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The Ill-Posed Problem in Growth Empirics


  • Peter Sandholt Jensen

    (Department of Economics, University of Aarhus)

  • Allan H. Würtz

    (Department of Economics, University of Copenhagen)


A problem encountered in growth empirics is that the number of explanatory variables is large compared to the number of observations. This makes it impossible to condition on all regressors when determining if a variable is important. We investigate methods used to resolve this problem: Extreme bounds, Sala-i-Martin’s test, BACE, general-to-specific, minimum t-statistics, BIC and AIC. We prove that the problem in general is ill-posed and that the existing methods are inconsistent. We propose a test and apply it to determine if "good policy" increases the effectiveness of foreign aid on growth. The test rejects inference regarding good policy.

Suggested Citation

  • Peter Sandholt Jensen & Allan H. Würtz, 2005. "The Ill-Posed Problem in Growth Empirics," CAM Working Papers 2005-11, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
  • Handle: RePEc:kud:kuieca:2005_11

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    More about this item


    AIC; BACE; BIC; extreme bounds; general-to-specific; ill-posed inverse problem; robustness;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • O10 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - General

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