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- W1485289420 abstract "A problem encountered in, for instance, growth empirics is that the number of explanatory variables is large compared to the number of observations. This makes it infeasible to condition on all variables in order to determine the importance of a variable of interest. We prove identifying assumptions under which the problem is not ill-posed. Under these assumptions, we derive properties of the most commonly used methods: Extreme bounds analysis, Sala-i-Martin’s method, BACE, generalto-specific, minimum t-statistics, BIC and AIC. We propose a new method and show that it has good finite sample properties." @default.
- W1485289420 created "2016-06-24" @default.
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- W1485289420 date "2008-01-01" @default.
- W1485289420 modified "2023-09-23" @default.
- W1485289420 title "On Determining the Importance of a Regressor with Small and Undersized Samples" @default.
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- W1485289420 doi "https://doi.org/10.2139/ssrn.1147067" @default.
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