Although business incentive programs of different forms have been the bulk of local economic development policies in many industrialized countries for more than the last three decades, evaluating their impact on employment or local economic growth outcomes remains a challenging task due to the persisting lack of randomized experiments and the presence of many confounding factors which affect firms and economic growth outcomes. Moreover, much of the recent advancements in the statistical program evaluation methodology applicable to non-experimental settings do not make any direct reference to the specificities posed by business incentive policies. This paper aims at offering some clear guidance on how to choose the appropriate focus of the evaluation, the policy relevant evaluation parameters and empirical impact identification strategies when applying statistical methods attempting to estimate how much of the different outcomes between treatment and control groups are attributable to the program/s being evaluated. Each methodological option discussed in the paper is linked to the different features of commonly implemented US and EU policies and to whether or not the analysis focuses on outcomes recorded at a firm-level or at the level of the geographic areas in which the assisted firms are located.
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Find related papers by JEL classification: C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General H81 - Public Economics - - Miscellaneous Issues - - - Governmental Loans and Credits
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