Quantitative methods to evaluate geographically-targeted economic development programs
AbstractIn recent years an increasing amount of efforts has been devoted, both in the U.S. and within the E.U., to perform impact evaluation of geographically-targeted economic development (GTED) programs. The surging interest for the evaluation of GTED programs is challenged by the difficulty to assess the causality link between the program intervention and the observed changes in the economic outcomes of interest. Evaluating GTED programs is a difficult task because it requires the evaluator to distinguish changes due to the program from changes due to the many factors independent from the program intervention. Such a task is particularly difficult also due to the lack of experimental data available to the evaluator. This paper illustrates the sources of the potential biases that can affect impact estimates of GTED programs when no experimental data are available, and presents a number of statistical methods that control for such sources. As a conclusion of the paper, a number of criteria are developed to select the most appropriate methodology for the analysis, based on the program characteristics and on the type of data available.
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Bibliographic InfoPaper provided by Institute of Public Policy and Public Choice - POLIS in its series POLIS Working Papers with number 13.
Length: 27 pages
Date of creation: Apr 2000
Date of revision:
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Web page: http://polis.unipmn.it
impact evaluation; economic development programs; selection bias; omitted variable bias; one group design; comparison group design.;
Find related papers by JEL classification:
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Longitudinal Data; Spatial Time Series
- O1 - Economic Development, Technological Change, and Growth - - Economic Development
- R5 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis
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