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Bureau of Economic Research, University of Dhaka

The Role of Credit in Food Production and Food Security in Bangladesh Presented by Dr. Bazlul Haque Khondker Bureau of Economic Research University of Dhaka. Bureau of Economic Research, University of Dhaka. Objectives of this Presentation.

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Bureau of Economic Research, University of Dhaka

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  1. The Role of Credit in Food Production and Food Security in Bangladesh Presented by Dr. Bazlul Haque Khondker Bureau of Economic Research University of Dhaka Bureau of Economic Research, University of Dhaka

  2. Objectives of this Presentation • The prime objective is to present the results of activities between this and the last presentation. • More specifically our focus is on • major observations of a desk review of major agricultural credit programmes in Bangladesh; • relationship between agricultural credit and food security, food production. Bureau of Economic Research, University of Dhaka

  3. Background: Data and Methodology • To test the relationship between credit and food security and production, both quantitative analysis and qualitative evaluation have been adopted. • Quantitative analyses were based on two data sets: HIES 2010 and Primary survey by BER. • BER survey was conducted to supplement the HIES 2010. BER survey was used to get additional information on (i) access to credit; and (ii) food security. • Stratified sampling methodology. The 64 administrative districts were divided into 3 strata – low, medium and high credit recipient districts. • Randomly chose 2 Upazillas from each districts and then randomly choose 1 Union Parishad from each Upazilla. We prepared a list of villages of the randomly drawn UPs and randomly chose 3 villages from each UP. • BER survey was conducted in 30 villages of 10 UPs in 5 districts. In total 1200 respondents – 40 from each of the 30 villages • Ten FGDs of credit recipient as well as non-recipients. Bureau of Economic Research, University of Dhaka

  4. Background: Data and Methodology (Cont.) • OLS Estimation: The model that we primarily tried to estimate is: Y=δC+βX+u • We attempted to estimate Average Treatment Effect (ATE) of credit dummy on household food security. This technique is expected to control the unobserved factors that might affect household’s decision to avail credit and it should take care of the problem of self-selection bias. • In the 1st stage we estimate a probit model of availability of credit on relevant household and village characteristics and get the predicted value of credit dummy. In the next stage, we regressed our food security variable (daily per capita calorie consumption) on predicted value obtained from the 1st stage of regression and on credit dummy. • One of the criticisms of OLS in this kind of exercise is the possibility of endogeneity of credit variable. We applied instrumental variable (IV) estimation technique and we instrumented credit dummy with two variables: distance to nearest bank and its squared. Bureau of Economic Research, University of Dhaka

  5. Review of Major Agricultural Credit Programs in Bangladesh Major agricultural credit programs operated during 1996-2011 have been reviewed. Also reviewed BRAC’s special agriculture credit program. Key observations: Farmers who have access to formal credit prefer credit of NCB or NSB rather than that of Private Commercial Banks or NGOs . Most of the formal credit schemes require formal security like landed property, inaccessible to most of the marginal and poor farmers including sharecroppers. Timely sanction of credit, hassle free advance is more important to farmers than lower interest rate or any waiver on interest. Due to inadequacy of credit from a single source, recipients sometimes simultaneously opt for credit from other sources to meet their need. Credit swapping between purpose and use. That is credit obtained for farm purpose used in non-farm purposes and vice-versa. Bureau of Economic Research, University of Dhaka

  6. Credit, Food Security and Dietary Diversity • To understand the relationship between credit and food security and dietary diversity, both quantitative analysis involving secondary as well as primary survey data and qualitative evaluation with FGDs have been adopted. • Using HIES and survey data socio-economic features of households with or without credit has been examined. • In addition, borrowers disaggregated by credit sources e.g. formal, informal and micro credit and the differences across these groups on the basis of education, land holding, income, household size, occupation, food consumption, agricultural production etc. have been examined. Bureau of Economic Research, University of Dhaka

  7. Credit, Food Security and Dietary Diversity (Cont.) Table 1: Loan characteristics by source (HIES-2010) Bureau of Economic Research, University of Dhaka

  8. Credit, Food Security and Dietary Diversity (Cont.) Table 2: Household characteristics by loan status Bureau of Economic Research, University of Dhaka

  9. Credit, Food Security and Dietary Diversity (Cont.) • UsingHIES 2010, for food security we considered ‘daily per capita calorie consumption’ as the representative variable and access to credit has been proxied by a dummy variable (1 for credit recipient). • In addition to OLS, this analysis has also applied PSM method to control the possibility of self-selection bias. Both OLS as well as PSM found that, credit has positive and significant effect on household’s food security and this is true for all 3 sources of credit. • Similar analysis with OLS and PSM has been conducted with the primary survey data and this has also provided evidence in favor of the positive and significant contribution of credit on household food security status. • In addition to OLS and PSM, this analysis also employs IV method to test for any plausible endogeneity of credit variable but the results show no sign of endogeneity. Bureau of Economic Research, University of Dhaka

