595	184	14	with	with	ADP
ajst-15595	184	15	non	non	ADJ
ajst-15595	184	16	-	-	ADJ
ajst-15595	184	17	normal	normal	ADJ
ajst-15595	184	18	distributions	distribution	NOUN
ajst-15595	184	19	or	or	CCONJ
ajst-15595	184	20	unobservable	unobservable	ADJ
ajst-15595	184	21	random	random	ADJ
ajst-15595	184	22	effects	effect	NOUN
ajst-15595	184	23	.	.	PUNCT
ajst-15595	185	1	through	through	ADP
ajst-15595	185	2	the	the	DET
ajst-15595	185	3	review	review	NOUN
ajst-15595	185	4	and	and	CCONJ
ajst-15595	185	5	summary	summary	NOUN
ajst-15595	185	6	of	of	ADP
ajst-15595	185	7	the	the	DET
ajst-15595	185	8	existing	exist	VERB
ajst-15595	185	9	literature	literature	NOUN
ajst-15595	185	10	,	,	PUNCT
ajst-15595	185	11	we	we	PRON
ajst-15595	185	12	can	can	AUX
ajst-15595	185	13	get	get	VERB
ajst-15595	185	14	the	the	DET
ajst-15595	185	15	following	follow	VERB
ajst-15595	185	16	enlightenment	enlightenment	NOUN
ajst-15595	185	17	:	:	PUNCT
ajst-15595	185	18	on	on	ADP
ajst-15595	185	19	the	the	DET
ajst-15595	185	20	one	one	NUM
ajst-15595	185	21	hand	hand	NOUN
ajst-15595	185	22	,	,	PUNCT
ajst-15595	185	23	the	the	DET
ajst-15595	185	24	theory	theory	NOUN
ajst-15595	185	25	and	and	CCONJ
ajst-15595	185	26	method	method	NOUN
ajst-15595	185	27	of	of	ADP
ajst-15595	185	28	quantile	quantile	ADJ
ajst-15595	185	29	regression	regression	NOUN
ajst-15595	185	30	have	have	AUX
ajst-15595	185	31	been	be	AUX
ajst-15595	185	32	recognized	recognize	VERB
ajst-15595	185	33	,	,	PUNCT
ajst-15595	185	34	popularized	popularize	VERB
ajst-15595	185	35	and	and	CCONJ
ajst-15595	185	36	applied	apply	VERB
ajst-15595	185	37	by	by	ADP
ajst-15595	185	38	many	many	ADJ
ajst-15595	185	39	economists	economist	NOUN
ajst-15595	185	40	,	,	PUNCT
ajst-15595	185	41	and	and	CCONJ
ajst-15595	185	42	the	the	DET
ajst-15595	185	43	development	development	NOUN
ajst-15595	185	44	of	of	ADP
ajst-15595	185	45	its	its	PRON
ajst-15595	185	46	related	related	ADJ
ajst-15595	185	47	theories	theory	NOUN
ajst-15595	185	48	tends	tend	VERB
ajst-15595	185	49	to	to	PART
ajst-15595	185	50	be	be	AUX
ajst-15595	185	51	mature	mature	ADJ
ajst-15595	185	52	and	and	CCONJ
ajst-15595	185	53	perfect	perfect	ADJ
ajst-15595	185	54	.	.	PUNCT
ajst-15595	186	1	however	however	ADV
ajst-15595	186	2	,	,	PUNCT
ajst-15595	186	3	there	there	PRON
ajst-15595	186	4	are	be	VERB
ajst-15595	186	5	still	still	ADV
ajst-15595	186	6	gaps	gap	NOUN
ajst-15595	186	7	in	in	ADP
ajst-15595	186	8	the	the	DET
ajst-15595	186	9	extended	extend	VERB
ajst-15595	186	10	quantile	quantile	ADJ
ajst-15595	186	11	regression	regression	NOUN
ajst-15595	186	12	model	model	NOUN
ajst-15595	186	13	,	,	PUNCT
ajst-15595	186	14	and	and	CCONJ
ajst-15595	186	15	it	it	PRON
ajst-15595	186	16	is	be	AUX
ajst-15595	186	17	possible	possible	ADJ
ajst-15595	186	18	to	to	PART
ajst-15595	186	19	improve	improve	VERB
ajst-15595	186	20	the	the	DET
ajst-15595	186	21	existing	exist	VERB
ajst-15595	186	22	parameter	parameter	NOUN
ajst-15595	186	23	solving	solving	NOUN
ajst-15595	186	24	methods	method	NOUN
ajst-15595	186	25	.	.	PUNCT
ajst-15595	187	1	for	for	ADP
ajst-15595	187	2	example	example	NOUN
ajst-15595	187	3	,	,	PUNCT
ajst-15595	187	4	there	there	PRON
ajst-15595	187	5	are	be	VERB
ajst-15595	187	6	few	few	ADJ
ajst-15595	187	7	scholars	scholar	NOUN
ajst-15595	187	8	involved	involve	VERB
ajst-15595	187	9	in	in	ADP
ajst-15595	187	10	the	the	DET
ajst-15595	187	11	study	study	NOUN
ajst-15595	187	12	of	of	ADP
ajst-15595	187	13	logistic	logistic	ADJ
ajst-15595	187	14	quantile	quantile	ADJ
ajst-15595	187	15	regression	regression	NOUN
ajst-15595	187	16	model	model	NOUN
ajst-15595	187	17	and	and	CCONJ
ajst-15595	187	18	the	the	DET
ajst-15595	187	19	comparative	comparative	ADJ
ajst-15595	187	20	study	study	NOUN
ajst-15595	187	21	of	of	ADP
ajst-15595	187	22	unconditional	unconditional	ADJ
ajst-15595	187	23	quantile	quantile	ADJ
ajst-15595	187	24	regression	regression	NOUN
ajst-15595	187	25	and	and	CCONJ
ajst-15595	187	26	conditional	conditional	ADJ
ajst-15595	187	27	quantile	quantile	ADJ
ajst-15595	187	28	regression	regression	NOUN
ajst-15595	187	29	.	.	PUNCT
ajst-15595	188	1	on	on	ADP
ajst-15595	188	2	the	the	DET
ajst-15595	188	3	other	other	ADJ
ajst-15595	188	4	hand	hand	NOUN
ajst-15595	188	5	,	,	PUNCT
ajst-15595	188	6	the	the	DET
ajst-15595	188	7	research	research	NOUN
ajst-15595	188	8	on	on	ADP
