




































American International Journal of Agricultural Studies  

Vol. 5, No. 1; 2021 

ISSN 2641-4155   E-ISSN 2641-418X 

Published by American Center of Science and Education, USA 

 

 31  

SPATIAL ANALYSIS OF PADDY RICE PRICE VARIABILITY IN 

DASS AND TAFAWA BALEWA LGAS OF BAUCHI STATE, 

NIGERIA 
 

 

Andarawus Musa 

Department of Agricultural Economics and Extension, FUW, Taraba State, Nigeria 

E-mail: mandarawus@gmail.com 

 

R.M. Sani 

Department of Agricultural Economics and Extension, ATBU Bauchi State, Nigeria 

 

Godiya Bulus 

Department of Agricultural Economics and Extension, ATBU Bauchi State, Nigeria 

 

 

 

Received: July 27, 2021      Accepted: August 30, 2021     Online Published: September 15, 2021  

 

DOI: 10.46545/aijas.v5i1.202                                   URL: https://doi.org/10.46545/aijas.v5i1.202 

 

 

ABSTRACT 

The study was conducted on the spatial analysis of paddy rice (Oryza sativa) price variability in 

Dass and Tafawa Balewa LGAs of Bauchi State, Nigeria. Data were collected using 

questionnaires administered to 120 respondents sampled through random sampling technique. 

Secondary data were also collected from BSADP Bauchi on monthly prices of paddy rice. Data 

were analyzed using descriptive statistics (mean, frequency, ranking and likert scale), pearson 

product correlation, T-test and ratio to moving average model. It was revealed that the leading 

causes of spatial rice price variability were spatial variation in supply, high cost of 

transportation and inadequate market information. There was existence of price integration or 

perfect price transmission between and among the urban and rural markets during the period of 

study. The magnitude of paddy rice price variability in the rural markets were higher, and the t-

test shows that there was a significant (P < 0.05) difference in price of paddy rice between rural 

and urban markets. Spatial variation in supply, bad road condition, seasonal variation in supply, 

inadequate contact with extension agents and low capital outlay were the major constraints 

militating against paddy rice marketing in the study area. Therefore, it is recommended that 

Rural feeder roads should be constructed by government, NGOs or individuals to enable easy 

movement of produce   as well as all year round production/supply of rice should be encouraged 

through provision of fund and inputs by relevant stakeholders to farmers for dry season farming 

in order to curtail the problem of price variation due to seasonality in production. 

 

Keywords: Spatial, Markets, Paddy Rice, Price Variability. 

 

http://www.acseusa.org/journal/index.php/aijas
mailto:mandarawus@gmail.com


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32 

INTRODUCTION 

 Over the past decade, the rice consumption rates have risen rapidly. According to Terwase and 

Madu (2018) only in the last decade, the consumption rate has risen to 7 million Metric Tons per 

annum. Still, only 2.7 million metric tons are produced by Nigerian farmers. This means that 

even the increase in rice production in Nigeria still leaves a significant gap of 4.2-4.3 million 

metric tons. Therefore, Nigeria is only able to supply 49% of the domestic demand. Nigeria’s per 

capita consumption of rice has grown significantly at about 7.3% (Akande, 2019). To bridge the 

gap, the federal government of Nigeria over the years has embarked on policies and incentives 

for the farmers to increase production. The most recent among them is the presidential initiative 

on rice inaugurated by the Buhari’s administration in 2018. The objective of the initiative was to 

increase rice production, improve milling quality, and promote marketing to provide domestic 

rice for consumption and to reduce/band national rice importation as well as to achieve 15 

million metric tons of rice production from the 3 million hecters of the consolidated farm land by 

2025. (USAID, 2019). As beautiful as this may be, such may not be fully realizable without 

proper marketing and pricing system 

Agricultural marketing is bedeviled by a lot of problems. Some of the problems arise 

because of the basic characteristics and problem of Nigeria’s agriculture. Marketing constraints 

or challenges arise due to many factors such as limited knowledge and use of market 

information, lack of access to high-value reliable markets, high transactional costs, distance from 

the markets, poor quality of the products, lack of storage facilities, low educational level of 

farmers/marketers, poor agricultural extension services, lack of financial support and most 

recently poor price control/system (Antwi & Seahlodi, 2011). Matungul et al. (2012) added that 

inadequate market infrastructure, lack of adequate access to finance, lack of good roads, risks 

and uncertainty, poor communication of information regarding prices, lack of bargaining power 

and excesses of intermediaries bedeviled agricultural marketing. According to Xaba and Masuku, 

(2012) socio-economic factors of the marketers for example: training, marketing experience, age, 

level of education, household size, and gender all contributed to problems of agricultural 

marketing and pricing. 

