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Rejoinder: Asymptotic Theory of Outlier Detection Algorithms for Linear Time Series Regression Models

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Cited by:

  1. Brian Chi-ang Lin & Siqi Zheng & Felix Pretis & Lea Schneider & Jason E. Smerdon & David F. Hendry, 2016. "Detecting Volcanic Eruptions In Temperature Reconstructions By Designed Break-Indicator Saturation," Journal of Economic Surveys, Wiley Blackwell, vol. 30(3), pages 403-429, July.
  2. Jiao, Xiyu & Pretis, Felix & Schwarz, Moritz, 2024. "Testing for coefficient distortion due to outliers with an application to the economic impacts of climate change," Journal of Econometrics, Elsevier, vol. 239(1).
  3. Ericsson, Neil R., 2017. "How biased are U.S. government forecasts of the federal debt?," International Journal of Forecasting, Elsevier, vol. 33(2), pages 543-559.
  4. Emmanuel Flachaire & Gilles Hacheme & Sullivan Hu'e & S'ebastien Laurent, 2022. "GAM(L)A: An econometric model for interpretable Machine Learning," Papers 2203.11691, arXiv.org.
  5. Ericsson, Neil R., 2016. "Eliciting GDP forecasts from the FOMC’s minutes around the financial crisis," International Journal of Forecasting, Elsevier, vol. 32(2), pages 571-583.
  6. Andrew B. Martinez, 2020. "Forecast Accuracy Matters for Hurricane Damage," Econometrics, MDPI, vol. 8(2), pages 1-24, May.
  7. Hendry, David F., 2018. "Deciding between alternative approaches in macroeconomics," International Journal of Forecasting, Elsevier, vol. 34(1), pages 119-135.
  8. David H. Bernstein & Andrew B. Martinez, 2021. "Jointly Modeling Male and Female Labor Participation and Unemployment," Econometrics, MDPI, vol. 9(4), pages 1-14, December.
  9. Ericsson, Neil R., 2017. "Interpreting estimates of forecast bias," International Journal of Forecasting, Elsevier, vol. 33(2), pages 563-568.
  10. Neil R. Ericsson, 2021. "Dynamic Econometrics in Action: A Biography of David F. Hendry," International Finance Discussion Papers 1311, Board of Governors of the Federal Reserve System (U.S.).
  11. Atkinson, Anthony C. & Riani, Marco & Torti, Francesca, 2016. "Robust methods for heteroskedastic regression," Computational Statistics & Data Analysis, Elsevier, vol. 104(C), pages 209-222.
  12. Vanessa Berenguer Rico & Bent Nielsen & Søren Johansen, 2019. "Uniform Consistency of Marked and Weighted Empirical Distributions of Residuals," Economics Series Working Papers 871, University of Oxford, Department of Economics.
  13. Jennifer Castle & David Hendry, 2016. "Policy Analysis, Forediction, and Forecast Failure," Economics Series Working Papers 809, University of Oxford, Department of Economics.
  14. Pretis, Felix, 2020. "Econometric modelling of climate systems: The equivalence of energy balance models and cointegrated vector autoregressions," Journal of Econometrics, Elsevier, vol. 214(1), pages 256-273.
  15. David F. Hendry & Grayham E. Mizon, 2016. "Improving the teaching of econometrics," Cogent Economics & Finance, Taylor & Francis Journals, vol. 4(1), pages 1170096-117, December.
  16. Baiardi, Donatella & Morana, Claudio, 2021. "Climate change awareness: Empirical evidence for the European Union," Energy Economics, Elsevier, vol. 96(C).
  17. Jennifer L. Castle & David F. Hendry & Andrew B. Martinez, 2017. "Evaluating Forecasts, Narratives and Policy Using a Test of Invariance," Econometrics, MDPI, vol. 5(3), pages 1-27, September.
