(Luận văn) the relationship between the agricultural trade and productivity in vietnam case

UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES THE HAGUE VIETNAM THE NETHERLANDS t to HO CHI MINH CITY ng hi ep w VIETNAM – NETHERLANDS n lo PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS ad ju y th yi pl n ua al THE RELATIONSHIP BETWEEN n va AGRICULTURAL TRADE AND PRODUCTIVITY ll fu IN VIETNAM CASE oi m at nh z A thesis submitted in partial fulfillment of requirements for degree of Master of z ht vb Arts in Development Economics Academic supervisor n a Lu Dr TRAN TIEN KHAI om l.c gm NGUYEN HOANG DIEP k jm By n va y te re HO CHI MINH CITY, JANUARY 2015 [Type text] ACKNOWLEDGEMENT t to ng hi ep So many persons that I want to say thanks to them I write these acknowledgments to express my gratitude to them who helped me directly and w indirectly to finish this thesis n lo First of all, Dr Tran Tien Khai who is my supervisor, he helped me to ad y th complete my ideas Furthermore, he also gave me advices to writing logical for this ju thesis, and already gave his hands when I needed yi The other person that is Dr Tran Khanh Nam, who gave me advice from pl data set to apply in my thesis n ua al beginning when I wrote the thesis design In addition, he provided me the VARHS va Important to me is to thank the Vietnam-Netherlands program and all of people n ll fu and lecturers who supported and gave me their knowledge oi m Finally yet importantly, with all my respect for my parents who gave me a at nh change to study in this program They have encouraged me to continue my studying z z ht vb k jm om l.c gm n a Lu n va y te re [Type text] ABBREVIATION t to FAOSTAT The Food and Agricultural Organization Corporate ng Statistical Database hi The Vietnam Access to Resources Household Survey TFP The Total Factor Productivity OLS The Ordinary Least Square ep VARHS w n ad Dickey-Fuller Test ju y th DF Gross Domestic Product lo GDP yi pl n ua al n va ll fu oi m at nh z z ht vb k jm om l.c gm n a Lu n va y te re [Type text] ABSTRACT t to This thesis tries to find out whether trade has an effect on agricultural productivity in ng Vietnam case There are two models to estimate relationship between trade and hi ep productivity including national-level model and farm-level model The time series data of nine agricultural commodities, which is taken from FAOSTAT, is used in w national-level model Farm-level model uses cross section data from VARHS 2010 n lo including 1449 farm household in nine provinces In both models, yield refers as ad y th agricultural productivity The both models support for a strong positive relationship ju between trade and yield The result also indicates that the land, irrigation, human yi capital, cost of production might be necessary for improve productivity pl ua al n Key words: Agricultural productivity, international trade, cross-section, time series n va ll fu oi m at nh z z ht vb k jm om l.c gm n a Lu n va y te re [Type text] TABLE OF CONTENT Page t to ACKNOWLEDGEMENT ng ABBREVIATION hi ep ABSTRACT TABLE OF CONTENT w LIST OF TABLE n lo LIST OF FIGURE ad y th Chapter 1: INTRODUCTION Problem statement 1.2 Research objective 10 1.3 Thesis structure 11 ju 1.1 yi pl ua al n Chapter 2: LITERATURE REVIEW 12 va 2.1 Theory .12 n ll fu 2.1.1 Agricultural productivity 12 oi m 2.1.2 Agricultural trade 15 nh 2.2 Empirical study 17 at 2.3 Conceptual framework 19 z z Chapter 3: RESEARCH METHODOLOGY 21 vb ht 3.1 Agricultural productivity measurement 21 jm 3.2 The tradability index 22 k gm 3.3 Empirical model 23 l.c 3.3.1 The national level model 23 om 3.3.2 The farm level model .24 3.5 Analytic method 28 n va 3.5.1 Test for multicollinearity 29 n a Lu 3.4 Data 25 3.5.4 Test for stationary 31 Chapter 4: RESULT AND DISCUSSION 32 y 3.5.3 Test for autocorrelation 30 te re 3.5.2 Test for heteroscedastiscity 30 [Type text] 4.1 Overview Vietnam agricultural trade 32 4.1.1 Agricultural production in Vietnam 32 t to 4.1.2 Land 34 ng 4.1.3 Irrigation 35 hi ep 4.1.4 Fertilizer 35 4.1.5 Farm machinery .36 w 4.1.6 Human capital 36 