These marketing constraints constitute the greatest barrier for small-scale farmers when it 

comes to access high value markets (Baloyi, 2010), and these factors restrain farmers and 

marketers from making decisions to participate in the markets (Uchezuba et al., 2009). 

Therefore, overcoming marketing constraints is critical for small-scale farmers to access 

lucrative markets (Baloyi, 2010). He added that Shifting the focus from production-oriented 

programmes to more market-oriented interventions will place a renew attention on institutions of 

collective action, such as farmer groups, as an efficient mechanism for enhancing market 

performance. 

Much research work has been done on agricultural commodity marketing and specifically 

on price analysis. Majority of these studies have concluded that price variation which is a 

common phenomenon in agricultural commodity marketing is caused by temporal and spatial 

production as well as constraints that marketers face such as cost of transportation and 

inadequate market information. Other marketing studies such as the ones carried out by Madre 

and Pieter (2018), Taru (2012), Emokaro and Ayantoyinbo (2014) and Debaniyu et al. (2011) all 

lend credence to the fact that inefficiency in marketing and pricing information transmission is 

one of the major causes of price variation. Few or no studies have been conducted on the effect 

of spatial price variability on the part of marketers, consumers and the farmers  

Hence, this study which is aimed at analysing the effect of spatial price variability on the 



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33 

part of rice marketers, consumers and the farmers in Dass and Tafawa Balewa LGAs, Bauchi 

State. Consequently, the broad objective of this research is to analyse the effect of spatial price 

variability of paddy rice in Dass and Tafawa Balewa LGAs of Bauchi state. The specific 

objectives of the study are-: 

 To identify the causes of spatial price variation of paddy rice in the study area. 

 To determine the market integration of paddy rice in the selected markets. 

 To determine the effect and magnitude of rice price variability in the study area. 

 

METHODOLOGY 

The Study Area 

This study was carried out in Dass and Tafawa Balewa LGAs of Bauchi State. The study area has 

an estimated population of 532,210. Its coordinates are: latitude 10.15N and 12.3N, and 

longitude 8.45E and 9.00E with a land mass of 22, 852 km2 (BSADP, 2015). This means that it 

lies in the guinea savanna region. The state is located in the North-East geopolitical region of the 

country bounded in the south by Plateau state, in the north by Jigawa and Yobe states and in the 

east by Gombe state. Agriculture is the traditional occupation of the people in the study area. The 

tropical nature of the climate favors the growth of a variety of food crops such as cereals and 

legumes which include rice, maize, millet, acha, cowpea, groundnut etc. The vegetation consist 

of guinea savanna and derived sahel savanna towards the north. The climate is tropical with two 

distinct seasons. Usually, the wet season last between May and October, while the dry season 

comes between November and April. Mean annual rainfall is 1300mm per annum. Maximum 

temperature is 40oC in April/May while Minimum is 9o-10oC in Dec/Jan.  

 

Source and Method of Data Collection 
Both primary and secondary source of data were used as follows: 

 

Primary Source 

Semi structured questionnaire consisting of both open and closed ended questions and verbal 

interview were used to gather information on the socio economic characteristics of rice 

marketers. These characteristics include age, sex, marital status, years of marketing experience, 

level of education attained, level of capital outlay and source of initial capital. Other information 

collected were causes of price changes and problems rice marketers face in the study area.  

