A crucial issue is whether social insurance affects work decisions through income or substitution effects. We examine this in the context of U.S. Social Security Disability Insurance (DI), exploiting discontinuous changes in the benefit formula with a regression kink design to estimate the income effect of payments on earnings and employment. Using administrative data on all new DI beneficiaries from 2001 to 2007, our preferred estimate is that an increase in DI payments of one dollar causes an average decrease in beneficiaries’ earnings of twenty cents and that annual employment rates decrease by 1.3 percentage points per $1,000 of DI payments. These findings suggest that the income effect accounts for a majority of DI-induced reductions in earnings.

The acceptance of new growth theory relates, in part, to a number of highly touted regional success stories – or what I term “Knowledge Based Economic Areas” (KBEAs) in this and past essays. The United States, and California in particular, is viewed as perhaps the most robust creators of KBEAs, providing an influential model that is visited and revisited by business and government leaders, and other Flagship (or leading national) universities, that wish to replicate their strengths within their own cultural and political terms.  While California has a number of unique characteristics, including a robust University of California system with a strong internal academic culture and devotion to public service, the story of its historical and contemporary success as an agent of economic development is closely linked to a number of key contextual factors. These relate to the internal culture, governance and management capacity of major universities in the United States, national investment patterns in R&D, the business environment, including the concentration of Knowledge Based Businesses, the acceptance of risk, and the availability of venture capital, legal variables related to Intellectual Property (IP) and tax policies, the quality of regional workforces, and quality of life factors that are important components for attracting and retaining talent. In most of these KBEAs variables, California has enjoyed an advantage that helps to partially explain the success of the University of California (UC) and other major research universities as agents of economic development. This study focuses on seven contextual variables common to all KBEAs in the United States and much of the world, and with particular attention to the UC system – a network of ten research-intensive campuses.

For centuries, thinkers have considered whether and how climatic conditions—such as temperature, rainfall, and violent storms—influence the nature of societies and the performance of economies. A multidisciplinary renaissance of quantitative empirical research is illuminating important linkages in the coupled climate-human system. We highlight key methodological innovations and results describing effects of climate on health, economics, conflict, migration, and demographics. Because of persistent “adaptation gaps,”current climate conditions continue to play a substantial role in shaping modern society, and future climate changes will likely have additional impact. For example, we compute that temperature depresses current U.S. maize yields by ~48%, warming since 1980 elevated conflict risk in Africa by ~11%, and future warming may slow global economic growth rates by ~0.28 percentage points per year. In general, we estimate that the economic and social burden of current climates tends to be comparable in magnitude to the additional projected impact caused by future anthropogenic climate changes. Overall, findings from this literature point to climate as an important influence on the historical evolution of the global economy, they should inform how we respond to modern climatic conditions, and they can guide how we predict the consequences of future climate changes.

Identifying the effect of climate on societies is central to understanding historical economic development, designing modern policies that react to climatic events, and managing future global climate change. Here, I review, synthesize, and interpret recent advances in methods used to measure effects of climate on social and economic outcomes. Because weather variation plays a large role in recent progress, I formalize the relationship between climate and weather from an econometric perspective and discuss the use of these two factors as identifying variation, highlighting trade-offs between key assumptions in different research designs and deriving conditions when weather variation exactly identifies the effects of climate. I then describe recent advances, such as the parameterization of climate variables from a social perspective, use of nonlinear models with spatial and temporal displacement, characterization of uncertainty, measurement of adaptation, cross-study comparison, and use of empirical estimates to project the impact of future climate change. I conclude by discussing remaining methodological challenges.

Large-scale social experiments were pioneered in labor economics, and are the basis for much of what we know about topics ranging from the effect of job training to incentives for job search to labor supply responses to taxation. Random assignment has provided a powerful solution to selection problems that bedevil non-experimental research. Nevertheless, many important questions about these topics require going beyond random assignment. This applies to questions pertaining to both internal and external validity, and includes effects on endogenously observed outcomes, such as wages and hours; spillover effects; site effects; heterogeneity in treatment effects; multiple and hidden treatments; and the mechanisms producing treatment effects. In this Chapter, we review the value and limitations of randomized social experiments in the labor market, with an emphasis on these design issues and approaches to addressing them. These approaches expand the range of questions that can be answered using experiments by combining experimental variation with econometric or theoretical assumptions. We also discuss efforts to build the means of answering these types of questions into the ex ante design of experiments. Our discussion yields an overview of the expanding toolkit available to experimental researchers.