201 © 2018 by the authors; licensee Asian Online Journal Publishing Group Asian Journal of Economics and Empirical Research Vol. 5, No. 2, 201-208, 2018 ISSN(E) 2409-2622/ ISSN(P) 2518-010X DOI: 10.20448/journal.501.2018.52.201.208 © 2018 by the authors; licensee Asian Online Journal Publishing Group A Comparative Analysis Based on Economic Factors of Students Emigration from South Asia Yasir Khan1  Taimoor Hassan2 Wang Ming Yi3 Rahimullah Gulzar4 ( Corresponding Author) 1Ph.D. School of Economics & Management, Southeast University Nanjing 211189, China 2PhD. School of Economics and Management, Nanjing University of Science and Technology, China 3School of International Trade and Economics, Shandong University of Finance and Economics, Shandong, China 4School of Engineering Management, Southeast university Nanjing PR China Abstract Economic instability and higher unemployment significantly increased the number of students migration from all over the world, particularly South Asian countries in the last decade. Growing number of international student migration to abroad for higher education and search for better economic opportunity. This study will determine the economic impact of students‘ emigration from South Asian countries particularly Pakistan, India, and Bangladesh. A comparative analysis of the three border sharing countries have shown the long-term economic and political instability and a result of an economic and financial collapse in 2008, and also discuss how such an environment has affected student emigration from South Asia. This study is quantitative research using questioners as a tool to collect primary data, from the large sample size of 300 South Asian students studying in Chinses universities in China. This research work is based on two factors, 1) the deterioration of economic factors in Pakistan, India, and Bangladesh have changed the students‘ perception to migrate abroad; 2) the study also reflected that majority of Pakistani, Indian and Bangladeshi students want to stay in the host country. The findings indicated that all the related variables have significantly positive, economic instability, higher unemployment, lower salary, political instability, and lower quality education system. The logit-probit regression models with these variables could predict the higher value of the variance in the overall student migration to abroad. Findings are relevant for academic institutions and government agencies interested in international education, student migration behavior, comparative data as well as strategic policies. Keywords: South Asia, International students, Economic factors, Comparative analysis, Migration, Probit-logit regression. Citation | Yasir Khan; Taimoor Hassan; Wang MingYi; Rahimullah Gulzar (2018). A Comparative Analysis Based on Economic Factors of Students Emigration from South Asia. Asian Journal of Economics and Empirical Research, 5(2): 201-208. History: Received: 16 August 2018 Revised: 19 September 2018 Accepted: 22 October 2018 Published: 26 November 2018 Licensed: This work is licensed under a Creative Commons Attribution 3.0 License Publisher: Asian Online Journal Publishing Group Contribution/Acknowledgement: All authors contributed to the conception and design of the study. Funding: This research was financially supported by the Social Science Foundation Project No.: 15BJY120. Competing Interests: The authors declare that they have no conflict of interests. Transparency: The authors confirm that the manuscript is an honest, accurate, and transparent account of the study was reported; that no vital features of the study have been omitted; and that any discrepancies from the study as planned have been explained. Ethical: This study follows all ethical practices during writing. Contents 1. Introduction .................................................................................................................................................................................... 202 2. Literature Review .......................................................................................................................................................................... 203 3. Research Methodology ................................................................................................................................................................. 204 4. Result and Discussion ................................................................................................................................................................... 206 5. Conclusion ....................................................................................................................................................................................... 207 References ............................................................................................................................................................................................ 