 

Secondary Source 

Data on monthly mean price of paddy rice were obtained from Planning, Monitoring and 

Evaluation Unit of BSADP, Bauchi, covering prices in both urban and rural markets of Dass and 

Tafawa Balewa Local Government Areas. As seen in the Table 1 below, two local government 

areas purposively selected were Dass and Tafawa Balewa LGAs based on the relatively high 

level of rice production in the state. In each local government, 2 urban and 2 rural markets were 

selected through simple random sampling. Urban markets selected in Dass Local Government 

were Dass and Baraza markets while the selected rural markets from the area were Wandi and 

Bazali markets. In the same vein, Tafawa Balewa and Bununu urban markets were selected; and 

Marti and Zwal rural markets were selected from Tafawa Balewa Local Government area. Based 

on the markets size and the number of rice marketers, 20% of the population were sampled. In 

total, 120 questionnaires were distributed and retrieved.  

 



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34 

Table 1. Sample Size Selection Plan 

 

Local Government Market  Sample Frame  Sample Size (20%) 

Tafawa Balewa Tafawa Balewa      102    20 

Tafawa Balewa Bununu      81    16 

Tafawa Balewa Zwal      69    14 

Tafawa Balewa Marti      51    10 

Dass Dass      95    19 

Dass Baraza      86    17 

Dass Wandi       55    11 

Dass Bazali      64    13 

 Total     603    120 

Source: Field Survey, 2018 

 

DATA ANALYSIS 

The data collected were analysed using the following statistical tools: Objective (i and iv) were 

achieved using descriptive statistics such as mean, percentage, ranking, frequency and likert 

scale. Objective (ii) was achieved using pearson product correlation analysis. Objective (iii) was 

achieved using Ratio to Moving Average Model and independent t-test. 

 

Independent T-test  

T-Test for Difference of Means between Markets. The formula for computing a t-test which was 

used to compare the mean prices between urban markets and rural market in the two local 

government areas is given as:  

                     X1 - X2 

T-cal =    S12 + S22 

            √n1+n2                                                                          …… (1)     

                                             

Where; 

T-cal = calculated value of t-distribution  

X1 = mean of rice prices for rural markets.  

X2 = mean of rice prices for the urban markets. 

S12 = Standard deviation of rice prices for rural market.  

S22 = Standard deviation of rice prices for urban market. 

 

Correlation Analysis 

Pearson Product Correlation coefficient was computed for the urban and rural markets in line 

with the method of Oladapo et al. (2007) to determine the market integration. The formula used 

was:  

rij  =   (Pit -Pit) (Pjt - Pjt) 

       √(Pit -Pit)  √(Pjt - Pjt)                                                            …(2) 

 

Where;  

i = rural markets.            

j = Urban market.            



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Pit and Pjt are the prices of rice in the rural (i) and urban (j) markets measured at time t.   

Pit and Pjt  =  Mean of rural and urban rice prices respectively. 

 n = Number of respondents 

rij = Correlation between rural and urban markets. 

  

Ratio to Moving Average Model 

The ratio to moving average model was used to estimate the magnitude of rice price variability 

(Kilima et al., 2013). The method is commonly used since it eliminates the trend cyclical and 

irregular components from the original data. Venture (2005) defined magnitude of variability as 

the percentage change of the difference between the highest and the lowest seasonal price of a 

commodity among the months of a year or a given term period under study as shown in the 

equation below:  

M =  x 100                                                                                    … (3) 

Where; 

M = magnitude of rice price variability. 

Max = maximum price recorded during the season 

Min = minimum price recorded during the season 

  

Likert Scale 

Likert scale was adopted to analyse the respondents’ views on the causes of spatial and temporal 

price variation as well as constraints of paddy rice marketing in the study area. Various kind of 

rating scales have been developed to measure attitudes directly. (i.e. the person knows their 

attitude being studied). The most widely used is the Likert scale. In its final form, the Likert 

scale is a five (or seven) point scale which is used to allow the individual to express how much 

they agree or disagree with a particular statement. Jamieson (2004). A Likert scale assumes that 

the strength/intensity of an attitude is linear, i.e. on a continuum from strongly agree to strongly 

disagree and make the assumption that attitudes can be measured. Each of the five or seven 

responses would have a numerical value which would be used to measure the attitude under 

investigation. For example,  

 

Strongly Agree Agree Undecided Disagree Strongly 

Disagree 

(1) (2) (3) (4) (5) 

