DETERMINANTS OF ACCESSIBILITY TO MICROCREDIT IN TERMS OF FORMAL SECTOR AND INFORMAL SECTOR

UNIVERSITY OF ECONOMICS, HO CHI MINH CITY VIET NAM – NETHERLANDS PROGRAMME FOR M.A PROGRAM IN DEVELOPMENT ECONOMICS DETERMINANTS OF ACCESSIBILITY TO MICROCREDIT IN TERMS OF FORMAL SECTOR AND INFORMAL SECTOR o0o TRAN THI NGOC ANH MAI Academic Supervisor: DR CAO HAO THI Dec – 2014 ABSTRACT Microcredit is an emerging concept helping the poor out of poverty situation This dissertation attempts to investigate the determinants affecting the probability of participation in different types of credit sectors in terms of formal sector and informal sector Using a sample size of 1,522 households participate in credit market from The Vietnam Access to Resources Household Survey (VARHS) 2012, bivariate probit model is employed to explore the determinants of household credit demand due to the binary nature of the dependent variables Various explanatory variables include age, gender, marital_stt, edu, hhsize, income, savingamount, landsize, agriculture_act, network and location that influence probability of accessibility to different sectors of credit Furthermore, relationship between dependent variables is accounted in this research Results reveal that factors affecting formal credit participation are different from factors affecting informal credit participation Additionally, the result indicates that there is negative correlation across two sectors of credit ACKNOWLEDGEMENT I would like to express my deepest thankfulness to my advisor, Dr Cao Hao Thi who spent lots of his precious time to support and guide me throughout this research and continuously led me to the right way I would also like to extend my appreciation to the teachers working on Vietnam Netherlands programme who gave great lectures and invaluable knowledge for us to complete the course I am grateful to my parents and my siblings that always encourage and support me in my study and in every aspect of life I also want to express my gratitude to my friends for sharing with me the difficulties and giving me the ideas, knowledge and materials for the study and for all the time we were at Master in Development Economics 19 LIST OF FIGURES Figure 2.1 Probability of success and expected returns to borrowers Figure 2.2 Return to the bank 11 Figure 3.1 Microfinance Systems in Vietnam 22 Figure 4.1 Process of research 30 Figure 4.2 Participation in credit sector 33 LIST OF TABLES Table 2.1 Definition of Variables 18 Table 3.1 Microfinance Institutions in Vietnam 20 Table 3.2 Comparison between formal and informal lenders 28 Table 4.1 Summary of Participation in different credit sectors 32 Table 4.2 Conditional and Unconditional Credit Participation Probabilities 33 Table 4.3 Summary statistics 34 Table 5.1 Determinants of accessibility to formal and informal credit sector 38 Table 5.2 Marginal effects for conditional probability of formal sector participation 44 Table 5.3 Marginal effects for conditional probability of informal sector participation 46 TABLE OF CONTENTS CHAPTER 1: INTRODUCTION 1.1 Problem statement 1.2 Research objective 1.3 Research questions 1.4 Research Structure CHAPTER 2: LITERATURE REVIEW 2.1 Concept of credit 2.2 Theory of demand for credit 2.3 Credit rationing theory 2.4 Determinants of participation in microcredit programs 11 CHAPTER 3: OVERVIEW OF MICROFINANCE SYSTEM 19 The history of Microfinance 19 3.2 The role of government in microfinance: 21 3.3 Overview of credit market in Vietnam 22 3.3.1 The formal credit market 23 3.3.2 The semi-formal credit market: 26 3.3.3 The informal credit market 26 CHAPTER 4: RESEARCH METHODOLOGY 30 4.1 Research process 30 4.2 The data 31 4.3 Data Analysis Method 35 CHAPTER 5: RESULTS AND DISCUSSION 38 5.1 Estimation of determinants of microcredit participation 38 5.2 Estimation of conditional marginal effects 44 CHAPTER 6: CONCLUSION 48 6.1 Research Findings 48 6.2 Policy implications 49 6.3 Limitations 50 REFERENCES 52 APPENDIX 57 CHAPTER 1: INTRODUCTION 1.1 Problem statement There are about 1.22 billion people (21 percent of population) in the world living on less than $1.25 a day in 2010 (World Bank) Focusing towards poverty reduction and finding ways to improve living condition have taken a lot of attention of public policies in the world The rate of poverty in Vietnam decreases remarkably in recent years According to annual report shown by GSO, the poverty rate declined from 15.5 percent in 