Effecting of loan amount on farm households income in tan chau district tay ninh province

UNNERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS VIETNAM- THE NETHERLANDS PROJECT FOR M.A ON DEVELOPMENT ECONOMICS EFFECTING OF LOAN AMOUNT ON FARM HOUSEHOLDS INCOME IN TAN CHAD DISTRICT TAY NINH PROVINCE A thesis submitted in partial fulfillment of the requirements for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS BY DANG NGOC QUY ' BQ GIAO DI)C VA eAo TAO '~ Academic Supervisor: TRLIClNG 9H KINH TE TP.HCM, THtf VItN Dr LE KHUONG NINH ~ 1b rs-G Ho Chi Minh City, June 2007 CERTIFICATION "I certify that the substance of thesis has not already been submitted for any degree and is not being currently submitted for any degree I certify that, to the best of my knowledge, and help received in preparing this thesis, and all sources used, have been acknowledged in this thesis" Signature Dang Ngoc Quy Date: June 2007 ACKNOWLEDGMENT This thesis would not have been finished without the helps and supports of numerous individuals and institutions Therefore, I would express my sincerest gratitude to them Firstly, I would like to thank my academic supervisor, Dr Le Khuong Ninh He spent a lot of time on my thesis His ideas and comments make my thesis become more concise, more clearly I sincerely thank Dr Nguyen Hoang Bao, Mr Truong Dang Thuy They have helped me to orient for the topic and to collect books from the beginning until finishing of the thesis I would like to thank all lecturers and staffs of the project who have helped me anyway to improve my knowledge They have settled my foundations on development economics and international standard research methodology I would like to thank all my classmates and my colleagues for their helps, encouragement and cooperation during my learning and studying time Last, but not least, I would like to devote sincere gratitude to my family They has encouraged and helped me from the beginning until finishing of the thesis ii ABSTRACT The farm households need credit to buy production inputs such as land, fertilizers, insecticides and seeds, etc If the farm households lack of credit and insufficient funds to buy the production of input results in unattainable profitmaximizing quantity of inputs Therefore, credit is essential for farm households' productivities Due to the limited access to credit that creates a bad consequence for poor farm households Hence, credit is one of the tools that can solve this problem for farm household Therefore, this study aims at studying the effect of loan size on income of farm households who are facing credit constraint in Tan Chau district, Tay Ninh province Data used in this thesis is collected from a survey in Tan Chau district, Tay Ninh province iii TABLE OF CONTENTS CHAPTER 1: INTRODUCTION 1.1 Problem Statement 1.2 Research question 1.2.1 Research main question 1.2.2 Research sub-question •.• • .3 1.3 Objectives of the thesis 1.3.1 General objectives •• • .• •• 1.3.2 Specific objectives .•• ••• •• • • •• 1.4 Research hypotheses 1.5 Structure of the thesis CHAPTER 2: LITERATURE REVIEW 2.1 Definitions 2.1.1 Farm households .•• • • • .•• • •• .•.••• 2.1.2 Conditional loan •• • •.• 2.1.3 Subject loan •• • •• .• .• • • •.6 2.1.4 Credit rationing • • •.•• .• .• .•• ••.• .6 2.1.5 Access to credit •• • .• .•• •6 2.1.6 Formal and informal financial • • •• ••• 2.2 Theoretical backgrounds 2.2.1 Producer problem 2.2.2 Consumer problem •• • •.•• • •• •• 2.2.3 Worker problem .• • .• ••• 2.2.4 Household model •• .• •.• .•• • 10 2.2.5 Household model with credit constraint ll 2.2.6 Household model credit constraint (Gershon Feder Lawrence J Lau Justin Y Lin and Xiaopeng Luo, (1990),) 13 2.2.6.1 Definition of initial endowments 13 2.2.6.2 Production •• •••• • ~ • .•• •• •• 13 2.2.6.3 The Utility function • ••.• .••• • • •• •• ••.• •• •.• 14 2.2.6.4 Second period consumption and capital 14 2.2.6.5 The Budget constraint 15 iv 2.3 Empirical studies 17 2.3.1 Empirical study of Gershon Feder Lawrence J Lau Justin Y Lin and Xiaopeng Luo, (1990) 17 2.3.2 Empirical study of Heidhues (2002) •• .