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Call for papers: Conference on computational social science, April 2017, U-M

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Post-doc fellowship in computational social science for summer or fall 2017, U-Penn

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Mon, Feb 13, 2017, noon:
Daniel Almirall, "Getting SMART about adaptive interventions"

Evaluating multi-treatment programs: theory and evidence from the US Job Training Partnership Act experiment

Publication Abstract

Plesca, M., and Jeffrey A. Smith. 2007. "Evaluating multi-treatment programs: theory and evidence from the US Job Training Partnership Act experiment." Empirical Economics, 32(2-3): 491-528.

This paper considers the evaluation of programs that offer multiple treatments to their participants. Our theoretical discussion outlines the tradeoffs associated with evaluating the program as a whole versus separately evaluating the various individual treatments. Our empirical analysis considers the value of disaggregating multi-treatment programs using data from the U.S. National Job Training Partnership Act Study. This study includes both experimental data, which serve as a benchmark, and non-experimental data. The JTPA experiment divides the program into three treatment "streams" centered on different services. Unlike previous work that analyzes the program as a whole, we analyze the streams separately. Despite our relatively small sample sizes, our findings illustrate the potential for valuable insights into program operation and impact to get lost when aggregating treatments. In addition, we show that many of the lessons drawn from analyzing JTPA as a single treatment carry over to the individual treatment streams.

DOI:10.1007/s00181-006-0095-0 (Full Text)

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