2006, to 13.4 percent in 2008, to 10.7 percent in 2010 In a report of GSO in 2010, it also revealed that poverty level in rural area (13.2 percent) is much higher compared to that in urban area (5.1 percent) How to distribute the benefits of economics growth, especially to rural area is one of the challenges remained Therefore, rural economy deserves more attention and support to reduce inequality between rural and urban area According to McCarty (2001) and Pham & Lensink (2002), lack of ability to obtain the fund for the purpose of working capital and investment is one of the reasons among other things that lead to poverty in developing countries Providing a channel to ease the credit constraints for the poor rural household is the primary object in poverty alleviation strategy of developing countries, including Vietnam Farmers need an instrument such as credit to enhance productivity and promote standard of standard of living because of their seasonal activities and uncertainty they are facing (Ololade & Ologunju, 2013) Accessing to microcredit is recognized as a potentially effective tool out of under poverty line situation and improve living standards (ADB, 2000a; Morduch and Haley, 2002; Khandker, 2003) Agricultural credit plays an important role in sustainable achievement in any country in the world Microfinance industry has been known in many decades in developing countries, and its role was further attended with rapid growth worldwide when Mohammad Yunus who pioneered the principle of microfinance and microcredit received Nobel Peace prize in 2006 (Tra Pham and Robert Lensink, 2007) And a variety of previous researches demonstrated the position of microfinance in poverty reduction by focusing on the effect on household welfare The demand for rural credit has increased sharply due to the decollectivization of agriculture launched in Vietnam in the year 1986 Hence, the spread of microfinance with amendment of regulations on banking operation in Vietnam plays an important component in fighting again poverty over the last decades Vietnam has introduced several of microcredit programs via a lot of channels such as banks, credit funds, money lenders and advance input providers to supply credit for a variety of clients Despite the importance of credit to the poor, the poor family that lacks ability to access to adequate financial service leads to the fact that they not have prospects for increasing their productivity and living standard And the fact that commercial banks have no interest in allocating credit to the poor because of their lack of viable collateral Because of these reasons, governments in developing countries have set up credit programs that aim at improving the process of rural household access to formal credit during the past four decades (Diagne, 1999) However, the lending mechanisms as well as the nature of the credit market which are highly regulated by government intervention such as controls of interest rates and credit quota allocation not function well Similarly, Robinson (2001) and Gonzalez Vega (2003) also indicated that most of microfinance institutions have been not sustainable in developing countries Credit subsidized interest rate provided by “Agricultural development banks” which established by commercial banks to extend credit to rural household not considered creditworthy However, majority of these credit programs have failed to reach their targets both to be sustainable credit providers and serve the poor (Adams, Graham, and von Pischke 1984; Adams and Vogel 1986; Braverman and Guasch 1986) Risk management and transaction costs associated with Asymmetric information are the most problematic features facing by lenders and borrowers (Pham & Lensinnk, 2007) It is also well know that different forms of credit market serve different group of borrowers, it is difficult for large number of poor households to access to credit sources Households often face limited access to credit because of rationing of credit demand that leads to the poor and low income households are generally excluded from the formal credit sector (Stiglitz & Weiss, 1981) In fact that formal provider, semi-formal provider and informal provider exist side by side in Vietnamese financial market To deal the level of information asymmetry between borrowers and different lenders, many government microcredit programs are accompanied by the local Peoples Committees in terms of lending process to