An analysis of housing credit program for urban hoausehold case study in HCMC housing development bank(HDBANK) (2)

UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS AN ANALYSIS OF HOUSING CREDIT PROGRAM FOR URBAN HOUSEHOLD CASE STUDY IN HCMC HOUSING DEVELOPMENT BANK (HDBANK) DA R A THESIS PRESENTED BY DO HONG NGOC IN PARTIAL FULFILMENT OF THE REQUIREMENT FOR THE DEGREE OF MASTER OF ARTS IN DEVELOPMENT ECONOMICS SUPERVISOR DR TRAN TIEN KHAI He Chi Minh CitY, February 2009 P CERTIFICATION “I certify that the substance of this study has not already been submitted for any degree and is not being currently submitted for any other degree I certify that to the best of my knowledge any help received in preparing this thesis, and all sources used, have been acknowledged in this dissertation.” Ho Chi Minh City, February 2009 Do Hong Ngoc ACKNOWLEDGEMENT I would like to express deeply my appreciation and many thanks to the following individuals and organization helped me to finish this thesis Doctor Tran Tien Khai, the academic supervisor who has spent much time to give me his guides, comments, assistance in this research All lecturer and staff of Viet Nam-Netherland master program which is helpful program for me to obtain the knowledge and the method of science studying with international standard All my classmates, especially my group have encouragement, cooperation and help during my studying and doing the thesis All of my family members have help and encouragement for me to try my best to finish this research ABSTRACT Viet Nam is going on the way of modernization, industrialization and especially of globalization with the purpose of economic development and enhancing the life standard of the resident This implies to increase further with a rise in the urbanization levels and in the population along with increasing the demand for housing in urban of Viet Nam To solve the demand of urban household, the government has many policies to support the resident such as housing finance system from bank or other financial institution, housing program for low income This study only concentrates to analysis housing credit program from bank for urban household on two major aspects The first is the determinants of probability to get a housing loan And the second is the determinants of housing loan amount So the household should improve their character and capacity to be able to ‘borrow housing loan from bank Conversely, the bank also should have suitable credit policy and condition for the customer to speed up effective and sustainable credit development TABLES OF CONTENTS Certification , .i Acknowledgement , ii Abstract iii Contents i List of tables and figures viii Abbreviation ix CHAPTER ‘I: INTRODUCTION 1.1Problem statement I 1.2Objectives of the study 1.2.1General objective .2 1.2.2Specific objective 1.3 Research question 1.4Summary on research methodology and data .2 1.5 The organization of the thesis CHAPTER II: LITERATURE REVIEW .4 2.1Theory bac 2.1.1 Major concepts Household Credit Borrowing Household credit market 2.1.2 Banking theory .