•• •• .• 19 2.3.3 Empirical study of Pham Bao Duong and Yoichi Izumida (University of Tokyo, Japan) • • • 21 2.4 Chapter conclusion 23 CHAPTER 3: METHODOLOGY 25 3.1 The Econometric Design 25 3.2 The Conceptual Design 26 3.2.1 Dependent Variable (Income ) • • • • •• • 26 3.2.2 Independent variable • 26 3.3 Data collection method 29 3.4 The sampling method 30 3.5 Summary this chapter 32 CHAPTER 4: MODEL SPECIFICATION, EMPIRICAL RESULTS AND INTERPRETATION 34 4.1 Overview of Tan Chao District 34 4.1.1 Geographical location and population .• • • •• 34 4.2 The Rural Credit in Tan Chao district 36 4.2.1 The Financial Institution 36 4.2.1.1 The Vietnam Bank for Agriculture and Rural Development (VBARD) 36 4.2.1.2 The Vietnam bank for poor (VBP) • 37 4.2.1.3 Commercial bank (CB) 37 4.2.1.4 People Credit Fund (PCFs) 37 4.2.1.5 Moneylenders 38 4.2.1.6 Storekeepers 38 4.2.1.7 Relatives and Friends .• .• 38 4.2.1.8 Rotating savings and credit associations (ROSCA) • •.• 39 v 4.3 Empirical Results and Interpretation 39 4.3.2 Descriptive statistic analysis •• .•• •• • • 42 4.3.2.1 Farm income and non-farm income of farm households • • • 43 4.3.2.2 Income-loan size of farm households • • • • 44 4.3.3 Econometric analysis S3 4.4 Summary this chapter 58 CHAPTER 5: CONCLUSION AND POLICY IMPLICATIONS 60 5.1 Conclusion 60 5.2 Policy implications 62 vi LIST OF TABLE Table 3.1 Variable summary 29 Table 3.2 Distribution of population in six communities in Tan Chau district 30 Table 3.3 Calculating distribution of population in six communes in Tan Chau district 32 Table 4.1 Distribution of population 35 Table 4.2 Distribution of sample in various regions in Tan Chau district 40 Table 4.3 descriptive statistics of continuous variables for the sample 42 Table 4.4 descriptive statistics of income of farm households 43 Table 4.5 descriptive statistics of income -loan size of farm households 44 Table 4.6 Distribution of households borrow from formal and informal sector 44 Table 4.7 Loan size of households from formal and informal credit and needing credit 46 Table 4.8 loan size of households borrowed from formal credit 47 Table 4.9loan size of households from informal credit 48 Table 4.1 Oa purposes of households using loan 49 Table 4.1 Ob purposes of households using loan 49 Table 4.1 Oc income-loan size purpose of households 50 Table 4.11 Distribution of average borrowing costs and interest rate 51 Table 4.12 Distribution of average recipient of loan and repayment duration 52 vii ABBREVIATIONS CB Commercial Bank GSO General Statistic Office m2 meter square OLS Ordinary Least Square PCFs People's Credit Funds ROSCA Rotating Savings and Credit Associations VBARD Bank for Agriculture and Rural Development VBP Vietnam Bank for Poor VLSS Vietnam Living Standards Survey VND Vietnamese dong % Percent viii CHAPTER 1: INTRODUCTION 1.1 Problem Statement In Vietnam, there are two credit institutional systems in co-existence, formal and informal credits The formal credit refer to this paper are the Bank for Agriculture and Rural Development (VBARD), Vietnam Bank for the Poor (VBP), commercial bank (CB) and People's Credit Funds (PCFs) This system provides credit for poor farm households with favor interest rate While the informal sector include rotating savings and credit associations (ROSCAs), moneylenders, storekeepers, relatives, neighbors and friends This system provides credit for farm households with a higher interest rate compare to formal credit However, the probability of access to formal credit is limited According to the 2004 Vietnam Living Standards Survey (VLSS), there are only 30 % of total loans of households were received from formal credit while informal credit provided about 70% This limitation may be due to the unavailable assets for collateral or might be the lack of knowledge of loaning procedures Vietnam is an agrarian nation where 75% of the population settles in the countryside and about 70% of labor force has fieldwork Most of the population of Vietnam concentrates in farm area