208 http://crossmark.crossref.org/dialog/?doi=10.20448/journal.501.2018.52.201.208&domain=pdf&date_stamp=2017-01-14 http://creativecommons.org/licenses/by/3.0/ http://creativecommons.org/licenses/by/3.0/ http://asianonlinejournals.com/index.php/AJEER/article/view/260 https://orcid.org/0000-0002-9391-1772 https://orcid.org/0000-0003-3512-3847 https://orcid.org/0000-0001-9311-8275 http://asianonlinejournals.com/index.php/AJEER/article/view/260 https://orcid.org/0000-0002-9391-1772 https://orcid.org/0000-0003-3512-3847 https://orcid.org/0000-0001-9311-8275 http://asianonlinejournals.com/index.php/AJEER/article/view/260 https://orcid.org/0000-0002-9391-1772 https://orcid.org/0000-0003-3512-3847 https://orcid.org/0000-0001-9311-8275 http://asianonlinejournals.com/index.php/AJEER/article/view/260 https://orcid.org/0000-0002-9391-1772 https://orcid.org/0000-0003-3512-3847 https://orcid.org/0000-0001-9311-8275 http://asianonlinejournals.com/index.php/AJEER/article/view/260 https://orcid.org/0000-0002-9391-1772 https://orcid.org/0000-0003-3512-3847 https://orcid.org/0000-0001-9311-8275 Asian Journal of Economics and Empirical Research, 2018, 5(2): 201-208 202 © 2018 by the authors; licensee Asian Online Journal Publishing Group 1. Introduction The past few years student emigration from Pakistan, Bangladesh, and India have been significantly increased. This research work analyzes the reasons for students‘ emigration from Pakistan and their possible consequences on Pakistan economy. The brain drains from Pakistan particularly for higher education has been increased. The deterioration of economic factors increased the emigration outflow from Pakistan. the results reflect that unemployment and lower GDP rate have significantly increased in the past few years which enforce Pakistani student to migrate to other countries. The consequences of student migration of the are assessed analyzing migration theories. Economist stresses that reasons leading to migration are sustained by and motivated three main types of influences: demand-pull factors in the destination place; supply-push factors in the origin place; network factors that link destination and origin places. The migration flow changing due to the deterioration of economic factors. Unemployment significantly increased and was more critical in countries such as Pakistan, India, and Bangladesh. Therefore, in these south Asian nations, the immigration is reduced and emigration has started to increase. Countries with a good economic position such as China, Japan, South Korea, Singapore, and Malaysia experienced an higher number of students inward mobility for the short-term. The aim of student migration to is to increase their income and improve their well-being by mobility to other nations where earnings are significantly higher. There are over 4 million globally mobile tertiary education students, and this number is set to increase. For most countries, this remains the major form of internationalization, whether focused on international student recruitment, scholarships or mobility programs. Find out about current and future global patterns, trends, national strategies, motivations, targets, and institutional strategies. ―International students appear to have significant positive impacts on host institutions and countries as well as on host economies. Acknowledging the potential benefits international students can bring on board, we found that China, Canada, Australia, and the U.K. are prompt in understanding the big-picture impact of international students. In the U.S. context, except for NAFSA‘s annual economic impact report, voices on the benefits of international students to the national economy and institutional welfare are yet to be heard. We pay on prior mobility and emigration of students in Pakistan, India, and Bangladesh in this paper (Guruz, 2011). Generally, the mobility of students gives an opportunity to improve their knowledge in other foreign educational institutions of a different country during their studies. Akulavicius and Grundey (2011) enabling students can learn different approaches that expand their horizon and improving their potential opportunities for a future job especially in a time of economic downturn and higher international competition (Akulavicius and Grundey, 2011). Moreover, international student mobility has been a top priority of the international institutions and the most of the countries aim to attract international students because it involves several benefits such as extra income, higher labor market participation and economic growth. Migration processes were analyzed recently by Cekanavičius and Kasnauskienė (2009); Reher and Requena (2009). 1.1. Quantifying Short-Term Costs Our major assessment of the economic short-term costs of international students was informed by a review of the literature on the costs and benefits of immigration. Based on this we identified the following short-term costs:  Consumption of public services: the most typically cited cost of immigration is the additional consumption of public services (health, education, police, fire, transport, waste removal etc).  Increased congestion: increased congestion can impose costs on other residents. One example would be increased traffic congestion which, by increasing journey times, can impact upon local business productivity and hence GDP. Immigration has also had the effect of increasing house and rental prices (as the supply of housing tends to be fairly fixed in the short-term) but for this report, we will assume that this simply generates a transfer of resources between owners and tenants with no net impact on GDP.  