Causal Analysis with Panel Data

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Steven E. Finkel - University of Pittsburgh, USA

Volume: 105

Series:
Quantitative Applications in the Social Sciences

Other Titles in:
Quantitative/Statistical Research

January 1995 | 104 pages | SAGE Publications, Inc

Panel data - information gathered from the same individuals or units at several different points in time - are commonly used in the social sciences to test theories of individual and social change. This book highlights the developments in this technique in a range of disciplines and analytic traditions.

Providing an overview of models appropriate for the analysis of panel data, the book focuses specifically on the area where panels offer major advantages over cross-sectional research designs: the analysis of causal interrelationships among variables. Finkel demonstrates how panel data offer multiple ways of strengthening the causal inference process. He also explores how to estimate models that contain a variety of lag specifications, reciprocal effects and imperfectly measured variables.

Introduction

Modeling Change with Panel Data

Models with Reciprocal Causation

Measurement Error Models

Models of Spurious Association

Concluding Note on Causal Inference in Panel Analysis

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Steven E. Finkel

Steven E. Finkel is the Daniel Wallace Professor of political science at the University of Pittsburgh. His areas of expertise include comparative political behavior, democratization, public opinion, and quantitative methods. He is the author of Causal Analysis With Panel Data (SAGE, 1995) as well as numerous articles on political participation, voting behavior, and civic education in new and established democracies. He holds a PhD in political science from the State University of New York at Stony Brook and has taught previously at the University of Virginia, Arizona State University, the Hertie School of Governance (Berlin), the... More About Author

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