Abstract

Internal migration can increase regional disparities in healthcare costs between economically disadvantaged and more prosperous regions in the same country. Persons who move to more prosperous regions tend to be young and healthy while persons who move to or remain in economically disadvantaged regions are on average older and sicker. In this study, we propose a novel framework that allows estimating the effect of internal migration and resulting changes in population composition on average healthcare costs in different regions. Our framework refines a “move people back” approach by adjusting for place effects. Based on data for the entire population of the Netherlands we show that internal migration during the 1998-2018 period  increased average healthcare costs in economically disadvantaged provinces by up to 3.4%, and it explains 29.3% of regional variation in healthcare costs.

Abstract

Characteristics of a place, such as healthcare access and the local environment, influence healthcare utilization. Refugees resettled in developed countries are often assigned locations based on the host country’s assignment policies, yet the impact of initial placement on their healthcare usage remains understudied. I use Dutch administrative data to examine the effect of conditions in the initial municipality on healthcare utilization of refugees, leveraging the random assignment of refugees. Being assigned to a municipality with a higher healthcare utilization as measured by depression medication usage, hospital visits, and general practitioner costs among non-refugees increases healthcare utilization of refugees. I provide suggestive evidence on possible mechanisms and find that local healthcare access and socio-economic status of the municipality play an important role in healthcare utilization of refugees. This study contributes to the ongoing policy debates on providing separate and more targeted healthcare services for the refugee population.

Abstract

India consistently ranks among the countries with the highest levels of ambient air pollution worldwide. At the same time, it faces significant challenges in neonatal health, with newborns having low birth weights which has been shown to have long term impacts on health and labor market outcomes. Using data from the Indian Demographic and Health Survey (DHS), we examine the impact of in-utero exposure to particulate matter (PM2.5) on birth outcomes. We exploit variation in wind direction as an instrument for in-utero particulate matter exposure for each child. We find that reducing in-utero PM2.5 exposure by one standard deviation would lead to 1.4% increase in average birth weight. Combining our estimates with prior studies, we find that the observed improvements in both average birth weight and reductions in low birth weight incidence from meeting WHO air quality standards could yield substantial long-run economic benefits, potentially amounting to billions of dollars annually in addition to broader gains in child health.

Abstract

Previous research, focusing primarily on high income countries, has linked later sunsets to sleep deficits and worse health outcomes. These results might not generalize to low- and middle- income countries, which have different socioeconomic, cultural, and environmental conditions. Using data from the 2015-16 and 2019-21 waves of India’s Demographic and Health Surveys (DHS) and exploiting within-district variation in annual average sunset times, we estimate the causal impact of later sunsets on the long-term health outcomes of individuals. We find that later sunsets leads to a lower prevalence of anemia, diabetes, and thyroid disorders and an improvement in the overall health index. To explore mechanisms, we analyze variation in time allocation due to a later sunset time using the 2019 Time Use Survey. We find that individuals experiencing later sunsets sleep better and exercise more, but do not change their sedentary leisure activities. Additionally, they consume healthier food and increase labor supply. These lifestyle changes may explain the health improvements associated with delayed sunsets in India.

Abstract

In this study, I delve into the factors shaping the adoption of new farming practices among Indian farmers, with a particular focus on the role of information access and its diverse sources. Leveraging nationally representative data on rural households from the National Sample Survey Office, Government of India for the year 2019, I employ logistic regression to gauge the likelihood of farmers adopting new agricultural techniques based on the information they receive from various channels. Additionally, I undertake spatial linear regression analysis to unravel the dynamics of information spillovers pertaining to new farming practices across districts. The results highlight the significance of the information source in driving adoption decisions, with progressive farmers and input dealers emerging as influential sources. Moreover, the spatial analysis provides compelling evidence of information diffusion across district boundaries, highlighting the varying efficacy of different information channels. These findings offer valuable insights for policymakers aiming to craft targeted interventions aimed at shaping farmers' decision-making processes regarding the adoption of innovative farming practices.