Reduced social capital: some authors have argued that immigration can reduce the level of ―social capital‖ in an economy by reducing social cohesion. Tertiary education institutions, universities in particular, have always encouraged international co-operation and free flow between countries of staff, students and ideas. They have appreciated that science and scholarship do not recognize national boundaries and that progress in research will be facilitated by effective international sharing of ideas and discoveries the need to promote such co-operation is even greater today than in the past. National economies generally are becoming increasingly interdependent, while each year new technological advances in http://www.nafsa.org/Explore_International_Education/Impact/Data_And_Statistics/The_International_Student_Economic_Value_Tool/ Asian Journal of Economics and Empirical Research, 2018, 5(2): 201-208 203 © 2018 by the authors; licensee Asian Online Journal Publishing Group communication and transport mean that nations generally are in closer contact with one another. Added to this is the realization that many areas of scientific, technological and medical research are becoming increasingly expensive, and that facilitating mobility of professional personnel is, on balance, likely to advantage rather than disadvantage most countries socially, culturally and economically. ―Indeed‖, ―academic free trade may be more important than any other kind‖. Curiosity still motivates a number of students to seek study abroad, but in the latter half of the twentieth century, international education has increasingly become tied to the development of global markets and worldwide economic restructuring. The internationalization of tertiary education is expanding and as the production of wealth increasingly becomes based on knowledge rather than manual labor or mechanization, it can be expected that the exploitation of international ―knowledge-markets‖ will assume even greater importance. The number of students enrolled outside their country of citizenship has increased from 0.8 million in 1975 to 4.1 million in 2010 worldwide. This growth has greatly accelerated over the past decade or so with an average annual increase of 7.1 percent, ―mirroring the globalization of economies and societies‖ (OECD, 2010; OECD, 2012). There is little or no evidence to suggest that growth in international student mobility is likely to abate in the near future. Furthermore, in promoting student mobility, governments finance in one form or another various education co-operative effort. Many governments expend a proportion of their international aid in the form of overseas fellowships and scholarships. (By so doing, of course, they recoup some of the international aid via overseas student financial expenditure at the host institutions.) Many cultural treaties between nations contain an explicit provision for exchange of academic staff and students, and several government ministries of education have created formal programmers to further the international activities of their respective education systems. Governments promote international co-operative schemes not merely for the cultural and academic enhancement of students and staff who participate in them. Governments are becoming increasingly concerned that they occupy for economic and political purposes an advantageous position in the international knowledge-market. These are clearly motivating factors behind Australia‘s prominent role in international education. Australia is recognized as a world leader with respect to promoting the mobility of international tertiary education students. Although a small country in terms of population, China ranks third in terms of its worldwide share (5.9 percent) of international students. While the United States has the largest share of international students at around 18 percent, it‘s overall market share until quite recently has significantly declined following the events of 9/11. In terms of the percentage of tertiary education students who are international, 2. Literature Review The student emigrations are huge particular form South Asian nations, Pakistan, India, and Bangladesh due to deteriorations of economic factors. The migration process was currently analyzed by Sakienė (2011). Increase international migration flows that are very selective nations and regions, have been almost known everywhere since the 1980s Cushing and Poot (2004). Economic factors have been increasingly determents by this situation. Thus, constantly lack of employment in many countries significantly increase the percentage of seasonal works, has encouraged emigration to countries with less unemployment Cattaneo (2008); Martinoia (2009). Economic factors have a major impact on migration. From the economics point of view, international migration must be studied very carefully Sumption (2011). Migration reasons the most analyzed authors Faggian and McCann (2006); Tigau (2013); Mihi-Ramirez and Kumpikaite (2014). Such major factors, economic, political, demographical, geographical and others, analyzing factors which attract students and worker migrate to other countries, they are called demand-pull factors in the destination place. Economic factors attracted people by one or more factors Faggian and McCann (2006); Kumpikaite and Zickute (2012); Mihi-Ramirez and Kumpikaite (2014). Better availability of employment, higher income, lower taxes, economic stability, political stability, religious tolerance, better education facilities, better weather, better medical and other social facilities, better behavior among people, law and order situation and family reasons. Higher unemployment can increase emigration Kumpikaite and Zickute (2012). When the advantage of these factors more than cost, then the process of migration starts (Mixon, 1992). Our analysis of these factors is based on empirical