The impact of rural electrification on income and education: Evidence from Bhutan

• DOI: http://doi.org/10.1111/rode.12378
• Author: Santosh Kumar,Ganesh Rauniyar
• Date: 01 August 2018
• Published date: 01 August 2018

REGULAR ARTICLE

The impact of rural electrification on income and

education: Evidence from Bhutan

Santosh Kumar

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Ganesh Rauniyar

2

1

Sam Houston State University,

Huntsville, Texas, USA

2

Independent Evaluator, Paraparaumu,

New Zealand*

Correspondence

Santosh Kumar, Department of

Economics and International Business,

Sam Houston State University, Huntsville,

TX 77341-2118, USA.

Email: skumar@shsu.edu

Abstract

We investigate the impact of a rural electrification pro-

gram on household income and children’s schooling in

rural Bhutan. Using propensity score matching, we find

that electrification had a statistically significant impact on

nonfarm income and education. Nonfarm income

increased by 61 percent and children gained 0.72 addi-

tional years of schooling and 9 minutes of study time per

day. We do not observe significant effects on farm

income. Results are consistent and robust to different

matching algorithms. Our findings indicate that invest-

ments in reducing energy deficit may help improve

human welfare in Bhutan.

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INTRODUCTION

Despite large efforts targeted to ending poverty worldwide, close to 1 billion people still lived on

less than U.S.$1.25 a day in 2011 (World Bank, 2015). In the last decade, there has been a grow-

ing interest in understanding the role of rural electrification (RE) programs in improving welfare

and poverty reduction. Providing access to electricity remains one of the critical binding constraints

in spurring rural development and achieving the United Nations Development Programme’s com-

mitment to end poverty and provide universal energy access (UNDP, 2015). The electricity access

is expected to reduce rural poverty by increasing employment opportunities and access to

improved public services.

Access to electrification can potentially affect economic development through several channels

but the most evident link is through improved productivity at the individual and household levels.

The primary direct benefit of electricity is clean lighting source but it can also positively contribute

*Formerly with the Independent Evaluation Department, Asian Development Bank, Manila, The Philippines.

DOI: 10.1111/rode.12378

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©2018 John Wiley & Sons Ltd wileyonlinelibrary.com/journal/rode Rev Dev Econ. 2018;22:1146–1165.

to farm and nonfarm productivity through the improved production process and reduced cost of

production (Rud, 2012). Access to electricity could also facilitate the start of new businesses,

adoption of new technology, and mechanization of agricultural practices. Among other benefits,

electricity access contributes to health improvements as households switch away from kerosene

and coal to electricity (Barron & Torero, 2017): higher educational attainment (Lipscomb,

Mobarak, & Barham, 2013), and better food security and gender empowerment (Dinkelman,

2011; World Bank, 2008). Electrification may also enhance labor supply through time savings

when households switch away from firewood collection to a clean source of energy (Dinkelman,

2011).

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Despite these benefits, however, an estimated 1.2 billion people—16 percent of the global pop-

ulation—lacked access to electricity globally in 2016 (International Energy Agency, 2016). In this

study, we evaluate the impacts of the rural electrification program on household income and

schooling in rural Bhutan, a landlocked country neighboring India and China. With assistanc e from

the Asian Development Bank (ADB) and other international donors, Bhutan has made significant

progress in increasing electricity coverage from 17 percent in 1995 to 60 percent by 2009 (ADB,

2010). Despite this expanded electricity coverage and the far-reaching effects it may have on

human welfare, empirical studies on the impact of increased electrification rate in Bhutan are rare.

Against this background and context, this study aims to fill this gap in the existing literature by

estimating the impacts of electricity access on income and nonincome indicators of welfare in a

resource-constrained setting.

Although Bhutan has large sources of clean and renewable hydropower energy, electrification

rate has been limited and at subsistence level in the country.

2

Bhutan is a unique setting to exam-

ine the impacts of RE because mountainous terrains, scattered settlements, and low electricity

demand in the villages make the extension of grid lines difficult and capital intensive. First, the

rugged terrain and scattered population densities make it challenging to realize the full benefits

electrification may have on agriculture, thereby affecting farm income in unpredictable ways. Sec-

ond, compared with other sources of electricity generation (coal, thermal etc.), selection bias inher-

ent in the evaluation of infrastructure projects owing to nonrandom project placements may be

smaller because hydropower projects can only be placed near a river source, which is given by nat-

ure. Our study covers the evaluation of two RE projects funded by the ADB from 2000 to 2006 in

Bhutan.

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Evaluating impacts of large infrastructural projects such as electricity provision suffers from the

econometric challenge as experimental data are not readily available. In the nonexperimental set-

ting, the major challenge is to address the potential selection bias. It is quite possible that charac-

teristics of electrified households are different from nonelectrified households and this may bias

the impact results. Furthermore, infrastructure projects could be targeted in areas that are growing,

politically important, industrialized, and close to urban centers. The nonrandom selection of pro-

jects is likely to bias the comparison of electrified and nonelectrified groups and would be con-

founded with the unobserved heterogeneity. Some of the previous studies on this topic either have

relied on randomized experiments (Bernard & Torero, 2015) or instrumental variables (IV) meth-

ods to deal with the fact that access to electricity is not randomly assigned (Chakravorty, Pelli, &

Beyza,2014; Dinkelman, 2011; Rud, 2012).

In the absence of a valid instrument and suitable data, we use statistical matching techniques to

estimate the plausible causal effect of electricity access on income and education. Our empirical

analysis uses nonexperimental data collected by the authors in 2010. We use a rich set of

household and village-level variables to capture individual and village-level heterogeneity so that

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