Bio
I'm an economist at the King's India Institute and Department of International Development at King's College London,
and I work on questions of causal inference in development using observational data, particularly in the context of discrimination and inequality.
I am an Associate Editor for the Journal of Development Studies and Economia Politica, and am currently leading an ESRC-funded project on the role of small firms in UK-India trade.
I received my PhD in Economics from the University of East Anglia, MA in Economics from the Delhi School of Economics, and BA (Hons.) in Mathematics from St. Stephen’s College, Delhi University. Before embarking on my PhD I worked for the Social Initiatives Group of ICICI Bank, an erstwhile major funder of non-profit activities in India.
Publications
(with Ragupathy Venkatachalam)
Review of Development Economics, 2023
Abstract (click to expand): A key aim of studying development is to understand the factors that shape socioeconomic progress and explain inequalities. In empirical work, the predominant focus has been on posing these questions in the language of causal inference: how one or more variables effect an outcome of interest, with the estimation of Average Treatment Effects (ATE) becoming prioritised as the key objective. The ‘credibility revolution’ and the emphasis on randomised controlled trials in research on development has cemented this dominance, because randomisation is well-suited to estimating the ATE. This paper argues that this dual dominance—ATE as main question of interest, and experiment as preferred method—is narrow and restrictive. We propose causal mediation frameworks as an alternative, which are routinely used in disciplines including epidemiology, psychology, sociology and political science where causal mechanisms are an equally important focus. We introduce key concepts and definitions of path-specific effects, and discuss identification and estimation approaches. We illustrate applications for development and demonstrate how causal mediation brings the focus back to contextual knowledge, combining this with empirical rigour.
(with Lucio Esposito, Adrián Villaseñor & Roney Fraga )
Journal of Income Distribution (forthcoming)
Abstract (click to expand): Hey and Lambert (1980) provided an interpretation of indices of relative deprivation in terms of interpersonal comparisons: the indices would quantify harmful feelings of frustration, inadequacy and inferiority arising from looking upward to better off others. A growing body of literature has followed this interpretation in quantitative studies which indeed typically reveal a negative association between relative deprivation and social outcomes such as happiness, health or education. However, evidence able to directly link a negative coefficient of relative deprivation to the mechanisms deflating and harmful for the self which underlie Hey and Lambert’s interpretation is lacking. We fill this gap by conducting a mixed method study. Using data from three waves of Brazilian high-stake secondary education exams for the state of Rio de Janeiro (N=245,555), we first analyse exam scores in econometric models where absolute income and relative deprivation are jointly employed as explanatory variables. Next, we interpret and expand upon our quantitative results using primary data collected via semi-structured interviews and focus group discussions with 30 local secondary school teachers. In conformity with Hey and Lambert’s interpretation, we find robust negative coefficients for relative deprivation, which teachers explain reporting the detrimental effects lower socioeconomic status and upward comparisons have on pupils’ self-esteem, motivation and aspirations.
(with Ying-Fang Kao)
in Artificial Intelligence, Learning and Computation in Economics and Finance. (Ed. Ragupathy Venkatachalam), 2023, New York: Springer.
Abstract (click to expand): The use of computers has revolutionised our ability to learn about ourselves and the world around us. Beyond the goal of performance or prediction, the extent to which machine actions and algorithms are explainable and intelligible to human beings - Explainable AI - are increasingly becoming important, especially so in socio-economic contexts, and where life and health outcomes are involved. While the Turing test aims to distinguish between machine and human, Judea Pearl’s ‘mini’ Turing test focuses on one crucial aspect of this distinction: the ability to reason causally and thereby answer causal queries based on counterfactuals. At the heart of counterfactual-based reasoning lies the role of causal expla- nation, or delineating the underlying causal mechanisms. In this chapter we make a small step towards demonstrating how causal models can be brought to observational data to answer useful counterfactual queries in contexts where complex social processes are at play. We estimate the causal effects of education on female labour-force participation in India in a causal mediation framework. We consider the role of positive assortative marital-matching in terms of education which leads to husbands’ levels of education mediating the effect of women’s education on their subsequent labour force participation, and we use a g-formula based approach to estimate the total causal and natural direct effect of education.
in Handbook on Economics of Discrimination and Affirmative Action (Ed. Ashwini Deshpande), 2022, New Delhi: Springer.
Abstract (click to expand): This essay provides a thematic discussion of discrimination in credit. Through a selective review of the literature I illustrate that caste, gender and race are all persistent axes of discrimination in credit, and that discrimination has been shown to exist across diverse contexts. I examine the main conceptual tools used in this literature to shed light on the causal mechanisms that lead to discrimination, and in particular attempt to delineate the role of individuals, institutions and formal regulation. By briefly exploring the links between discrimination in credit and group-based inequality in other arenas of economy and society, I argue why the implications of the former extend far beyond credit alone, and are a powerful force in shaping inequality more generally including across generations.
