Pro-poorness of rural economic growth and the roles of education in Bhutan, 2007–2017

Abstract

Among south Asian countries, Bhutan has the second lowest poverty incidence; but, there is a large difference in poverty incidence between urban and rural areas. While urban areas registered a very small poverty incidence, 12.0% of rural population were still below the national poverty line in 2017. Poverty is by and large a rural phenominon in Bhutan. Against this background, this study examines whether Bhutan’s rural economic growth was pro-poor from 2007–2017 by using the Bhutan Living Standard Surveys. It also conducts an IV probit analysis to explore the determinants of poverty. Even in rural areas, growth is necessary for the reduction of poverty. Besides relying on trickle-down effects from hydropower projects and tourism, promotion of agriculture-based small scale industries is essential for the acceleration of rural economic growth, where further development of basic industrial and transportation infrastructure and socioeconomic facilities is imperative. The country also needs to promote and strengthen basic education since education is found to have played an important role in reducing poverty. Many rural households are vulnerable to poverty. To prevent vulnerable households from falling into poverty, more effective social safety net programs may be necessary based on regional differences in factors affecting living conditions.

Keywords:

• Pro-poor growth
• rural economic growth
• poverty incidence
• expenditure inequality
• education; Bhutan

JEL CODE:

• I32
• O15
• O18

Acknowledgement

The authors would like to thank reviewers for their helpful comments.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 Poverty incidence or poverty headcount ratio is defined as the proportion of people below the poverty line. In this paper, poverty incidence and poverty headcount ration are used interchangeably.

2 Using the national poverty line, the incidence of poverty is 33.7% in Afghanistan (2016), 24.3% in Bangladesh (2016), 21.9% in India (2011), 4.1% in Sri Lanka (2016), 25.2% in Nepal (2010) and 24.3% in Pakistan (2015) (World Bank 2020).

3 In this paper, income redistribution is referred to as the change in income distribution.

4 Kakwani (1997) rectified the poverty decompositioin method advanced by Datt and Ravallion (1992), which includes the residual term in addition to the growth and income redistribution components. Datt and Ravallion (1992) used their method to examine the contributions of economic growth and income redistribution to the change in poverty in India and Brazil.

5 Deutsch and Silber (2011) summarized the various alternative approaches that have appeared in the literature on pro-poor growth.

6 The amount of poverty is often measured by the following Foster-Greer-Thorbecke (FGT) poverty index (Foster, Greer, and Thorbecke 1984): $P_{\alpha }(z)=\frac{1}{n}{\sum }_{i=1}^q{\left(\frac{z-y_i}{z}\right)}^{\alpha },$ where n, q and $y_i$ are, respectively, the total number of people, the number of poor people, and per capita expenditure of ith person. When α = 0, 1 and 2, the index is, respectively, the head count ratio, the poverty gap index and the poverty severity index. In this study, we focus on the poverty headcount ratio (or the incidence of poverty), though it cannot account for the depth and severity of poverty.

7 Some studies use consumption expenditure per adult equivalence scale to account for differences in needs among household members, where children are given much smaller weights than adult household members. According to Haughton and Khandker (2009), however, adult equivalence scales are controversial and may not be estimated satisfactorily; thus, this study uses consumption expenditure per capita as a measure of welfare. It should be noted that the NSB estimates poverty incidence using per capita expenditures.

8 Using the current price poverty lines, Miranti (2010) converted current price expenditures to constant price expenditures in Indonesia.

9 For the definition of income redistribution, please see note 3.

10 We determined years of education based on the levels of education used in the Bhutan Living Standard Survey (see Table A2 in the appendix).

11 The correlation coefficient between edyear and m_edyear is around 0.5, while the correlation coefficient between the dependent variable and m_edyear is around -0.2.

12 The Gini coefficient can be obtained by the following formula: $G=\frac{2}{n\mu }\mathrm{c}\mathrm{\text{ov}}\left(i,y_i\right),$ where n is total number of households, $\mu$ is mean per capita expenditure, and $y_i$ is per capita expenditure of household i. The Gini coefficient satisfies several desirable properties as a measure of inequality such as anonymity principle, income homogeneity, population homogeneity and Pigou-Dalton transfer principle (Anand 1983). It ranges between 0 (perfect equality) and 1 (perfect inequality).

13 Hereafter, we use ‘the distribution of expenditure’ or ‘the expenditure distribution’ to refer to ‘the distribution of per capita expenditures’.

14 No education group includes those who have attended monastic schools as their highest education.

15 Though not shown in Table 8, 33% and 16% of urban households were in the no education and primary education groups in 2017, respectively.

Additional information

Funding

Akita is grateful to the Japan Society for the Promotion of Science for its financial support (Grant-in-Aid for Scientific Research 18K01589).

Notes on contributors

Takahiro Akita

Takahiro Akita is a Professor Emeritus of the International University of Japan. He holds a Ph.D. in regional science from the University of Pennsylvania. His research interests center around regional and urban economic development, Asian economic development, income inequality, poverty, and international trade. His research has appeared in Social Indicators Research, Asian Economic Journal, Bulletin of Indonesian Economic Studies, Annals of Regional Science, International Regional Science Review, and Journal of the Asia Pacific Economy among others. He serves as a member of the International Advisory Board of Bulletin of Indonesian Economic Studies and the Editorial Board of Bulletin of Monetary Economics and Banking.

Dorji Lethro

Dorji Lethro received MA in international development from the Graduate School of International Relations, International University of Japan and now works for National Statistics Bureau, Royal Government of Bhutan.