MEAN SQUARED PREDICTION ERROR REDUCTION WITH INSTRUMENTAL VARIABLES
Antonis Michis ()
No 2016-5, Working Papers from Central Bank of Cyprus
The mean squared prediction error of the linear regression model is examined when estimation is performed with instrumental variables. It is shown that increasing the number of instruments in the estimation procedure, can reduce the mean squared prediction error of the model through more efficient estimation of the coefficient vector.
Keywords: Mean squared prediction error; efficiency; instrumental variables (search for similar items in EconPapers)
JEL-codes: C01 C26 C53 (search for similar items in EconPapers)
Pages: 9 pages
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Persistent link: https://EconPapers.repec.org/RePEc:cyb:wpaper:2016-5
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