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Full-Text Articles in Social and Behavioral Sciences
Semiparametric Estimation In Time Series Of Simultaneous Equations, Jiti Gao, Peter C.B. Phillips
Semiparametric Estimation In Time Series Of Simultaneous Equations, Jiti Gao, Peter C.B. Phillips
Cowles Foundation Discussion Papers
A system of vector semiparametric nonlinear time series models is studied with possible dependence structures and nonstationarities in the parametric and nonparametric components. The parametric regressors may be endogenous while the nonparametric regressors are strictly exogenous and represent trends. The parametric regressors may be stationary or nonstationary and the nonparametric regressors are nonstationary time series. This framework allows for the nonparametric treatment of stochastic trends and subsumes many practical cases. Semiparametric least squares (SLS) estimation is considered and its asymptotic properties are derived. Due to endogeneity in the parametric regressors, SLS is generally inconsistent for the parametric component and a …
The Impact Of A Hausman Pretest On The Size Of Hypothesis Tests, Patrik Guggenberger
The Impact Of A Hausman Pretest On The Size Of Hypothesis Tests, Patrik Guggenberger
Cowles Foundation Discussion Papers
This paper investigates the size properties of a two-stage test in the linear instrumental variables model when in the first stage a Hausman (1978) specification test is used as a pretest of exogeneity of a regressor. In the second stage, a simple hypothesis about a component of the structural parameter vector is tested, using a t -statistic that is based on either the ordinary least squares (OLS) or the two-stage least squares estimator (2SLS) depending on the outcome of the Hausman pretest. The asymptotic size of the two-stage test is derived in a model where weak instruments are ruled out …
Vector Autoregression And Causality, Hiro Y. Toda, Peter C.B. Phillips
Vector Autoregression And Causality, Hiro Y. Toda, Peter C.B. Phillips
Cowles Foundation Discussion Papers
This paper develops a complete limit theory for Wald tests of Granger causality in levels vector autoregression (VAR’s) and Johansen-type error correction models (ECM’s) allowing for the presence of stochastic trends and cointegration. Earlier work by Sims, Stock and Watson (1990) on trivariate VAR systems is extended to the general case, thereby formally characterizing the circumstances when these Wald tests are asymptotically valid as chi-square criteria. Our results for inference from unrestricted levels VAR are not encouraging.
The Spurious Effect Of Unit Roots On Exogeneity Tests In Vector Autoregressions: An Analytical Study, Hiro Y. Toda, Peter C.B. Phillips
The Spurious Effect Of Unit Roots On Exogeneity Tests In Vector Autoregressions: An Analytical Study, Hiro Y. Toda, Peter C.B. Phillips
Cowles Foundation Discussion Papers
This paper analyzes whether inclusion of a statistically independent random walk in a vector autoregression can result in spurious inference. The problem was raised originally by Ohanian (1988). In a Monte Carlo simulation based on the VAR’s estimated by Sims (1980b, 1982), Ohanian found that block exogeneity of the genuine variables with respect to an artificially generated random walk variable was rejected too often. In the present paper we attempt a full analytical study of this problem. It can be shown that if the genuine variables are nonstationary, the Wald statistic for testing the block exogeneity hypothesis does not have …
Estimating Long Run Economic Equilibria, Peter C.B. Phillips, Mico Loretan
Estimating Long Run Economic Equilibria, Peter C.B. Phillips, Mico Loretan
Cowles Foundation Discussion Papers
Our subject is econometric estimation and inference concerning long-run economic equilibria in models with stochastic trends. Our interest is focused on single equation specifications such as those employed in the Error Correction Model (ECM) methodology of David Hendry (1987, 1989 inter alia) and the semiparametric modified least squares method of Phillips and Hansen (1989). We start by reviewing the prescriptions for empirical time series research that are presently available. We argue that the diversity of choices is confusing to practitioners and obscures the fact that statistical theory is clear about optimal inference procedures. Part of the difficulty arises from the …