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THE IMPOSSIBILITY OF CONSISTENT DISCRIMINATION BETWEEN I(0) AND I(1) PROCESSES
9 references·7 citing·41 second hop
THE IMPOSSIBILITY OF CONSISTENT DISCRIMINATION BETWEEN I(0) AND I(1) PROCESSES (2008)THE IMPOSSIBILITY OF CONSISTENT DISCRIMIN…Size and power of tests of stationarity in highly autocorrelated time series (2004)Size and power of tests of st…Nonparametric tests for unit roots and cointegration (2002)Nonparametric tests for unit …Establishing conditions for the functional central limit theorem in nonlinear and semiparametric time series processes (2002)Establishing conditions for t…Size distortions of tests of the null hypothesis of stationarity: evidence and implications for the PPP debate (2001)Size distortions of tests of …New Tools for Understanding Spurious Regressions (1998)New Tools for Understanding S…Near Observational Equivalence and Theoretical size Problems with Unit Root Tests (1996)Near Observational Equivalenc…The relationship between power and level for generic unit root tests in finite samples (1992)The relationship between powe…Testing the null hypothesis of stationarity against the alternative of a unit root (1992)Testing the null hypothesis o…Brownian Motion (1980)Brownian MotionSummability of stochastic processes—A generalization of integration for non-linear processes (2013)Summability of stochastic pro…Summability of stochastic processes: a generalization of integration and co-integration valid for non-linear processes (2011)Summability of stochastic pro…Co-summability from linear to non-linear co-integration (2011)Co-summability from linear to…Reducing the size distortion of the KPSS test (2010)Reducing the size distortion …When is a Time‐Series I(0)?* (2009)When is a Time‐Series I(0)?*A POWERFUL TEST OF THE AUTOREGRESSIVE UNIT ROOT HYPOTHESIS BASED ON A TUNING PARAMETER FREE STATISTIC (2009)A POWERFUL TEST OF THE AUTORE…Testing Covariance Stationarity (2007)Testing Covariance Stationari…Distribution of the Estimators for Autoregressive Time Series with a Unit Root (1979)Distribution of the Estimators for Autoregressive Time Series With a Unit Root (1979)Testing for a Unit Root in Time Series Regression (1988)A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test (1999)Unit root tests for panel data (2001)Modelling Asymmetric Cointegration and Dynamic Multipliers in a Nonlinear ARDL Framework (2014)Understanding spurious regressions in econometrics (1986)Towards a Unified Asymptotic Theory for Autoregression (1987)Spurious Regressions in Financial Economics? (2000)HAC ESTIMATION BY AUTOMATED REGRESSION (2005)Brownian Motion and Stochastic Calculus (2007)On the Impact of GDP per Capita, Carbon Intensity and Innovation for Renewable Energy Consumption: Worldwide Evidence (2021)Generalized autoregressive conditional heteroskedasticity (1986)A model of fractional cointegration, and tests for cointegration using the bootstrap (2002)Testing Models of Low-Frequency Variability (2008)Structural Breaks in Financial Time Series (2009)Statistical analysis of cointegration vectors (1988)New Simple Tests for Panel Cointegration (2005)Unit Roots and Cointegration in Panels (2008)Risk Premiums in Dynamic Term Structure Models with Unspanned Macro Risks (2013)Testing for Unit Roots in Autoregressive-Moving Average Models of Unknown Order (1984)Long-Run PPP May Not Hold after All (1999)Estimating and testing rational expectations models when the trend specification is uncertain (2001)Finite-sample simulation-based inference in VAR models with application to Granger causality testing (2005)Trends and random walks in macroeconmic time series (1982)Co-Integration and Error Correction: Representation, Estimation, and Testing (1987)Understanding spot and forward exchange rate regressions (1997)Confidence Intervals for Half-Life Deviations From Purchasing Power Parity (2005)How predictable is technological progress? (2016)Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models (1991)Nonparametric predictive regression (2014)Efficient Tests for an Autoregressive Unit Root (1996)Prewhitening Bias in HAC Estimation* (2005)Real exchange rates and Purchasing Power Parity: mean-reversion in economic thought (2006)The CO 2 emissions-income nexus: Evidence from rich countries (2011)Determining the cointegrating rank in nonstationary fractional systems by the exact local Whittle approach (2006)A simple, robust and powerful test of the trend hypothesis (2007)Confidence sets for the date of a single break in linear time series regressions (2007)Bootstrap Unit Root Tests (2003)A Delayed Black and Scholes Formula (2007)Fractal Time Series—A Tutorial Review (2009)
this work references cited by second hop

References

  • 1992Testing the null hypothesis of stationarity against the alternative of a unit root12,634 cited
  • 1980Brownian Motion457 cited
  • 2002Nonparametric tests for unit roots and cointegration454 cited
  • 2001Size distortions of tests of the null hypothesis of stationarity: evidence and implications for the PPP debate232 cited
  • 2002Establishing conditions for the functional central limit theorem in nonlinear and semiparametric time series processes180 cited
  • 1998New Tools for Understanding Spurious Regressions178 cited
  • 1992The relationship between power and level for generic unit root tests in finite samples169 cited
  • 2004Size and power of tests of stationarity in highly autocorrelated time series101 cited
  • 1996Near Observational Equivalence and Theoretical size Problems with Unit Root Tests59 cited

Cited by

  • 2013Summability of stochastic processes—A generalization of integration for non-linear processes29 cited
  • 2007Testing Covariance Stationarity26 cited
  • 2009A POWERFUL TEST OF THE AUTOREGRESSIVE UNIT ROOT HYPOTHESIS BASED ON A TUNING PARAMETER FREE STATISTIC23 cited
  • 2009When is a Time‐Series I(0)?*22 cited
  • 2010Reducing the size distortion of the KPSS test17 cited

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2011
Summability of stochastic processes: a generalization of integration and co-integration valid for non-linear processes
17 cited
  • 2011Co-summability from linear to non-linear co-integration13 cited