assist microcredit market operation In respect of this, narrowing gaps in term of whom it serves and the service it provides, improving the efficiency and effectiveness of microfinance system is the main challenge of policy makers as well as program organizers With data collected from The Vietnam Access to Resources Household Survey 2012 (VARHS) which supplements and extends the VHLSS (Vietnam household Living Standards Survey) by repeating surveys of the same household with data from VHLSS and asking more questions about income, expenses, land, agriculture, asset, investment, migration, climate change, social welfare and so on; VARHS received assistance from University of Copenhagen, CIEM, ILSSA (Institute For Labor Science and Social Affair), and IPSARD (Institute of Policy and Strategy for Agricultural and Rural Development), econometrics techniques are employed in this research to explore the factors that affect access to credit in terms of formal credit and informal credit 1.2 Research objective The objective of this thesis is to empirically investigate the determinants that influence on the probability of household accessing to different types of credit sectors as well as the relationship between formal credit participation and informal credit participation at the same time Additionally, marginal effects of each independent variable on the choice of credit source are also shown in this research 1.3 Research questions This research is to answer two central questions: What are determinants affecting the probability of household accessing to different types of credit sector? Is there any evidence of a correlation between participating in formal credit and participating in informal credit at the same time? 1.4 Research Structure This dissertation is organized as follows In chapter one, problem statement and objectives of this research are presented Chapter two provides concepts related to this research, discusses theory for demand credit and credit rationing theory and introduces explanatory variables Chapter three presents the history of microfinance as well as the role of government in microfinance It also provides insight into the structure of credit market in Vietnam Chapter four presents research structure, data description and methodology method used in this research Chapter five gives empirical models and the estimated results Finally, conclusion, policy suggestions and limitations are highlighted in chapter six CHAPTER 2: LITERATURE REVIEW This chapter presents the overview of theory and discusses previous studies relate to the research topic The first part mentions about microcredit regarding concept of credit The second part discusses about theory for demand credit and credit rationing theory The last part discusses about the determinants affecting credit accessibility 2.1 Concept of credit There are several and various definitions regarding the word credit as follows: Credits are referred as loans which permit consuming in the present, in exchange for an agreement to make repayment at sometimes in the future (Pischie et al., 1983) Obtaining credit was considered as the process of controlling over the use of money, goods and services based upon a promise to repay at a future day (Adegeye & Dittoh, 1985) Ololade & Ologunju (2013) defined credit as a mean for temporary transfer of assets to individuals or organizations that has not them from individuals or organizations that has This process required evidences of debt obligation in return for a loan, in the case of transaction between friends or relative which based on good relationship excluded Microcredit which is a component of microfinance provides small loan to the poor for self –employment That generates income, helping them care for themselves and their family (The Microcredit Summit, 1997) To raise income level and improve living standard of semi-urban and urban areas are considered as targets of microcredit by providing of thrift, credit, other financial services and products of every small amount to the rural household (Reserve Bank of India- Master Circular, 2011) CHAPTER 6: CONCLUSION Chapter six presents findings of this research, policy recommendations as well as limitations of the research 6.1 Research Findings Households apply for the loan, but some of them are not included because of accountability to repay loan and insufficient collateral These borrowers turn to informal credit sector as an alternative source