‘ Credit management Credit analysis and loan decision Issues in credit market 2.2Experiences of housing development in some Asian countries 2.2.1 In Singapore 2.2.2 In China 2.2.3 In Thailand 10 2.2.4 In Korea .11 2.3 Theoretical models and empirical studies for house demand 12 2.3.1 General observations 12 2.3.2 Determinants of housing loan .13 3.3 Determinants of loan amount .15 2.3.4 Theoretical models 16 The basic models 16 The extended models .16 2.3.5Empirical models applied in previous studies .17 CHAPTER III: RESEARCH METHODOLOGY .20 3.1 Analytical framework 20 3.1.1Hypotheses 20 3.1.2Determinants of the probability .20 3.1.3Determinants of loan amount .21 3.1.4Specific empirical models 22 Model .22 Description of the model I 22 Definition and explanation of variables of the model .22 Expected signs of the variables’ coefficients .23 Model .24 Description of the model , 24 Definition and explanation of variables of the model .24 Expected signs of the variables’ coefficients .25 3.2 Data source 3.2.1 Data source .26 Where is data source? .26 What is its va1idip? 26 When are they collected? 26 Population .26 3.2.2 Sampling .27 Sample size ‘ 27 Sampling method 27 3.3 Analysis methods .29 3.3.1 Stat istical tests for descriptive analysis 29 3.3.2 Correlation analysis .29 3.3.3 Statistical tests for validity of specific models 30 3.4 Analysis tool 30 CHAPTER IV: RESULTS AND DISCUSSION ., 31 4.1Situation of housing credit program for urban household in He Chi Minh City 31 4.1.1 Housing demand of urban household 31 4.1.2National strategy on housing up to the year 2010 31 4.1.3 The overview of urban financial system, borrowing by urban households and housing finance project 32 Financial system and source of credit to urban households in Viet Nam 32 Overview of borrowing by urban households 32 4.1.4 HCMC Housing development program 35 4.2 HCMC Housing Development Bank .35 4.2.1 Overview of HDBank .35 4.2.2 Housing credit program of HDBank .38 4.3HCMC Housing Development Bank .40 4.3.1 .Analysis of borrower’ characteristics .40 4.3.2 Correlation analysis 44 4.3.3 Statistical tests for validity of specific models 47 4.3.4Description collecting data and choosing suitable method 48 4.4Results of models testing and explanation .49 4.4.1 Empirical result — Model I .‘ .49 4.4.1.1Enter method 49 4.4.1.2Backward LR method 50 4.4.1.3 Analysis the factor affect to the probability to get housing loan for household 50 4.4:2 Empirical re‘sult — Model 54 4.4.2.1Enter method 54 4.4.2.2Backward LR method 54 4.4.2.3Analysis the factor affect to the probability to get housing loan for household 54 CHAPTER V: CONCLUSION AND IMPLICATION .58 5.1Conclusion on the applied methodology and limitation 58 5.2 Conclusion on the studied results 58 5.3 Policy implication in macro level 59 5.4 Policy implication for HDBank as well as housing credit program 59 References Annex LIST OF TABLES Table 1.1: Compare mean of variable Table 1.2: Correlation Matrix Table 1.3: Durbin — Watson in model Table 1.4: Durbin — Watson in model Table 1.5: Regression result of model from stepl to step by back ward method Table 1.6: Regression result of model from stepl to step by back ward method LIST OF FIGURES Figure 2.1: Structure of probability to get housing loan Figure 2.2: Structure of samples possibility to get a housing loan Figure 2.3: Growth of total assets and chartered capital in HDBank Figure 2.4: Growth of loan outstanding debts in HDBank Figure 2.5: Outstanding of housing credit program and total loan outstanding in HDBank