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Causal Inference

The Mixtape
Pages
584
Published
2021
Language
English

Synopsis

Causal inference encompasses the tools that allow social scientists to determine what causes what. In a messy world, causal inference is what helps establish the causes and effects of the actions being studied—for example, the impact (or lack thereof) of increases in the minimum wage on employment, the effects of early childhood education on incarceration later in life, or the influence on economic growth of introducing malaria nets in developing regions. Scott Cunningham introduces students and practitioners to the methods necessary to arrive at meaningful answers to the questions of causation, using a range of modeling techniques and coding instructions for both the R and the Stata programming languages.

About the author

S
Scott Cunningham

Scott Cunningham is an associate professor of economics at Baylor University. He specializes in the economics of risky behaviors, with a special focus on crime, black markets, abortion and sexually transmitted infections. His research has been published in the Review of Economic Studies, Journal of Urban Economics, Health Economics, and several other journals in economics and health. He is also the recipient of several grants including the Robert Wood Johnson Foundation. He is also co-editor at...

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