n lo 4.1.7 Trade .37 Export 37 y th Import 38 ju 4.1.7.2 ad 4.1.7.1 yi 4.2 Econometric result .39 pl ua al 4.2.1 The product tradability index and national level response 39 n 4.2.2 The farm tradability index and farm level response 42 va Chapter 5: CONCLUSION 47 n ll fu 5.1 Conclusion 47 oi m 5.2 Future research 48 nh REFERENCE 49 at APPENDIX 53 z z ht vb k jm om l.c gm n a Lu n va y te re [Type text] LIST OF TABLE Page t to ng hi 27 Table 4.1: Production quantity of selected crops 33 Table 4.2: Annual growth rate of quantity of selected crops 33 Table 4.3: Evolution of crop production value per 33 Table 4.4: Water use in Vietnam in 2005 35 ep Table 3.1: The description of each variable and expected sign w n 36 lo Table 4.5: The mechanization rate in agricultural production activities ad y th Table 4.6: Labor force in Vietnam by resident region in selected years 36 ju (thousand people) yi Table 4.7: Structure of employed population by industrial sector pl 37 ua al 2000-2013 (percentage) 40 n Table 4.8: The ADF test result for yield of nine commodities va Table 4.9: The ADF test result of tradable index of nine commodities 40 n ll fu Table 4.10: Results of national-level analyses (dependent variable = 41 oi m yield per each commodity between 1961-2010) 42 Table 4.12: The correlation among coefficients in farm level model 43 at nh Table 4.11: Summary statistics of variables in farm level model z 43 z Table 4.13: The correlation result of each variable (VIF, TOL=1/VIF) vb ht Table 4.14: Production function result of the farm-level analyses jm (dependent variable = yield of an important crop in a farm) 44 k om l.c gm n a Lu n va y te re [Type text] LIST OF FIGURE Page t to Figure 2.1: The linkage between agricultural productivity and ng hi 20 Figure 4.1: The value of agricultural production 34 Figure 4.2: The land of annual and perennial crops 1990-2012 in Vietnam 34 Figure 4.3: Export value of main agricultural commodities since 1990-2011 38 ep international trade w n lo Figure 4.4: The import value of main agricultural commodities in Vietnam ad 39 Figure 4.5: The relationship between maize yield and tradable index over time 42 ju y th during period 1990-2011 yi pl n ua al n va ll fu oi m at nh z z ht vb k jm om l.c gm n a Lu n va y te re [Type text] Chapter INTRODUCTION t to ng 1.1 Problem statement hi ep Trade helps people, regions, and countries exchange what they have and what they need In food security side, world population might be reach at billion people in w 2050; the question is asked how to meet this great demand of food with limited n lo producers, scare land and water resources The answer is productivity, and open trade ad y th may encourage farmers to increase quantity of agricultural products to meet a ju requirement of food in the world yi The core of role of agriculture can summary in three issues: “raising pl 2009) However, traditional farmers n (Johnson, ua al productivity, providing market, and generating saving for economic diversification” have suspicions about va commercialization process that generate new demand, output or more competition n ll fu An increase agricultural productivity has attracted many economists studying oi m about role of it in development economics in years (Matsuyama, 1992; Machicado et nh al., 2008) In addition, agricultural productivity has an essential role in at industrialization and development economics That means country improves its z z productivity with using less labors in agriculture, and access labors in agriculture vb ht transfer into manufacturing Furthermore, when producers in agriculture sector jm increase their incomes thanks to efficient production, demand for manufacturing k gm increases to meet more demand On the other hand, some argue that agricultural l.c productivity has a negative relationship with industrialization Field (1978) and om Wright (1979) indicate labor force can be a main fight between manufacturing and n va Matsuyama (1991) shows explanation about these conflicting debates may be n productivity, manufacturing has an abundant supply of