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Systematic Sampling, Temporal Aggregation, Seasonal Adjustment, and Cointegration: Theory and Evidence

Citations

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Cited by:

  1. is not listed on IDEAS
  2. Hugo Oliveros C., 1995. "Estaciones y Pruebas de Ra�ces Unitarias: Algunas Consideraciones Generales," Borradores de Economia 2591, Banco de la Republica.
  3. Cubadda, Gianluca & Omtzigt, Pieter, 2005. "Small-sample improvements in the statistical analysis of seasonally cointegrated systems," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 333-348, April.
  4. Maria Nikoloudaki & Dikaios Tserkezos, 2008. "Temporal Aggregation Effects in Choosing the Optimal Lag Order in Stable ARMA Models: Some Monte Carlo Results," Working Papers 0822, University of Crete, Department of Economics.
  5. Mamingi Nlandu, 2017. "Beauty and Ugliness of Aggregation over Time: A Survey," Review of Economics, De Gruyter, vol. 68(3), pages 205-227, December.
  6. Terraza Virginie & Toque Carole, 2008. "Times series Factorial models with incertitute measures on ARMA processes and its application to final data," LSF Research Working Paper Series 08-07, Luxembourg School of Finance, University of Luxembourg.
  7. Pesaran, M. Hashem & Chudik, Alexander, 2014. "Aggregation in large dynamic panels," Journal of Econometrics, Elsevier, vol. 178(P2), pages 273-285.
  8. Wróblewska, Justyna, 2025. "Bayesian analysis of seasonally cointegrated VAR models," Econometrics and Statistics, Elsevier, vol. 35(C), pages 55-70.
  9. Aadland, David, 2005. "Detrending time-aggregated data," Economics Letters, Elsevier, vol. 89(3), pages 287-293, December.
  10. von Cramon-Taubadel, Stephan & Loy, Jens-Peter & Meyer, Jochen, 2006. "Data Aggregation and Vertical Price Transmission: An Experiment with German Food Prices," 2006 Annual Meeting, August 12-18, 2006, Queensland, Australia 25291, International Association of Agricultural Economists.
  11. Carlomagno, Guillermo & Fornero, Jorge & Sansone, Andrés, 2023. "A proposal for constructing and evaluating core inflation measures," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 4(3).
  12. Guillermo Carlomagno & Jorge Fornero & Andrés Sansone, 2021. "Toward a general framework for constructing and evaluating core inflation measures," Working Papers Central Bank of Chile 913, Central Bank of Chile.
  13. Ivan D. Trofimov, 2024. "Testing Wagner’s hypothesis using disaggregated data: evidence from a global panel," International Journal of Economic Policy Studies, Springer, vol. 18(1), pages 143-171, February.
  14. José Casals & Miguel Jerez & Sonia Sotoca, 2009. "Modelling and forecasting time series sampled at different frequencies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(4), pages 316-342.
  15. Tierney, Heather L.R. & Kim, Jiyoon (June) & Nazarov, Zafar, 2018. "The Effects of Temporal Aggregation on Search Engine Data," MPRA Paper 84474, University Library of Munich, Germany.
  16. Jung, Young Cheol & Das, Anupam & McFarlane, Adian, 2020. "The asymmetric relationship between the oil price and the US-Canada exchange rate," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 198-206.
  17. von Cramon-Taubadel, Stephan & Loy, Jens-Peter & Meyer, Jochen, 2003. "The Impact Of Data Aggregation On The Measurement Of Vertical Price Transmission: Evidence From German Food Prices," 2003 Annual meeting, July 27-30, Montreal, Canada 21987, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  18. Bohl, Martin T., 2000. "Nonstationary stochastic seasonality and the German M2 money demand function," European Economic Review, Elsevier, vol. 44(1), pages 61-70, January.
  19. repec:hal:journl:peer-00815563 is not listed on IDEAS
  20. Rotger, Gabriel Pons, "undated". "Testing for Seasonal Unit Roots with Temporally Aggregated Time Series," Economics Working Papers 2003-16, Department of Economics and Business Economics, Aarhus University.
  21. Cleiton Guollo Taufemback, 2023. "Asymptotic Behavior of Temporal Aggregation in Mixed‐Frequency Datasets," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(4), pages 894-909, August.
  22. J. Isaac Miller, 2014. "Mixed-frequency Cointegrating Regressions with Parsimonious Distributed Lag Structures," Journal of Financial Econometrics, Oxford University Press, vol. 12(3), pages 584-614.
  23. Gabriel Pons, 2006. "Testing Monthly Seasonal Unit Roots With Monthly and Quarterly Information," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(2), pages 191-209, March.
  24. Benos, Nikos & Karagiannis, Stelios, 2013. "Do Cross-Section Dependence and Parameter Heterogeneity Matter? Evidence on Human Capital and Productivity in Greece," MPRA Paper 53326, University Library of Munich, Germany.
  25. J. Isaac Miller, 2016. "Conditionally Efficient Estimation of Long-Run Relationships Using Mixed-Frequency Time Series," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 1142-1171, June.
  26. Hugo Oliveros, 1995. "Estacionalidad y Pruebas de Raíces Unitarias:Algunas Consideraciones Generales," Borradores de Economia 040, Banco de la Republica de Colombia.
  27. Cláudia Duarte, 2015. "Covariate-augmented unit root tests with mixed-frequency data," Working Papers w201507, Banco de Portugal, Economics and Research Department.
  28. Markus Eberhardt & Francis Teal, 2011. "Econometrics For Grumblers: A New Look At The Literature On Cross‐Country Growth Empirics," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 109-155, February.
  29. Marcellino, Massimiliano, 1999. "Some Consequences of Temporal Aggregation in Empirical Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 129-136, January.
  30. Markus Eberhardt & Francis Teal, 2011. "Econometrics For Grumblers: A New Look At The Literature On Cross‐Country Growth Empirics," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 109-155, 02.
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