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Impact of farm level corruption on the food security of households in Bangladesh

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Abstract

In this article, we have analyzed the impact of farm level corruption on households’ food security using survey data collected from 210 Bangladeshi rice farmers. Econometric results confirm that the cost of corruption adversely affects households’ calorie consumption. The marginal effect of corruption is higher for the low expenditure households relative to the high expenditure households. This happens because the high expenditure households exhibit more flexibility in terms of adjusting their budgets and hence, are able to cover the cost of corruption without affecting their food consumption, whereas for the low expenditure households such flexibility is limited and hence are forced to compromise on their food budget. Variables such as the better education of women and land holding also positively contribute to food security.

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Notes

  1. The ranking here was done using the TIB’s database of ‘National Household Survey 2007 on Corruption in Bangladesh.’

  2. An administrative unit in Bangladesh that is above the village level but below the district level.

  3. The dependent variable is basically a snapshot of household’s annual consumption. Whereas the list of independent variables also includes two annual variables (annual expenditure and annual cost of corruption). Since establishing a relationship here denies possibilities of seasonal effects, one may argue for annual consumption data. But the accuracy of food consumption data reduces with the length of recall period (Bouis 1994) and hence we have used the seven day recall method during the survey. Use of this method is common in the literature (Garrett and Ruel 1999; Babatunde and Qaim 2009).

  4. Nutritional (calorie) based Equivalence Scales have been sourced from Dercon and Krishnan (1998).

  5. To deal with seasonality and to obtain a high response rate during interview, expenditure was used instead of income (Thomas 1993; Subramanian and Deaton 1996; Garrett and Ruel 1999; Aguiar and Hurst 2003).

  6. This variable was included to describe the relationship between calorie intake and price. Rice, potato and lentil were considered as these three accounted for more than 81 percent of our sample households’ calorie intake. It is the ratio of a household’s total expenditure for calories to the total calories obtained from the three selected food items. Expenditure for a food item was estimated by multiplying calorie price by total calories obtained from that particular food item.

  7. The variables here were included in order to ascertain whether expenditure and calorie price have a stronger effect on calorie regression for households with higher costs of corruption, and vice versa.

  8. Household members, who were below seven years of age, were considered as children.

  9. For households, where the mother was absent, the education of women (in most cases, the grandmother or elder sister) who carried out the responsibility of the mother was used.

  10. Based on a household’s per-capita annual expenditure, households were classified as poor or non-poor. The area specific poverty lines available in HIES (2010) were used (BBS 2010). The poverty lines were estimated using the Cost of Basic Needs (CBN) method.

    .

  11. One can also be suspicious of the interaction term being endogenous. We have conducted Durbin-Wu-Hausman χ 2 test for the cross term, accepting endogeneity for the expenditure variable. The test statistics for both models were insignificant, suggesting that the cross term is exogenous.

  12. The variable, off-farm income, can also be endogenous due to its simultaneous causality with the expenditure variable. To be sure of this, the Durbin-Wu-Hausman χ 2 test was conducted. Five variables were selected as instruments here. These were: dummy of location, age of the household head, dummy of membership in NGOs, number of active adult members in the family and distance from the nearest market. The test statistics here weere non-significant, suggesting that off-farm income does not exhibit an endogeneity problem.

  13. The output of the 1st stage regression is presented in Appendix Table 4.

  14. Baum et al. (2007) wrote the ivreg2 command for STATA, and it is used here.

  15. Marginal effect is also calculated for Model 2, but as the results from both models were similar, only those from Model 1 are presented here due to space constraints.

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Acknowledgements

The financial support by the German Academic Exchange Service (DAAD) is gratefully acknowledged. Authors are grateful to two anonymous referees for helpful comments on an earlier version of this paper. Authors acknowledge Mr. R.H. Itagi for editing the manuscript. All errors that remain are ours.

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Authors and Affiliations

  1. Department of Agricultural Economics, Bangabandhu Sheikh Mujibur Rahman Agricultural University (BSMRAU), Salna, Gazipur, 1706, Bangladesh

    Asif Reza Anik

  2. Agricultural Development and Rural Transformation Centre, Institute for Social and Economic Change, Bangalore, 560072, India

    A. V. Manjunatha

  3. Institute of Project and Regional Planning, Justus Liebig University, Giessen, Senckenbergstr. 3, 35390, Giessen, Germany

    Siegfried Bauer

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  1. Asif Reza Anik
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Correspondence to Asif Reza Anik.

Appendix

Appendix

Table 4 First stage regression results of the 2SLS (Dependent variable: Expenditure (BDT/AE))
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Anik, A.R., Manjunatha, A.V. & Bauer, S. Impact of farm level corruption on the food security of households in Bangladesh. Food Sec. 5, 565–574 (2013). https://doi.org/10.1007/s12571-013-0282-8

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