The Ill-Posed Problem in Growth Empirics
AbstractA 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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Bibliographic InfoPaper provided by University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics in its series CAM Working Papers with number 2005-11.
Length: 32 pages
Date of creation: Jul 2005
Date of revision:
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Web page: http://www.econ.ku.dk/CAM/
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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 and Methodology: General - - - Hypothesis Testing: General
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- O10 - Economic Development, Technological Change, and Growth - - Economic Development - - - General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-08-08 (All new papers)
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