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Rural Livelihood Diversification Strategies and Household Welfare in Bhutan

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Abstract

This paper analyzes rural livelihood diversification strategies and their impact on household welfare using the Bhutan Living Standard Survey 2012. The multinomial estimation shows that education, asset endowment, labor availability, and sex (male/female) of the household head play a vital role in livelihood diversification into non-agricultural sectors. Propensity score matching estimates illustrate that rural households diversifying outside agriculture have higher income and lower poverty levels compared to households pursuing only farming for their livelihoods. Livelihood diversification into non-farm activities can help reduce poverty levels in the range of 6–9 per cent, suggesting the importance of livelihood diversification in reducing poverty and increasing household income in Bhutan.

Cet article analyse les stratégies de diversification des moyens de subsistance en milieu rural et leur impact sur le bien-être des ménages à l’aide du sondage de 2012 sur le niveau de vie au Bhoutan. L’estimation multinomiale montre que l’éducation, la dotation en capital, la disponibilité de la main-d’œuvre et le sexe (masculin/féminin) du chef de ménage jouent un rôle essentiel dans la diversification des moyens de subsistance dans les secteurs non agricoles. Les estimations du score de propension illustrent le fait que les ménages en milieu rural qui se diversifient en dehors de l’agriculture ont des revenus plus élevés et des niveaux de pauvreté inférieurs à ceux des ménages qui n’ont que l’agriculture pour leur subsistance. La diversification des moyens de subsistance vers des activités non agricoles peut aider à réduire les niveaux de pauvreté de l’ordre de 6 à 9%, ce qui montre l’importance de la diversification des moyens de subsistance pour réduire la pauvreté et augmenter le revenu des ménages au Bhoutan.

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Acknowledgements

We would like to acknowledge with thanks the National Statistical Bureau (NSB) of Bhutan for providing us the Bhutan Living Standard Survey data.

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Authors and Affiliations

  1. International Maize and Wheat Improvement Center (CIMMYT), Carretera Mex-Veracruz, km. 45, El Batan, CP 56237, Texcoco, Mexico, Mexico

    Dil Bahadur Rahut & Khondoker Abdul Mottaleb

  2. International Maize and Wheat Improvement Center (CIMMYT), NARC Park Road, Islamabad, Pakistan

    Akhter Ali

Authors
  1. Dil Bahadur Rahut
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  2. Khondoker Abdul Mottaleb
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  3. Akhter Ali
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Corresponding author

Correspondence to Dil Bahadur Rahut.

Appendix

Appendix

Since some researchers might raise concerns about the assumptions being imposed when using the multinomial logit model and since some results run somewhat counter to prior expectations, we undertake a number of robustness checks. First, we performed Wald tests and LR tests for combining alternatives to test that all of the coefficients associated with an independent variable are simultaneously equal to zero (i.e., test that a variable has no effect) and presented the result in Table A.1.

Table A.1 Likelihood-ratio and Wald tests for independent variables
Full size table

Second, we performed the likelihood-ratio and Wald tests for independent variables to examine whether or not the independent variables distinguish between two outcomes; this test is normally used to determine if two outcomes can be combined. The results of the likelihood-ratio and Wald tests for independent variables are presented in Table A.2.

Table A.2 Testing pooling restrictions in regressions shown in Table 4 in the main body of the paper
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Third, we performed a Hausman test to assess the assumption of the independence of irrelevant alternatives (IIA). We performed a test for pooling states in the multinomial logit model; that is, we test whether the different groups of households (Groups 1 through 5) can be combined based on their characteristics. The results of tests shown in Table A.3 demonstrate that the effects of the independent variables for different groups are not similar. The Chi-square test statistics calculated for each specification indicate that the IIA assumption could not be rejected.

Table A.3 Hausman tests of the IIA assumption
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Rahut, D.B., Mottaleb, K.A. & Ali, A. Rural Livelihood Diversification Strategies and Household Welfare in Bhutan. Eur J Dev Res 30, 718–748 (2018). https://doi.org/10.1057/s41287-017-0120-5

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