 

 

RESULTS AND DISCUSSION 

Causes of Spatial Price Variation  

According to Taru (2012) Spatial price variability refers to likelihood of fluctuation in price 

levels over space, i.e, between two or more locations that are separated by distance. The 

infrastructural factors influencing spatial price of paddy rice are; the cost of transportation and 

availability of storage facilities. Again, the economic factors that influence spatial price of paddy 

rice are; the number of paddy buyers, market information, market organization and individual 

price fixing. The need for spatial price analysis arises because agricultural commodity’s 

production and consumption point are spatially dispersed, bulky and seasonally produced 

(Nwibo et al., 2013). 

Thus, the result of Table 2 revealed that the leading causes of spatial rice price variability 



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were spatial variation in supply, high cost of transportation and inadequate market information, 

among the major causes of spatial price variation of rice which accounted for 95.83%, 93.33% 

and 59.93% of the marketers, respectively. Other important causes as indicated by the marketers 

were inadequate supply of the produce (4th) and lack of standard unit of measurement (5th) which 

accounted for 46.67% and 21.67%, respectively.  

 

Table 2. Causes of Spatial Price Changes in Rice Marketing 

 

Causes  SA A U D SD R 

Spatial variation in supply 96(80) 19(15.83) 2(1.67) 2 (1.67) 1(0.83) 1st  

High cost of transportation  73(60.83) 39(32.5) 5(4.1) 3 (2.5) 0 2nd  

Inadequate market information 5(4.1) 67(55.83) 36(30.0) 11 (9.17) 1 (0.83) 3rd  

Inadequate supply of the produ  15(12.5) 41(34.17) 21(17.5) 37 (30.83) 6 (5) 4th  

Lack of standard unit of meas 0 26(21.67) 36(30.0) 52 (43.33) 6(5) 5th  

Unfriendly activities of T/unio 3(2.5) 18(15)8 31(25.83) 64 (53.33) 4 (3.33) 6th  

Seasonal variation in supply 0 8(6.67) 6(5) 23 (19.17) 83(69.17) 7th  

High cost of storage chemicals 5(4.1) 2(1.67) 9(7.5) 57 (47.5) 47(39.17) 8th  

   SA = Strongly Agreed, A = Agreed, U = Undecided, D = Disagreed, SD = Strongly Disagreed 

and R = Rank  

NOTE: Values in brackets are in percentages 

Source: Field Survey, 2018 

 

 However, Fraudulent activities of trade union (6th), seasonal variation in supply (7th) and 

high cost of storage chemicals (8th) accounted for 17.50%, 6.67% and 5.77% of the marketers 

respectively were the least significant causes of spatial price variation in the study area. This 

means that a considerable number of the factors considered in Table 2 contributed greatly to 

spatial price variation with much emphasis on spatial variation in supply (1st), transportation cost 

(2nd) and inadequate market information (3rd). This agrees with the work of Taru (2012) who 

reported that infrastructural factors influencing spatial price of paddy rice are; the cost of 

transportation and availability of storage facilities. Again, the economic factors that influence 

spatial price of paddy rice are; the number of paddy buyers, market information, market 

organization and individual price fixing. Similarly, Minot (2017) posited that spatial/scattered 

production and cost of transportation are the major causes of spatial price variability. The 

implication of this result is that unless these factors are mitigated, price of paddy rice will 

continue to differ between markets in the study area 

 

Paddy Rice Price Integration 

Price integration refers to a situation in which prices of a commodity in separate markets move 

together, thereby offering smooth transmission of price signals and information. The study of 

market integration is important in determining the co-movements of prices and the transmission 

of price signals and information across spatially separated markets. The high and significant 

correlation of price is an indication of co-movement in the prices. The positive correlation shows 

that an increase in the retail price in one market would follow the price increase in the other 

market. Emokaro and Ayntoyinbo (2014). Without spatial price integration of market, price 

signals will not be transmitted from food deficit to food surplus areas; prices will be more 

volatile; agricultural producers will fail to specialize according to long-term comparative 



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advantage, and the gains from trade will not be realized. 