ajst-15595	188	9	quantile	quantile	ADJ
ajst-15595	188	10	regression	regression	NOUN
ajst-15595	188	11	model	model	NOUN
ajst-15595	188	12	of	of	ADP
ajst-15595	188	13	panel	panel	NOUN
ajst-15595	188	14	data	datum	NOUN
ajst-15595	188	15	is	be	AUX
ajst-15595	188	16	in	in	ADP
ajst-15595	188	17	its	its	PRON
ajst-15595	188	18	infancy	infancy	NOUN
ajst-15595	188	19	.	.	PUNCT
ajst-15595	189	1	since	since	SCONJ
ajst-15595	189	2	koenker	koenker	NOUN
ajst-15595	189	3	(	(	PUNCT
ajst-15595	189	4	2004	2004	NUM
ajst-15595	189	5	)	)	PUNCT
ajst-15595	189	6	proposed	propose	VERB
ajst-15595	189	7	this	this	DET
ajst-15595	189	8	method	method	NOUN
ajst-15595	189	9	,	,	PUNCT
ajst-15595	189	10	there	there	PRON
ajst-15595	189	11	are	be	VERB
ajst-15595	189	12	still	still	ADV
ajst-15595	189	13	many	many	ADJ
ajst-15595	189	14	areas	area	NOUN
ajst-15595	189	15	worth	worth	ADJ
ajst-15595	189	16	exploring	explore	VERB
ajst-15595	189	17	and	and	CCONJ
ajst-15595	189	18	improving	improve	VERB
ajst-15595	189	19	in	in	ADP
ajst-15595	189	20	the	the	DET
ajst-15595	189	21	research	research	NOUN
ajst-15595	189	22	of	of	ADP
ajst-15595	189	23	such	such	ADJ
ajst-15595	189	24	models	model	NOUN
ajst-15595	189	25	.	.	PUNCT
ajst-15595	190	1	firstly	firstly	ADV
ajst-15595	190	2	,	,	PUNCT
ajst-15595	190	3	for	for	ADP
ajst-15595	190	4	the	the	DET
ajst-15595	190	5	parameter	parameter	PROPN
ajst-15595	190	6	estimation	estimation	NOUN
ajst-15595	190	7	problem	problem	NOUN
ajst-15595	190	8	of	of	ADP
ajst-15595	190	9	fixed	fix	VERB
ajst-15595	190	10	effect	effect	NOUN
ajst-15595	190	11	and	and	CCONJ
ajst-15595	190	12	random	random	ADJ
ajst-15595	190	13	effect	effect	NOUN
ajst-15595	190	14	models	model	NOUN
ajst-15595	190	15	,	,	PUNCT
ajst-15595	190	16	how	how	SCONJ
ajst-15595	190	17	to	to	PART
ajst-15595	190	18	improve	improve	VERB
ajst-15595	190	19	the	the	DET
ajst-15595	190	20	existing	exist	VERB
ajst-15595	190	21	methods	method	NOUN
ajst-15595	190	22	to	to	PART
ajst-15595	190	23	get	get	VERB
ajst-15595	190	24	a	a	DET
ajst-15595	190	25	simpler	simple	ADJ
ajst-15595	190	26	and	and	CCONJ
ajst-15595	190	27	easier	easy	ADJ
ajst-15595	190	28	solution	solution	NOUN
ajst-15595	190	29	is	be	AUX
ajst-15595	190	30	one	one	NUM
ajst-15595	190	31	of	of	ADP
ajst-15595	190	32	the	the	DET
ajst-15595	190	33	problems	problem	NOUN
ajst-15595	190	34	to	to	PART
ajst-15595	190	35	be	be	AUX
ajst-15595	190	36	solved[1	solved[1	NOUN
ajst-15595	190	37	]	]	PUNCT
ajst-15595	190	38	.	.	PUNCT
ajst-15595	191	1	secondly	secondly	ADV
ajst-15595	191	2	,	,	PUNCT
ajst-15595	191	3	the	the	DET
ajst-15595	191	4	literature	literature	NOUN
ajst-15595	191	5	on	on	ADP
ajst-15595	191	6	nonlinear	nonlinear	PROPN
ajst-15595	191	7	quantile	quantile	ADJ
ajst-15595	191	8	regression	regression	NOUN
ajst-15595	191	9	,	,	PUNCT
ajst-15595	191	10	spatial	spatial	ADJ
ajst-15595	191	11	quantile	quantile	ADJ
ajst-15595	191	12	regression	regression	NOUN
ajst-15595	191	13	and	and	CCONJ
ajst-15595	191	14	quantile	quantile	ADJ
ajst-15595	191	15	autoregressive	autoregressive	ADJ
ajst-15595	191	16	models	model	NOUN
ajst-15595	191	17	of	of	ADP
ajst-15595	191	18	panel	panel	NOUN
ajst-15595	191	19	data	datum	NOUN
ajst-15595	191	20	is	be	AUX
ajst-15595	191	21	relatively	relatively	ADV
ajst-15595	191	22	lacking	lacking	ADJ
ajst-15595	191	23	,	,	PUNCT
ajst-15595	191	24	which	which	PRON
ajst-15595	191	25	needs	need	VERB
ajst-15595	191	26	further	further	ADJ
ajst-15595	191	27	research	research	NOUN
ajst-15595	191	28	.	.	PUNCT
ajst-15595	192	1	thirdly	thirdly	ADV
ajst-15595	192	2	,	,	PUNCT
ajst-15595	192	3	the	the	DET
ajst-15595	192	4	advanced	advanced	ADJ
ajst-15595	192	5	quantile	quantile	ADJ
ajst-15595	192	6	regression	regression	NOUN
ajst-15595	192	7	methods	method	NOUN
ajst-15595	192	8	,	,	PUNCT
ajst-15595	192	9	such	such	ADJ
ajst-15595	192	10	as	as	ADP
ajst-15595	192	11	variable	variable	ADJ
ajst-15595	192	12	coefficient	coefficient	NOUN
ajst-15595	192	13	quantile	quantile	ADJ
ajst-15595	192	14	regression	regression	NOUN
ajst-15595	192	15	,	,	PUNCT
ajst-15595	192	16	cointegrated	cointegrate	VERB
ajst-15595	192	17	quantile	quantile	ADJ
ajst-15595	192	18	regression	regression	NOUN
ajst-15595	192	19	and	and	CCONJ
ajst-15595	192	20	structural	structural	ADJ
ajst-15595	192	21	mutation	mutation	NOUN
ajst-15595	192	22	test	test	NOUN
ajst-15595	192	23	of	of	ADP