of capital at much higher interest rate compared to that form informal credit sector As known, formal credit provider exists in parallel with the informal credit provider but not many researches include both in their investigation Almost of them investigate the determinants of household’s participation in credit sector in terms of formal sector or informal sector separately; therefore, they failed to account for the relationship between two types of credit sector This research differs from most previous findings; it attempt to find out the relationship between the choice of formal credit using and informal credit using This research employs bivariate probit model to exam the factors influencing household accessibility to formal credit sector and informal credit sector as well as relationship between two of them is investigated The results show that the determinants of the use of formal credit sector are different from the determinants of the use of informal credit sector Furthermore, the probability of formal sector participation will be decreased if there is an existence of informal credit sector participation and vice versa Bases on estimated results, seven determinants namely age, edu, hhsize, income, savingamount, landsize and location affect the formal credit participation The estimation indicates that formal lender tend to provide credit to household who are better off with collateral requirement such as land size or saving amount 48 6.2 Policy implications Based on the research results, in order to improve the smooth of microfinance system operation, some policies are suggested: Firstly, network of commercial bank should be expanded at village level Additionally, administrative process for lending should be more simplified Accessing credit source is necessary for the poor improving living standard Providing credit from formal sector for the poor is very important However, it is very difficult for the poor living in Vietnamese rural areas to approach credit provided by formal institutions Therefore, developing a banking system in rural areas to reduce the gap between the poor and the bank is crucial issue Additionally, simplifying administrative process to help the poor borrowing money promptly and timely is necessary As research result indicated, education level is statistically significant factor of formal credit sector; therefore, complicated process leads to imperfects in choosing credit source of poor household which have low level of education Secondly, criteria for lending assessment process should reflect the primary target of microfinance system, not depend on the confidence the lender has Credit providers should base on household’s characteristics demonstrating that household is the poor instead of depending on collateral such as saving amount or the size of the land that household has Actually, household with large saving amount or land size have more capital and have means for livelihood compared to household not have that Thirdly, implementing interest rate policies in rural areas which are in accordance with market capitalism gradually abandon preferential interest rates Recently, VBSP acts as the loan provider delivering Government fund to the poor at preferential interest rates However, preferential interest rates lead to consequences which are different from primary targets of the fund establishment Firstly, it is 49 difficult for the poor to get loan because credit officers face high default risk when they loan for the poor In this case, banks usually have incentive to lend out the fund for the households which have collaterals such as saving amount or landsize because of two sides benefits Secondly, low interest rate lead to use credit in inefficient way Interest rate reflects cost of capital as well as adverse selection reduction Capital will be invested in bad project if the cost of capital is low Fourthly, developing an appropriate management system to manage informal credit source is to promote the positive role of this sector in poverty reduction in rural areas Actually, loans from informal sector represent a significant share in the credit and play important role in the life of the poor; therefore, improving the operation of informal credit sector should be encouraged However, informal credit sector provides loan at sky-high interest rate; especially, in remote area where formal credit source is shortage Therefore, the operation of formal credit sector