Non-linearity Induced Weak Instrumentation

Ioannis Kasparis, Peter Phillips and Tassos Magdalinos
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Ioannis Kasparis: Dept. of Economics, University of Cyprus
Tassos Magdalinos: Dept. of Economics, University of Southampton

No 1872, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University

Abstract: In regressions involving integrable functions we examine the limit properties of IV estimators that utilise integrable transformations of lagged regressors as instruments. The regressors can be either I(0) or nearly integrated (NI) processes. We show that this kind of nonlinearity in the regression function can significantly affect the relevance of the instruments. In particular, such instruments become weak when the signal of the regressor is strong, as it is in the NI case. Instruments based on integrable functions of lagged NI regressors display long range dependence and so remain relevant even at long lags, continuing to contribute to variance reduction in IV estimation. However, simulations show that OLS is generally superior to IV estimation in terms of MSE, even in the presence of endogeneity. Estimation precision is also reduced when the regressor is nonstationary.

Keywords: Instrumental variables; Integrable function; Integrated process; Invariance principle; Local time; Mixed normality; Stationarity; Nonlinear cointegration; Unit roots; Weak Instruments (search for similar items in EconPapers)
JEL-codes: C22 C32 (search for similar items in EconPapers)
Pages: 38 pages
Date: 2012-09
New Economics Papers: this item is included in nep-ets
Note: CFP 1404
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Published in Econometric Reviews (2014), 33(5-6): 676-712

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Journal Article: Nonlinearity Induced Weak Instrumentation (2014)
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