ajst-15595	192	24	quantile	quantile	ADJ
ajst-15595	192	25	regression	regression	NOUN
ajst-15595	192	26	,	,	PUNCT
ajst-15595	192	27	are	be	AUX
ajst-15595	192	28	extended	extend	VERB
ajst-15595	192	29	to	to	ADP
ajst-15595	192	30	panel	panel	NOUN
ajst-15595	192	31	data	datum	NOUN
ajst-15595	192	32	samples	sample	NOUN
ajst-15595	192	33	,	,	PUNCT
ajst-15595	192	34	which	which	PRON
ajst-15595	192	35	is	be	AUX
ajst-15595	192	36	also	also	ADV
ajst-15595	192	37	a	a	DET
ajst-15595	192	38	further	further	ADJ
ajst-15595	192	39	improvement	improvement	NOUN
ajst-15595	192	40	of	of	ADP
ajst-15595	192	41	the	the	DET
ajst-15595	192	42	theoretical	theoretical	ADJ
ajst-15595	192	43	system	system	NOUN
ajst-15595	192	44	of	of	ADP
ajst-15595	192	45	such	such	ADJ
ajst-15595	192	46	models	model	NOUN
ajst-15595	192	47	.	.	PUNCT
ajst-15595	193	1	finally	finally	ADV
ajst-15595	193	2	,	,	PUNCT
ajst-15595	193	3	for	for	ADP
ajst-15595	193	4	the	the	DET
ajst-15595	193	5	cuttingedge	cuttingedge	ADJ
ajst-15595	193	6	theoretical	theoretical	ADJ
ajst-15595	193	7	methods	method	NOUN
ajst-15595	193	8	in	in	ADP
ajst-15595	193	9	such	such	ADJ
ajst-15595	193	10	models	model	NOUN
ajst-15595	193	11	,	,	PUNCT
ajst-15595	193	12	mature	mature	ADJ
ajst-15595	193	13	application	application	NOUN
ajst-15595	193	14	software	software	NOUN
ajst-15595	193	15	modules	module	NOUN
ajst-15595	193	16	or	or	CCONJ
ajst-15595	193	17	function	function	NOUN
ajst-15595	193	18	commands	command	NOUN
ajst-15595	193	19	have	have	AUX
ajst-15595	193	20	not	not	PART
ajst-15595	193	21	been	be	AUX
ajst-15595	193	22	developed	develop	VERB
ajst-15595	193	23	,	,	PUNCT
ajst-15595	193	24	and	and	CCONJ
ajst-15595	193	25	it	it	PRON
ajst-15595	193	26	is	be	AUX
ajst-15595	193	27	difficult	difficult	ADJ
ajst-15595	193	28	to	to	PART
ajst-15595	193	29	simply	simply	ADV
ajst-15595	193	30	implement	implement	VERB
ajst-15595	193	31	them	they	PRON
ajst-15595	193	32	through	through	ADP
ajst-15595	193	33	the	the	DET
ajst-15595	193	34	interface	interface	NOUN
ajst-15595	193	35	operation	operation	NOUN
ajst-15595	193	36	of	of	ADP
ajst-15595	193	37	measurement	measurement	NOUN
ajst-15595	193	38	software	software	NOUN
ajst-15595	193	39	such	such	ADJ
ajst-15595	193	40	as	as	ADP
ajst-15595	193	41	eviews	eview	NOUN
ajst-15595	193	42	or	or	CCONJ
ajst-15595	193	43	stata	stata	NOUN
ajst-15595	193	44	,	,	PUNCT
ajst-15595	193	45	which	which	PRON
ajst-15595	193	46	brings	bring	VERB
ajst-15595	193	47	great	great	ADJ
ajst-15595	193	48	inconvenience	inconvenience	NOUN
ajst-15595	193	49	to	to	PART
ajst-15595	193	50	parameter	parameter	NOUN
ajst-15595	193	51	estimation	estimation	NOUN
ajst-15595	193	52	and	and	CCONJ
ajst-15595	193	53	statistical	statistical	ADJ
ajst-15595	193	54	analysis	analysis	NOUN
ajst-15595	193	55	of	of	ADP
ajst-15595	193	56	quantile	quantile	ADJ
ajst-15595	193	57	regression	regression	NOUN
ajst-15595	193	58	of	of	ADP
ajst-15595	193	59	panel	panel	NOUN
ajst-15595	193	60	data	datum	NOUN
ajst-15595	193	61	,	,	PUNCT
ajst-15595	193	62	and	and	CCONJ
ajst-15595	193	63	is	be	AUX
ajst-15595	193	64	also	also	ADV
ajst-15595	193	65	an	an	DET
ajst-15595	193	66	urgent	urgent	ADJ
ajst-15595	193	67	problem	problem	NOUN
ajst-15595	193	68	to	to	PART
ajst-15595	193	69	be	be	AUX
ajst-15595	193	70	solved	solve	VERB
ajst-15595	193	71	in	in	ADP
ajst-15595	193	72	the	the	DET
ajst-15595	193	73	future	future	NOUN
ajst-15595	193	74	.	.	PUNCT
ajst-15595	194	1	to	to	PART
ajst-15595	194	2	sum	sum	VERB
ajst-15595	194	3	up	up	ADP
ajst-15595	194	4	,	,	PUNCT
ajst-15595	194	5	the	the	DET
ajst-15595	194	6	development	development	NOUN
ajst-15595	194	7	of	of	ADP
ajst-15595	194	8	quantile	quantile	ADJ
ajst-15595	194	9	regression	regression	NOUN
ajst-15595	194	10	model	model	NOUN
ajst-15595	194	11	has	have	AUX
ajst-15595	194	12	gradually	gradually	ADV
ajst-15595	194	13	matured	mature	VERB
ajst-15595	194	14	,	,	PUNCT
ajst-15595	194	15	and	and	CCONJ
ajst-15595	194	16	the	the	DET
ajst-15595	194	17	research	research	NOUN
ajst-15595	194	18	on	on	ADP
ajst-15595	194	19	panel	panel	NOUN
ajst-15595	194	20	quantile	quantile	ADJ
ajst-15595	194	21	regression	regression	NOUN
ajst-15595	194	22	model	model	NOUN
ajst-15595	194	23	has	have	AUX
ajst-15595	194	24	also	also	ADV
ajst-15595	194	25	made	make	VERB
ajst-15595	194	26	great	great	ADJ
ajst-15595	194	27	progress	progress	NOUN