should be controlled partially to reduce the danger of putting the poor into cycle of poverty 6.3 Limitations The number of households which participate in semi-formal credit in sample collected is small, so this research cannot examine the relationship between the choice of semi-formal credit sector and that of formal credit sector as well as that of informal credit sector Secondly, one of the most significant determinants of household credit demand is the distance from borrower’s location to lender which household borrows from (Ho, 2004; Vaessen, 2000; Zeller & Sharma, 2000) However, this information is not available; information about distance from the borrower’s house to the nearest credit institution available only Therefore, this research cannot investigate if distance from household’s location to credit providers affects microcredit participation in this case 50 Moreover, the literature shows that determinants of credit participation come from demand side characteristics and supply side characteristic (Vaessen, 2002; Duong Pham, 2002) However, in this research, I focus on demand side presented by characteristics of household only These limitations mentioned are suggested for further research 51 REFERENCES Abdul-Muhmin, Alhassan G, & Umar, Yakubu A (2007) Credit card ownership and usage behaviour in Saudi Arabia: The impact of demographics and attitudes towards debt Adams, Dale, Graham, Douglas , & J.D Von Pischke (1984) Undermining Rural Development with Cheap Credit Adegeye, A.J, & Dittoh, J.S (1985) Essentials of Agricultural Economics Impact Publishers Economics Nigeria,Limited, Ibadan Ambrose, B., LarCour-Little, M., & Sanders, A (2004) The effect of conforming loan status on mortgage yield spreads: a loan level analysis Anjugam M, & C Ramasamy (2007) Determinants of Women’s participation in Self- Help Group led micro finance programme in Tamil Nadu Balogun, O., & Yusuf, S (2011) Determinants of Demand for Microcredit among the Rural Households in South-Western States , Nigeria Bendig, M, Giesbert, L, & Steiner, S (2009) Savings, Credit and Insurance: Household Demand for Formal Financial Services in Rural Ghana Bendig, M G., & Susan, S (n.d.) Transformation in the Process of Globalisation Savings , Credit and Insurance : Household Demand for Formal Financial Services in Rural Ghana Braverman, A, & JL Guasch (1986) Rural Credit Markets and Institutions in Developing Countries: Lessons for Policy Analysis from Practice and Modern Theory Bridges, S, & Disney R (2004) Use of credit and arrears on debt among lowincome families in the United Kingdom Chen, A, & Jensen H (1985) Home equity use and the life cycle hypothesis Del-Rio, A., & Young, G (2005) The determinants of unsecured borrowing: evidence from the British household panel survey 52 Doan, T., Gibson, J., & Holmes, M (2010) What determines credit participation and credit Constraint of the Poor in Per-urban area, Vietnam Duca, J., & Rosenthal, S (1994) Do mortgage rates vary based on household default characteristics? Evidence on rate sorting and credit rationing Duong, P., & Izumida, Y (2002) Rural development finance in Vietnam: A microeconometric analysis of household surveys Ferede, K H (2012) Determinants of Rural Households Demand for and Access to Credit in Microfinance Institutions The Case of Alamata Woreda- Ethiopia George, O (n.d.) Gonzalez-Vega, C., Meyer, R L., Schreiner, M., & Navajas, S (2003) Microcredit and the Poorest of the Poor:Theory and Evidence from Bolivia Grootaert, C (1999) Social capital, household welfare, and poverty in Indonesia Hall, R (1978) Permanent Income Hao, Q M (2005) Access to finance and poverty reduction an application to rural Vietnam Izumida, Y., & Pham, B D (2002) Rural development finance in Vietnam: A microeconometric analysis of household surveys Jappelli, T., & Pistaferri, L (2007) Do people respond to tax incentives? An analysis of the Italian reform of the deductibility of home mortgage interest Jonathan Morduch , & Barbara Haley (2002) Analysis of the Effects of Microfinance on Poverty Reduction Kamleitner, B., & Kirchler, E (2007) Consumer credit use: a process model and literature review Khandker, R S (1998) Fighting Poverty with Microcredit: Experience in Bangladesh, New York Khandker, R S (2001) Does Micro-finance Really Benefit the Poor? Evidence from Bangladesh Khandker, R S (2003) Microfinance and Poverty: Evidence Using Panel Data from Bangladesh 53 Khandker, R