labor with cheap wage a Lu agriculture sector because of comparative advantage When agriculture has low contribute to economic growth However, in open economy “high productivity and output in the agriculture sector may, without offsetting changes in relative price, y agricultural productivity might make agricultural labors shift to manufacturing and te re relative to opened economy He debates that in closed economy an increase [Type text] squeeze out the manufacturing sector and the economy will de-industrialize over time, and in some case, achieve a lower welfare level.” t to From Doi Moi 1980, Vietnam agriculture has improved from production and ng especially exporting (Nguyen, 1998) Agriculture sector shifts from self-sufficient to hi ep commercialization to supply both domestic and export markets Vietnam became the second biggest rice exporter in the world, and production of coffee, pepper, rubber, w cashew nut, fruit and vegetable have increased in quantity and export value During n lo 1980-1990, agricultural export value increased from 339 US$ million to 2,404 US$ ad y th million, and total value of trade increased 3.89 times Quantity of export rice went ju rapidly up from million tons in 1990 to million tons in 1997 Coffee increased yi from 90,000 tons to 404,000 tons, cashew increased 27,400 tons to 99,000 tons When pl ua al Vietnam joined World Trade Organization (WTO), the agricultural export coffee went n up 1,256,400 tons, and 178,500 tons for cashew nut, respectively These evidences va may support for advantage effects of opening trade in agricultural Vietnam n ll fu Furthermore, the question is asked that how trade affects productivity in individual oi m farm household nh Correspondingly, this study tends to analyze the linkage between agricultural at trade and productivity in Vietnam, contributes to debate above and tries to answer z z whether international trade (import and export) in agricultural commodities is related vb ht to agricultural productivity at national and farm level This paper applies the product jm tradable index measurement to represent international trade In order to analysis of k gm productivity, country and farm level analyses are implemented with time series and l.c Research objective om 1.2 cross-section analysis in Vietnam agricultural productivity in Vietnam Some questions, which this thesis tries to n va answer: whether international trade increases agricultural productivity in Vietnam? n a Lu This thesis concentrates on studying and evaluating effect of trade on agricultural productivity 10 y analysis from overview to detail to understand clearly how trade influences te re In order to answer these questions, this thesis uses two different levels of [Type text] Coffee **-3,938 1,573 *487 249 Note: *, **, *** represent significance at 10%, 5%, and 1% level t to The negative relationship of maize is a consequence of decreasing tradable ng index over period Vietnam has a great demand of maize to supply for feed industry in hi ep hog and poultry feed However, the maize production in Vietnam cannot meet demand and maize has a higher price than in the world Therefore, almost maize in Vietnam is w imported and the negative sign in econometric result is not surprised The import and n lo export quantity of maize is presented in figure 4.7 On the other hand, the productivity ad y th of coffee increase due to increase land, however, farmers lack awareness of effective ju technique to plant coffee Therefore, demand goes down due to a poor quality There yi is a same result for pepper pl ua al Figure 4.7: The import and export quantity of maize commodity in Vietnam during n 1961-2011 va 2000000 n ll fu 1500000 1000000 oi m Import Quantity (tonnes) nh 500000 z z 1961 1967 1973 1979 1985 1991 1997 2003 2009 Export Quantity (tonnes) at ht vb Year k jm Source: FAOSTAT 2014 gm 4.2.2 The farm tradability index and farm-level response l.c At the beginning, the overview of statistical analysis of variable in farm level om model will provide a comprehensive view with table 4.11 involving mean, standard