IDEAS home Printed from
MyIDEAS: Login to save this paper or follow this series

Improving the Quality of Data and Impact-Evaluation Studies in Developing Countries

  • Guy Stecklov


  • Alex Weinreb


Registered author(s):

    While the science of program evaluation has come a tremendous distance in the past couple of decades, measurement error remains a serious concern and its implications are often poorly understood by both data collectors and data analysts. The primary aim here is to offer a type of “back-to-basics” approach to minimizing error in developing country settings, particularly in relation to impact evaluation studies. Overall, the report calls for a two-stage approach to dealing with mismeasurement. In the first stage, researchers should attempt to minimize mismeasurement during data collection, but also incorporate elements into the study that allow them to estimate its overall dimensions and effects on analysis with more confidence. Econometric fixes for mismeasurement—whose purview is limited to a smaller subset of errors—then serve as a secondary line of defense. Such a complementary strategy can help to ensure that decisions are made based on the most accurate empirical evaluations. The main body of the report includes four main sections. Section two discusses in detail many of the problems that can arise in the process of data collection and what is known about how they may affect measurement error. Section three provides a basic introduction to statistical—particularly econometric—methods that have been developed and used to help avoid the most problematic effects of mismeasurement. Section four offers an alternative approach to dealing with measurement error—one that focuses on reducing error at source. It offers pointers to current “best practice” on how to reduce measurement error during data collection, especially as to how those methods relate to evaluation research, and how to incorporate elements into research design that allow researchers to estimate the dimensions of error. Section five focuses on the role of incentives as one possible approach to shifting one particular aspect of error. It uses data from the PROGRESA program to evaluate indirectly the impact of incentives on certain aspects of data quality in Mexico. The report concludes with a short summary and includes a list of ten steps that can be taken to reduce measurement error at source.

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL:
    Our checks indicate that this address may not be valid because: 500 Internal Server Error ( [301 Moved Permanently]-->,7101.html?id=8416 [301 Moved Permanently]-->,7101.html?id=8416 [301 Moved Permanently]-->,7101.html?id=8416 [302 Found]--> [301 Moved Permanently]--> If this is indeed the case, please notify (Monica Bazan)

    Download Restriction: no

    Paper provided by Inter-American Development Bank, Office of Strategic Planning and Development Effectiveness (SPD) in its series SPD Working Papers with number 1002.

    in new window

    Date of creation: May 2010
    Date of revision:
    Handle: RePEc:idb:spdwps:1002
    Contact details of provider: Postal: 1300 New York Avenue, NW, Washington, DC 20577
    Phone: 202-623-1000
    Web page:

    More information through EDIRC

    No references listed on IDEAS
    You can help add them by filling out this form.

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:idb:spdwps:1002. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Monica Bazan)

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.