To further determine the extent to which prices move together in the study area, pearson 

correlation analysis was applied to average monthly market prices of paddy rice in rural and 

urban markets of Dass and Tafawa Balewa LGAs (Table 3). The result revealed that in all the 

market pairs both urban-urban, urban-rural and rural-rural, there was strong linear relationship 

among the prices of paddy rice during the period of study as t-values range between 0.801 – 

0.998. This implies that there was existence of price integration or perfect price transmission 

between and among the urban and rural markets in the study area. This agrees with Emokaro and 

Ayintoyinbo (2014) who reported that the strong linear relationship among the prices of paddy 

rice during the period of their study was possible due to the transmission of market information 

by marketers through various means, particularly via the use of mobile phones and short distance 

between the markets. It could also be deduced from the result that, factors that influence price of 

paddy in the rural markets are similar to those in the urban markets in the study area. 

 

Table 3. Pearson Correlation Matrix of Average Monthly Price of Paddy Rice in the Study Area 

 

It was also revealed from the Table 3 that correlation coefficient between the urban 

market pairs were higher (above 0.93) than those between urban and rural market pairs (below 

0.89) which implies that the flow of information on rice price was faster among the urban 

markets than between rural and urban markets and so, a deficit/surplus in one urban market may 

have been promptly transmitted to the other.  

This findings was corroborated by Bassey et al. (2013) who found out that correlation 

coefficient between the urban market pair was higher (0.81) than those between the rural and 

urban market pairs which ranged from 0.41 to 0.46 in Akwa Ibom State rice traders. Similarly, 

these arguments collaborate with the findings of Ojiako et al. (2012) in their analysis of the 

spatial integration of cassava product market price in Nigeria, where it was reported that the 

mean price value of Lafun in the urban market was higher than prices in the rural markets. The 

high and significant correlation of price is an indication of co-movement in the prices. The 

positive correlation shows that an increase in the retail price in one market would follow the 

price increase in the other market (Emokaro & Ayntoyinbo, 2014). This could be possible due to 

the transmission of market information by marketers through various means, particularly via the 

use of mobile phones. 

 T/Balewa 

(U) 

Bununu 

(U) 

Zwal 

(R) 

Marti 

(R) 

Dass 

(U) 

Baraza(

U) 

Wandi 

(R) 

Bazali 

(R) 

T/Balewa 

(U) 

1 0.993** 0.819** 0.857** 0.951** 0.942** 0.830** 0.844** 

Bununu(U)  1 0.864** 0.895** 0.943** 0.937** 0.874** 0.888** 

Zwal(R)   1 0.992** 0.801** 0.813** 0.994** 0.993** 

Marti (R)    1 0.858 0.869 0.989** 0.993** 

Dass (U)     1 0.993 0.816** 0.834** 

Baraza (U)      1 0.828** 0.844** 

Wandi (R)       1 0.998** 

Bazali (R)        1 



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Effect of Paddy Rice Price Variation  

The magnitude of price variability is the percentage change of the difference between the highest 

and the lowest seasonal price of a commodity among the months of a year or a given term 

period. The magnitude and frequency of price movement in both temporal and spatial directions 

have effects on farmers, traders as well as consumers. Generally, the greater the magnitude of 

variability, the larger is the effect especially on the farmers’ income, consumers’ purchasing 

power and traders’ income and welfare. Large increase in price may exacerbate poverty as poor 

consumers will not be able to afford basic food leading to poor nutrition (Mustapha & Richard, 

2013; Camara, 2013). The information presented in Table 4 revealed that the magnitude of price 

variability for Bazali (rural), Marti (rural), Wandi (rural) and Zwal (rural) are about 58.89%, 

54.81%, 54.72% and 53.11%, respectively. This high level of variability is highly associated with 

the drastic fall in rice prices from September to November. 