where they struggle for their daily needs They need credit to buy production inputs such as land, fertilizers, insecticides and seeds As a result, credit is essential for poor farm households for productivity However, due to the limited access to credit, input factor must be necessary for farm households at the beginning of crops Consequently, credit constraint limits the optimum production or consumption choices of farm households along the line suggested by Sadoulet & de Janvry, 1995, Chapter 6, pp 149-150 REFERENCE Adams, Dale W (1995) From Agricultural Credit to Rural Finance Quarterly Journal of International Agriculture 34, no 2: 109-20 Adams, Dale W, H Y Chen, and M B Lamberte (1993) Differences in uses of rural financial markets in Taiwan and the Philippines World Development 21, no 4: 555-63 Adams, Dale W, H Douglas, JD Graham and V Pishchke (1984) (editors) Undermining Rural Development with cheap credit London: Westview Press: pp 61-64 Adams, Dale W (1980) Recent Performance of Rural Financial Markets in John Howell (ed) (1980) Borrowers and Lenders: Rural financial markets and Institutions in Developing countries London: Oversea Development Institute pp 15-33 Atieno, Rosemary 2001 Formal and informal institutions' lending policies and access to credit by small-scale enterprises in Kenya: an empirical assessment African Economic research Consortium (AERC) Ed The Regal Press Kenya http://www.aercafrica.org/credentials/rp111.pdf Balisacan, A M 2001 Pathways of poverty reduction, rural development and transmission mechanisms in the Philippines Philippines: Asian Development Bank (ADB).http:www.eldis.org Diagne, D.A (1999) Determinant of Household Access to and Participaton in Formal and Informal Credit market in Malawi, FCND Working paper No 37 Washington D.c: Food Consumption and Nutrition Division Donald, G (1976) Credit for Small Farmers in Developing Countries, Westview Express D6 T N (2006) Tin Dr,mg Ngan Hang DO'i Vdi Kinh Te' Hq iJ Vift Nam: pp 48-58 Frankfort-nachmias and Nachmias (1996) Research Methods in the Social Sciences New York: St Martin's press, 51h edition Floro, S.L and P.A Yotopoulos (1991) Informal Credit Markets and the New Institutional Economics: The Case of Philippine Agriculture Boulder: Westview Press Pp 7-20 Gershon Feder Lawrence J Lau Justin Y Lin and Xiaopeng Luo, (1990) "Credit's Effect on Productivity in Chinese Agriculture a Microeconomic Model of Disequilibrium" Gujarati, D.N (1995)"Basis Econometrics" Singapore: McGraw-Hill, Inc Heidhues (2002) Financial Markets under Transformation: A Study of Credit Supply and Demand in Romania's Private Farm Sector 65 Le N H (2002) An Analysis of Access to Formal Credit by Household Farms: The Case of Vietnam Master of Arts in Economics of Development, VietnamNetherlands Project, Ho Chi Minh City Ledgerwood, J (1999) Suitable Banking With the Poor - Microfinance Handbook: An Institutional and Financial Perspective Washington, D.C: World Bank Meyer, L.R and Nagarajan, G (2000), Rural Financial Market in Asia: Policy, Paradigms, and Performance: Published for Asean Development Bank by Oxford University Press: pp 26-65 Moll, H.A.J (Ed) (2000) Banks in Rural Financial Market (D120-229), Wageningen: university Press Nguyen V N (2003) Effects of the Value of Assets on Farming Households' Access to Credit in Rural Vietnam: The Case of Chauthanh A District, Cantho Province Master of Arts in Economics of Development, Vietnam-Netherlands Project, Ho Chi Minh City Nguyen, M.H (2001) Effect of Farmer's Education on Household's Access to Formal Credit: A Case of Vietnam Rural Master of Arts in Economics of Development, Vietnam-Netherlands Project, Ho Chi Minh City Nguyen, T.T.H.(1996) The Rural Financial System in Vietnam: An Assessment of Microfinance Policy and Credit Based Programmes for the Poor Master of Arts in Economics of Development, Vietnam-Netherlands Project, Ha Noi Nguyen, T.T.H (2002) An Analysis of Informal versus Formal Microfinance Activities of the Rural poor in Vietnam Master of Arts in Economics of Development, Vietnam-Netherlands Project, Ha Noi Nguyen, T.P.