Generic Uniform Convergence

Donald Andrews ()

No 940, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University

Abstract: This paper presents several generic uniform convergence results that include generic uniform laws of large numbers. These results provide conditions under which pointwise convergence almost surely or in probability can be strengthened to uniform convergence. The results are useful for establishing asymptotic properties of estimators and test statistics. The results given here have the following attributes, (1) they extend results of Newey to cover convergence almost surely as well as convergence in probability, (2) they apply to totally bounded parameter spaces (rather than just to compact parameter spaces), (3) they introduce a set of conditions for a generic uniform law of large numbers that has the attribute of giving the weakest conditions available for iid contexts, but which apply in dependent non-identically distributed contexts as well, and (4) they incorporate and extend the main results in the literature in a parsimonious fashion.

Keywords: Consistency; law of large numbers; uniform convergence; asymptotic theory; test statistics; estimators (search for similar items in EconPapers)
Pages: 21 pages
Date: 1990-03
Note: CFP 810.
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Citations: View citations in EconPapers (16)

Published in Econometric Theory (1992), 8: 241-257

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Journal Article: Generic Uniform Convergence (1992)
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