ajst-15595	194	28	.	.	PUNCT
ajst-15595	195	1	the	the	DET
ajst-15595	195	2	two	two	NUM
ajst-15595	195	3	types	type	NOUN
ajst-15595	195	4	of	of	ADP
ajst-15595	195	5	models	model	NOUN
ajst-15595	195	6	have	have	AUX
ajst-15595	195	7	been	be	AUX
ajst-15595	195	8	applied	apply	VERB
ajst-15595	195	9	more	more	ADV
ajst-15595	195	10	and	and	CCONJ
ajst-15595	195	11	more	more	ADV
ajst-15595	195	12	widely	widely	ADV
ajst-15595	195	13	in	in	ADP
ajst-15595	195	14	social	social	ADJ
ajst-15595	195	15	life	life	NOUN
ajst-15595	195	16	,	,	PUNCT
ajst-15595	195	17	and	and	CCONJ
ajst-15595	195	18	their	their	PRON
ajst-15595	195	19	research	research	NOUN
ajst-15595	195	20	results	result	NOUN
ajst-15595	195	21	and	and	CCONJ
ajst-15595	195	22	value	value	NOUN
ajst-15595	195	23	have	have	AUX
ajst-15595	195	24	been	be	AUX
ajst-15595	195	25	recognized	recognize	VERB
ajst-15595	195	26	by	by	ADP
ajst-15595	195	27	more	more	ADJ
ajst-15595	195	28	and	and	CCONJ
ajst-15595	195	29	more	more	ADJ
ajst-15595	195	30	scholars	scholar	NOUN
ajst-15595	195	31	and	and	CCONJ
ajst-15595	195	32	government	government	NOUN
ajst-15595	195	33	decision	decision	NOUN
ajst-15595	195	34	-	-	PUNCT
ajst-15595	195	35	making	make	VERB
ajst-15595	195	36	departments	department	NOUN
ajst-15595	195	37	.	.	PUNCT
ajst-15595	196	1	however	however	ADV
ajst-15595	196	2	,	,	PUNCT
ajst-15595	196	3	there	there	PRON
ajst-15595	196	4	are	be	VERB
ajst-15595	196	5	still	still	ADV
ajst-15595	196	6	many	many	ADJ
ajst-15595	196	7	problems	problem	NOUN
ajst-15595	196	8	to	to	PART
ajst-15595	196	9	be	be	AUX
ajst-15595	196	10	further	far	ADV
ajst-15595	196	11	solved	solve	VERB
ajst-15595	196	12	,	,	PUNCT
ajst-15595	196	13	especially	especially	ADV
ajst-15595	196	14	for	for	ADP
ajst-15595	196	15	the	the	DET
ajst-15595	196	16	relatively	relatively	ADV
ajst-15595	196	17	lacking	lacking	ADJ
ajst-15595	196	18	research	research	NOUN
ajst-15595	196	19	field	field	NOUN
ajst-15595	196	20	in	in	ADP
ajst-15595	196	21	quantile	quantile	ADJ
ajst-15595	196	22	regression	regression	NOUN
ajst-15595	196	23	model	model	NOUN
ajst-15595	196	24	of	of	ADP
ajst-15595	196	25	panel	panel	NOUN
ajst-15595	196	26	data	datum	NOUN
ajst-15595	196	27	,	,	PUNCT
ajst-15595	196	28	it	it	PRON
ajst-15595	196	29	is	be	AUX
ajst-15595	196	30	urgent	urgent	ADJ
ajst-15595	196	31	for	for	SCONJ
ajst-15595	196	32	more	more	ADJ
ajst-15595	196	33	econometricians	econometrician	NOUN
ajst-15595	196	34	to	to	PART
ajst-15595	196	35	make	make	VERB
ajst-15595	196	36	contributions	contribution	NOUN
ajst-15595	196	37	and	and	CCONJ
ajst-15595	196	38	breakthroughs	breakthrough	NOUN
ajst-15595	196	39	in	in	ADP
ajst-15595	196	40	some	some	DET
ajst-15595	196	41	aspects	aspect	NOUN
ajst-15595	196	42	.	.	PUNCT
ajst-15595	197	1	references	reference	NOUN
ajst-15595	197	2	[	[	X
ajst-15595	197	3	1	1	NUM
ajst-15595	197	4	]	]	PUNCT
ajst-15595	197	5	koenker	koenker	NOUN
ajst-15595	197	6	,	,	PUNCT
ajst-15595	197	7	r.	r.	PROPN
ajst-15595	197	8	,	,	PUNCT
ajst-15595	197	9	koenker	koenker	PROPN
ajst-15595	197	10	,	,	PUNCT
ajst-15595	197	11	r.	r.	PROPN
ajst-15595	197	12	,	,	PUNCT
ajst-15595	197	13	bassett	bassett	PROPN
ajst-15595	197	14	,	,	PUNCT
ajst-15595	197	15	g.	g.	PROPN
ajst-15595	197	16	j.	j.	PROPN
ajst-15595	197	17	,	,	PUNCT
ajst-15595	197	18	&	&	CCONJ
ajst-15595	197	19	bassett	bassett	PROPN
ajst-15595	197	20	,	,	PUNCT
ajst-15595	197	21	g.	g.	PROPN
ajst-15595	197	22	j.	j.	PROPN
ajst-15595	197	23	.(1978).regressions	.(1978).regressions	PROPN
ajst-15595	197	24	quantiles	quantile	NOUN
ajst-15595	197	25	.	.	PUNCT
ajst-15595	198	1	[	[	X
ajst-15595	198	2	2	2	NUM
ajst-15595	198	3	]	]	PUNCT
ajst-15595	198	4	koenker	koenker	NOUN
ajst-15595	198	5	,	,	PUNCT
ajst-15595	198	6	r.	r.	PROPN
ajst-15595	198	7	.(2004	.(2004	PROPN
ajst-15595	198	8	)	)	PUNCT
ajst-15595	198	9	.	.	PUNCT
ajst-15595	199	1	quantile	quantile	ADJ
ajst-15595	199	2	regression	regression	NOUN
ajst-15595	199	3	for	for	ADP
ajst-15595	199	4	longitudinal	longitudinal	ADJ
ajst-15595	199	5	data	datum	NOUN
ajst-15595	200	1	[	[	X
ajst-15595	200	2	j	j	X
ajst-15595	200	3	]	]	X
ajst-15595	200	4	,	,	PUNCT
ajst-15595	200	5	journalofmultivariateanalysis,91,74–89	journalofmultivariateanalysis,91,74–89	X
ajst-15595	200	6	.	.	PUNCT
ajst-15595	201	1	[	[	X
ajst-15595	201	2	3	3	NUM
ajst-15595	201	3	]	]	X
ajst-15595	201	4	thompson	thompson	PROPN
