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10. The Uncertain Unit Root in Real GNP: Comment
13 references·16 citing·39 second hopsampled
10. The Uncertain Unit Root in Real GNP: Comment (1999)10. The Uncertain Unit Root in Real GNP: …The Uncertain Unit Root in Real GNP (2020)The Uncertain Unit Root in Re…Unit Root Tests in ARMA Models with Data-Dependent Methods for the Selection of the Truncation Lag (1995)Unit Root Tests in ARMA Model…Testing for a Unit Root in Time Series With Pretest Data-Based Model Selection (1994)Testing for a Unit Root in Ti…Efficient Tests for an Autoregressive Unit Root (1992)Efficient Tests for an Autore…Pitfalls and Opportunities: What Macroeconomists Should Know about Unit Roots (1991)Pitfalls and Opportunities: W…Confidence intervals for the largest autoregressive root in U.S. macroeconomic time series (1991)Confidence intervals for the …Unit roots in real GNP: Do we know, and do we care? (1990)Unit roots in real GNP: Do we…The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis (1989)The Great Crash, the Oil Pric…The Estimation of Prewar Gross National Product: Methodology and New Evidence (1989)The Estimation of Prewar Gros…Long memory and persistence in aggregate output (1989)Long memory and persistence i…How Big Is the Random Walk in GNP? (1988)How Big Is the Random Walk in…The Prewar Business Cycle Reconsidered: New Estimates of Gross NationalProduct, 1869-1918 (1986)The Prewar Business Cycle Rec…Trends and random walks in macroeconmic time series (1982)Trends and random walks in ma…Trend Time–Series Modeling and Forecasting With Neural Networks (2008)Trend Time–Series Modeling an…Potential Pitfalls in Determining Multiple Structural Changes With an Application to Purchasing Power Parity (2007)Potential Pitfalls in Determi…Non-renewable resource prices: Deterministic or stochastic trends? 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References

  • 1989The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis7,685 cited
  • 1982Trends and random walks in macroeconmic time series4,670 cited
  • 1992Efficient Tests for an Autoregressive Unit Root4,234 cited
  • 1995Unit Root Tests in ARMA Models with Data-Dependent Methods for the Selection of the Truncation Lag1,459 cited
  • 1991Pitfalls and Opportunities: What Macroeconomists Should Know about Unit Roots1,314 cited
  • 1988How Big Is the Random Walk in GNP?1,270 cited
  • 1994Testing for a Unit Root in Time Series With Pretest Data-Based Model Selection701 cited
  • 1989Long memory and persistence in aggregate output546 cited
  • 1991Confidence intervals for the largest autoregressive root in U.S. macroeconomic time series416 cited
  • 1989The Estimation of Prewar Gross National Product: Methodology and New Evidence399 cited
  • 1986The Prewar Business Cycle Reconsidered: New Estimates of Gross NationalProduct, 1869-1918309 cited
  • 1990Unit roots in real GNP: Do we know, and do we care?265 cited
  • 2020The Uncertain Unit Root in Real GNP168 cited

Cited by

  • 1998The Past, Present, and Future of Macroeconomic Forecasting183 cited
  • 2006

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Non-renewable resource prices: Deterministic or stochastic trends?
156 cited
  • 2000Unit-Root Tests Are Useful for Selecting Forecasting Models152 cited
  • 2008Trend Time–Series Modeling and Forecasting With Neural Networks149 cited
  • 2000(Fractional) beta convergence141 cited
  • 2001Measuring predictability: theory and macroeconomic applications119 cited
  • 2000The uncertain trend in U.S. GDP100 cited
  • 2007Potential Pitfalls in Determining Multiple Structural Changes With an Application to Purchasing Power Parity86 cited
  • 2000Residual-Based Tests for Normality in Autoregressions: Asymptotic Theory and Simulation Evidence74 cited
  • 1998Estimating output gaps67 cited
  • 2000Unit-Root Tests Are Useful for Selecting Forecasting Models63 cited
  • 2004The Uncertain Unit Root in U.S. Real GDP: Evidence with Restricted and Unrestricted Structural Change61 cited
  • 1997Evaluating Simple Monetary-policy Rules for Australia58 cited
  • 1997The Uncertain Trend in U.S. GDP55 cited
  • 1997Monetary policy and inflation targeting54 cited
  • 2005Model combination in neural-based forecasting52 cited