The Effect of Domestic Violence on Cardiovascular Risk. Review of Economics of the Household (2022)
The prevalence of metabolic risk factors that contribute to cardiovascular disease (CVD), such as hypertension and high plasma glucose levels have seen a substantial increase globally. Violence elevates stress and increases CVD risk and yet, there is sparse evidence on the relationship between domestic violence and CVD risk factors. This study fills this gap by providing new empirical evidence by leveraging biomarker data from a large nationally representative survey. I find (i) a consistent positive causal effect of physical violence on prevalence of hypertension amongst women, (ii) a positive causal effect of emotional and sexual violence on prevalence of hypertension amongst women, (iii) No discernible effects of domestic violence on CVD risk for the men in these relationships.
The Effect of Marital Endowments on Domestic Violence in India. Journal of Development Economics (2020)
Numerous studies have documented a relationship between income and wealth of a woman and domestic violence. One such factor that could potentially impact domestic violence is the gold endowment a woman receives at the time of marriage. India presents a unique setting in which to test this relationship as, despite being unlawful, both dowry practices and domestic violence continue to prevail. As actual marital endowments may endogenously affect spousal match quality, I use the deviation of the price of gold at the time of marriage from its long-term trend as a source of exogenous variation to proxy for initial marital endowment and examine its effect on domestic violence. Results show a positive and significant effect of an unusually high price of gold at the time of marriage on domestic violence.
The Effect of Computer Use on Work Discretion and Work Intensity: Evidence from Europe (with Andrea Salvatori and Wouter Zwysen). British Journal of Industrial Relations (2019)
This paper studies changes in computer use and work discretion and intensity in the EU-15 between 1995 and 2015. We document that while the proportion of workers using computers has increased from 40% to more than 60%, there remain significant differences between countries even within the same occupations. Several countries have seen a significant increase in computer use even in low-skilled occupations generally assumed to be less affected by technology. Overall, the great increase in computer use between 1995 and 2015 coincided with a period of modest deterioration of job quality in the EU-15 as whole, as work discretion declined for most occupational and educational groups while work intensity increased slightly for most of them. Our OLS results exploiting variation within country-occupation cells point to a sizeable positive effect of computer use on work discretion, but to no effect on work intensity. Our instrumental variable estimates point to an even more benign effect of computer use on job quality as measured by work discretion and work intensity. Hence, the results suggest that the (moderate) deterioration in the quality of work observed in the EU-15 between 1995 and 2015 has occurred despite the spread of computers, rather than because of them.
Eliciting survival expectations of the elderly in low-income countries: Evidence from India (with Adeline Delavande & Jinkook Lee). Demography 54:673 (2017)
We examine several methodological considerations when eliciting probabilistic expectations in a developing country context using the Longitudinal Ageing Study in India (LASI). We conclude that although, on average, individuals are able to understand the concept of probability, responses are sensitive to framing effects and to own versus hypothetical-person effects. We find that overall, people are pessimistic about their survival probabilities compared with state-specific life tables and that socioeconomic status does influence beliefs about own survival expectations as found in previous literature in other countries. Higher levels of education and income have a positive association with survival expectations, and these associations persist even when conditioning on self-reported health. The results remain robust to several alternative specifications. We then compare the survival measures with objective measures of health. We find that activities of daily life, height, and low hemoglobin levels covary with subjective expectations in expected directions.
Regression Discontinuity Design (Edited by: P. Atkinson, S. Delamont, A. Cernat, J.W. Sakshaug, & R.A. Williams). SAGE Research Methods Foundations (2020)
Regression discontinuity design (RDD) is a causal inference technique that can be used with observational data. Social scientists are often faced with challenges when using observational data in contexts where an experimental design is infeasible. In such contexts, under fewer assumptions relative to other causal inference techniques, an RDD may be useful to isolate causal effects. RDD has gained traction over the past decades in various disciplines, including economics, political science, sociology, and epidemiology, to analyse questions related to labour, health, crime, voting behaviour, and environment, to name a few. This entry discusses the practicalities of implementing an RDD with a focus on the intuition behind its applicability. It first discusses its origins and details the identification strategy. This is followed by a discussion of some of the empirical applications of RDDs. Next, the entry outlines the key assumptions and considerations that must be satisfied for RDD to be valid and discusses the advantages of using RDDs. Finally, the entry discusses extensions to the RDD, namely cases with multiple cutoffs, regression discontinuity in time, regression kink design, and spatial discontinuities.