study. Table-1. Demand-push factors and demand- pull factors. Rank Push-Factors (native places) Pull-Factors (Foreign destination) 1 Low wage rate High wage rate 2 Lower (GDP) per capita Higher GDP (per capita income) 3 Higher unemployment rate High demand of labor 4 Relatively high taxes Relatively low taxes 5 Relatively high consumer prices (CPI) Relatively low consumer price index (CPI) 6 Political instability Strong political system 7 Low quality education system Quality education system Looking for reasons of migration the most analyzed authors (Mixon, 1992) depict such main factors: 1) Political, 2) Economical, 3) Demographic, 4) Geographical, and 5) Others. When analyzing factors, which attract people to migrate to another country, they are called Demand-pull factors in the destination area. People are at- traced to places of destination by one or more factors (Mixon, 1992; Mihi-Ramirez and Kumpikaite-Valiuniene, 2013) as Higher incomes, Lower taxes, Better availability of employment, Better weather, Political stability, Better education facilities, Better medical and other social facilities, National prestige, Better behavior among people, Religious tolerance and Family reasons. Our empirical study is based an analysis of these factors for students. Asian Journal of Economics and Empirical Research, 2018, 5(2): 201-208 204 © 2018 by the authors; licensee Asian Online Journal Publishing Group Farquharson et al. (2019) suggested the migration of highly-skilled and educated student has not been studied extensively. However, further research on migration outcomes particularly for international students who study outside their home country for any degree level is lacking. While considerable migration research exists, few studies observe the subsequent migration behavior of foreign graduates as it pertains to the United States. The number of international students‘ inflows entering the to China for educational purposes has increased considerably in the last ten years, as well as their degree levels attained prior to entrance. Academic mobility increases pertinent questions regarding the causes and effects of such a significant demographic movement of highly-skilled individuals. The broad phenomenon of student mobility departing their country of origin, gaining a higher level of skill or education abroad, and not returning home, has created such concepts, well-known in educational circles, as ―brain drain.‖ This pattern of movement highlights several issues for consideration. This research work builds the collective set of comparative data is useful for higher education in companies invested and promoting their stay or back to home as well as offering significant directions for future research. This research paper will consider possible impactions for political and educational organization as well as the current academic institutions, may be impacted by the findings of this study. Furthermore, on a broader scale, this study offers relevant implications and findings for educational institutions interested in the development of reciprocal international influence and government policymakers responsible for immigrations regulations and international students‘ trends. 3. Research Methodology 3.1. Regression Analysis Logistic regression works very similar to linear regression, but with a binomial response variable. The greatest advantage when compared to Mantel-Haenszel or is the fact that you can use continuous explanatory variables and it is easier to handle more than two explanatory variables simultaneously. Although apparently trivial, this last characteristic is essential when we are interested in the impact of various explanatory variables on the response variable. If we look at multiple explanatory variables independently, we ignore the covariance among variables and are subjected to confounding effects, as was demonstrated in the example above when the effect of treatment on death probability was partially hidden by the effect of age. A logistic regression will model the chance of an outcome based on individual characteristics. Because chance is a ratio, what will be actually modeled is the logarithm of the chance given by: Where π indicates the probability of an event (e.g., death in the previous example), and βi are the regression coefficients associated with the reference group and the xi explanatory variables. At this point, an important concept must to be highlighted. The reference group, represented by β0, is constituted by those individuals presenting the reference level of each and every variable x1...m. To illustrate, considering our previous example, these are the individuals older aged that received standard treatment. Later, we will discuss how to set the reference level. Probit regression is a special type of the Generalized Linear Models. Here, the bivariate outcome YY has a Bernoulli distribution with parameter pp (success probability p ∈ (0,1) p ∈ (0,1)). Recall that EY=p. The probit link function Probit (EY) = Φ−1(p) = Φ−1(P[Y=1]) is used to transform the expectation of this 0/1 dependent variable. Then, the probit of the mean is modelled as a linear combination of the covariates (regressors) XX, i.e., we have a linear predictor probit (EY) = Xβ. Where β is a vector of unknow parameters. The maximum likelihood-based approach is used for the parameter estimation, where a version of the IRLS algorithm is applied (Newton, Raphson method, Fisher‘s scoring method). Predicated probability can be obtained by the inverse