S., & Pitt, M M (1998) The impact of group-based credit programs on poor households in Bangladesh: Does the gender of participants matter? Lensink, R., & Pham, T T (2007) Lending policies of informal, formal and semiformal lenders Lin, C., & Yang, T (2005) Curtailment as a mortgage performance indicator Magri, S (2002) ITALIAN HOUSEHOLDS ’ DEBT : DETERMINANTS OF DEMAND AND SUPPLY Meyer, R., & Nagarajan, G (1992) An assessment of the role of informal finance in the development process Mitrakos , T., & Simigiannis, G (2009) The determinants of Greek household indebtedness and financial stress Modigliani, & Franco ( 1966) The life-cycle hypothesis of saving, the demand for wealth, and the supply of capital Mohamed, K (2003) Access to Formal and Quasi-Formal Credit by Smallholder Farmers and Artisanal Fishermen Morduch, & Jonathan (1999) The Microfinance Promise.” Journal of Economic Literature Morduch, J., & Aghion, B (n.d.) The Economics of Microfinance Morduch, J., & Haley, B (2002) Analysis of the Effects of Microfinance on Poverty Reduction Mpuga, P (2004) Demand for Credit in Rural Uganda : Who Cares for the Peasants  Mpuga, P (2008) Constraints in Access to and Demand for Rural Credit : Evidence from Uganda Nguyen, C H (2006) Determinants of credit participation and its Impact on household consumption: Evidence From Rural Vietnam Nguyen, C V (2011) The impact of Informal Credit on Poverty and Inequality: The Case of Vietnam 54 Nwaru, J C, Essien, U A, & Onuoha, R E (2011) Determinants of informal credit demand and supply among food crop farmers in AkwaIbom state, Nigeria Okten, C, & Osili, U O (2003) Contributions in heterogeneous communities: evidence from Indonesia Okunade, E O (2007) Accessibility of agricultural credit and inputs to women farmers of Isoya Rural development project Okurut, F N (2006) Access to credit by the poor in South Africa: Evidence from Household Survey Data 1995 and 2000 Ololade R.A., & Olagunju F.I (2013) Determinants of Access to Credit among Rural Farmers in Oyo Owuor George (2001) Is Micro-Finance Achieving Its Goal Among Smallholder Farmers in Africa? Empirical Evidence from Kenya Using Propensity Score Matching Pham, T T., & Lensink, R (2007) Household borrowing in Vietnam: A comparative study of default risks of informal, formal and semi-formal credit Phan, K D (2012) An Empirical Analysis of Accessibility and Impact of Microcredit: the Rural Credit Market in the Mekong River Delta, Vietnam Robinson, M S (2001) The Microfinance Revolution Schreiner, M, & G Nagarajan (1998) Predicting Creditworthiness with Publicly Observable Characteristics: Evidence from ASCRAs and RoSCAs in the Gambia Soman, D., & Cheema A (2002) The effect of credit on spending decisions: The role of the credit limit and credibility Stiglitz, J E., & Weiss, A (1981) Credit rationing in markets with imperfect information Tang, S., Guan, Z., & Zin, S (2010) Formal and Informal Credit Markets and Rural Credit Demand in China Vaessen, J (2001) Accessibility of rural credit in Northern Nicaragua: the importance of networks of information and recommendation 55 Yehuala, S (2008) Determinants of smallholder farmers access to formal credit: the case of Metema Woreda, north Gondar, Ethiopia Zeller, D A., & Sharma, M (2000) to Credit Empirical Mesearements of Households’ Access and Credit Constraints in Developing Countries:Methodological Issues and Evidence Zeller, M (1994) Determinants Of Credit Rationing - A Study of Informal Lenders And Formal Credit Groups In Madagascar Zhao, X., & N.Harris, M (2004) Demand for Marijuana, Alcohol and Tobacco:Participation, Levels of Consumption and Cross-equation Correlations 56 APPENDIX Appendix 1: Statistics variables summarize Variable Obs Mean hhsize age material edu gender 1522 1522 1522 1522 1522 5.754928 47.13272 8554534 8.339685 8390276 location formal semi_formal informal network 1522 1522 1522 1522 1522 marital_stt agricultur~s income landsize savingamount 1522 1522 1522 1522 1522 Std Dev Min Max 3.423013 12.3758 3517587 3.226634 3676263 18 25 93 13 7943495 6760841 0854139 4638633 5611038 404309 4681222 2795885 4988563 4964154 0 0 1 1 8554534 6708279 88.22605 10.99167 22.41842 3517587 470067 157.5349 16.30339 58.27375 0 2.005 035 1 4500 181.2 820 57 Appendix 2: Biprobit model result Seemingly unrelated bivariate probit Number of obs Wald chi2(22) Prob > chi2 Log likelihood = -1626.0435 Coef Std Err z P>|z| = = = 1522 244.13 0.0000 [95% Conf