Abstract: We suggest improved tests for cointegration rank in the vector autoregressive (VAR) mod... more Abstract: We suggest improved tests for cointegration rank in the vector autoregressive (VAR) model and develop asymptotic distribution theory and local power results. The tests are (quasi-) likelihood ratio tests based on a Gaussian likelihood, but of course the asymptotic results apply more generally. The power gains relative to existing tests are due to two factors.
Abstract: A frequent criticism of unit root tests concerns the poor power and size properties tha... more Abstract: A frequent criticism of unit root tests concerns the poor power and size properties that many of such tests exhibit. However, the past decade or so intensive research has been conducted to alleviate these problems and great advances have been made. The present paper provides a selective survey of recent contributions to improve upon both size and power of unit root tests and in so doing the approach of using rigorous statistical optimality criteria in the development of such tests is stressed.
Abstract. With the aim of improving the quality of asymptotic distributional approximations for n... more Abstract. With the aim of improving the quality of asymptotic distributional approximations for nonlinear functionals of nonparametric estimators, this paper revis% its the large% sample properties of an important member of that class, namely a kernel% based weighted average derivative estimator. Asymptotic linearity of the estimator is established under weak conditions. Indeed, we show that the bandwidth conditions employed are necessary in some cases.
Abstract: In an important generalization of zero frequency autoregressive unit root tests, Hylleb... more Abstract: In an important generalization of zero frequency autoregressive unit root tests, Hylleberg, Engle, Granger, and Yoo (1990) developed regression-based tests for unit roots at the seasonal frequencies in quarterly time series. We develop likelihood ratio tests for seasonal unit roots and show that these tests are" nearly efficient" in the sense of Elliott, Rothenberg, and Stock
Abstract: Employing the" small bandwidth" asymptotic framework of Cattaneo, Crump, and Jansson (2... more Abstract: Employing the" small bandwidth" asymptotic framework of Cattaneo, Crump, and Jansson (2009), this paper studies the properties of a variety of bootstrap-based inference procedures associated with the kernel-based density-weighted averaged derivative estimator proposed by Powell, Stock, and Stoker (1989). In many cases validity of bootstrap-based inference procedures is found to depend crucially on whether the bandwidth sequence satisfies a particular (asymptotic linearity) condition.
This paper presents a novel data-driven bandwidth selector compatible with the small bandwidth as... more This paper presents a novel data-driven bandwidth selector compatible with the small bandwidth asymptotics developed in Cattaneo, Crump, and Jansson (2009) for density-weighted average derivatives. The new bandwidth selector is of the plug-in variety, and is obtained based on a mean squared error expansion of the estimator of interest.
Abstract: Seemingly absent from the arsenal of currently available" nearly efficient" testing pro... more Abstract: Seemingly absent from the arsenal of currently available" nearly efficient" testing procedures for the unit root hypothesis, ie tests whose local asymptotic power functions are indistinguishable from the Gaussian power envelope, is a test admitting a (quasi-) likelihood ratio interpretation. We show that the likelihood ratio unit root test derived in a Gaussian AR (1) model with standard normal innovations is nearly efficient in that model.
Abstract Non-standard distributional approximations have received considerable attention in recen... more Abstract Non-standard distributional approximations have received considerable attention in recent years. They often provide more accurate approximations in small samples, and theoretical improvements in some cases. This paper shows that the seemingly unrelated ���many instruments asymptotics��� and ���small bandwidth asymptotics��� share a common structure, where the object determining the limiting distribution is a V-statistic with a remainder that is an asymptotically normal degenerate U-statistic.
Abstract: We suggest improved tests for cointegration rank in the vector autoregressive (VAR) mod... more Abstract: We suggest improved tests for cointegration rank in the vector autoregressive (VAR) model and develop asymptotic distribution theory and local power results. The tests are (quasi-) likelihood ratio tests based on a Gaussian likelihood, but of course the asymptotic results apply more generally. The power gains relative to existing tests are due to two factors.
Abstract: A frequent criticism of unit root tests concerns the poor power and size properties tha... more Abstract: A frequent criticism of unit root tests concerns the poor power and size properties that many of such tests exhibit. However, the past decade or so intensive research has been conducted to alleviate these problems and great advances have been made. The present paper provides a selective survey of recent contributions to improve upon both size and power of unit root tests and in so doing the approach of using rigorous statistical optimality criteria in the development of such tests is stressed.
Abstract. With the aim of improving the quality of asymptotic distributional approximations for n... more Abstract. With the aim of improving the quality of asymptotic distributional approximations for nonlinear functionals of nonparametric estimators, this paper revis% its the large% sample properties of an important member of that class, namely a kernel% based weighted average derivative estimator. Asymptotic linearity of the estimator is established under weak conditions. Indeed, we show that the bandwidth conditions employed are necessary in some cases.
Abstract: In an important generalization of zero frequency autoregressive unit root tests, Hylleb... more Abstract: In an important generalization of zero frequency autoregressive unit root tests, Hylleberg, Engle, Granger, and Yoo (1990) developed regression-based tests for unit roots at the seasonal frequencies in quarterly time series. We develop likelihood ratio tests for seasonal unit roots and show that these tests are" nearly efficient" in the sense of Elliott, Rothenberg, and Stock
Abstract: Employing the" small bandwidth" asymptotic framework of Cattaneo, Crump, and Jansson (2... more Abstract: Employing the" small bandwidth" asymptotic framework of Cattaneo, Crump, and Jansson (2009), this paper studies the properties of a variety of bootstrap-based inference procedures associated with the kernel-based density-weighted averaged derivative estimator proposed by Powell, Stock, and Stoker (1989). In many cases validity of bootstrap-based inference procedures is found to depend crucially on whether the bandwidth sequence satisfies a particular (asymptotic linearity) condition.
This paper presents a novel data-driven bandwidth selector compatible with the small bandwidth as... more This paper presents a novel data-driven bandwidth selector compatible with the small bandwidth asymptotics developed in Cattaneo, Crump, and Jansson (2009) for density-weighted average derivatives. The new bandwidth selector is of the plug-in variety, and is obtained based on a mean squared error expansion of the estimator of interest.
Abstract: Seemingly absent from the arsenal of currently available" nearly efficient" testing pro... more Abstract: Seemingly absent from the arsenal of currently available" nearly efficient" testing procedures for the unit root hypothesis, ie tests whose local asymptotic power functions are indistinguishable from the Gaussian power envelope, is a test admitting a (quasi-) likelihood ratio interpretation. We show that the likelihood ratio unit root test derived in a Gaussian AR (1) model with standard normal innovations is nearly efficient in that model.
Abstract Non-standard distributional approximations have received considerable attention in recen... more Abstract Non-standard distributional approximations have received considerable attention in recent years. They often provide more accurate approximations in small samples, and theoretical improvements in some cases. This paper shows that the seemingly unrelated ���many instruments asymptotics��� and ���small bandwidth asymptotics��� share a common structure, where the object determining the limiting distribution is a V-statistic with a remainder that is an asymptotically normal degenerate U-statistic.
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Papers by Michael Jansson