Research Papers

Our paper is designed to consider some of the general issues that need to be addressed in evaluating racial profiling as a public policy question. Placing the discussion in the context of efficiency/equity trade-offs, this paper discusses profiling in the context of police traffic stops where the intent is to identify drug carriers.

While there is a growing body of theoretical and empirical work on profiling, relatively little attention has been paid to integrating efficiency and equity considerations in an overall assessment.

Racial profiling continues to be a contentious issue in American society. While official policing policies have in many places banned profiling, the impact of such regulations is unknown.

This paper provides a survey and synthesis of econometric tools that have been employed to study economic growth. It will both survey the body of econometric and statistical methods that have been brought to bear on growth questions and provide some assessments of the value of these tools.

The difficulties inherent in the empirical study of growth have prompted the field to evolve continuously, and to adopt a wide range of methods. We argue that a sufficiently rich set of statistical tools for the study of growth have been developed and applied that they collectively define an area of growth econometrics.

The empirical study of economic growth occupies a position that is notably uneasy. Understanding the wealth of nations is one of the oldest and most important research agendas in the entire discipline. At the same time, it is also one of the areas in which genuine progress seems hardest to achieve.

We survey the modern economics literature on the role of neighborhoods in influencing socioeconomic outcomes, covering a range of theoretical, econometric, and empirical topics.

Studies argue that geographic neighborhood influences are crucial for understanding inner city poverty. Methodological advances in economic theory now incorporate spillover effects into microeconomic models, similar to those in growth contexts. Additionally, analyzing neighborhood effects in game theory has become a significant research area.

Neighborhood effects have been analyzed in a range of theoretical and applied contexts and have proven to be of interest in understanding questions ranging from the asymptotic properties of various evolutionary games to explaining the persistence of poverty in inner cities.

We described approaches to macroeconomic policy evaluation under uncertainty about the economic environment’s structure. Our methods are designed to address several forms of uncertainty, such as ambiguity about the appropriate economic theory or functional forms required for statistical analysis. We incorporated model uncertainty into formal statistical inference methods to facilitate robust policy evaluation.

We aimed to provide a robust framework for policy evaluation in macroeconomic contexts where fundamental disagreements exist regarding determinants of the problem under study. Recognizing the limitations of traditional calibration methods, we sought to develop an approach that incorporates model uncertainty into policy evaluation.

Incorporating model uncertainty into policy evaluation enhances the robustness and reliability of macroeconomic policies. Our approach allows for more informed decision-making in the presence of theoretical and structural uncertainties, ultimately contributing to more effective and adaptive economic policies.

We developed general conditions under which complementarities between individual agents imply that assortative matching is efficient. Our analysis covered equal-sized groups, varying group sizes, sequences of replications, and the effects of feedback from group composition on efficient allocations.

We aimed to understand the efficiency of assortative matching in the presence of agent complementarities. By examining different scenarios and conditions, we sought to identify when and why assortative matching leads to efficient outcomes.

Our findings highlight the complexities in achieving efficient assortative matching in an economy. Understanding these complexities and the conditions for efficiency is crucial for designing policies and mechanisms that promote optimal allocation of resources and improve economic outcomes.

We describe the relationship between two different binary social interaction models–the mean-field model of Brock and Durlauf (1995) and the strategy adjustment model of Blume (1994).

We want to understand the behavior of these models when there is a significant random component to choice.

We expect that our results can be extended to some of the literature on search and sorting which proceeds in this manner, and we believe this to be an important area for future research.

We provided a critical overview of the literature on the convergence hypothesis, examining why statistical tests have not adequately addressed the notion of economic convergence. We proposed new research directions that focus on cross-country heterogeneity in the growth process to better understand convergence as an economic phenomenon.

We aimed to identify the shortcomings of existing empirical research on convergence and to suggest new approaches that explicitly consider cross-country differences. This approach seeks to enhance the understanding of convergence by addressing economic relevance more directly.

By focusing on cross-country heterogeneity, our proposed research directions can offer a more accurate and meaningful analysis of economic convergence. This improved understanding is essential for formulating effective economic policies that promote growth and reduce disparities between countries.

We provided an overview of an approach that integrates sociological ideas into economic models of individual behavior, emphasizing the influence of social context and interdependences on decision-making. We based our analysis on the framework developed by Brock and Durlauf (2001, forthcoming), assessing empirical evidence and exploring policy implications.

We aimed to bridge the gap between economics and sociology by incorporating social influences into economic models. This integration helps to provide a more comprehensive understanding of how social factors shape individual choices and economic outcomes.

Integrating sociological perspectives into economic models enhances the explanatory power of these models regarding individual behavior and social interactions. This approach can inform more effective policies that address the complex interplay between social context and economic decisions.

We developed a multinomial-choice model of individual decision-making in the presence of neighborhood effects. This model generalizes previous binary-choice models to account for the interdependencies between individual decisions and neighborhood characteristics.

We aimed to address the limitations of previous models by providing a more comprehensive framework for understanding how neighborhood effects influence individual behavior. This approach enhances the connection between theory and empirical work in economics.

Understanding neighborhood effects is crucial for explaining individual behaviors and their aggregate outcomes. Our model allows for structural estimation of these effects, improving the analysis of social interactions and economic policies.

We critically reviewed Robert Putnam’s influential work, “Bowling Alone,” focusing on its analysis of social capital in America. We assessed the book’s strengths and weaknesses, highlighting both its extensive documentation of community life and its conceptual and empirical shortcomings.

We aimed to evaluate “Bowling Alone” within the broader context of social capital literature, identifying its contributions and limitations. This evaluation helps to understand the validity and implications of Putnam’s claims about social capital’s role in socioeconomic phenomena.

Understanding the strengths and weaknesses of “Bowling Alone” is essential for assessing the broader social capital literature. By critically examining Putnam’s analysis, we can better gauge the importance of social capital in explaining socioeconomic outcomes and inform future research in this field.