Interval] formal age gender marital_stt edu hhsize income savingamount landsize agriculture_activities network location _cons 0075118 151997 0680732 0289365 0185429 -.0008037 0025958 0076207 0551399 -.0449324 8583475 -1.161806 0030486 1284223 1387999 0110286 0107979 0002655 0009093 0025141 0783177 0745282 082791 2348165 2.46 1.18 0.49 2.62 1.72 -3.03 2.85 3.03 0.70 -0.60 10.37 -4.95 0.014 0.237 0.624 0.009 0.086 0.002 0.004 0.002 0.481 0.547 0.000 0.000 0015367 -.0997061 -.2039696 0073209 -.0026207 -.001324 0008136 0026931 -.0983599 -.1910049 6960802 -1.622038 0134869 4037001 340116 0505521 0397064 -.0002834 0043779 0125483 2086397 1011402 1.020615 -.7015737 age gender marital_stt edu hhsize income savingamount landsize agriculture_activities network location _cons -.012557 -.2400197 4704264 0063396 -.0544963 0006474 -.0022606 -.0024476 -.0047116 1535791 -.33206 744359 0029225 1285607 1384631 0105358 0104913 0002615 0007772 0022311 0754129 071354 0821836 2261336 -4.30 -1.87 3.40 0.60 -5.19 2.48 -2.91 -1.10 -0.06 2.15 -4.04 3.29 0.000 0.062 0.001 0.547 0.000 0.013 0.004 0.273 0.950 0.031 0.000 0.001 -.018285 -.4919939 1990436 -.0143102 -.0750589 0001349 -.0037839 -.0068204 -.1525181 0137279 -.493137 3011452 -.0068289 0119546 7418092 0269893 -.0339337 0011599 -.0007373 0019252 1430949 2934304 -.1709831 1.187573 /athrho -1.137302 0615582 -18.48 0.000 -1.257954 -1.01665 rho -.8135035 0208197 -.850499 -.7684985 informal Likelihood-ratio test of rho=0: chi2(1) = 58 480.84 Prob > chi2 = 0.0000 Appendix 3: The marginal effects for Pr(formal=1, informal=1) mfx compute, predict(p11) Marginal effects after biprobit y = Pr(formal=1,informal=1) (predict, p11) = 18358534 variable age gender* marita~t* edu hhsize income saving~t landsize agricu~s* network* location* dy/dx Std Err -.0019257 -.0335559 1322072 0089765 -.0117955 -2.56e-06 -.0000426 0011303 0120594 0348592 1144395 00079 03532 02412 00286 00279 00007 00023 00068 01975 01875 01625 z -2.43 -0.95 5.48 3.14 -4.23 -0.04 -0.19 1.67 0.61 1.86 7.04 P>|z| [ 95% C.I ] 0.015 0.342 0.000 0.002 0.000 0.970 0.851 0.095 0.541 0.063 0.000 -.003478 -.000373 -.102772 03566 084942 179473 003379 014574 -.017266 -.006325 -.000138 000133 -.000488 000402 -.000198 002459 -.026649 050768 -.001897 071615 082583 146296 X 47.1327 839028 855453 8.33968 5.75493 88.226 22.4184 10.9917 670828 561104 79435 (*) dy/dx is for discrete change of dummy variable from to Appendix 4: The marginal effects for Pr(formal=1, informal=0) mfx compute, predict(p10) Marginal effects after biprobit y = Pr(formal=1,informal=0) (predict, p10) = 5045949 variable age gender* marita~t* edu hhsize income saving~t landsize agricu~s* network* location* dy/dx 0045826 0885767 -.1078536 0012581 0183539 -.0002817 0009607 0015651 0075307 -.0507289 2090319 Std Err .00109 04739 04918 00394 00392 0001 0003 00083 02821 02664 02819 z 4.20 1.87 -2.19 0.32 4.68 -2.89 3.25 1.89 0.27 -1.90 7.42 P>|z| [ 95% C.I 0.000 0.062 0.028 0.750 0.000 0.004 0.001 0.059 0.789 0.057 0.000 002444 006721 -.004315 181468 -.204247 -.01146 -.006467 008983 010675 026033 -.000472 -.000091 000381 00154 -.000061 003191 -.047753 062814 -.102937 001479 153788 264276 (*) dy/dx is for discrete change of dummy variable from to 59 ] X 47.1327 839028 855453 8.33968 5.75493 88.226 22.4184 10.9917 670828 561104 79435 Appendix 5: The marginal effects for Pr(formal=0, informal=1) mfx compute, predict(p01) Marginal effects after biprobit y = Pr(formal=0,informal=1) (predict, p01) = 27324684 variable age gender* marita~t* edu hhsize income saving~t landsize agricu~s* network* location* dy/dx -.0030544 -.061934 0469426 -.0064622 -.009818 0002593 -.000854 -.002101 -.0139282 0259274 -.2462988 Std Err .00093 04262 03907 00337 00331 00008 00027 00074 02414 02259 02885 z -3.29 -1.45 1.20 -1.92 -2.96 3.18 -3.19 -2.84 -0.58 1.15 -8.54 P>|z| [ 95% C.I 0.001 0.146 0.230 0.055 0.003 0.001 0.001 0.004 0.564 0.251 0.000 -.004876 -.145462 -.029635 -.013065 -.01631 000099 -.001379 -.00355 -.061251 -.018345 -.302848 ] -.001233 021594 12352 00014 -.003326 000419 -.000329 -.000652 033394 0702 -.189749 X 47.1327 839028 855453 8.33968 5.75493 88.226 22.4184 10.9917 670828 561104 79435 (*) dy/dx is for discrete change of dummy variable from to Appendix 6: The marginal effects for Pr(formal=0, informal=0) mfx compute, predict(p00) Marginal effects after biprobit y = Pr(formal=0,informal=0) (predict, p00) = 03857292 variable age gender* marita~t* edu hhsize income