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COINTEGRATING POLYNOMIAL REGRESSIONS: ROBUSTNESS OF FULLY MODIFIED OLS

协整多项式回归:完全修正最小二乘法的稳健性

Cointegrating polynomial regressions (CPRs) include deterministic variables, integrated variables, and their powers as explanatory variables. Based on a novel kernel-weighted limit result and a novel functional central limit theorem, this paper shows that the fully modified ordinary least squares (FM-OLS) estimator of Phillips and Hansen (1990, Review of Economic Studies 57, 99–125) is robust to being used in CPRs. Being used in CPRs refers to a widespread empirical practice…

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Fully modified OLS estimation and inference for seemingly unrelated cointegrating polynomial regressions and the environmental Kuznets curve for carbon dioxide emissions

似不相关协整多项式回归的完全修正OLS估计、推断与二氧化碳环境库兹涅茨曲线

This paper develops two fully modified OLS (FM-OLS) estimators for systems of seemingly unrelated cointegrating polynomial regressions, i.e., systems of regressions that include deterministic variables, integrated processes, and integer powers of integrated processes as explanatory variables. The stationary errors are allowed to be serially correlated and the regressors to be endogenous. Furthermore, the errors and regressors are allowed to be dynamically cross-sectionally…

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COINTEGRATING POLYNOMIAL REGRESSIONS: FULLY MODIFIED OLS ESTIMATION AND INFERENCE

协整多项式回归的完全修正 OLS 估计与推断

This paper develops a fully modified OLS (FM-OLS) estimator for cointegrating polynomial regressions, i.e., regressions that include as explanatory variables deterministic variables, integrated processes, and integer powers of integrated processes. The stationary errors are allowed to be serially correlated and the regressors are allowed to be endogenous. The paper extends the fully modified estimator of Phillips and Hansen (1990) from cointegrating regressions to…

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The Environmental Kuznets Curve, Cointegration and Nonlinearity

环境库兹涅茨曲线、协整与非线性

Summary This paper clarifies some conceptual shortcomings of the empirical environmental Kuznets curve (EKC) literature that arise because of the hitherto inadequate application of unit root and cointegration techniques. The literature to date has ignored the fact, and a fortiori the consequences, that powers of integrated processes are themselves not integrated processes. The paper explains why standard methods should not be applied and discusses some recently proposed…

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Nonparametric rank tests for non-stationary panels

非平稳面板的非参数秩检验

We develop a set of nonparametric rank tests for non-stationary panels based on multivariate variance ratios which use untruncated kernels. As such, the tests do not require the choice of tuning parameters associated with bandwidth or lag length and also do not require choices with respect to numbers of common factors. The tests allow for unrestricted cross-sectional dependence and dynamic heterogeneity among the units of the panel, provided simply that a joint functional…

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Integrated modified OLS estimation and fixed- inference for cointegrating regressions

This paper is concerned with parameter estimation and inference in a cointegrating regression, where as usual endogenous regressors as well as serially correlated errors are considered. We propose a simple, new estimation method based on an augmented partial sum (integration) transformation of the regression model. The new estimator is labeled integrated modified ordinary least squares (IM-OLS). IM-OLS is similar in spirit to the fully modified OLS approach of Phillips and…

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A FIXED- b PERSPECTIVE ON THE PHILLIPS–PERRON UNIT ROOT TESTS

Phillips–Perron 单位根检验的 fixed-b 视角

In this paper we extend fixed- b asymptotic theory to the nonparametric Phillips–Perron (PP) unit root tests. We show that the fixed- b limits depend on nuisance parameters in a complicated way. These nonpivotal limits provide an alternative theoretical explanation for the well-known finite-sample problems of the PP tests. We also show that the fixed- b limits depend on whether deterministic trends are removed using one-step or two-step detrending approaches. This is in…

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A STATE SPACE CANONICAL FORM FOR UNIT ROOT PROCESSES

单位根过程的状态空间规范形式

In this paper we develop a canonical state space representation of autoregressive moving average (ARMA) processes with unit roots with integer integration orders at arbitrary unit root frequencies. The developed representation utilizes a state process with a particularly simple dynamic structure, which in turn renders this representation highly suitable for unit root, cointegration, and polynomial cointegration analysis. We also propose a new definition of polynomial…

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