IDEAS home Printed from https://ideas.repec.org/p/wti/papers/197.html

Methods for Program Evaluation

Author

Listed:
  • Porto, Guido

Abstract

Throughout this chapter we will study the general framework for program evaluation, with the aim of assessing the causal effect of a determine program, such as the impact of job-training program on earnings. The objective of this chapter is to provide the research with enough tools to think of the problem of causality in a consistent way and offer the reader the menu of sources of causal inference and the most up-to-date techniques to estimate treatment effects. This Chapter is only introductory, containing many references to encourage further readings on the field and should be accessible for those readers with a basic knowledge of econometrics and statistics. 

Suggested Citation

  • Porto, Guido, 2011. "Methods for Program Evaluation," Papers 197, World Trade Institute.
    • Handle: RePEc:wti:papers:197
    as

    Download full text from publisher

    File URL: http://www.wti.org/media/filer_public/36/c5/36c5e22f-adce-4ba9-9117-1d934b19104b/wp26_galiani.pdf
    File Function: First version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. James J. Heckman & Jeffrey A. Smith, 1995. "Assessing the Case for Social Experiments," Journal of Economic Perspectives, American Economic Association, vol. 9(2), pages 85-110, Spring.
    2. Berlinski, Samuel & Galiani, Sebastian & Gertler, Paul, 2009. "The effect of pre-primary education on primary school performance," Journal of Public Economics, Elsevier, vol. 93(1-2), pages 219-234, February.
    3. Horowitz, Joel L., 2001. "The bootstrap and hypothesis tests in econometrics," Journal of Econometrics, Elsevier, vol. 100(1), pages 37-40, January.
    4. Edward Miguel & Michael Kremer, 2004. "Worms: Identifying Impacts on Education and Health in the Presence of Treatment Externalities," Econometrica, Econometric Society, vol. 72(1), pages 159-217, January.
    5. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2008. "Bootstrap-Based Improvements for Inference with Clustered Errors," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 414-427, August.
    6. Härdle, Wolfgang & Horowitz, Joel L. & Kreiss, Jens-Peter, 2001. "Bootstrap methods for time series," SFB 373 Discussion Papers 2001,59, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    7. Goldberger, Arthur S, 1972. "Structural Equation Methods in the Social Sciences," Econometrica, Econometric Society, vol. 40(6), pages 979-1001, November.
    8. Ahn, Hyungtaik & Powell, James L., 1993. "Semiparametric estimation of censored selection models with a nonparametric selection mechanism," Journal of Econometrics, Elsevier, vol. 58(1-2), pages 3-29, July.
    9. James Heckman, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    10. Horowitz, Joel L., 2001. "The Bootstrap," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 52, pages 3159-3228, Elsevier.
    11. Joshua D. Angrist, 1995. "Conditioning on the Probability of Selection to Control Selection Bias," NBER Technical Working Papers 0181, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gustavo J. Bobonis & Paul J. Gertler & Marco Gonzalez-Navarro & Simeon Nichter, 2022. "Vulnerability and Clientelism," American Economic Review, American Economic Association, vol. 112(11), pages 3627-3659, November.
    2. Groneck, Max & Ludwig, Alexander & Zimper, Alexander, 2016. "A life-cycle model with ambiguous survival beliefs," Journal of Economic Theory, Elsevier, vol. 162(C), pages 137-180.
    3. Benjamin Faber & Thibault Fally, 2022. "Firm Heterogeneity in Consumption Baskets: Evidence from Home and Store Scanner Data," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 89(3), pages 1420-1459.
    4. Gordon B. Dahl, 2002. "Mobility and the Return to Education: Testing a Roy Model with Multiple Markets," Econometrica, Econometric Society, vol. 70(6), pages 2367-2420, November.
    5. Mesnard, Alice & Vera-Hernández, Marcos & Fitzsimons, Emla & Malde, Bansi, 2012. "Household Responses to Information on Child Nutrition: Experimental Evidence from Malawi," CEPR Discussion Papers 8915, C.E.P.R. Discussion Papers.
    6. Perez, Victor, 2015. "Moving in and out of poverty in Mexico: What can we learn from pseudo-panel methods?," ISER Working Paper Series 2015-16, Institute for Social and Economic Research.
    7. Orth, Walter, 2012. "The predictive accuracy of credit ratings: Measurement and statistical inference," International Journal of Forecasting, Elsevier, vol. 28(1), pages 288-296.
    8. Astrid Grasdal, 2001. "The performance of sample selection estimators to control for attrition bias," Health Economics, John Wiley & Sons, Ltd., vol. 10(5), pages 385-398, July.
    9. Li, Jia & Todorov, Viktor & Tauchen, George & Chen, Rui, 2017. "Mixed-scale jump regressions with bootstrap inference," Journal of Econometrics, Elsevier, vol. 201(2), pages 417-432.
    10. Jones A.M & Rice N, 2009. "Econometric Evaluation of Health Policies," Health, Econometrics and Data Group (HEDG) Working Papers 09/09, HEDG, c/o Department of Economics, University of York.
    11. Sevan Gulesserian & Mohitosh Kejriwal, 2014. "On the power of bootstrap tests for stationarity: a Monte Carlo comparison," Empirical Economics, Springer, vol. 46(3), pages 973-998, May.
    12. Lechner, Michael & Melly, Blaise, 2007. "Earnings Effects of Training Programs," CEPR Discussion Papers 6400, C.E.P.R. Discussion Papers.
    13. A. Talha Yalta, 2016. "Bootstrap Inference of Level Relationships in the Presence of Serially Correlated Errors: A Large Scale Simulation Study and an Application in Energy Demand," Computational Economics, Springer;Society for Computational Economics, vol. 48(2), pages 339-366, August.
    14. Grammig, Joachim & Küchlin, Eva-Maria, 2017. "A two-step indirect inference approach to estimate the long-run risk asset pricing model," CFS Working Paper Series 572, Center for Financial Studies (CFS).
    15. Grammig, Joachim & Küchlin, Eva-Maria, 2017. "A two-step indirect inference approach to estimate the long-run risk asset pricing model," CFR Working Papers 17-01, University of Cologne, Centre for Financial Research (CFR).
    16. Rourke, Thomas, 2014. "The delta- and vega-related information content of near-the-money option market trading activity," Journal of Financial Markets, Elsevier, vol. 20(C), pages 175-193.
    17. Götz, Thomas B. & Hecq, Alain & Smeekes, Stephan, 2016. "Testing for Granger causality in large mixed-frequency VARs," Journal of Econometrics, Elsevier, vol. 193(2), pages 418-432.
    18. Puente-Ajovín, Miguel & Sanso-Navarro, Marcos, 2015. "Granger causality between debt and growth: Evidence from OECD countries," International Review of Economics & Finance, Elsevier, vol. 35(C), pages 66-77.
    19. Huang, Zhendong & Ferrari, Davide & Qian, Guoqi, 2017. "Parsimonious and powerful composite likelihood testing for group difference and genotype–phenotype association," Computational Statistics & Data Analysis, Elsevier, vol. 110(C), pages 37-49.
    20. Saqib Aziz & Michael Dowling & Jean-Jacques Lilti, 2016. "Bank Acquisitiveness and Financial Crisis Vulnerability," Post-Print hal-01393953, HAL.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wti:papers:197. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Morven McLean The email address of this maintainer does not seem to be valid anymore. Please ask Morven McLean to update the entry or send us the correct address (email available below). General contact details of provider: https://edirc.repec.org/data/wtibech.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.