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The Ill-Posed Problem in Growth Empirics

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Author Info
Peter Sandholt Jensen (Department of Economics, University of Aarhus)
Allan H. Würtz (Department of Economics, University of Copenhagen)

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Abstract

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.

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Publisher Info
Paper provided by University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics in its series CAM Working Papers with number 2005-11.

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Length: 32 pages
Date of creation: Jul 2005
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Handle: RePEc:kud:kuieca:2005_11

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Related research
Keywords: AIC; BACE; BIC; extreme bounds; general-to-specific; ill-posed inverse problem; robustness;

Find related papers by JEL classification:
C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing
C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
O10 - Economic Development, Technological Change, and Growth - - Economic Development - - - General

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