  10. Credit, Food Security and Dietary Diversity (Cont.) • In the context of dietary diversity, we relied on 2 types of scores, e.g. Food Consumption Score (FCS) and Household Dietary Diversity Score (HDDS). • Using HIES 2010, FCS has been constructed and our estimation of OLS shows that access to credit have positive contribution to this score. Similar analyses with primary data using HDDS have been applied. • Along with OLS and PSM, IV method is also applied and the relevant tests suggest presence of endogeneity in credit variable. In the presence of endogeneity, IV estimates provide evidence of the positive contribution of credit in household dietary diversity. Bureau of Economic Research, University of Dhaka

  11. Credit, Food Security and Dietary Diversity (Cont.) • Credit plays a significant role in household food consumption and a household with credit tends to consume around 60 calorie more per capita on a daily basis than an otherwise similar household without credit. • HHs with greater number of literate adults have significantly higher probability to consume more calories and tend to have greater level of food security. • Rural as opposed to urban households are more food secured and more aged household heads tends to have greater consumption. • Individuals in HHs with formal credit consume around 66 calorie per capita than an otherwise similar household without formal. Similarly households with MFI credit consumes 44 calorie. Bureau of Economic Research, University of Dhaka

  12. Credit, Food Security and Dietary Diversity (Cont.) Table 3: Dietary diversity scenario by credit program participation status Bureau of Economic Research, University of Dhaka

  13. Credit, Food Security and Dietary Diversity (Cont.) Figure 1: Frequency Distribution of Households by FCS FCS lies between 0 and 112 Bureau of Economic Research, University of Dhaka

  14. Credit, Food Security and Dietary Diversity (Cont.) Figure 2: Household Dietary Diversity Score HDDS ranges between 0 and 12 Bureau of Economic Research, University of Dhaka

  15. Credit and Agricultural Production • The study on credit and agricultural production tries to find out whether there exists relationship between agricultural production and credit in Bangladesh. We used three types of information to examine this association: HIES 2010; BER primary survey; and FGDs. • Agriculture production is represented by the total money value of different types of agricultural production (e.g. crop, fish, livestock and forestry) added up and converted in Taka (i.e. 000 taka). • Credit sources have been represented by three dummies for credit (i.e. formal, informal and quasi-formal or microcredit). Bureau of Economic Research, University of Dhaka

  16. Credit and Agricultural Production (Cont.) • The estimates show that, it is formal credit rather than informal or microcredit that have significant relationship with household agriculture production. • Further analysis to check whether the ‘access to credit dummy’ might cause self-selection bias in estimating agricultural production regression using PSM technique also indicate the above association between credit and agriculture production. Bureau of Economic Research, University of Dhaka

  17. Credit and Agricultural Production (Cont.) • With BER data: We used following variables for agricultural production e.g. ‘value of agricultural production in last year (i.e. 2011) converted in ‘000 taka’. Credit variables that have been used are ‘amount of loan received in last yearin ‘000 taka’. • Regression analysis using the BER survey data also found positive association between participation in credit program and agricultural production. • According to the regression results ‘value of agricultural production in last year (2011)’ shows a positive and significant association with the ‘amount of loan received in last year (2011). Bureau of Economic Research, University of Dhaka

  18. Key Findings • A major finding of the study is to show significant positive association between agricultural credit, food security and food production. This is true for all types of credit. • Credit augments household income from farm as well as nonfarm activities. • Among the three types of credit formal credit turn out to be a preferred option by the credit recipient despite some know problem of collateral, and transaction cost etc. • Another important observation is that timely sanction of credit, hassle free advance is more important to farmers than lower interest rate or any waiver on interest. • Inadequacy of the credit amount is another important finding. • Credit from micro-credit institutions has reported to be helpful for HHs in meeting expenditure such as education, health, housing, and food purchase etc. Bureau of Economic Research, University of Dhaka

  19. Policy Implications What are the main policy implications: Expansion of agriculture credit by formal financial institutions. In this regard, recent strategy adopted by Bangladesh Bank that ‘all types of commercial bank must extend agricultural credit facility’ is a programme in the right direction. Credit augments household income from farm as well as nonfarm activities. A careful balance must be maintained both formal and quasi formal institutions while devising their credit portfolio. In the case of credit from public institutions the potential recipient has to undergo unofficial transaction cost (e.g. time consumption due to bureaucratic process). Therefore an important policy issue is to streamlining the bureaucratic processes in public institutions. Along side the policy to expand formal credit, adequate attention must also be provided for hassle free operation of quasi-formal credit ensuring fair price and quantity. Bureau of Economic Research, University of Dhaka

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