(2000) The Determinants of Moneylender Interest Rates in Rural Vietnam, Master of Arts in Economics of Development, Vietnam-Netherlands Project, Ho Chi Minh City Padmanabhan, K.P (1998) Rural credit: Lesson for Rural Bankers and Policy London: Intermediate Technology Publication Ltd: pp 25 Pham and Yoichi Izumida, (2002) Rural Development Finance in Vietnam: A Micro econometric Analysis of Household Survey "The Impact of Credit on Household production" Ramu Ramanathan (2002) "Introductory econometrics with application" Chapter 8, pp 347-357 Ray, Debra (1998) Development Economics New Jersey: Princeton University Press Stiglitz, J.E and A Weiss (1981) Credit Rationing in Markets With Imperfect Information, American Economic Review, Vol.71, no pp 393-410 66 Stiglitz, J.E and K hoff (1993) Imperfect information and Rural Credit Markets: Puzzles and Policy Perspective' in K.Hoff, A Braverman and J.E.Stiglitz (1993) The Economics of Rural Organization: Theory, Practice and Policy Oxford University Press, pp 33-35 Si'l Ke' Hot;tch Va Ddu Tu (2005) Tay Ninh Tiim Nang Va Cd Hqi Ddu Tu: pp 10-23 Tran, V.D (2002) Determinant Factors of the Repayment Rate of Formal Credit for People Under the Nation Income Poverty Line: A Case Study of Ninh Thuan Province in Vietnam Master of Arts in Economics of Development, VietnamNetherlands Project, Ho Chi Minh City Sadoulet & de Janvry (1995) Chapter 6, pp 149-150 Tt;tp Chi Ngan Hang, Ngan Hang Nha Nude Vi?t Nam so' thdng 412006 pp 7-13 Von Pischke, J.D (1980) The Political Economy of Specialized Farm Credit Institution in J.Howell Borrowers and Lenders, Oversea Development Institution pp 81-104 Von Pischke, J.D (1983) A Penny Saved: Kenya's Cooperative Savings Scheme in J.D Von Pischhke, D W Adams and G Donald Rural Credit Market in Developing Countries Their Use and Abuse, John Hopkins University Press: pp 302-307 67 QUESTIONAIRE ABOUT RURAL CREDIT Appendix Part I Information about household Information about household Name of farm household head: Date of interviewer: Hamlet commune: Code Job Number of households Number of working in agricultural Numbers have income Gender Age Education (chool year) (1) (2) (3) (4) (5) (6) (7) (8) farmer D staff D other MaleD FemaleD Part II Information about Land Information about Land Land title a Cultivation b Garden of land c Dwelling land d Other Have or no Have (1) Yes D Yes D NoD Yes D Yes D Hectare (10.000m2) (2) Have "red" certification or not (3) NoD NoD Yes D Yes D NoD NoD Yes D Yes D NoD NoD NoD Total Part Ill Information about Credit 68 A Formal Credit Source Loan From (a), (b), (c), (d), (e) (1) a VBARD Yes D NoD Last loan to now (months) (2) Received amount (1000) (3) Repayment Duration (Months) (4) Debt (1000) (5) Interest rate (%) (6) Applied day to received Your house (Days) to lender's office (7) (km) (8) By meant(9) How long for a tour (minute) (10) motorbikeD Taking loan procedure Yourself D Other D Housing D Red D WageD other D Yourself D Other D Housing D Red D WageD other D Yourself D Other D Housing D Red D WageD other D Yourself D Other D Housing D Red D WageD other D Yourself D Other D Housing D Red D WageD other D Yourself D Other D Housing D Red D WageD otl@D walkingD Yes D NoD motorbikeD walkingD bicycleD otherD c.CB Yes D No D motorbikeD walkingD bicycleD otherD d PCFs Yes D No D motorbikeD walkingD bicycleD otherD e Project and programs f other YesD NoD motorbikeD walkingD bicycleD otherD Yes D No D motorbikeD walkingD bicycleD otherD (12) (11) bicycleD otherD b VBP collateral Has your family borrowed money from formal credit (Banks, cooperatives, people credit funds ) Yes o No o (If yes, continuing; If No move to part B) How much is estimated cost of lending per one taking loan? Information about asked loan purpose and loan use? purpose Aims in application Amount (l.OOOVND) (2) (1) a Production b Breeding c Business d consumption e Construction f Other Yes Yes Yes Yes Yes Yes o o o o o o No No No No No No o o o o o o B Informal Credit Has your family borrowed money