• Graduate Programs
    • Tinbergen Institute Research Master in Economics
      • Why Tinbergen Institute?
      • Research Master
      • Admissions
      • Course Registration
      • Facilities
      • PhD Vacancies
      • Selected PhD Placements
    • Research Master Business Data Science
    • PhD Vacancies
  • Research
  • Browse our Courses
  • Events
    • Summer School
      • Applied Public Policy Evaluation
      • Deep Learning
      • Economics of Blockchain and Digital Currencies
      • Economics of Climate Change
      • Foundations of Machine Learning with Applications in Python
      • From Preference to Choice: The Economic Theory of Decision-Making
      • Gender in Society
      • Machine Learning for Business
      • Marketing Research with Purpose
      • Sustainable Finance
      • Tuition Fees and Payment
      • Business Data Science Summer School Program
    • Events Calendar
    • Events Archive
    • Tinbergen Institute Lectures
    • 16th Tinbergen Institute Annual Conference
    • Annual Tinbergen Institute Conference
  • News
  • Alumni
    • PhD Theses
    • Master Theses
    • Selected PhD Placements
    • Key alumni publications
    • Alumni Community

Elbers, C., Lanjouw, J.O.L. and Lanjouw, P. (2005). Imputed welfare estimates in regression analysis Journal of Economic Geography, 5(1):101--118.


  • Affiliated authors
    Chris Elbers, Peter Lanjouw
  • Publication year
    2005
  • Journal
    Journal of Economic Geography

We discuss the use of imputed data in regression analysis, in particular the use of highly disaggregated welfare indicators (from so-called 'poverty maps'). We show that such indicators can be used both as explanatory variables on the right-hand side and as the phenomenon to explain on the left-hand side. We try out practical ways of adjusting standard errors of the regression coefficients to reflect the error introduced by using imputed, rather than actual, welfare indicators. These are illustrated by regression experiments based on data from Ecuador. For regressions with imputed variables on the left-hand side, we argue that essentially the same aggregate relationships would be found with either actual or imputed variables. We address the methodological question of how to interpret aggregate relationships found in such regressions. {\textcopyright} Oxford University Press 2005; all rights reserved.