probit (i.e., standard normal cdf) transformation. Asian Journal of Economics and Empirical Research, 2018, 5(2): 201-208 205 © 2018 by the authors; licensee Asian Online Journal Publishing Group Pˆ[Yi=1] = Φ(Xi,∙βˆ). The result indicated that Pakistan has the higher unemployment rate since 2005 comparatively with India and Bangladesh. Higher unemployment rate significantly increased the number of Pakistani, Indian and Bangladeshi students. The number of unemployment among youth also increased in these three countries. The unemployment in Pakistan suddenly increased since 2007 and it has been higher than the European average from that time (see Table 1). Simultaneously the long-term unemployment and the employment of the highest studies level in India and Bangladesh have also continued to rise over the same period far above the South-Asian average. Pakistan is a leader for unemployment for youth in South-Asian as well. The fastest-growing unemployment was observed in India, Bangladesh, and Nepal. However, the unemployment of young people decreased in Bangladesh from 2011, at the same time when in Pakistan it was still growing and reached more than 50 percent. Table-2. Unemployment rates in the percentage of active population Pakistan, India and Bangladesh. Unemployment active population in % 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Pakistan 7.69 6.09 5.09 4.98 5.46 5.55 5.94 6.5 6.23 4.05 5.90 India 4.4 4.33 3.72 4.15 3.91 3.55 3.54 3.62 3.57 3.53 3.49 Bangladesh 4.3 4.5 4 3 5.0 4.5 4.5 4.5 4.3 4.2 4.1 Unemployment of youth in % 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Pakistan 12.02 8.75 7.75 7.86 8.83 9.02 10.92 10.98 11.30 10.63 10.93 India 9.89 9.90 8.83 9.97 9.60 10.13 10.24 10.61 10.54 10.12 9.83 Bangladesh 8.65 8.50 7.30 7.84 9.82 8.57 8.67 8.77 8.96 10.03 10.27 Source: International labor organization (ILO), IMF, Bangladesh Bureau of statistics, FRED The last decade economic recession and the fall of GDP per capita increase the migration flow from Pakistan, India, and Bangladesh. Such a situation encourages students‘ migration outflow from their country (see Figure 2). The three countries GDP per capita is less than two thousand US dollars which means the growth rate of these three countries are significantly slower. The weak economic situation makes the country less attractive. The gross domestic product (GDP) per capita allows showing the international level of development. Consequently, it is widely acknowledged that a higher development could a prerequisite for a reduction of the extent of migration (Mixon, 1992). The gross domestic product (GDP) is one of the primary indicators used to gauge the health of a country's economy. It represents the total dollar value of all goods and services produced over a specific time period, often referred to as the size of the economy. Usually, GDP is expressed as a comparison to the previous quarter or year. For example, if the Q3 2017 GDP of a country is up 3%, the economy of that country has grown by 3% over the third quarter. While quarterly growth rates are a periodic measure of how the economy is faring, annual GDP figures are often considered the benchmark for the size of the economy. Fig-1. Gross domestic product per capita Source: International Monterey Fund (IMF) Source: International Monterey Fund One of the main economic factors that affect the flow of migration is wage (Table. 3). Lower wage rate is one of the key factors for student emigration. Student intention to migrate for education where wage rate is high. Thus, with high unemployment emigration increases and vice versa. But in spite of the wide believe there is no evidence of higher immigration causes higher unemployment (Heid and Larch, 2012). Furthermore, a reduction of long-term unemployed could mean a higher productivity and lower emigration. Likewise, the unemployment of the highest education employees demonstrates whether the labor market is demanding for educated labor, which is related to youth emigration and the worst consequences for the country's economy (Glinskiene and Petuskiene, 2011). Inflation is the long-term rise in the prices of goods and services caused by the devaluation of currency Fig 2. While there are advantages to inflation which I will discuss later in this article, I want to first focus on some of the negative aspects of inflation. inflationary problems arise when we experience unexpected inflation which is not adequately matched by a rise in people‘s incomes. If incomes do not increase along with the prices of goods, everyone‘s purchasing power has been effectively reduced, which can turn to lead to a slowing or stagnant economy. Moreover, excessive inflation can also wreak havoc on retirement savings as it reduces the purchasing power of the money that savers and investors have squirreled away. https://www.investopedia.com/terms/g/gdp.asp https://www.investopedia.com/terms/i/indicator.asp https://www.moneycrashers.com/how-good-is-your-retirement-plan/ Asian Journal of Economics and Empirical Research, 2018, 5(2): 201-208 206 © 2018 by the authors; licensee Asian Online Journal Publishing Group Table-3. Other economic indicators among Pakistan, India, Bangladesh, 2005-2015 Minimum average daily wage rate 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Pakistan 37.90 37.40 37.59 36.20 37 36.40 37.59 337.90 37.59 38.09 38.70 India 15.69 15.30 16.60 17.70 17.29 18.20 20.10 20.10 19.70 19.60 19.70 Bangladesh 31.79 33.23 34.70 36 36.79 37.5 38.79 40.09 41.09 