ajst-15595	201	5	,	,	PUNCT
ajst-15595	201	6	p.	p.	NOUN
ajst-15595	201	7	,	,	PUNCT
ajst-15595	201	8	cai	cai	X
ajst-15595	201	9	,	,	PUNCT
ajst-15595	201	10	y.	y.	PROPN
ajst-15595	201	11	,	,	PUNCT
ajst-15595	201	12	moyeed	moyeed	PROPN
ajst-15595	201	13	,	,	PUNCT
ajst-15595	201	14	r.	r.	PROPN
ajst-15595	201	15	,	,	PUNCT
ajst-15595	201	16	reeve	reeve	PROPN
ajst-15595	201	17	,	,	PUNCT
ajst-15595	201	18	d.	d.	PROPN
ajst-15595	201	19	,	,	PUNCT
ajst-15595	201	20	&	&	CCONJ
ajst-15595	201	21	stander	stander	PROPN
ajst-15595	201	22	,	,	PUNCT
ajst-15595	201	23	j.	j.	PROPN
ajst-15595	201	24	.	.	PUNCT
ajst-15595	202	1	(	(	PUNCT
ajst-15595	202	2	2010	2010	NUM
ajst-15595	202	3	)	)	PUNCT
ajst-15595	202	4	.	.	PUNCT
ajst-15595	203	1	bayesian	bayesian	PROPN
ajst-15595	203	2	nonparametric	nonparametric	PROPN
ajst-15595	203	3	quantile	quantile	ADJ
ajst-15595	203	4	regression	regression	NOUN
ajst-15595	203	5	using	use	VERB
ajst-15595	203	6	splines	spline	NOUN
ajst-15595	203	7	.	.	PUNCT
ajst-15595	204	1	computational	computational	ADJ
ajst-15595	204	2	statistics	statistic	NOUN
ajst-15595	204	3	&	&	CCONJ
ajst-15595	204	4	data	datum	NOUN
ajst-15595	204	5	analysis	analysis	NOUN
ajst-15595	204	6	,	,	PUNCT
ajst-15595	204	7	54(4	54(4	NUM
ajst-15595	204	8	)	)	PUNCT
ajst-15595	204	9	,	,	PUNCT
ajst-15595	204	10	1138	1138	NUM
ajst-15595	204	11	-	-	SYM
ajst-15595	204	12	1150	1150	NUM
ajst-15595	204	13	.	.	PUNCT
ajst-15595	205	1	[	[	X
ajst-15595	205	2	4	4	NUM
ajst-15595	205	3	]	]	X
ajst-15595	205	4	yeh	yeh	PROPN
ajst-15595	205	5	,	,	PUNCT
ajst-15595	205	6	c.	c.	PROPN
ajst-15595	205	7	c.	c.	PROPN
ajst-15595	205	8	,	,	PUNCT
ajst-15595	205	9	wang	wang	PROPN
ajst-15595	205	10	,	,	PUNCT
ajst-15595	205	11	k.	k.	PROPN
ajst-15595	205	12	m.	m.	PROPN
ajst-15595	205	13	,	,	PUNCT
ajst-15595	205	14	&	&	CCONJ
ajst-15595	205	15	suen	suen	PROPN
ajst-15595	205	16	,	,	PUNCT
ajst-15595	205	17	y.	y.	PROPN
ajst-15595	205	18	b.	b.	PROPN
ajst-15595	205	19	.	.	PUNCT
ajst-15595	206	1	(	(	PUNCT
ajst-15595	206	2	2011	2011	NUM
ajst-15595	206	3	)	)	PUNCT
ajst-15595	206	4	.	.	PUNCT
ajst-15595	207	1	a	a	DET
ajst-15595	207	2	quantile	quantile	ADJ
ajst-15595	207	3	framework	framework	NOUN
ajst-15595	207	4	for	for	ADP
ajst-15595	207	5	analysing	analyse	VERB
ajst-15595	207	6	the	the	DET
ajst-15595	207	7	links	link	NOUN
ajst-15595	207	8	between	between	ADP
ajst-15595	207	9	inflation	inflation	NOUN
ajst-15595	207	10	uncertainty	uncertainty	NOUN
ajst-15595	207	11	and	and	CCONJ
ajst-15595	207	12	inflation	inflation	NOUN
ajst-15595	207	13	dynamics	dynamic	NOUN
ajst-15595	207	14	across	across	ADP
ajst-15595	207	15	countries	country	NOUN
ajst-15595	207	16	.	.	PUNCT
ajst-15595	208	1	applied	apply	VERB
ajst-15595	208	2	economics	economic	NOUN
ajst-15595	208	3	,	,	PUNCT
ajst-15595	208	4	43(20	43(20	NUM
ajst-15595	208	5	)	)	PUNCT
ajst-15595	208	6	,	,	PUNCT
ajst-15595	208	7	2593	2593	NUM
ajst-15595	208	8	-	-	SYM
ajst-15595	208	9	2602	2602	NUM
ajst-15595	208	10	.	.	PUNCT
ajst-15595	209	1	[	[	X
ajst-15595	209	2	5	5	NUM
ajst-15595	209	3	]	]	X
ajst-15595	209	4	antonio	antonio	PROPN
ajst-15595	209	5	,	,	PUNCT
ajst-15595	209	6	f.	f.	PROPN
ajst-15595	209	7	,	,	PUNCT
ajst-15595	209	8	galvao	galvao	PROPN
ajst-15595	209	9	,	,	PUNCT
ajst-15595	209	10	&	&	CCONJ
ajst-15595	209	11	jr	jr	PROPN
ajst-15595	209	12	.	.	PROPN
ajst-15595	209	13	.(2011	.(2011	PUNCT
ajst-15595	209	14	)	)	PUNCT
ajst-15595	209	15	.	.	PUNCT
ajst-15595	210	1	quantile	quantile	ADJ
ajst-15595	210	2	regression	regression	NOUN
ajst-15595	210	3	for	for	ADP
ajst-15595	210	4	dynamic	dynamic	ADJ
ajst-15595	210	5	panel	panel	NOUN
ajst-15595	210	6	data	datum	NOUN
ajst-15595	210	7	with	with	ADP
ajst-15595	210	8	fixed	fix	VERB
ajst-15595	210	9	effects	effect	NOUN
ajst-15595	210	10	.	.	PUNCT
ajst-15595	211	1	journal	journal	NOUN
ajst-15595	211	2	of	of	ADP
ajst-15595	211	3	econometrics	econometric	NOUN
ajst-15595	211	4	.	.	PUNCT
ajst-15595	212	1	[	[	X
ajst-15595	212	2	6	6	NUM
ajst-15595	212	3	]	]	PUNCT
ajst-15595	212	4	koenker	koenker	NOUN
ajst-15595	212	5	,	,	PUNCT
ajst-15595	212	6	r.	r.	PROPN
ajst-15595	212	7	.	.	PUNCT
ajst-15595	213	1	(	(	PUNCT
ajst-15595	213	2	2015	2015	NUM
ajst-15595	213	3	)	)	PUNCT
ajst-15595	213	4	.	.	PUNCT
ajst-15595	214	1	additive	additive	NOUN
ajst-15595	214	2	models	model	NOUN
ajst-15595	214	3	for	for	ADP
ajst-15595	214	4	quantile	quantile	ADJ
