Ridhi Kashyap

Global cultural diffusion theories have long emphasized how institutional actors such as intergovernmental organizations, international non-governmental organizations, and state agencies spread cultural scripts. We theorize that mobile internet constitutes a qualitatively distinct pathway for the diffusion of these scripts, shifting exposure from institutionally mediated and episodic to more individualized, continuous, and algorithmically curated. This reconfiguration changes both which cultural models individuals encounter and the frequency with which individuals are exposed to them. Using the staggered rollout of mobile internet across Nigeria as an empirical case, we find that expanding coverage reduces fertility, corresponding to a 9% relative decline in the annual probability of birth, consistent with shifts in contraceptive use, ideal family size, and women’s autonomy in financial and healthcare decision-making. These findings suggest that digital infrastructure does not simply extend existing diffusion processes but can reshape them, with measurable consequences for family life.

The quantification and analysis of forced displacement, driven by political unrest or natural disasters, has become increasingly central to both humanitarian and demographic research. With displaced populations reaching record numbers, there is an urgent need for accurate and timely data on displacement patterns, particularly disaggregated by age and gender. This paper introduces an analytical toolbox designed to leverage the growing diversity of digital trace data that overcomes disruptions of traditional data collection systems during crises, enabling high‐frequency monitoring of forced displacement. The toolbox enhances our understanding of the magnitude, pace, and subpopulation heterogeneity of displacement dynamics. We apply this toolbox to the Gaza Strip following the 2023 Hamas attack. Deriving population estimates using data from Facebook's marketing API in combination with pre‐war population data, we demonstrate how this toolbox facilitates a multifaceted assessment of the consequences of war on population movement, connects mobility patterns to ground events, dissects displacement by gender, and enables cross‐country comparisons. Ultimately, the analysis highlights the unparalleled relative magnitude of forced displacement in the Gaza Strip from October 7, 2023, to May 15, 2024, with up to 70 percent of the population displaced, alongside increasing volatility in population movements as the conflict persists.

The COVID-19 pandemic led to substantial life expectancy losses globally. Historically, life expectancy reversals have been followed by rapid returns to previous trajectories, but whether this is true for the COVID-19 pandemic is still unknown. We update life expectancy estimates through 2024 for 34 high-income countries and quantify annual and cumulative life expectancy “deficits” by comparing observed life expectancy with counterfactuals based on pre-pandemic trends. Five years after the pandemic’s onset, recovery remains incomplete in most countries. In 2024, 31 out of 34 countries still had lower life expectancy than expected. Across 2020-2024, cumulative deficits were statistically significant in nearly all countries. We identify four distinct life expectancy trajectories: (a) first wave peak (largest deficits in 2020 with gradual recovery); (b) second wave peak (largest deficits in 2021 with a sharper rebound); (c) late peak (minimal early impact followed by smaller deficits from 2022 onward); (d) prolonged depression (smaller but persistent deficits without a sharp peak). In general, countries with severe second-wave peaks (such as the USA and Bulgaria) had the largest cumulative deficits. In contrast, countries that delayed widespread infection (e.g., Norway, Japan) saw later deficits that persisted through 2024, but with lower cumulative mortality. Our findings suggest that COVID-19 was not a uniform, short-lived mortality shock. Instead, most high-income countries experienced multi-year disruptions to life expectancy trajectories, with variable patterns of recovery that continue to shape population health five years on.

Human sex ratios at birth (SRBs) shape population composition and are closely linked to maternal health and gender discrimination. In the context of environmental change, SRBs may theoretically be skewed by physiological or behavioral responses to exposure to extreme heat. However, evidence for this is limited. In this study, we estimate the effect of prenatal exposure to temperature on birth sex by linking survey data on 5 million live births in 33 sub-Saharan African countries and India with high-resolution temperature data. To distinguish between spontaneous and induced abortions, we exploit sociodemographic differentials, exposure timing, and regional differences in son preference. We find that days with a maximum temperature above 20 °C are negatively associated with male births in both regions. In sub-Saharan Africa, we observe fewer male births after high first-trimester temperature exposure, consistent with increased spontaneous abortions from maternal heat stress. This is particularly true for births by mothers in rural areas, with little formal education, and for higher birth orders. By contrast, in India, we find that second-trimester temperature exposure is associated with fewer male births, consistent with reductions in induced sex-selective abortions. As expected, these reductions are concentrated in high birth orders and older mothers. We also find large reductions in male births by sonless mothers in northern Indian states, where son preference is greater. These findings demonstrate that heat exposure harms maternal health, increases prenatal mortality, and influences family planning behavior, leading to a complex effect on SRBs.

The digital revolution has ushered in many societal and economic benefits. Yet access to digital technologies such as mobile phones and internet remains highly unequal, especially by gender in the context of low- and middle-income countries (LMICs). While national-level estimates are increasingly available for many countries, reliable, quantitative estimates of digital gender inequalities at the subnational level are lacking. These estimates, however, are essential for monitoring gaps within countries and implementing targeted interventions within the global sustainable development goals, which emphasize the need to close inequalities both between and within countries. We develop estimates of internet and mobile adoption by gender and digital gender gaps at the subnational level for 2,075 regions in 117 LMICs from 2015 through 2025, a context where digital penetration is low and national-level gender gaps disfavoring women are large. We construct these estimates by applying machine-learning algorithms to Facebook user counts, geospatial data, development indicators, and population composition data. We calibrate and assess the performance of these algorithms using ground-truth data from subnationally representative household survey data from 33 LMICs. Our results reveal striking disparities in access to mobile and internet technologies between and within LMICs. These disparities imply that as of 2025, women are 19% less likely to use the internet and 8% less likely to own a mobile phone in LMICs, corresponding to over 190 million fewer women owning a mobile phone and over 320 million fewer women using the internet.

