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Social, Economic, and Environmental Issues in Developing Economies

Paper Session

Friday, Jan. 4, 2019 12:30 PM - 2:15 PM

Hilton Atlanta, 223
Hosted By: Association of Indian Economic and Financial Studies
  • Chair: Amit Batabyal, Rochester Institute of Technology

Aid Effectiveness: Human Rights as a Conditionality Measure

Mustapha Douch
Loughborough University
Huw Edwards
Loughborough University
Todd Landman
University of Nottingham
Sushanta Mallick
Queen Mary University of London


The ’conditionality hypothesis’ proposed by Burnside and Dollar (2000) suggests that aid is only effective
in augmenting growth in the presence of a sound policy environment. This hypothesis was so influential that its
policy recommendation, to provide aid conditional upon recipient domestic policies, is currently the dominant
ODA allocation criterion. However non-economic dimensions of development (political and institutional) are
increasingly seen as fundamental. For this reason, this paper focuses on the relationship between repression
and corruption, and argues that the measurement and monitoring of human rights provision in particular, is
a useful tool in gauging the likely effectiveness of aid, based on the finding that countries with better human
rights performance experience positive growth, reflecting stronger governance.

A Safe Minimum Standard, an Elasticity of Substitution, and the Cleanup of the Ganges in Varanasi

Amit Batabyal
Rochester Institute of Technology
Shiqi Xing
Rochester Institute of Technology


Despite the salience of campaign from both environmental and touristic perspectives,
there are only two papers by Batabyal and Beladi (2017, 2018) that
have shed theoretical light on the Ganges cleanup problem and its connection to the sustainability
of tourism. Given the insufficient attention that has been devoted to the cleanup of the Ganges in
the literature, we extend the analysis in Batabyal and Beladi (2017, 2018) and concentrate on two
specific research questions. First, we introduce the notion of a safe minimum standard (SMS)1
into the analysis and then show how to analyze a stochastic model of the Ganges cleanup problem when
the SMS is explicitly accounted for. Second, we study how the elasticity of substitution between a
composite consumption good and water quality in the Ganges---modeled by the SMS---affects the
tradeoff between consumption and water quality maintenance. We now provide additional details
about how we propose to theoretically study the above described research questions.

Are Urban-Rural Welfare Differences Growing in India?

Azam Mehtabul 
Institute of Labor Economics


Using data from the large scale consumption expenditure surveys collected by Indian National
Sample Survey Organization, we examine the urban-rural welfare gap in India in
1983, 1993-94, 2004-05, and 2011-12 across the entire distribution. Our main measure of
welfare is spatially adjusted per capita consumption expenditure. We nd that the urbanrural
gap increased considerably between 1993-94 and 2004-05, and increase is larger at the
higher quantiles. Using the unconditional quantile regression decomposition, we nd that
the majority of the gap is explained by the urban advantage in endowments in all four years.
The contribution of the unexplained eect (dierences in rewards) in urban advantage was
negative in 1983 and 1993-94 across the entire distribution. We nd that dierence in educational
distribution across urban and rural areas is the most important driver of the observed
gap. We nd similar patterns using income data for 2004-05 and 2011-12 from India Human
Development Surveys

Digging deeper into the Dynamics of Female Ownership of Firms and Access to Finance: An Empirical analysis of Indian Firms

Nabamita Dutta
University of Wisconsin-La Crosse
Sushanta Mallick
Queen Mary University of London


Access to finance for firms is a much explored topic in the development as well as entrepreneurship literature. Studies on these topics are relatively scant in the context of firms in emerging markets. Using World Bank Enterprise Survey (WBES) data for 9281 Indian firms during June 2013-December 2014, we explore the role of gender in explaining difficulty in accessing finance for start-up activity. Our baseline results show that female-owned firms actually face less obstacles in accessing finance compared to male owned firms. But on delving deeper, we find that the composition of firm ownership in terms of gender matters. Our results show that firms that are dominantly managed by females face greater difficulty in accessing finance compared to firms that have low levels of female leadership. This supports two strands of theoretical studies - ‘ownership signaling theory’ reflecting a venture’s viability and the entrepreneurs’ commitment to business, and ‘gender congruity theory’ suggesting stereotypical beliefs about the abilities of male and female entrepreneurs. Our results are robust to different identification strategies including propensity score matching. Further, we also explore possible channels explaining the negative impact of female dominated firms in accessing finance. These channels are greater government ownership of firms, funding investment through one’s own capital and higher level of sales at the national level, which lend support to our main result that women entrepreneurs, under certain circumstances, may not be as credit-constrained as male entrepreneurs.

India's Mid-day Meal Program and Schooling: An Evaluation Based on Machine Learning

Dweepobotee Brahma
Western Michigan University
Debasri Mukherjee
Western Michigan University


Using state-level data on India’s Mid-Day Meal program (school lunch program for children) we scrutinize
if funds disbursed and food-grains supplied for the purpose can actually serve as good determinants of
number of children covered (fed) by the scheme (our dependent variable). Our standard regression studies
find that the effect of food-grain supplied has statistically significant effect on the dependent variable while
the marginal effects of funds/money disbursed is not statistically significant. Using LASSO based Machine
Learning techniques and after controlling for several correlated variables and state level factors we find that
both policy variables - funds and food-grains however act as good out-of-sample predictors of number of
children being covered. Evaluation of out-of-sample prediction performance of regression models and
covariates is a very important but mostly an uncharted territory in development economics. Note that funds
are used partly to provide fixed costs of the food service provided, and therefore it is not surprising that the
coefficient estimate of this covariate (i.e., its marginal effect on dependent variable) does not appear to be
statistically significant; but it can still act as a good overall predictor for our dependent variable.
Valerie Cerra
International Monetary Fund
Banani Nandi
AT&T Labs
Ram Upendra Das
Center for Regional Trade-India
Kandarp Srinivasan
Northeastern University
Keshab Bhattarai
University of Hull
JEL Classifications
  • Y9 - Other
  • O5 - Economywide Country Studies