Figure 2.6: Regression standardized residual LIST OF ANNEXS: Annex 1: T-Test result Annex 2: The result of model 1- Enter method Annex 3: The result of model — Backward method Annex 4: The result of model 2- Enter method Annex 5: The result of model — Backward method ABBREVIATION HDBank: Housing Development Bank ADB: Asian‘ Development Bank SBV: State Bank of Viet Nam SOB: State Owned Bank DLH: Department of Land and House Omnibus Tests of Model Coefficients Chisquare Step Step 2(a) Step3(a) Step4(a) Step5(a) Step6(a) df Sig Step 346.401 10 000 Block 346.401 10 000 Model 346.401 10 000 -.052 I 820 Block 346.350 000 Model 346.350 000 -.131 717 Block 346.219 000 Model 346.219 000 -.984 321 Block 345.235 000 Model 345.235 000 Step -1.018 313 Block 344.217 000 Model 344.217 000 Step -2.600 I 107 Block 341.617 000 Model 341.617 000 Step Step Step a A negative Chi-squares value indicates that the Chi-squares value has decreased from the previous step Model Summary Step -2 Log likelihoo d Cox & Snell R Square 23.237(a) 23.289(a) 697 697 968 968 23.420(a) 697 967 24.404(a) 696 966 25.422(b) 695 964 28.022(b) 692 96l Nagelkerke R Square a Estimation terminated at iteration number 20 because maximum iterations has been reached Final solution cannot be found b Estimation terminated at iteration number 10 because parameter estimates changed by less than 00l Classification Table(a) Observed Step Predicted‘ 94 B 192 Overall Percentage Step B 98.6 95 192 95 97.9 99.5 99.0 97.9 191 99.0 Overall Percentage Step B Overall Percentage Step B 98.6 94 96.9 191 99.0 Overall Percentage Step B 98.3 94 96.9 i 191 99.0 98.3 Overall Percentage Step B 96.9 99.5 94 96.9 190 98.4 97.9 Overall Percentage a The cut value is 500 19 Variables in the Equation B Step 1(a) Sig Exp(B) 12.523 000 967 029 015 3.626 057 1.030 SEX -1.412 1.423 985 321 244 AGE -.181 146 1.552 213 834 EDU -.613 2.752 050 824 542 903 309 8.553 I 003 2.467 -1.727 1.145 2.275 I 131 178 1.110 2.972 139 709 3.034 007 003 6.612 I 010 1.007 19.476 4396.54 000 996 2873999 26.014 -13.519 4396.55 000 998 000 -.033 009 12.518 000 967 028 015 3.577 I 059 1.029 SEX -1.366 1.424 921 337 255 AGE -.174 145 1.449 229 840 893 305 8.564 I 003 2.442 -1.737 1.152 2.273 I 132 176 1.043 2.971 1.23 726 2.836 007 003 6.582 010 1.007 19.006 4540.62 000 997 1795480 85.712 000 l 998 000 -.033 009 12.492 000 967 028 015 3.597 058 1.028 SEX -1.303 1.411 852 356 272 AGE -.171 143 919 305 -1.538 980 007 003 18.421 4617.60 1.442 9.072 2.460 7.707 230 843 003 2.508 117 215 005 1.007 997 1000706 mTUR HHNo HOUSEVAL COLL Constant LA mTUR INCOME SIZE HHNO HOUSEVAL COLL Constant Step 3(a) df 009 SIZE Step Wald -.033 LA INcoME 2(a) S.E LA ›+‹TUR INcoME SIZE HOUSEVAL COLL -13.650 4540.62 20 - 000 B Constant Step 4(a) -12.298 LA Sig 4617.61 Exp(B) 75.374 998 000 000 969 056 1.024 024 012 13.848 3.638 -.151 134 1.269 260 860 873 286 9.296 002 2.394 -1.584 944 2.813 093 205 006 002 8.703 003 1.006 17.990 4795.83 997 6501364 7.068 -12.559 4795.83 000 998 000 -.035 009 16.098 000 966 024 011 4.431 035 1.024 AGE -.245 093 6.971 008 782 INCOME 1.007 279 12.991 000 2.738 -1.239 837 2.192 139 290 007 002 9.818 002 1.007 Constant 6.660 3.261 4.171 041 780.672 LA MATUR -.033 025 008 011 17.913 4.844 1 000 028 968 1.025 AGE -.298 109 7.474 006 742 INCOME 891 235 14.340 