  18. Pollack, Adam B. & Kaufmann, Robert K., 2022. "Increasing storm risk, structural defense, and house prices in the Florida Keys," Ecological Economics, Elsevier, vol. 194(C).
  19. Neil R. Ericsson & Mohammed H. I. Dore & Hassan Butt, 2022. "Detecting and Quantifying Structural Breaks in Climate," Econometrics, MDPI, vol. 10(4), pages 1-27, November.
  20. Vanessa Berenguer-Rico & Søren Johansen & Bent Nielsen, 2019. "The analysis of marked and weighted empirical processes of estimated residuals," Economics Papers 2019-W03, Economics Group, Nuffield College, University of Oxford.
  21. David H. Bernstein & Bent Nielsen, 2019. "Asymptotic Theory for Cointegration Analysis When the Cointegration Rank Is Deficient," Econometrics, MDPI, vol. 7(1), pages 1-24, January.
  22. Vassilios Bazinas & Bent Nielsen, 2022. "Causal Transmission in Reduced-Form Models," Econometrics, MDPI, vol. 10(2), pages 1-25, March.
  23. Anthony C. Atkinson & Andrea Cerioli & Marco Riani, 2016. "Discussion of ‘Asymptotic Theory of Outlier Detection Algorithms for Linear Time Series Regression Models’ by Johansen and Nielsen," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 349-352, June.
  24. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2023. "Robust Discovery of Regression Models," Econometrics and Statistics, Elsevier, vol. 26(C), pages 31-51.
  25. Khan, Faridoon & Muhammadullah, Sara & Sharif, Arshian & Lee, Chien-Chiang, 2024. "The role of green energy stock market in forecasting China's crude oil market: An application of IIS approach and sparse regression models," Energy Economics, Elsevier, vol. 130(C).
  26. Felix Pretis, 2022. "Does a Carbon Tax Reduce CO2 Emissions? Evidence from British Columbia," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 83(1), pages 115-144, September.
  27. Fernandes, Leonardo H.S. & Silva, José W.L. & de Araujo, Fernando H.A. & Tabak, Benjamin M., 2023. "Multifractal cross-correlations between green bonds and financial assets," Finance Research Letters, Elsevier, vol. 53(C).
  28. Kaufmann, Robert K., 2023. "Energy price volatility affects decisions to purchase energy using capital: Motor vehicles," Energy Economics, Elsevier, vol. 126(C).
  29. Vanessa Berenguer Rico & Bent Nielsen, 2017. "Marked and Weighted Empirical Processes of Residuals with Applications to Robust Regressions," Economics Series Working Papers 841, University of Oxford, Department of Economics.
  30. Grossi, Luigi & Nan, Fany, 2019. "Robust forecasting of electricity prices: Simulations, models and the impact of renewable sources," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 305-318.
  31. Sullivan Hué, 2022. "GAM(L)A: An econometric model for interpretable machine learning," French Stata Users' Group Meetings 2022 19, Stata Users Group.
  32. Corbellini, Aldo & Magnani, Marco & Morelli, Gianluca, 2021. "Labor market analysis through transformations and robust multivariate models," Socio-Economic Planning Sciences, Elsevier, vol. 73(C).
  33. Antoni Espasa & Eva Senra, 2017. "Twenty-Two Years of Inflation Assessment and Forecasting Experience at the Bulletin of EU & US Inflation and Macroeconomic Analysis," Econometrics, MDPI, vol. 5(4), pages 1-28, October.
  34. James Reade & Genaro Sucarrat, 2016. "General-to-Specific (GETS) Modelling And Indicator Saturation With The R Package Gets," Economics Series Working Papers 794, University of Oxford, Department of Economics.
  35. Xiyu Jiao & Felix Pretis, 2022. "Testing the Presence of Outliers in Regression Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(6), pages 1452-1484, December.
  36. Ericsson Neil R., 2016. "Testing for and estimating structural breaks and other nonlinearities in a dynamic monetary sector," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 377-398, September.
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