Research Papers

We provide a systematic analysis of identification in linear social interactions models. We develop an incomplete information game that describes individual choices in the presence of social interactions.

The theoretical models used to study social interactions are distinct from the econometric environments in which identification is studied, while empirical work generally does not systematically exploit the implications of theory and econometrics for formulating data analyses. This paper aims to facilitate the integration of the theoretical, econometric, and empirical sides of the social interactions literature.

While the proposition that individuals are subject to social influence states the obvious, the study of social influences on individual behavior in economics is a relatively recent phenomenon. In the last two decades, however, a rich theoretical, econometric, and empirical literature in social economics, has emerged.

We investigated the mixed empirical evidence on the deterrent effect of capital punishment and potential explanations for these inconsistencies.

Our findings can contribute to the ongoing debate about capital punishment and inform policy decisions regarding its use as a criminal deterrent.

We shed light on the complexities of measuring deterrence and highlight the need for careful consideration of various factors before drawing conclusions about capital punishment’s effectiveness.

We identified potential methodological pitfalls in using time series analysis to study the relationship between capital punishment and crime rates.

We wanted to improve the quality of research on capital punishment and prevent misleading conclusions based on flawed methodology.

We encourage rigorous methods in research on capital punishment and highlight the importance of considering potential biases and confounding factors.

We critically reviewed the literature on model uncertainty and its implications for empirical policy analysis in economics.

Our goal was to raise awareness of the challenges posed by model uncertainty and promote robust methods for policy evaluation under such conditions.

We highlight the importance of acknowledging and addressing model uncertainty to ensure reliable and informative policy recommendations.

We discussed the importance of incorporating process and context into economic models of individual choice behavior.

We aimed to improve the accuracy and realism of economic models by taking into account the dynamics of decision-making and the influence of context.

We advocate for more nuanced and context-aware models of economic behavior, acknowledging the influence of cognitive and social factors on individual choices.

This paper examines how estimates of the deterrent effect of capital punishment depend on alternate choices of assumptions concerning the homicide process. We demonstrate how various assumptions have driven the conflicting findings from studies on capital punishment, and isolate a particular set of assumptions that are required to find a positive deterrent effect.

Results on the deterrent effect of capital punishment are disparate. This article is designed to understand the sources of the disparate literature findings. Specifically, we consider how different substantive assumptions about the homicide process affect deterrence effect estimates.

The effectiveness of capital punishment in deterring homicides has remained unclear despite the fact that the Supreme Court’s moratorium on capital punishment and the subsequent adoption of capital punishment by a subset of states, combined with very different rates of execution across polities, would appear to be an ideal environment for revealing deterrence effects using panel data methods.

We explored the presence of nonlinearities in economic growth and their implications for policy, considering how different growth regimes may require different policy responses.

We aimed to provide insights into the effectiveness of policy interventions by acknowledging and understanding the nonlinearities in economic growth processes.

Our recognition of nonlinearities in economic growth help policymakers tailor interventions to specific growth contexts, enhancing the precision and effectiveness of economic policies.

We explored the concept of poverty traps with a focus on the Appalachian region, examining factors contributing to persistent poverty.

We aimed to provide a nuanced understanding of poverty traps in a specific geographic context, offering insights that could inform targeted anti-poverty policies.

We contribute to the literature on poverty traps, providing region-specific insights that can guide policymakers in designing effective interventions to break the cycle of poverty.

We analyzed how education influences beliefs about racial stereotypes, discrimination awareness, and support for affirmative action policies among whites, Asians, Hispanics, and blacks.

We aimed to fill gaps in existing research that predominantly focuses on white attitudes toward blacks, neglecting other minority populations.

Our findings reveal that higher education levels among whites, Hispanics, and blacks are associated with rejecting negative stereotypes and increased awareness of discrimination against minorities. However, education does not uniformly increase support for affirmative action policies across all racial groups, highlighting complex dynamics influenced by racial hierarchy positions.

We explored the implications of complexity theory for economics and public policy, considering how complex systems thinking can enhance policy analysis.

Our goal was to integrate insights from complexity theory into economic and policy analysis, providing a more realistic framework for understanding and addressing complex social and economic phenomena.

We contribute to advancing the application of complexity theory in policy analysis, offering a more robust and adaptable approach to addressing real-world challenges.