ajst-15595	214	5	regression	regression	NOUN
ajst-15595	214	6	:	:	PUNCT
ajst-15595	214	7	model	model	NOUN
ajst-15595	214	8	selection	selection	NOUN
ajst-15595	214	9	and	and	CCONJ
ajst-15595	214	10	confidence	confidence	NOUN
ajst-15595	214	11	bands	band	NOUN
ajst-15595	215	1	[	[	X
ajst-15595	215	2	j	j	X
ajst-15595	215	3	]	]	X
ajst-15595	215	4	.	.	PUNCT
ajst-15595	216	1	brazilian	brazilian	ADJ
ajst-15595	216	2	journal	journal	PROPN
ajst-15595	216	3	of	of	ADP
ajst-15595	216	4	probability	probability	NOUN
ajst-15595	216	5	and	and	CCONJ
ajst-15595	216	6	statistics	statistic	NOUN
ajst-15595	216	7	,	,	PUNCT
ajst-15595	216	8	25（3	25（3	PROPN
ajst-15595	216	9	）	）	PROPN
ajst-15595	216	10	:	:	PUNCT
ajst-15595	216	11	239	239	NUM
ajst-15595	216	12	-	-	SYM
ajst-15595	216	13	262	262	NUM
ajst-15595	216	14	.	.	PUNCT
ajst-15595	217	1	[	[	X
ajst-15595	217	2	7	7	NUM
ajst-15595	217	3	]	]	X
ajst-15595	217	4	waldmann	waldmann	PROPN
ajst-15595	217	5	,	,	PUNCT
ajst-15595	217	6	e.	e.	PROPN
ajst-15595	217	7	,	,	PUNCT
ajst-15595	217	8	kneib	kneib	PROPN
ajst-15595	217	9	,	,	PUNCT
ajst-15595	217	10	t.	t.	PROPN
ajst-15595	217	11	,	,	PUNCT
ajst-15595	217	12	yue	yue	PROPN
ajst-15595	217	13	,	,	PUNCT
ajst-15595	217	14	&	&	CCONJ
ajst-15595	217	15	y.	y.	PROPN
ajst-15595	217	16	,	,	PUNCT
ajst-15595	217	17	r.	r.	PROPN
ajst-15595	217	18	,	,	PUNCT
ajst-15595	217	19	et	et	PROPN
ajst-15595	217	20	al	al	PROPN
ajst-15595	217	21	.	.	PROPN
ajst-15595	217	22	.	.	PUNCT
ajst-15595	218	1	(	(	PUNCT
ajst-15595	218	2	2013	2013	NUM
ajst-15595	218	3	)	)	PUNCT
ajst-15595	218	4	.	.	PUNCT
ajst-15595	219	1	bayesian	bayesian	NOUN
ajst-15595	219	2	semiparametric	semiparametric	VERB
ajst-15595	219	3	additive	additive	ADJ
ajst-15595	219	4	quantile	quantile	ADJ
ajst-15595	219	5	regression	regression	NOUN
ajst-15595	219	6	.	.	PUNCT
ajst-15595	220	1	statistical	statistical	ADJ
ajst-15595	220	2	modelling	modelling	NOUN
ajst-15595	220	3	-letchworth-	-letchworth-	NOUN
ajst-15595	220	4	,	,	PUNCT
ajst-15595	220	5	13(3	13(3	NUM
ajst-15595	220	6	)	)	PUNCT
ajst-15595	220	7	,	,	PUNCT
ajst-15595	220	8	223	223	NUM
ajst-15595	220	9	-	-	SYM
ajst-15595	220	10	252	252	NUM
ajst-15595	220	11	.	.	PUNCT
ajst-15595	221	1	[	[	X
ajst-15595	221	2	8	8	NUM
ajst-15595	221	3	]	]	X
ajst-15595	221	4	kato	kato	PROPN
ajst-15595	221	5	,	,	PUNCT
ajst-15595	221	6	k.	k.	PROPN
ajst-15595	221	7	,	,	PUNCT
ajst-15595	221	8	galvao	galvao	PROPN
ajst-15595	221	9	,	,	PUNCT
ajst-15595	221	10	a.	a.	PROPN
ajst-15595	221	11	f.	f.	PROPN
ajst-15595	221	12	,	,	PUNCT
ajst-15595	221	13	&	&	CCONJ
ajst-15595	221	14	montes	montes	PROPN
ajst-15595	221	15	-	-	PUNCT
ajst-15595	221	16	rojas	rojas	PROPN
ajst-15595	221	17	,	,	PUNCT
ajst-15595	221	18	g.	g.	PROPN
ajst-15595	221	19	v.	v.	PROPN
ajst-15595	221	20	.	.	PUNCT
ajst-15595	222	1	(	(	PUNCT
ajst-15595	222	2	2012	2012	NUM
ajst-15595	222	3	)	)	PUNCT
ajst-15595	222	4	.	.	PUNCT
ajst-15595	223	1	asymptotics	asymptotic	NOUN
ajst-15595	223	2	for	for	ADP
ajst-15595	223	3	panel	panel	NOUN
ajst-15595	223	4	quantile	quantile	ADJ
ajst-15595	223	5	regression	regression	NOUN
ajst-15595	223	6	models	model	NOUN
ajst-15595	223	7	with	with	ADP
ajst-15595	223	8	individual	individual	ADJ
ajst-15595	223	9	effects	effect	NOUN
ajst-15595	223	10	.	.	PUNCT
ajst-15595	224	1	journal	journal	NOUN
ajst-15595	224	2	of	of	ADP
ajst-15595	224	3	econometrics	econometric	NOUN
ajst-15595	224	4	,	,	PUNCT
ajst-15595	224	5	170(1	170(1	NUM
ajst-15595	224	6	)	)	PUNCT
ajst-15595	224	7	,	,	PUNCT
ajst-15595	224	8	76	76	NUM
ajst-15595	224	9	-	-	SYM
ajst-15595	224	10	91	91	NUM
ajst-15595	224	11	.	.	PUNCT
ajst-15595	225	1	[	[	X
ajst-15595	225	2	9	9	NUM
ajst-15595	225	3	]	]	SYM
ajst-15595	225	4	aghamohammadi	aghamohammadi	NOUN
ajst-15595	225	5	,	,	PUNCT
ajst-15595	225	6	a.	a.	NOUN
ajst-15595	225	7	,	,	PUNCT
ajst-15595	225	8	&	&	CCONJ
ajst-15595	225	9	mohammadi	mohammadi	PROPN
ajst-15595	225	10	,	,	PUNCT
ajst-15595	225	11	s.	s.	PROPN
ajst-15595	225	12	.	.	PUNCT
ajst-15595	226	1	(	(	PUNCT
ajst-15595	226	2	2015	2015	NUM
ajst-15595	226	3	)	)	PUNCT
ajst-15595	226	4	.	.	PUNCT
ajst-15595	227	1	bayesian	bayesian	NOUN
ajst-15595	227	2	analysis	analysis	NOUN
ajst-15595	227	3	of	of	ADP
ajst-15595	227	4	penalized	penalize	VERB
ajst-15595	227	5	quantile	quantile	ADJ
ajst-15595	227	6	regression	regression	NOUN
ajst-15595	227	7	for	for	ADP
ajst-15595	227	8	longitudinal	longitudinal	ADJ