between variables are indicated in table 4.12 It indicates that all independence te re Observations Mean 42 Std Dev Min y Table 4.11: Summary statistics of variables in farm level model Variable n dependence variable (yield) va variables (fti, ir, tland, dm, dsex, l, edu, k) have a positive relationship with n a Lu deviation, and max of each variable Then the relationship and correlation matrix Max [Type text] 0.377 6.959 Farm tradability index 1450 0.312 0.358 0.000 2.048 Irrigation 1450 0.816 0.203 0.007 1.000 Ln_Land 1450 -0.654 1.032 -4.075 2.737 Machinery 1450 0.509 0.500 0.000 1.000 Sex 1450 0.862 0.345 0.000 1.000 1450 1.112 0.475 0.000 2.398 Ln_Education 1449 2.077 0.305 0.000 2.552 Ln_Capital 1450 8.281 1.003 4.489 11.657 ep 0.899 w n Ln_Labor lo ad y th ju Source: Own calculation from VAHRS 2010 data set yi pl Table 4.12: The correlation among variables in farm level model Ln_Capital Ln_Education Ln_Labor Sex ll fu Farm tradable index n va Ln_Yield n ua al oi m at nh z 1.000 0.111 0.002 0.064 0.191 0.046 1.000 0.169 0.136 0.302 -0.009 1.000 0.114 1.000 0.127 0.248 1.000 -0.008 0.042 0.152 -0.098 0.135 0.276 0.081 0.089 z ht vb k jm 1.000 l.c gm 0.038 1.000 om Ln_Yield 1.000 Farm 0.287 1.000 tradable index Irrigation 0.357 0.043 Ln_Land 0.450 0.102 Machinery 0.210 0.139 Sex 0.200 0.038 Ln_Labor 0.407 -0.014 Ln_Educati 0.062 -0.077 on Ln_Capital 0.410 0.452 Source: Own calculation Machinery hi 4.336 Ln_Land ng 1450 Irrigation t to Ln_Yield a Lu According to methodology section, the regression result may be misleading Table 4.13: The correlation result of each variable (VIF, TOL=1/VIF) 43 y problem in this model te re regressor and mean of VIF are lower than 10, therefore the multicollinearity may not a n 4.13 provides the result of VIF of variables in farm level model The VIF of each va regression in stata, VIF is used to detect whether multicollinearity may occur Table n because of multicollinearity among regressors Therefore, after running farm [Type text] Variable VIF 1/VIF t to ng hi 1.39 0.719 Ln_Land 1.15 0.873 Ln_Labor 1.23 0.813 Farm tradable index 1.30 0.771 Machinery 1.11 0.897 1.08 0.927 1.07 0.932 1.04 0.961 ep Ln_Capital w n Sex lo ad Irrigation 1.17 ju Mean VIF y th Ln_Education yi pl Source: Author’s calculation ua al Another test must be considered in cross section analysis that is n heteroscedasticity of error term As mentioned above in methodology, this thesis uses va n the Breusch-Godfrey test to detect an existence of heteroscedasticity The result shows fu ll the value of chi-square obtained 8.78 with statistical significant probability 0.003, m oi hence, the farm level model exists the heteroscedasticity In order to remedy this at nh problem, the “robust” command must be added when running regression The output z of Breusch-Pagan test for heteroscedasticity is presented in appendix B z The main objective of this thesis is to analysis whether the trade affects vb ht agricultural productivity of farming household; hence, the result of econometric jm statistic of farm level model is presented in table The farm level model runs following k gm the OLS regression with 1450 observation in nine provinces that come from VHRS l.c 2010 data set The OLS regression refers yield as dependent variable and estimates the om effect of farm tradable index on crop yield with other independent variables referring relationship with crop yield After robust the regression, table 4.14 reported the result va n of farm-level model y te re Table 4.14: Production function result of the farm-level analyses (dependent variable = yield of an important crop in a farm) Variables n a Lu as control variables in model The result reports that all variables are positive Coefficients Std error 44 [Type text] t to Farm tradable index ***0.237 0.057 Irrigation ***1.362 0.091 Ln_Land ***0.248 0.018 0.043 0.034 Sex ***0.140 0.043 Ln_Labor ***0.409 0.038 0.031 0.052 ***0.295 0.021 0.211 0.218 0.506 0.435 ng Machinery hi ep w n Ln_Education lo ju R-squared y th Constant ad Ln_Capital yi pl Robust standard errors in parentheses *** p