42.09 43.40 Consumer Prices Index 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Pakistan 55.31 59.69 64.23 77.26 87.81 100 111.91 122.75 132.19 141.70 145.30 India 65.82 69.87 74.32 80.35 89.28 100 108.85 118.99 131.97 140.75 147.65 Bangladesh 69.15 73.83 80.55 87.72 92.48 100 110.70 117.58 126.44 135.28 143.66 Wage and salaried workers, total (% of total employment) Source: World Bank Moreover, the variable, purchasing power parity of the country of origin (PPP), was hypothesized to be positively related to migration outcomes, this study showed no significance in their correlation. In other words, the study showed no relation to the objective economic differences of a student‘s country of origin and their choice of residence after graduation. Great value lies in this finding. It serves to correct assumptions about any particular student‘s migration outcome. Figure-2. An Inflation rate of the three countries in percentage Source: Federal Reserve Economic Data. Source: World Bank 4. Result and Discussion In this study, statistical analyses were performed using SPSS version 18.0, employing probit-logit regression. For all analysis, probability values below 0.05 were considered statistically significant. Probit-logit regression was performed to estimate which concerned variables may be related to the likelihood of foreign students ‗financial aid, employment, better education facilities, comparative lower taxes, in Table 5. International students are vital to supporting China‘s innovation, bringing new opportunities, perspectives to our classrooms, and creating new connections between the global workforces. a large number of survey questioners were disturbed among the students from Pakistan, India, and Bangladesh studying in Chinese universities. The students were asked about the causes of migration. Their responses showed (see Table 4). The mean score of employment is 3.35 while the standard deviation is 0.751. the mean score of high wage 3.42 while the standard deviation is 0.776. this indicating the mean is around the coefficient of high wage factor. The mean score of political and high consumer prices index are 3.65 and 3.41 while the standard deviation is 0.773 and 0.765. the average score mean of lower taxes and cultural factors are 3.35 and 3.31 while standard of deviation 0.761 and 0.752. Finally, the mean score of economic stability and religious intolerance are 3.30 and 3.43 while the standard deviation is 0.856 and 0.574. all the variables are equally important for international students to move abroad. Table-4. Mean scores of international students‘ migration by economic factors. Mean Std Dev. Employment opportunity 3.35 0.751 High wages 3.42 0.776 Political stability 3.65 0.773 High consumer price index 3.41 0.765 Lower taxes 3.35 0.761 Cultural 3.31 0.752 Economic stability 3.30 0.856 Religious intolerance 3.43 0.574 This study is empirical in nature and the results were based on an assessment of the respondents. For this purpose, a questionnaire was designed using a modified SERVQUAL model to measure the service quality of business schools in the public sector and how the quality of services will help to gain student satisfaction. Questionnaire for this study was comprised of 45 questions, which are further subdivided into 6 constructs out of which; 5 constructs used to measure service quality and the 6th constructs used to measure the student satisfaction about the overall service quality of the business school. These constructs are tangibles (20 items), reputation (12 Asian Journal of Economics and Empirical Research, 2018, 5(2): 201-208 207 © 2018 by the authors; licensee Asian Online Journal Publishing Group items), cooperation and support (8 items), reliability (8 items) responsiveness (6 items) and student satisfaction (5 items). The responses were measured on a five-point Likert scale (Farquharson et al., 2019) for strongly satisfied and Akulavicius and Grundey (2011) for strongly dissatisfied. The population of this study comprises all student studying graduate and undergraduate level in 4 public sector universities in the city Lahore. Personal efforts were made to collect the data. This city is also known as a hub of educational institutions. A total of 550 questionnaires were distributed among students and a total 798 questionnaire were selected for the analysis and the remaining 49 questionnaires were rejected due to incomplete response. Therefore, it represents a very good rate of 91% of the total population. The data was entered into SPSS 16.0 and Amos 16.0 was used to develop a structural equation model to draw inferences. Reliability of the data was checked using Cronbach Alpha which provides a value of 0.956 is more than the. Table-5. The Ordered Logit and Ordered-Probit model. Overall satisfaction Ordered Logit Ordered Probit Coef. Robust S.E Z P > |z| Coef. Robust S.E Z P > |z| Financial Aid 0.4221185 0.1457244 2.90 0.004*** 0.2659591 0.0822039 3.24 0.001*** Employment opportunity 0.7057732 0.1541789 4.58 0.000*** 0.4152735 0.0830044 5.00 0.000*** High Salaries 0.2526937 0.1443204 1.75 0.080** 0.1216005 0.0808547 1.50 0.073** 0.1040839 0.1470028 0.71 0.479 0.0848014 0.0838407 1.01 0.312 Exploring new culture 0.2242361 0.1206783 1.86 0.063 ** 0.0950729 0.0671435 1.42 0.077** Mutually benefited 0.2586725 0.1206783 1.60 0.109 0.1380521 0.0870535 1.59 0.113 Promoting prosperity and development 0.3735674 0.1505924 2.48 0.013** 0.2217842 0.0831047 2.67 0.008*** Bring economic stability 0.2773888 