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Temporal aggregation, systematic sampling, and the Hodrick-Prescott filter

Citations

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Cited by:

  1. Moghtaderi, Azadeh & Flandrin, Patrick & Borgnat, Pierre, 2013. "Trend filtering via empirical mode decompositions," Computational Statistics & Data Analysis, Elsevier, vol. 58(C), pages 114-126.
  2. Sbrana, Giacomo, 2013. "The exact linkage between the Beveridge–Nelson decomposition and other permanent-transitory decompositions," Economic Modelling, Elsevier, vol. 30(C), pages 311-316.
  3. Álvarez, Luis J. & Gómez-Loscos, Ana, 2018. "A menu on output gap estimation methods," Journal of Policy Modeling, Elsevier, vol. 40(4), pages 827-850.
  4. Andreas Billmeier, 2009. "Ghostbusting: which output gap really matters?," International Economics and Economic Policy, Springer, vol. 6(4), pages 391-419, December.
  5. Mikko Myrskylä, 2010. "The effects of shocks in early life mortality on later life expectancy and mortality compression: A cohort analysis," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 22(12), pages 289-320.
  6. Francisco J. Ib��ez-Hern�ndez & Miguel �. Pe�a-Cerezo & Andr�s Araujo, 2015. "Countercyclical capital buffers: credit-to-GDP ratio versus credit growth," Applied Economics Letters, Taylor & Francis Journals, vol. 22(5), pages 385-390, March.
  7. Aliaga Lordemann, Javier & Villegas Quino, Horacio & Rubín de Celis, Raúl, 2011. "Ciclos Económicos e Inversión en Bolivia," Documentos de trabajo 2/2011, Instituto de Investigaciones Socio-Económicas (IISEC), Universidad Católica Boliviana.
  8. Hiroshi Yamada & Lan Jin, 2013. "Japan’s output gap estimation and ℓ 1 trend filtering," Empirical Economics, Springer, vol. 45(1), pages 81-88, August.
  9. Ballestar, María Teresa & Díaz-Chao, Ángel & Sainz, Jorge & Torrent-Sellens, Joan, 2021. "Impact of robotics on manufacturing: A longitudinal machine learning perspective," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
  10. Fritz, Marlon, 2019. "Steady state adjusting trends using a data-driven local polynomial regression," Economic Modelling, Elsevier, vol. 83(C), pages 312-325.
  11. Carlo Ciccarelli & Stefano Fenoaltea & Tommaso Proietti, 2010. "The effects of unification: markets, policy, and cyclical convergence in Italy, 1861–1913," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 4(3), pages 269-292, October.
  12. Victor M. Guerrero, 2008. "Estimating Trends with Percentage of Smoothness Chosen by the User," International Statistical Review, International Statistical Institute, vol. 76(2), pages 187-202, August.
  13. Chiarella, Carl & Hung, Hing & T, Thuy-Duong, 2009. "The volatility structure of the fixed income market under the HJM framework: A nonlinear filtering approach," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2075-2088, April.
  14. Ballestar, María Teresa & García-Lazaro, Aida & Sainz, Jorge & Sanz, Ismael, 2022. "Why is your company not robotic? The technology and human capital needed by firms to become robotic," Journal of Business Research, Elsevier, vol. 142(C), pages 328-343.
  15. Terence C. Mills, 2013. "Trends, cycles and structural breaks," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 3, pages 45-60, Edward Elgar Publishing.
  16. Kathavate, Jay, 2013. "Direct & Indirect Effects of Aid Volatility on Growth: Do Stronger Institutions Play a Role?," MPRA Paper 45187, University Library of Munich, Germany.
  17. Marlon Fritz, 2019. "Data-Driven Local Polynomial Trend Estimation for Economic Data - Steady State Adjusting Trends," Working Papers Dissertations 49, Paderborn University, Faculty of Business Administration and Economics.
  18. Borja Jalón & Simón Sosvilla-Rivero & José A. Herce, 2017. "Countercyclical Labor Productivity: The Spanish Anomaly," IREA Working Papers 201712, University of Barcelona, Research Institute of Applied Economics, revised Jun 2017.
  19. Xu, Jia & Tan, Xiujie & He, Gang & Liu, Yu, 2019. "Disentangling the drivers of carbon prices in China's ETS pilots — An EEMD approach," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 1-9.
  20. Galimberti, Jaqueson K. & Moura, Marcelo L., 2016. "Improving the reliability of real-time output gap estimates using survey forecasts," International Journal of Forecasting, Elsevier, vol. 32(2), pages 358-373.
  21. Aliaga Lordemann, Javier & Rubin de Celis, Raúl & Villegas Quino, Horacio, 2011. "No Linealidad de los Ciclos Económicos en Bolivia," Documentos de trabajo 7/2011, Instituto de Investigaciones Socio-Económicas (IISEC), Universidad Católica Boliviana.
  22. Víctor M. Guerrero & Adriana Galicia‐Vázquez, 2010. "Trend estimation of financial time series," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 26(3), pages 205-223, May.
  23. Jaqueson K. Galimberti & Marcelo L. Moura, 2011. "Improving the reliability of real-time Hodrick-Prescott filtering using survey forecasts," Centre for Growth and Business Cycle Research Discussion Paper Series 159, Economics, The University of Manchester.
  24. Ringwald, Leopold & Zörner, Thomas O., 2023. "The money-inflation nexus revisited," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 293-333.
  25. Riccardo De Bonis & Andrea Silvestrini, 2014. "The Italian financial cycle: 1861-2011," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 8(3), pages 301-334, September.
  26. Tapia, Jose, 2016. "Oil prices and the world business cycle: A causal investigation," MPRA Paper 68978, University Library of Munich, Germany.
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