from informal credit (Moneylenders, Storekeepers, Relatives, Friends, ROSCA) Yes o No o (If Yes, continuing ; If No move to part C) 70 Source Loan From (a), (b), (c), (d), (e) (1) Last loan to now (months ) Received amount (1000) (3) Repayment Debt Duration (Months) (1000) (5) Interest rate(%) (6) (4) (Days) (7) (2) a Moneyle nders Applied day to received Your house By meant(9) to lender's office How long for a tour (minute) (10) Taking loan procedure collateral (12) (11) (km) (8) Yes D NoD motorbikeD Yourself D Other D Housing D Red D other D Yourself D Other D Housing D Red D other D walkingD bicycleD otherD b Storekee pers Yes D NoD motorbikeD walkingD bicycleD otherD c ROSCA d Relativ e e other Yes D NoD If (a), (b) continuing If (c), (d), (e) go to (4) Stopping Yes D NoD Yes D NoD 71 How much is estimated cost of lending per one taking loan? Information about asked loan purpose and loan use? purpose a Production Aims in application (1) Yes D NoD b Breeding Yes D NoD Yes D No D Yes D No D c Business d consumption e Construction f Other Amount (l.OOOVND) (2) Yes D No D Yes D NoD C Information about households not borrow Why have not you borrowed from formal and informal credit? Yes D NoD a Not apply because lack of requirement of collateral Yes D NoD b Apply but be refused Yes D NoD c No need of credit Yes D NoD d difficult of procedure loan Yes D NoD e Not loan because can not payment Yes D NoD f Not know institutions that give loan Yes D NoD g Other 10 If the Banks give loan, can you borrow? Yes D NoD (If Yes, continuing; If No Stopping) 11 How much you borrow? 72 12 Information about asked loan purpose and loan use? Aims in application (1) Amount (l.OOOVND) (2) purpose Yes o No o a Production Yes o No o b Breeding Yes o No o c Business Yes o No o d consumption Yes o No o e Construction Yes o No o f Other Part IV Information about Income and Cost of farm households 13 income from cultivation (unit: 1000 VND/year) Cultivation of households (Within 12 months) (a) cassavas (b) Sugar-cane (c) Paddy (d) Fruit-tree (e) others Total Have or Not Hectare (2) Output (Tonlha/year) Price (Kg/VND) (3) (4) Cost (1,000/ yearlha) Rent of land or Not (6) Cost of land (1,000/ha) The year cultivate (8) (7) (5) Yes Yes Yes Yes Yes o o o o o No No No No No o o o o o Yes Yes Yes Yes Yes o o o o o No No No No No o o o o o 73 14 Income from livestock (Unit: IOOOVND/year) Livestock of households (Within 12 months) (a) Buffalos ( b )Bulls HaveorNot (c) pigs Yes o NoD (d) Fowls Yes o NoD (e) Fish Yes o NoD input (lOOOVND/Unit/year) (2) Price of input (lOOOVND/unit/year) Output (lOOOVND/Unit/year) Price of output (lOOOVND/unit/year) (3) (4) (5) Cost (l,OOOVND/ unit/year (6) Yes o NoD Yes o NoD Total 15 income from Working (Unit: lOOOVND/year) Numbers of households (Within 12 months) Wages or Part time a Husband or wife Yes o NoD b Sons Yes o NoD c Girls Yes o NoD Numbers of households (numbers) (2) Wages Part time (lOOOVND/ (lOOOVND/ month) (3) month) (4) Number of months working( number) (5) Other income (lOOOVND/ month) (6) Total 74 Appendix2 Test Econometric Model Unrestricted model Table Appendix2.1 Dependent Variable: INCOME Method: Least Squares Date: 06/15/07 Time: 13:27 Sample: 178 Included obseNations: 178 Variable Coefficient Std Error t-Statistic Pro b c -19642.95 0.425488 236.7936 85.11545 -0.134631 1536.104 9504.930 5552.032 6979.666 0.097730 118.9666 384.0632 0.086780 1140.120 850.3687 7277.058 -2.814311 4.353720 1.990421 0.221618 -1.551406 1.347319 11.17742 0.762950 0.0055 0.0000 0.0481 0.8249 0.1227 0.1797 0.0000 0.4466 LOAN SIZE AGE EDU FACTOR LABOR LAND RATIO R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood Durbin-Watson stat 0.748747 0.738402 14807.97 3.73E+10 -1957.798 1.558435 Mean dependent var S.D.dependentvar Akaike info criterion Schwarz criterion F-statistic Prob{F-statistic} 25645.95 28951.96 22.08762 22.23062 72.37285 0.000000 Source: Author's calculation based on survey data Firstly, in order to estimate the reliability of the regression results, it is to test the problems of individual