0.1292438 2.15 0.032*** 0.1374364 0.07202 1.91 0.056*** Log likelihood Number of Obs. Walid Chi2(8) Prob > Chi 2 -332.08617 359 144.48 0.0000 Log likelihood Numb of Obs. Walid Chi2(8) Prob > Chi2 -332.88523 359 142.88 0.0000 Pseudo R2 0.1787 Pseudo 0.1767 Significance level at 1%, 5%, 10%, *, ***, *** The results indicating that international students who are studying in China are significantly satisfied by the Built and Road initiative which was first proposed by Chinese President Xi Jinping in 2013. International students who are studying in China under the Built and Road initiative β = 0.433 while the P > 0.004 which is quite statistically significant. The variable employment opportunity under Built and Road initiative the β value is 0.705 while the P value is 0.00 which is indicating strongly statistically significant. The students were asked whether the Built and Road initiative is helpful for those nations who are less developed the response was β = 0.252 while the P value is 0.08 which is statistically significant. The final model showed international student migration to foreign countries and its related economic factors. Employment opportunities, high wages, and economic stability are the key and important factors for international students. different statistical tools and methods were applied to obtain the outcomes. In the first model, the significance values are quite close to each other. All the values are statistically significant and correlated with each other. Hence the students have shown their migration decision are associated with economic reasons in the most cases, such as bigger salary expectations and the higher opportunities to get a better job 5. Conclusion The result showed the economic factors are the most important reasons in the case of academic student migration. The result also described that unemployment, wage are common reasons among these three nations Pakistan, India and, Bangladesh. More Indian and Bangladeshi students are attracted by higher consumer price index (Table. 4). The result also indicated the lower wage rate also common in Pakistani, Indian and Bangladeshi students. The study has re-examined previous researches and its results have shown the economic factors are the most important reasons in the case of academic migration for both studied groups of students. Looking at these results we could conclude that perhaps most importantly, emigration should not be seen as a substitute for job creation at home. If students would have appropriate employment as a better possibility to get a job and bigger salary at home, most, people as well as, students would prefer to remain in their own country. These results are scientifically very important due to the evidence of previous research (Faggian and McCann, 2006; Ciarniene and Kumpikaite, 2011). The influencing of demand-pull factors in the destination place that encouraging international students to migrate across countries. Growing international student migration and competition are also important for international institutions and governments are also benefits because of international migration involve. These results are important for scientific due to the confirmation of previous researches about influences – demand-pull factors in the destination area that encourage the undergraduate students to migrate across countries. It is also important for scholars as a result of showing growing international competition and mobility and for the governments and international institutions because the benefits of international migration involve. These results are important for scientific due to the confirmation of previous researches (Mixon, 1992; Faggian and McCann, 2006; Ciarniene and Kumpikaite, 2011) about influences – demand-pull factors in the destination area that encourage the undergraduate students to migrate across countries. It is also important for scholars as a result showing growing international competition and mobility and for the governments and international institutions because the benefits of international migration involve. The results, however, were useful in designing the future research and for the comparison with other studies. These results—in demonstrating what factors were and were Asian Journal of Economics and Empirical Research, 2018, 5(2): 201-208 208 © 2018 by the authors; licensee Asian Online Journal Publishing Group not related to location upon graduation—provide relevant information for the institution to clearly communicate to its constituency and administration as to the correlated factors associated with the migration behavior of foreign students and tomorrow‘s international leaders. In addition, if an educational institution has a special initiative for international exchange and reciprocation, this study offers strategic information on capitalizing on achieving desired outcomes. Fawcett (1985) determined as migration involves ―individual behavior with respect to movement across space,‖ the present research discussed migration for international study in particular. International migration is a complex engagement of personal motivations, economic prospects, geopolitical factors, and cultural transitions. In that process, this study offers important data adding to the current lack of research. Foreign student migration, with its impact both on the host and home country as well as on the individual lives of migrants, is an area worthy of continued research. 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