ajst-15595	227	9	data	datum	NOUN
ajst-15595	227	10	.	.	PUNCT
ajst-15595	228	1	statistical	statistical	ADJ
ajst-15595	228	2	papers	paper	NOUN
ajst-15595	228	3	.	.	PUNCT
ajst-15595	229	1	[	[	X
ajst-15595	229	2	10	10	NUM
ajst-15595	229	3	]	]	X
ajst-15595	229	4	galvao	galvao	PROPN
ajst-15595	229	5	,	,	PUNCT
ajst-15595	229	6	a	a	PRON
ajst-15595	229	7	.	.	PUNCT
ajst-15595	230	1	f.	f.	PROPN
ajst-15595	230	2	,	,	PUNCT
ajst-15595	230	3	kato	kato	PROPN
ajst-15595	230	4	,	,	PUNCT
ajst-15595	230	5	k.	k.	PROPN
ajst-15595	230	6	,	,	PUNCT
ajst-15595	230	7	amemiya	amemiya	NOUN
ajst-15595	230	8	,	,	PUNCT
ajst-15595	230	9	t.	t.	PROPN
ajst-15595	230	10	,	,	PUNCT
ajst-15595	230	11	et	et	PROPN
ajst-15595	230	12	al	al	PROPN
ajst-15595	230	13	.	.	PROPN
ajst-15595	230	14	.	.	PUNCT
ajst-15595	231	1	(	(	PUNCT
ajst-15595	231	2	2016	2016	NUM
ajst-15595	231	3	)	)	PUNCT
ajst-15595	231	4	.	.	PUNCT
ajst-15595	232	1	smoothed	smooth	VERB
ajst-15595	232	2	quantile	quantile	ADJ
ajst-15595	232	3	regression	regression	NOUN
ajst-15595	232	4	for	for	ADP
ajst-15595	232	5	panel	panel	NOUN
ajst-15595	232	6	data[j	data[j	NOUN
ajst-15595	232	7	]	]	PUNCT
ajst-15595	232	8	.	.	PUNCT
ajst-15595	233	1	journal	journal	PROPN
ajst-15595	233	2	of	of	ADP
ajst-15595	233	3	econometrics	econometric	NOUN
ajst-15595	233	4	,	,	PUNCT
ajst-15595	233	5	193	193	NUM
ajst-15595	233	6	(	(	PUNCT
ajst-15595	233	7	1	1	NUM
ajst-15595	233	8	):	):	PUNCT
ajst-15595	233	9	92	92	NUM
ajst-15595	233	10	-	-	SYM
ajst-15595	233	11	112	112	NUM
ajst-15595	233	12	.	.	PUNCT
ajst-15595	234	1	[	[	X
ajst-15595	234	2	11	11	NUM
ajst-15595	234	3	]	]	PUNCT
ajst-15595	234	4	xu	xu	PROPN
ajst-15595	234	5	,	,	PUNCT
ajst-15595	234	6	b.	b.	PROPN
ajst-15595	234	7	,	,	PUNCT
ajst-15595	234	8	&	&	CCONJ
ajst-15595	234	9	lin	lin	PROPN
ajst-15595	234	10	,	,	PUNCT
ajst-15595	234	11	b.	b.	PROPN
ajst-15595	234	12	.	.	PUNCT
ajst-15595	235	1	(	(	PUNCT
ajst-15595	235	2	2016	2016	NUM
ajst-15595	235	3	)	)	PUNCT
ajst-15595	235	4	.	.	PUNCT
ajst-15595	236	1	a	a	DET
ajst-15595	236	2	quantile	quantile	ADJ
ajst-15595	236	3	regression	regression	NOUN
ajst-15595	236	4	analysis	analysis	NOUN
ajst-15595	236	5	of	of	ADP
ajst-15595	236	6	china	china	PROPN
ajst-15595	236	7	's	's	PART
ajst-15595	236	8	provincial	provincial	ADJ
ajst-15595	236	9	co	co	ADJ
ajst-15595	236	10	2	2	NUM
ajst-15595	236	11	emissions	emission	NOUN
ajst-15595	236	12	:	:	PUNCT
ajst-15595	236	13	where	where	SCONJ
ajst-15595	236	14	does	do	AUX
ajst-15595	236	15	the	the	DET
ajst-15595	236	16	difference	difference	NOUN
ajst-15595	236	17	lie	lie	VERB
ajst-15595	236	18	?	?	PUNCT
ajst-15595	236	19	.	.	PUNCT
ajst-15595	237	1	energy	energy	NOUN
ajst-15595	237	2	policy	policy	NOUN
ajst-15595	237	3	.	.	PUNCT
ajst-15595	238	1	[	[	X
ajst-15595	238	2	12	12	NUM
ajst-15595	238	3	]	]	X
ajst-15595	238	4	roca	roca	PROPN
ajst-15595	238	5	-	-	PUNCT
ajst-15595	238	6	pardinas	pardinas	PROPN
ajst-15595	238	7	,	,	PUNCT
ajst-15595	238	8	j.	j.	PROPN
ajst-15595	238	9	,	,	PUNCT
ajst-15595	238	10	&	&	CCONJ
ajst-15595	238	11	ordonez	ordonez	PROPN
ajst-15595	238	12	,	,	PUNCT
ajst-15595	238	13	c.	c.	PROPN
ajst-15595	238	14	.	.	PUNCT
ajst-15595	239	1	(	(	PUNCT
ajst-15595	239	2	2019	2019	NUM
ajst-15595	239	3	)	)	PUNCT
ajst-15595	239	4	.	.	PUNCT
ajst-15595	240	1	predicting	predict	VERB
ajst-15595	240	2	pollution	pollution	NOUN
ajst-15595	240	3	incidents	incident	NOUN
ajst-15595	240	4	through	through	ADP
ajst-15595	240	5	semiparametric	semiparametric	NOUN
ajst-15595	240	6	quantile	quantile	ADJ
ajst-15595	240	7	regression	regression	NOUN
ajst-15595	240	8	models	model	NOUN
ajst-15595	240	9	.	.	PUNCT
ajst-15595	241	1	stochastic	stochastic	ADJ
ajst-15595	241	2	environmental	environmental	ADJ
ajst-15595	241	3	research	research	NOUN
ajst-15595	241	4	and	and	CCONJ
ajst-15595	241	5	risk	risk	NOUN
ajst-15595	241	6	assessment(3	assessment(3	NOUN
ajst-15595	241	7	)	)	PUNCT
ajst-15595	241	8	,	,	PUNCT
ajst-15595	241	9	33	33	NUM
ajst-15595	241	10	.	.	PUNCT
ajst-15595	242	1	[	[	X
ajst-15595	242	2	13	13	NUM
ajst-15595	242	3	]	]	X
ajst-15595	242	4	fredj	fredj	NOUN
ajst-15595	242	5	,	,	PUNCT
ajst-15595	242	6	j.	j.	PROPN
ajst-15595	242	7	,	,	PUNCT
ajst-15595	242	8	nabila	nabila	PROPN
ajst-15595	242	9	,	,	PUNCT
ajst-15595	242	10	j.	j.	PROPN
ajst-15595	242	11	,	,	PUNCT
ajst-15595	242	12	abdoulkarim	abdoulkarim	PROPN
ajst-15595	242	13	,	,	PUNCT