I 000 2.437 HOUSEVAL 007 002 9.155 I 002 1.007 5.387 3.171 2.887 089 218.605 ××TUR SIZE HOUSEVAL COLL Constant LA ›‹›‹TUR SIZE HOUSEVAL Step 6(a df 008 INcoME 5(a) Wald -.031 AGE Step S.E Constant a Variable(s) entered on step I: LA, MATUR, SEX, AGE, EDU, INCOME, SIZE, HHNO, HOUSEVAL, COLL ‘ Model if Term Removed Variable Model Log Likelihoo d Change in -2 Log Likelihoo d 21 df Sig of the Change Step Step2 Step3 Step4 Step5 LA -54.513 85.788 000 MATUR -14.261 5.284 022 SEX -12.178 1.119 290 AGE -12.446 1.655 EDU -11.644 052 1 l98 820 INCOME -28.774 34.310 000 SIZE -13.130 3.023 082 HHNO -11.693 148 700 HOUSEVAL -17.706 12.176 I 000 COLL -12.227 1.217 270 LA -55.937 88.586 000 MATUR -14.306 5.323 021 SEX -12.178 1.067 302 AGE -12.466 1.643 200 INCOME -31.260 39.232 000 SIZE -13.153 3.017 082 HHNO -11.710 131 HOUSEVAL -17.823 12.358 COLL -12.260 1.231 1 717 000 267 LA -58.543 93.665 000 MATUR -14.363 5.307 021 SEX -12.202 984 321 AG,E -1‘2.524 1.628 202 INCOME -31.336 39.252 000 SIZE -13.350 3.281 070 HOUSEVAL -18.816 14.213 000 COLL -12.260 1.101 I 294 LA -58.544 92.685 000 MATUR -14.571 4.739 029 AGE -12.893 1.381 240 INCOME -31.363 38.322 000 SIZE -13.922 3.441 064 HOUSEVAL -18.930 13.456 000 COLL -12.711 1.018 313 LA -66.759 108.097 000 22 Step MATUR -15.402 5.383 020 AGE -20.020 14.618 000 INCOME -49.005 72.588 000 SIZE -14.01 I 2.600 I 107 HOUSEVAL -20.386 15.351 000 LA -69.172 110.322 000 MATUR -17.041 6.059 014 AGE -22.800 17.578 000 INCOME -49.013 70.005 000 HOUSEVAL -21.572 15.123 000 Variables not in the Equation Score Step 2(a) Step 3(b) Step 4(c) Variables EDU 824 Overall Statistics 049 824 Variables EDU 033 856 HHNO 727 Overall Statistics 122 , i7! 918 Variables SEX 907 341 EDU 000 993 HHNO 046 830 I 114 840 096 018 722 1 l I HHNO 1.620 1.046 003 2.460 618 l 774 359 756 895 395 805 306 955 117 432 COLL 101 751 4.461 485 Variables SEX EDU HHNO COLL Overall Statistics Step 6(e) Sig .049 Overall Statistics Step 5(d) df Variables SEX EDU SIZE Overall Statistics a Variable(s) rem oVed on step 2: EDU b Variable(s) removed‘ on step 3: HHNO 23 1 c Variable(s) rem oved on step 4: SEX d Variable(s) removed on step 5: COLL e Variable(s) rem civéd on step 6: SIZE 24 ANNEX 4: THE RESULT OF MODEL 2- ENTER METHOD Regression Notes 09-DEC-2008 17:04:02 Output Created Comments Input - 100) SIZE Backward (criterion: Probability of Fto-remove >- 100) EDU Backward (criterion: Probability of Fto-remove >- 100) a All requested variables entered b Dependent Variable: LA Model Summary Mode I R Adjusted R Square R Square Std Error of the Estimate 858(a) 858(b) 736 736 724 726 75.596 75.396 857(c) 735 726 75.358 857(d) 734 727 75.204 855(e) 732 726 75.343 a Predictors: (Constant), HOUSEVAL, SEX, MATUR, EDU, HHNO, INCOME, AGE, SIZE b Predictors: (Constant), HOUSEVAL, MATUR, EDU, HHNO, INCOME, AGE, SIZE c Predictors: (Constant), HOUSEVAL, MATUR, EDU, HHNO, INCOME, SIZE d Predictors: (Constant), HOUSEVAL, MATUR, EDU, HHNO, INCOME e Predictors: (Constant), HOUSEVAL, MATUR, HHNO, INCOME ANOVA(I) 29 Sum of Squares Model Mean Square df Regression Residual 2927304.453 1051502.108 365913.057 184 5714.685 Total 3978806.561 192 Regression 2927158.717 Residual 1051647.844 185 Total 3978806.561 192 Regression 2922545.608 Residual 1056260.953 186 Total 3978806.561 192 Regression 2921204.838 