Digital resources such as laptops have the potential to improve access to educational resources and provide personalized and uninterrupted learning opportunities for students. The impacts of these technologies may be especially salient in contexts where classroom sizes are large and schooling quality is poor. Here, we study the impacts of access to laptops on foundational math proficiency in one such context, i.e., India, exploiting plausibly exogenous variation in the implementation of the Tamil Nadu Free Laptop Scheme (TFLS). Introduced in 2011, the TFLS was one of the largest and targeted free laptop programs in the world, distributing over 5 million laptops. Using data from the Annual Status of Education Report (ASER) and India Human Development Survey (IHDS) within a double difference design, we show positive effects of access to laptops on foundational math proficiency of students, with the largest improvements experienced by those in economically disadvantaged households. We further find that these positive effects on foundational math proficiency are complemented by improvements in other education-related outcomes of students, such as more time spent on learning, better comprehension of language, and a reduction in private tuition. We provide evidence that laptops are able to close economic and gender divides in education. Our results remain robust to a variety of falsification and sensitivity checks.

To mark the Population and Development Review's (PDR) 50th anniversary, we analyze its contributions to the landscape of population research. We examine the trajectory of research published in PDR and compare it with two leading and long‐standing English‐language demographic journals, Demography and Population Studies. Through a computational meta‐analysis of all articles published across the three journals over the past 50 years, we explore trends in knowledge production focusing on research themes and authorship characteristics. Our automated text analysis highlights the prominence of fertility, family, and mortality themes across all three journals, but with PDR placing greater emphasis on development, policy, and population growth. Interest in migration and health‐related topics has also increased over time across all journals, including PDR. Our analysis of authorship characteristics reveals a persistent overrepresentation of scholars located in Global North countries, particularly the United States, across all three journals. While the prominence of the United States has declined in PDR, European representation has grown, alongside a relative decline in Global South authors compared with earlier decades. Over the past 50 years, all three journals have had a male‐dominated authorship, but gender balance has improved significantly, reaching near parity in recent years.

The digital revolution has ushered in many societal and economic benefits. Yet access to digital technologies such as mobile phones and internet remains highly unequal, especially by gender in the context of low- and middle-income countries (LMICs). While national-level estimates are increasingly available for many countries, reliable, quantitative estimates of digital gender inequalities at the subnational level are lacking. These estimates, however, are essential for monitoring gaps within countries and implementing targeted interventions within the global sustainable development goals, which emphasize the need to close inequalities both between and within countries. We develop estimates of internet and mobile adoption by gender and digital gender gaps at the subnational level for 2,075 regions in 117 LMICs from 2015 through 2025, a context where digital penetration is low and national-level gender gaps disfavoring women are large. We construct these estimates by applying machine-learning algorithms to Facebook user counts, geospatial data, development indicators, and population composition data. We calibrate and assess the performance of these algorithms using ground-truth data from subnationally-representative household survey data from 33 LMICs. Our results reveal striking disparities in access to mobile and internet technologies between and within LMICs. These disparities imply that as of 2025, women are 15% less likely to use the internet and 10% less likely to own a mobile phone in LMICs, corresponding to over 235 million fewer women owning a mobile phone and over 265 million fewer women using the internet.

Despite the recent milestone of the world population surpassing 8 billion, disparities in population data reliability persist, with many countries facing outdated or incomplete census data. Such inaccuracies have far-reaching implications for various sectors, including public health, urban planning, and resource allocation. The study capitalizes on the rich data environment provided by the detailed 2018 Colombian census data and census coverage indicators, offering a unique opportunity to assess census-independent population estimation approaches. Drawing from a diverse range of environmental landscapes in Colombia, the research evaluates the effectiveness of satellite imagery-derived settlement maps in conjunction with various modeling techniques. We explore two census-independent population estimation approaches based on settlement maps: pure data driven machine learning approach exemplified by a random forest model and a process-structure driven probabilistic approach exemplified by a hierarchical Bayesian model. Our findings underscore the efficacy of Bayesian modeling in addressing data scarcity and bias, providing robust estimates and quantifying model uncertainty. Nonetheless the random forest model is better suited when the data inputs are detailed and unbiased. Additionally, we highlight the importance of considering settlement map characteristics and population sample sizes in the modeling process. Through rigorous evaluation at different stages of the population modeling pipeline, including data input, model selection, and outcome assessment, this study offers insights into the requirements and challenges of leveraging satellite imagery-derived settlement maps for population estimation in data-scarce contexts.

Human sex ratios at birth (SRBs) shape population composition and are closely linked to maternal health and gender discrimination. In the context of climate change, SRBs may theoretically be skewed by physiological or behavioral responses to exposure to global warming. However, evidence for this is limited. In this study, we estimate the effect of prenatal exposure to temperature on birth sex by linking survey data on 5 million live births in 33 sub-Saharan African countries and India with high-resolution temperature data. To distinguish between spontaneous and induced abortions, we exploit sociodemographic differentials, exposure timing, and regional differences in son preference. We find that days with a maximum temperature above 20°C are negatively associated with male births in both regions. In sub-Saharan Africa, we observe fewer male births after high first trimester temperature exposure, consistent with increased spontaneous abortions from maternal heat stress. This is particularly true for births by mothers in rural areas, with little formal education, and for higher birth orders. By contrast, in India we find second trimester temperature exposure is associated with fewer male births, consistent with reductions in induced sex-selective abortions against girls. As expected, these reductions are concentrated in higher birth orders and older mothers. We also find large reductions in male births by sonless mothers in northern Indian states, where son preference is greater. These findings demonstrate that climate change harms maternal health, increases prenatal mortality, and reduces engagement with the health system, leading to a complex effect on sex ratios at birth.