A Critical Survey of Empirical Methods for Evaluating Active Labor Market Policies

By Jeffrey A. Smith. 2000

221 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/0fc7e5af9b1c1a14b3b66320864b0fc71ae2f67e

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1. Marco Caliendo
2. Hans Lööf
3. Inha Oh
4. Sabine Kopeinig
5. Liuyi Yao
6. Jeong-Dong Lee
7. Almas Heshmati
8. Yaliang Li

Citations in the corpus

• A Survey on Causal Inference (2020, result): “ how we should select a perfect matching method. Asymptotically all matching methods should yield the same results as the sample size grows and they will become closer to comparing only exact matches [128]. When we only have small samples size, this choice will be important [52]. There is one trade-”
• Evaluating the effectiveness of private education across countries: a comparison of methods (2004, background): “This problem can be seen as a specific case of the more general Evaluation Problem (e.g. Smith, 2000; Schmidt, 2001).”
• Impacts of active labor market programs: new evidence from evaluations with particular attention to developing and transition countries (2004, background): “As Smith (2000) emphasizes, governments can do many things to improve the data available for evaluations including making data from both administrative and survey sources widely available (with appropriate privacy precautions) to the research community.”
• Some Practical Guidance for the Implementation of Propensity Score Matching (2008, methodology): “For example, in the case of NN matching with one NN, treating the matched observations as given will understate the standard errors (Smith, 2000).”
• The use of propensity score matching in the evaluation of active labour market policies (2002, methodology): “For a detailed discussion of the magnitude and relevance of general equilibrium effects to evaluations using a partial equilibrium framework see Smith (2000).”
• The Impact of Public Funds on Private R&D Investment: New Evidence from a Firm Level Innovation Study ∗ (2005, methodology): “In a non-experimental evaluation, as pointed out by Smith (2000); “statistical techniques are used to adjust the results of persons who choose to participate, in order to assess the result had they not participated.”
• The Employment Effects of Job Creation Schemes in Germany: A Microeconometric Evaluation (2008, unknown): “Clearly, all approaches should yield asymptotically the same results, because with growing sample size all of them become closer to comparing only exact matches (Smith, 2000).”
• Does knowledge diffusion between university and industry increase innovativeness? (2008, background): “(Heckman, Ichimura and Todd, 1997, Heckman, Ichimura, Smith and Todd, 1998, Heckman, Ichimura and Todd, 1998, Smith and Todd, 2004, and Smith, 2000, provide critical discussions on strengths and weakness of matching estimators).”
• Evaluation of credit guarantee policy using propensity score matching (2009, background): “…score matching techniques, which has been developed in labor economics (Dehejia and Wahba, 1999, 2002; Frölich et al., 2004; Heckman et al., 1997; Smith, 2000), and recently has been applied to firm-level studies (Arnold and Hussinger, 2005; Yasar and Rejesus, 2005; Lööf and Heshmati, 2005).”
• The microeconometric estimation of treatment effects—An overview (2006, methodology): “We will not discuss these algorithms here (see Smith and Todd (2005) for an overview.”