 

Table 4. Effect of Rice Price Variation 

 

Market Max          Min         Annual 

Average 

Variability 

   (%)  

Seasonal 

Differential 

   t-Value 

T/Balewa(U) 145 105 127.22 38.10 40.00  

Bununu(U) 145 107 127.89 35.51 38.00  

Zwal (R) 139.33  91 118.60 53.11 48.33  39.18** 

Marti (R) 139.33  90 118.11 54.81 49.33  

Dass (U) 150 105 124.44 42.86 45  

Baraza (U) 146 100 123.52 46.00 46   37.42** 

Wandi (R) 139.25  90 118.09 54.72 49.25  

Bazali (R) 143  90 118.81 58.89 53.00  

** = significant (P≤0.05)U=Urban Market, R=Rural Market 

Source: Computed from BSADP, 2018 

 

The magnitude of variability is relatively low in urban markets (Baraza 46%, Dass 

42.86%, Tafawa Balewa 38.10% and Bununu 35.51%) than in the rural markets (in Bazali 

58.89%, Marti 54.81%, Wandi 54.72% and Zwal 53.11% 

These findings suggest that farmers located near rural areas (Bazali, Marti, Wandi and 

Zwal) are likely to have unstable earnings from the sales of their rice than those located near 

urban markets (Baraza, Dass, Tafawa Balewa and Bununu). This findings agrees with Emokaro 

and Ayantoyinbo (2014) who says the retail price for rice in the urban markets were more stable 

than what is obtained in the rural markets. They added that farmers located near urban markets 

benefit from higher prices than those in more remote areas. 

Also, the t-test analysis in Table 4 shows that there was a significant (p≤0.05) difference 

in price of rice between at least two or more rural and urban markets in the study area during the 

period of study. It indicates that mean price in the urban markets were significantly higher than 

those in the rural markets. This result agreed with Oladapo et al. (2007) who reported that prices 

in the urban markets were higher than those in the rural markets in their study area on marketing 

margin and spatial pricing efficiency of pineapple in Nigeria. They further confirm that prices of 

agricultural commodities depicts wide differences between zones and markets within same 

region. Taru (2012) added that prices for same product varies greatly between areas and this may 

be due to the cost of transportation, production area and communication difficulties. Such price 



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variation among markets in Nigeria is necessary for the existence of market, as it create 

incentives that attract market actors to engage in trade. 

 The implication for this urban – rural price differential as indicated in Table 4 is that it is 

economical to buy paddy rice from rural market as their price is significantly lower than those in 

the urban market so long as the marketing margin is less than the transport cost. 

 

Constraints of Paddy Rice Marketing in the Study Area 

Agricultural marketing is bedeviled by a lot of problems. Some of the problems arise because of 

the basic characteristics and problem of Nigeria’s agriculture. Marketing constraints or 

challenges arise due to many factors such as limited knowledge and use of market information, 

lack of access to high-value reliable markets, high transactional costs, distance from the markets, 

poor quality of the products, lack of storage facilities, low educational level of 

farmers/marketers, poor agricultural extension services, lack of financial support ( Antwi and 

Seahlodi, 2011).  

 

Table 5. Constraints of Paddy Rice Marketing  

 

Constraints SA A U D SD R 

Spatial variation in supply 99(82.5) 20(16.67) 0 1(0.83) 0 1st 

Bad road condition 68(56.67) 47(39.16) 0 4(3.33) 1(0.83) 2nd 

Seasonal variation in supply 86(71.67) 27(22.5) 1(0.83) 5(4.16) 1(0.83) 3rd 

 

Inadequate contact with extension 

agents 

49(40.83) 62(51.67) 1(0.83) 6(5) 2(1.67) 4th 

Unfriendly activities of brokers/agt  3(2.5) 89(74.17) 21(17.5) 7(5.83) 0 5th 

Unfriendly activities of middlemen 3(2.5) 81(67.5) 11(9.17) 19(15.83) 6(5) 6th 

Inadequate supply of produce 8(6.67) 76(63.33) 20(16.67) 16(13.33) 0 7th 

Lack of standard unit of 

measurement 

3(2.5) 76(63.33) 34(28.33) 40(33.33) 6(5)  8th 

 

Poor quality control measures  5(4.16) 42(35.0) 33(27.5) 34(28.33) 6(5.0)  9th 

Unfriendly market information 

Unfriendly acts of trade union 

High cost of storage chemicals 

5(4.16) 

0 

8(6.67) 

37(30.83) 

41(34.17) 

3(2.5) 

56(46.67) 

7(30.83) 

12(10.0) 

19(15.83) 

41(34.17) 

40(33.33) 

2(1.67) 

2(1.67) 

57(47.5) 

10th 

11th 

12th 

 

SA = Strongly Agreed, A = Agreed, U = Undecided, D = Disagreed and SD = Strongly Disagreed  

NOTE: Values in brackets are in percentage 

Source: Field Survey, 2018 

  

Table 5 shows that rice marketing in the study area was faced with constraints such as 

bad road conditions, inadequate market information, seasonal variability in rice supply and so on. 