partial regression coefficients (T -test) From the results of the unrestricted model, we found that five out of seven regression coefficients are statistically significant The coefficients of debt and land are significant at percent while the coefficients of factor, labor are significant at 10 percent and the coefficient of age at percent However, education and ratio are not statistically significant So the model can be omitted the, education and ratio variable Therefore, we run the restricted model Restricted model regression INCOME= a + a 1LOANSIZE + a AGE + a FACTOR + a LABOR + a LAND 75 Table Appendix2.2 Dependent Variable: INCOME Method: Least Squares Date: 06/15/07 Time: 13:29 Sample: 178 Included observations: 178 Variable Coefficient Std Error t-Statistic Pro b c -16140.14 0.427940 223.3021 -0.135888 1619.319 9562.663 5445.354 0.097257 117.2428 0.086420 1119.828 829.1894 -2.964021 4.400077 1.904613 -1.572406 1.446042 11.53254 0.0035 0.0000 0.0585 0.1177 0.1500 0.0000 LOAN SIZE AGE FACTOR LABOR LAND R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood Durbin-Watson stat 0.747784 0.740452 14749.83 3.74E+10 -1958.139 1.596247 Mean dependent var S.D.dependentvar Akaike info criterion Schwarz criterion F-statistic 25645.95 28951.96 22.06898 22.17623 101.9908 0.000000 Prob(F-statistic~ Source: Author's calculation based on survey data Use F-test to choice model Hypothesis H : a = a = (Use restricted model) Hypothesis H : At least a or a F= RSSR -RSSu RSSu * (Use unrestricted model) * n -k-1 = 3.74-3.73 * 178-7-1 = O.IS m 3.73 Calculate Critical use Excel =Finv (0.05, 3,170) = 2.65 F < Critical: Maintain Ho - use restricted model The equation of linear model Estimation Command: ===================== LS INCOME C LOANSIZE AGE FACTOR LABOR LAND Estimation Equation: ===================== INCOME= C(1) + C(2)*LOANSIZE + C(3)*AGE + C(4)*FACTOR + C(S)*LABOR + C{6)*LAND Substituted Coefficients: ===================== INCOME= -16140.14414 + 0.4279397841*LOANSIZE + 223.3020908*AGE0.1358876474*FACTOR + 1619.319172*LABOR + 9562.662916*LAND The third, we test the overall significant of the sample regression or the F test is done with the hypothesis that (Gujarati, 1995) as follows: 76 H0 : All slopes of coefficients are simultaneously zero (null hypothesis that means H 1: Not all slopes of coefficients are simultaneously zero (it means From the results on table Appendix2.2, we show that the F-statistic is larger (equals to 101.99) and the probability ofF-statistic equals to 0.0000, hence the Ha is rejected This leaded to not all slope of coefficients are simultaneously zero The third, the data of model is cross-section data, so we need test for multicollinearity and heteroscedasticity Test for multicollinearity (VIP) From the results on table Appendix2.2, we show that lower R2 and partial coefficients had statistic significant at 1% and 10% Variance -Inflation Factor (VIF) is used to test the problem of multicollinearity (Gujarati, 1995) VIF = - (1 - rif) All computed VIF is smaller than 10, and it means that there is no multicollinearity arising in the model 77 VIF Variables Loan size 1.47 Age 1.03 Factor 1.69 Labor 1.01 Land 1.42 Mean VIF 6.62 1NIF 0.68 0.97 0.59 0.99 0.7 Test for heteroscedasticity: Run regression (regression result from table appendix2.2) and calculate the residual Genr residual = resid Genr residual2 = resid"2 Genr absresidual= abs (residual) Regression the residual variables on the independent variables Briusch-Pagan test RESIDUAI2 = a +a1LOANSIZE+a2 AGE+a4 FACTOR+a5 LABOR+a6 LAND RESIDUAL2 = 42165584.32 + 3717.386296*LOANSIZE- 1215797.259*AGE4344.273668*FACTOR- 18200596.7*LABOR + 137673668.2*LAND R = 0.058 nR = 178*0.058 = 10.324 < z (0.05,5) = 11.07 There is no heteroscedasticity in model Glejser test ABSRESIDUAL =7517547.548 + 6276.681076*LOANSIZE + 873558.2041 *AGE - 5186.430217*FACTOR- 23864033.21 *LABOR+ 111093088.2*LAND R2 = 0.062 nR2 = 178*0.062 = 11.036 < z (0.05,5) = 11.07 There is no heteroscedasticity in model 78 I~ - 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