(with Ragupathy Venkatachalam)
Structural Change and Economic Dynamics, 2021
Abstract (click to expand): Economic systems are characterised by constant change and evolution, and explanations concerning the properties of economic structures have received sustained interest. The structure of a system and its dynamics can influence each other through feedback effects. In this paper we offer a brief survey of how structure plays a role in dynamic economic theory – in particular, growth and business cycles. We propose a morphogenetic framework, inspired from the creation of forms in developmental biology, as a potential unifying approach for studying economic structures and their dynamics. We synthesise insights from three different strands of research, focusing on the role of coupling, diffusion and symmetry-breaking. We highlight their existing and prospective links with economics.
(with Lucio Esposito & Adrián Villaseñor)
Journal of Population Economics, 33: 1069–1099, 2020
Abstract (click to expand): We study the effect of birth order on educational outcomes in Mexico using 2 million observations from the 2010 Census. We find that the effect of birth order is negative, and a variety of endogeneity and robustness checks suggest a causal interpretation of this finding. We then examine whether these effects vary across households’ economic status, and we find significant heterogeneity across absolute as well as relative standards of living, operationalized as household wealth and relative deprivation. Finally, we find that firstborns’ advantage is amplified when they are male, and in particular when other siblings are female.
(with Ragupathy Venkatachalam)
Journal of Development Studies, 55(8): 1816-1833, 2019
Abstract (click to expand): This paper examines caste-based differences in farmers’ access to bank loans in rural India. We investigate whether banks practice taste-based discrimination on the basis of caste. In order to identify potential discrimination, we consider loan applications and approval decisions separately. We find significant inter-caste differences in application rates, and evidence of discrimination against Scheduled Tribe borrowers at the approval stage. To rule out the role of statistical discrimination, we simulate unobserved credit histories with various distributions. Evidence for taste-based discrimination persists despite accounting for unobservables. However, we find that this discrimination does not affect small farmers.
Ideas for India article
Applied Economics Letters, 25(6): 409-414, 2018
Abstract (click to expand):
Recent research shows that the gap in learning achievement between private and government schools in India can be explained away by self-selection. Analysing four rounds of panel data and distinguishing between ‘knowing’ and ‘applying’ dimensions of maths learning, I find that there is no private school advantage in the applying domain but that there is an advantage in the knowing domain.
Economia Politica, 33: 83-98, 2016
Abstract (click to expand):
This paper considers the application of randomised controlled trials (RCTs) to improve public systems in developing countries. Arguing that existing critiques of RCTs as to problems with extrapolation and narrowness of scope are especially relevant in this context, I consider the claim that these shortcomings can be ameliorated through better causal explanations. I analyse how theoretical mathematical models are used to construct causal explanations, and argue that it is still difficult to extrapolate or address the subjectivity inherent in the choice of interventions. I illustrate these arguments using two prominent RCTs that have trialled interventions to improve government schools in India.
World Development, 43: 315-328, 2013
Abstract (click to expand):
This paper analyzes whether caste impedes access to formal agricultural credit in India. Credit is provided mainly through cooperative and commercial banks. Using national data, we find that cooperative banks discriminate against lower caste borrowers, and find weak evidence that commercial banks instead bias lending in their favor in accordance with affirmative action policies. We compare the organizational structures of the two types of bank, and explain discrimination by cooperative banks in terms of interest group capture at the district level by showing that discrimination takes place in those districts where higher castes dominate.
Ideas for India article.
Other writing
Times Higher Education. (April 28 2022)
UK in a Changing Europe. (May 25, 2021)
The Indian Express. (June 3, 2020)
With Ragupathy Venkatachalam.
IHDS newsletter (December 2018)
With Ragupathy Venkatachalam.
Ideas for India blog (September 2017)
Ideas for India blog (June 2013)
Economic and Political Weekly, 65(7): 41-45, 2010
Norwich Economic Papers, (2010), Vol. 1
Work in progress
With Ragupathy Venkatachalam
The absolute and relative facets of the economic gradient in educational attainment: mixed methods evidence from Rio de Janeiro
With Lucio Esposito, Adrián Villaseñor and Roney Fraga Souza
Research grants
ESRC-ICSSR grant, £431,070 (2020)
With Kamini Gupta and Prateek Raj
King’s Faculty Research Fund, £7,936 (2020)
DecovIndia website
Social and Economic Dimensions of Health and Morbidity (PI: Ashwini Deshpande)
Wellcome Trust Small Grant in Humanities and Social Science, £25000 (2019)
Caste in Contemporary India
King’s College London Faculty Research Fund, £4000 (2018)
Teaching
Quantitative methods for causal inference
2017-
Dissertation research methods
2020-
Economic analysis for emerging economies: microeconomics
2013-2016
India's economy: Structures, policies and challenges
2013-2016
Assorted
Website: This website was built using Hugo, relying heavily on Paul Clist's code. Feel free to copy my code.