It is likely that the same constraints are responsible for price fluctuation among locations and 

between time periods. Of all these problems, spatial variation in supply was ranked first 

(99.17%), this was followed closely by bad road condition, seasonal variation in supply and 

inadequate contact with extension agents with 95.83%, 94.17% and 92.40% respectively. Other 

important problems of rice marketing as indicated by the marketers were Unfriendly activities of 

brokers/agents (5th), unfriendly activities of middlemen (6th), inadequate supply of produce (6th) 



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and lack of standard unit of measurement (8th) which accounted for 76.67%, 70.00%, 70.00% 

and 65.8% of the total marketers, respectively. 

However, the least significant problems of rice marketing in the study area as indicated in 

the table were poor quality control measures (9th), inadequate market information (10th), 

Unfriendly activities of trade union (11th) and high cost of storage chemical (12th) which 

accounted for 39.16%, 34.99%, 34.12% and 9.17% of the marketers, respectively. This finding is 

in line with Nwibo et al. (2013) “the functioning of the rice markets is constrained by various 

problems and obstacles such as seasonal rice supply, imperfect market information for buying 

and selling rice, lack of credit and cash to finance the business, insufficient facilities for storage 

and transportation cost. This was also supported by Antwi and Seahlodi (2011) who stated that 

agricultural marketing is bedeviled by a lot of problems. Some of the problems arise because of 

the basic characteristics and problem of Nigeria’s agriculture. Marketing constraints or 

challenges arise due to many factors such as limited knowledge and use of market information, 

lack of access to high-value reliable markets, high transactional costs, distance from the markets, 

poor quality of the products, lack of storage facilities, low educational level of 

farmers/marketers, poor agricultural extension services, lack of financial support. Matungul et al. 

(2012) added that inadequate market infrastructure, lack of adequate access to finance, lack of 

good roads, risks and uncertainty, poor communication of information regarding prices, lack of 

bargaining power and excesses of intermediaries bedeviled agricultural marketing. According to 

Xaba and Masuku (2012) socio-economic factors of the marketers for example: training, 

marketing experience, age, level of education, household size, and gender all contributed to 

problems of agricultural marketing. The implication is that, rice marketers would continue to 

gain little or no profit from the business so long as these constraints continue to linger in the 

study area. And this would also boil down to farmers and consumers 

 

CONCLUSSION 

It can be concluded that the leading causes of spatial rice price variability were spatial variation 

in supply, high cost of transportation and inadequate market information. 

There was existence of price integration or perfect price transmission between and among the 

urban and rural markets during the study. 

The magnitude of paddy rice price variability is relatively high in rural markets than in 

the urban markets and that farmers located near rural areas are likely to have unstable earnings 

from the sales of their rice than those located near urban markets. 

Paddy rice marketing in the study area was faced with constraints such as spatial 

variation in supply, bad road condition, and seasonal variation in supply and inadequate contact 

with extension agents. 

 

RECOMMENDATIONS 

 Based on the findings of the research, the following recommendations were made: 

 Rural feeder roads should be constructed by government, NGOs or individuals to enable 

easy movement of produce. 

 Marketers should improve their savings and investment strategies in order to generate 

more capital to expand their business 

 All year round production/supply of rice should be encouraged through provision of fund 

and inputs by relevant stakeholders to farmers for dry season farming in order to curtail 

the problem of price variation due to seasonality in production. 



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Copyrights  

Copyright for this article is retained by the author(s), with first publication rights granted to the 

journal. This is an open-access article distributed under the terms and conditions of the Creative 

Commons Attribution license (http://creativecommons.org/licenses/by/4.0). 

http://dx.doi.org/10.5539/sar.v2nlp112y

