Department of Economics

[No abstract]

Abstract: We estimate productivity growth in England from 1250 to 1870. Real wages over this period were heavily influenced by plague-induced swings in the population. Our estimates account for these Malthusian dynamics. We find that productivity growth was zero before 1600. Productivity growth began in 1600—almost a century before the Glorious Revolution. Thus, the onset of productivity growth preceded the bourgeois institutional reforms of seventeenth-century England. We estimate productivity growth of 2% per decade between 1600 and 1800, increasing to 5% per decade between 1810 and 1860. Much of the increase in output growth during the Industrial Revolution is explained by structural change—the falling importance of land in production—rather than faster productivity growth. Stagnant real wages in the eighteenth and early nineteenth centuries—Engels’ Pause—is explained by rapid population growth putting downward pressure on real wages. Yet feedback from population growth to real wages is sufficiently weak to permit sustained deviations from the “iron law of wages” prior to the Industrial Revolution.

We show that adding noise before publishing data effectively screens [Formula: see text]-hacked findings: spurious explanations produced by fitting many statistical models (data mining). Noise creates baits that affect two types of researchers differently. Uninformed [Formula: see text]-hackers, who are fully ignorant of the true mechanism and engage in data mining, often fall for baits. Informed researchers, who start with an ex ante hypothesis, are minimally affected. We show that as the number of observations grows large, dissemination noise asymptotically achieves optimal screening. In a tractable special case where the informed researchers theory can identify the true causal mechanism with very few data, we characterize the optimal level of dissemination noise and highlight the relevant trade-offs. Dissemination noise is a tool that statistical agencies currently use to protect privacy. We argue this existing practice can be repurposed to screen [Formula: see text]-hackers and thus improve research credibility.

We study how human capital and economic conditions causally affect the choice of religious denomination. We utilize a longitudinal dataset monitoring the religious history of more than 5,000 Kenyans over twenty years, in tandem with a randomized experiment (deworming) that has exogenously boosted education and living standards. The main finding is that the program reduces the likelihood of membership in a Pentecostal denomination up to 20 years later when respondents are in their mid-thirties, while there is a comparable increase in membership in traditional Christian denominations. The effect is concentrated and statistically significant among a sub-group of participants who benefited most from the program in terms of increased education and income. The effects are unlikely due to increased secularization, because the program does not reduce measures of religiosity. The results help explain why the global growth of the Pentecostal movement, sometimes described a "New Reformation", is centered in low-income communities.

This article reviews and summarizes current reproduction and replication practices in political science. We first provide definitions for reproducibility and replicability. We then review data availability policies for 28 leading political science journals and present the results from a survey of editors about their willingness to publish comments and replications. We discuss new initiatives that seek to promote and generate high-quality reproductions and replications. Finally, we make the case for standards and practices that may help increase data availability, reproducibility, and replicability in political science.

In Kenya, the number of adults aged ≥60 is expected to nearly quadruple by 2050, making it one of the most rapidly aging countries in Sub-Saharan Africa (SSA). Accordingly, we designed the Longitudinal Study of Health and Ageing in Kenya (LOSHAK) to generate novel data to address the health and economic consequences of this demographic transition. Specifically, LOSHAK will investigate the social, economic, environmental, biological, and policy processes that shape late-life health and economic well-being in Kenya. Modeled on the U.S. Health and Retirement Study (HRS), LOSHAK joins a network of harmonized studies on aging in >45 countries worldwide; however, LOSHAK will be only the 2nd such study in SSA. The current feasibility and pilot phase of LOSHAK will validate measures and data collection procedures in a purposive sample of Kenyan adults aged ≥45 years. We have linguistically and culturally translated instruments while aiming to maintain harmonization with both existing HRS network studies and the ongoing Kenya Life Panel Survey. The current phase of LOSHAK is nested within the Kaloleni/Rabai Community Health and Demographic Surveillance System on the coast of Kenya. LOSHAK will advance population aging research in low- and middle-income countries through the study of (a) biomarkers and physiological measures; (b) the impacts of air pollution and climate vulnerability; (c) Alzheimers disease and related dementias, mental health, disability, caregiving, and psychosocial wellbeing; and (d) economic security, including the impact of social welfare. LOSHAK will inform future public health and economic policy to address challenges related to rapid aging in Kenya and throughout SSA. Accordingly, this paper aims to introduce and provide a description of LOSHAK and its aims and objectives, as well as to inform the scientific community of current study activities being used to build toward the full population-representative study.

Cardiovascular disease (CVD) is the most common non-communicable disease occurring globally. Although previous literature has provided useful insights into the important role that diet plays in CVD prevention and treatment, understanding the causal role of diets is a difficult task considering inherent and introduced weaknesses of observational (e.g. not properly addressing confounders and mediators) and experimental research designs (e.g. not appropriate or well designed). In this narrative review, we organised current evidence linking diet, as well as conventional and emerging physiological risk factors, with CVD risk, incidence and mortality in a series of diagrams. The diagrams presented can aid causal inference studies as they provide a visual representation of the types of studies underlying the associations between potential risk markers/factors for CVD. This may facilitate the selection of variables to be considered and the creation of analytical models. Evidence depicted in the diagrams was systematically collected from studies included in the British Nutrition Task Force report on diet and CVD and database searches, including Medline and Embase. Although several markers and disorders linked to conventional and emerging risk factors for CVD were identified, the causal link between many remains unknown. There is a need to address the multifactorial nature of CVD and the complex interplay between conventional and emerging risk factors with natural and built environments, while bringing the life course into the spotlight.