ajst-15595	242	14	i.	i.	PROPN
ajst-15595	242	15	c.	c.	PROPN
ajst-15595	242	16	,	,	PUNCT
ajst-15595	242	17	ameur	ameur	PROPN
ajst-15595	242	18	,	,	PUNCT
ajst-15595	242	19	h.	h.	PROPN
ajst-15595	242	20	b.	b.	PROPN
ajst-15595	242	21	.	.	PUNCT
ajst-15595	243	1	(	(	PUNCT
ajst-15595	243	2	2017	2017	NUM
ajst-15595	243	3	)	)	PUNCT
ajst-15595	243	4	.	.	PUNCT
ajst-15595	244	1	modelling	model	VERB
ajst-15595	244	2	the	the	DET
ajst-15595	244	3	effect	effect	NOUN
ajst-15595	244	4	of	of	ADP
ajst-15595	244	5	the	the	DET
ajst-15595	244	6	geographical	geographical	ADJ
ajst-15595	244	7	environment	environment	NOUN
ajst-15595	244	8	on	on	ADP
ajst-15595	244	9	islamic	islamic	ADJ
ajst-15595	244	10	banking	banking	NOUN
ajst-15595	244	11	performance	performance	NOUN
ajst-15595	244	12	:	:	PUNCT
ajst-15595	244	13	a	a	DET
ajst-15595	244	14	panel	panel	NOUN
ajst-15595	244	15	quantile	quantile	PROPN
ajst-15595	244	16	regression	regression	PROPN
ajst-15595	244	17	analysis[j	analysis[j	PROPN
ajst-15595	244	18	]	]	PUNCT
ajst-15595	244	19	.	.	PUNCT
ajst-15595	245	1	economic	economic	ADJ
ajst-15595	245	2	modelling	modelling	NOUN
ajst-15595	245	3	,	,	PUNCT
ajst-15595	245	4	300	300	NUM
ajst-15595	245	5	-	-	SYM
ajst-15595	245	6	306	306	NUM
ajst-15595	245	7	.	.	PUNCT
ajst-15595	246	1	[	[	X
ajst-15595	246	2	14	14	NUM
ajst-15595	246	3	]	]	X
ajst-15595	246	4	chang	chang	PROPN
ajst-15595	246	5	,	,	PUNCT
ajst-15595	246	6	c.	c.	PROPN
ajst-15595	246	7	p.	p.	PROPN
ajst-15595	246	8	,	,	PUNCT
ajst-15595	246	9	wen	wen	PROPN
ajst-15595	246	10	,	,	PUNCT
ajst-15595	246	11	j.	j.	PROPN
ajst-15595	246	12	,	,	PUNCT
ajst-15595	246	13	dong	dong	PROPN
ajst-15595	246	14	,	,	PUNCT
ajst-15595	246	15	m.	m.	NOUN
ajst-15595	246	16	,	,	PUNCT
ajst-15595	246	17	&	&	CCONJ
ajst-15595	246	18	hao	hao	PROPN
ajst-15595	246	19	,	,	PUNCT
ajst-15595	246	20	y.	y.	PROPN
ajst-15595	246	21	.	.	PUNCT
ajst-15595	247	1	(	(	PUNCT
ajst-15595	247	2	2018	2018	NUM
ajst-15595	247	3	)	)	PUNCT
ajst-15595	247	4	.	.	PUNCT
ajst-15595	248	1	does	do	AUX
ajst-15595	248	2	government	government	NOUN
ajst-15595	248	3	ideology	ideology	NOUN
ajst-15595	248	4	affect	affect	VERB
ajst-15595	248	5	environmental	environmental	ADJ
ajst-15595	248	6	pollutions	pollution	NOUN
ajst-15595	248	7	?	?	PUNCT
ajst-15595	249	1	new	new	ADJ
ajst-15595	249	2	evidence	evidence	NOUN
ajst-15595	249	3	from	from	ADP
ajst-15595	249	4	instrumental	instrumental	ADJ
ajst-15595	249	5	variable	variable	ADJ
ajst-15595	249	6	quantile	quantile	ADJ
ajst-15595	249	7	regression	regression	NOUN
ajst-15595	249	8	estimations	estimation	NOUN
ajst-15595	249	9	.	.	PUNCT
ajst-15595	250	1	energy	energy	NOUN
ajst-15595	250	2	policy	policy	NOUN
ajst-15595	250	3	,	,	PUNCT
ajst-15595	250	4	113(feb	113(feb	NUM
ajst-15595	250	5	.	.	NUM
ajst-15595	250	6	)	)	PUNCT
ajst-15595	250	7	,	,	PUNCT
ajst-15595	250	8	386	386	NUM
ajst-15595	250	9	-	-	SYM
ajst-15595	250	10	400	400	NUM
ajst-15595	250	11	.	.	PUNCT
ajst-15595	251	1	[	[	X
ajst-15595	251	2	15	15	NUM
ajst-15595	251	3	]	]	X
ajst-15595	251	4	saric	saric	NOUN
ajst-15595	251	5	,	,	PUNCT
ajst-15595	251	6	z.	z.	PROPN
ajst-15595	251	7	,	,	PUNCT
ajst-15595	251	8	xu	xu	PROPN
ajst-15595	251	9	,	,	PUNCT
ajst-15595	251	10	x.	x.	PROPN
ajst-15595	251	11	,	,	PUNCT
ajst-15595	251	12	duan	duan	PROPN
ajst-15595	251	13	,	,	PUNCT
ajst-15595	251	14	l.	l.	PROPN
ajst-15595	251	15	,	,	PUNCT
ajst-15595	251	16	&	&	CCONJ
ajst-15595	251	17	babic	babic	PROPN
ajst-15595	251	18	,	,	PUNCT
ajst-15595	251	19	d.	d.	PROPN
ajst-15595	251	20	.	.	PUNCT
ajst-15595	252	1	(	(	PUNCT
ajst-15595	252	2	2018	2018	NUM
ajst-15595	252	3	)	)	PUNCT
ajst-15595	252	4	.	.	PUNCT
ajst-15595	253	1	identifying	identify	VERB
ajst-15595	253	2	the	the	DET
ajst-15595	253	3	safety	safety	NOUN
ajst-15595	253	4	factors	factor	NOUN
ajst-15595	253	5	over	over	ADP
ajst-15595	253	6	traffic	traffic	NOUN
ajst-15595	253	7	signs	sign	NOUN
ajst-15595	253	8	in	in	ADP
ajst-15595	253	9	state	state	NOUN
ajst-15595	253	10	roads	road	NOUN
ajst-15595	253	11	using	use	VERB
ajst-15595	253	12	a	a	DET
ajst-15595	253	13	panel	panel	NOUN
ajst-15595	253	14	quantile	quantile	ADJ
ajst-15595	253	15	regression	regression	NOUN
ajst-15595	253	16	approach	approach	NOUN
ajst-15595	253	17	.	.	PUNCT
ajst-15595	254	1	traffic	traffic	NOUN
ajst-15595	254	2	injury	injury	PROPN
ajst-15595	254	3	prevention	prevention	NOUN
ajst-15595	254	4	.	.	PUNCT