Residual 1057601.723 187 Total 3978806.561 192 Regression 2911625.704 Residual 1067180.857 188 Total 3978806.561 192 F Sig 64.030 000(a) 73.561 000(b) 85.773 000(c) 103.303 000(d) 128.232 000(e) 418165.531 5684.583 487090.935 5678.822 584240.968 5655.624 727906.426 5676.494 a Predictors: (Constant), HOUSEVAL, SEX, MATUR, EDU, HHNO, INCOME, AGE, SIZE b Predictors: (Constant), HOUSEVAL, MATUR, EDU, HHNO, INCOME, AGE, SIZE c Predictors: (Constant), HOUSEVAL, MATUR, EDU, HHNO, INCOME, SIZE d Predictors: (Constant), HOUSEVAL, MATUR, EDU, HHNO, INCOME e Predictors: (Constant), HOUSEVAL, MATUR, HHNO, INCOME f Dependent Variable: LA Coefficients(a) Model Unstandardized Coefficients Standardized Coefficients I Sig B (Constant) -220.666 60.377 353 140 SEX 1.799 AGE 000 097 2.526 012 11.266 006 160 873 1.370 1.503 058 9l1 363 EDU 44.821 33.372 054 1.343 18l INCOME 15.146 1.300 562 11.653 000 -10.074 10.446 -.067 -.964 336 35.802 18.183 101 1.969 050 l31 014 394 9.356 000 -218.346 58.449 -3.736 000 351 139 096 2.531 012 AGE 1.341 1.489 057 901 369 EDU 44.316 33.134 054 1.337 l83 INCOME 15.136 1.295 562 11.691 000 SIZE -9.852 10.326 -.066 -.954 341 HHNO 35.787 18.135 101 1.973 050 131 014 395 9.394 000 -188.173 47.876 -3.930 000 361 138 099 2.611 0l0 EDU 39.720 32.722 048 1.214 226 INCOME 15.272 1.285 567 11.883 000 SIZE -3.815 7.852 -.025 -.486 628 HHNO 36.178 18.121 102 1.997 047 131 014 395 9.399 000 -189.006 47.747 -3.958 000 360 138 099 2.6 l‘4 0l0 EDU 42.043 32.305 051 1.301 195 INCOME 15.110 1.239 561 12.197 000 HHNO 31.498 15.317 089 2.056 041 131 014 394 9.407 000 -140.962 30.339 -4.646 000 346 l38 095 2.511 013 15.345 1.228 570 12.496 000 SIZE HHNO HOUSEVAL (Constant) MATUR HOUSEVAL (Constant) MATUR HOUSEVAL Beta -3.655 MATUR Std Error (Constant) MATUR HOUSEVAL (Constant) MATUR INCOME Unstandardized Coefficients Model B HHNO HOUSEVAL 26.925 l29 Standardized Coefficients Std Error Beta 14.936 014 t Sig .076 1.803 073 389 9.308 000 a Dependent Variable: LA Excluded Variables(e) Mode Beta In T Sig Partial Correlation Collinearity Statistics Tolerance SEX SEX 006(a) 002(b) 160 053 873 958 012 004 955 968 AGE 057(b) 901 369 066 362 SEX 001(c) 017 987 001 973 AGE 018(c) 370 712 027 626 SIZE -.025(c) -.486 628 -.036 522 SEX -.004(d) -.098 922 -.007 981 AGE 004(d) 088 930 006 655 SIZE -.035(d) -.670 504 -.049 533 EDU 051(d) 1.301 195 095 932 a Predictors in the Model: (Constant), HOUSEVAL, MATUR, EDU, HHNO, INCOME, AGE, SIZE b Predictors in the Model: (Constant), HOUSEVAL, MATUR, EDU, HHNO, INCOME, SIZE c Predictors in the Model: (Constant), HOUSEVAL, MATUR, EDU, HHNO, INCOME d Predictors in the Model: (Constant), HOUSEVAL, MATUR, HHNO, INCOME e‘ Dependent‘Variable: LA 32 ... financing from the commercial banks and financial organizations 1.3 The overview of urban financial system, lending by urban housing and housing finance project Financial system and source ofCFédit... determinants affect to loan amount 1.2.2Specific objective - The demand of house and housing system in urban Viet Nam - The demand of housing loan of urban household - The determinants of housing credit. .. for housing loan Figure 2.5 Outstanding ofhousing credit program and total loan outstanding in HDBank (SO1IFC!é annual report ofHDBank in the year 2007) Conditions & PFOO£!dure ofHDBank Housing