saving~t landsize agricu~s* network* location* dy/dx 0003976 0069132 -.0712963 -.0037724 0032595 0000249 -.0000641 -.0005944 -.0056619 -.0100577 -.0771727 Std Err .0003 01143 02445 00112 00109 00003 00009 00026 00787 00745 01421 z 1.32 0.61 -2.92 -3.38 2.98 0.96 -0.71 -2.26 -0.72 -1.35 -5.43 P>|z| [ 95% C.I 0.188 0.545 0.004 0.001 0.003 0.339 0.475 0.024 0.472 0.177 0.000 -.000194 000989 -.015482 029309 -.119209 -.023384 -.005961 -.001584 001114 005405 -.000026 000076 -.00024 000112 -.00111 -.000079 -.021077 009754 -.024654 004538 -.105026 -.04932 (*) dy/dx is for discrete change of dummy variable from to 60 ] X 47.1327 839028 855453 8.33968 5.75493 88.226 22.4184 10.9917 670828 561104 79435 Appendix 7: The marginal effects for the marginal probability of outcome Pr(formal=1) mfx compute, predict(pmarg1) Marginal effects after biprobit y = Pr(formal=1) (predict, pmarg1) = 68818024 variable age gender* marita~t* edu hhsize income saving~t landsize agricu~s* network* location* dy/dx 0026569 0550208 0243537 0102346 0065585 -.0002843 0009181 0026954 0195901 -.0158697 3234715 Std Err .00108 04746 0502 0039 00382 00009 00032 00089 02795 02628 03116 z 2.47 1.16 0.49 2.63 1.72 -3.03 2.86 3.04 0.70 -0.60 10.38 P>|z| [ 95% C.I 0.014 0.246 0.628 0.009 0.086 0.002 0.004 0.002 0.483 0.546 0.000 000544 -.038009 -.074042 002593 -.000921 -.000468 000289 000956 -.035183 -.067379 262403 ] 004769 14805 122749 017876 014038 -.0001 001547 004435 074363 035639 38454 X 47.1327 839028 855453 8.33968 5.75493 88.226 22.4184 10.9917 670828 561104 79435 (*) dy/dx is for discrete change of dummy variable from to Appendix 8: The marginal effects for the marginal probability of outcome Pr(informal=1) mfx compute, predict(pmarg2) Marginal effects after biprobit y = Pr(informal=1) (predict, pmarg2) = 45683218 variable age gender* marita~t* edu hhsize income saving~t landsize agricu~s* network* location* dy/dx -.0049801 -.0954899 1791499 0025143 -.0216135 0002568 -.0008966 -.0009707 -.0018688 0607866 -.1318592 Std Err .00116 05101 04944 00418 00416 0001 00031 00088 02991 02815 03237 z -4.30 -1.87 3.62 0.60 -5.20 2.48 -2.91 -1.10 -0.06 2.16 -4.07 P>|z| [ 95% C.I 0.000 0.061 0.000 0.547 0.000 0.013 0.004 0.273 0.950 0.031 0.000 -.007252 -.195475 082256 -.005675 -.029762 000053 -.001501 -.002705 -.0605 005609 -.195303 -.002709 004496 276044 010704 -.013465 00046 -.000293 000763 056762 115965 -.068415 (*) dy/dx is for discrete change of dummy variable from to 61 ] X 47.1327 839028 855453 8.33968 5.75493 88.226 22.4184 10.9917 670828 561104 79435 Appendix 9: The marginal effects for the conditional probability of outcome given outcome Pr(formal=1 | informal=1) mfx compute, predict(pcond1) Marginal effects after biprobit y = Pr(formal=1|informal=1) (predict, pcond1) = 40186605 variable age gender* marita~t* edu hhsize income saving~t landsize agricu~s* network* location* dy/dx 0001656 0091813 1823971 0174376 -.0068073 -.0002315 0006955 0033281 0280028 0232474 315576 Std Err .00139 05594 05544 00499 00485 00012 00042 00121 03472 0334 02744 z 0.12 0.16 3.29 3.49 -1.40 -1.94 1.65 2.75 0.81 0.70 11.50 P>|z| [ 95% C.I 0.905 0.870 0.001 0.000 0.161 0.052 0.099 0.006 0.420 0.486 0.000 -.002555 -.100455 073745 007654 -.01632 -.000465 -.000131 000957 -.040052 -.042209 261796 ] 002886 118818 291049 027221 002705 2.0e-06 001522 005699 096058 088704 369356 X 47.1327 839028 855453 8.33968 5.75493 88.226 22.4184 10.9917 670828 561104 79435 (*) dy/dx is for discrete change of dummy variable from to Appendix 10: The marginal effects for the conditional probability of outcome given outcome Pr(informal=1 | formal=1) mfx compute, predict(pcond2) Marginal effects after biprobit y = Pr(informal=1|formal=1) (predict, pcond2) = 26676927 variable age gender* marita~t* edu hhsize income saving~t landsize agricu~s* network* location* dy/dx -.0038282 -.0741843 1872024 0090764 -.0196825 0001065 -.0004178 0005976 0100288 0566662 060879 Std Err .00108 0505 03419 00388 00383 0001 00029 00088 02727 0256 02932 z -3.55 -1.47 5.48 2.34 -5.14 1.12 -1.42 0.68 0.37 2.21 2.08 P>|z| [ 95% C.I 0.000 0.142 0.000 0.019 0.000 0.265 0.155 0.497 0.713 0.027 0.038 -.005942 -.001715 -.173156 024788 120187 254218 001477 016676 -.027182 -.012183 -.000081 000294 -.000994 000158 -.001125 00232 -.043421 063478 006497 106836 00342 118338 (*) dy/dx is for discrete change of dummy variable from to 62 ] X 47.1327 839028 855453 8.33968 5.75493 88.226 22.4184 10.9917 670828 561104 79435