Estelle Bee Dagum

Personal Details

First Name:	Estelle
Middle Name:	Bee
Last Name:	Dagum
Suffix:
RePEc Short-ID:	pda523
	[This author has chosen not to make the email address public]

Affiliation

(50%) Dipartimento di Scienze Statistiche "Paolo Fortunati"
Alma Mater Studiorum - Università di Bologna

Bologna, Italy
http://www.stat.unibo.it/
RePEc:edi:dsbolit (more details at EDIRC)

(50%) Statistics Canada
Government of Canada

Ottawa, Canada
http://www.statcan.gc.ca/
RePEc:edi:stagvca (more details at EDIRC)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

1. Estela Bee Dagum & Alessandra Luati, 2002. "A linear transformation and its properties with special applications in time series filtering," Quaderni di Dipartimento 2, Department of Statistics, University of Bologna.

   Cited by:

   1. Luati, Alessandra & Proietti, Tommaso, 2008. "On the Spectral Properties of Matrices Associated with Trend Filters," MPRA Paper 11502, University Library of Munich, Germany.
      • Luati, Alessandra & Proietti, Tommaso, 2010. "On The Spectral Properties Of Matrices Associated With Trend Filters," Econometric Theory, Cambridge University Press, vol. 26(4), pages 1247-1261, August.

Articles

1. Simone Giannerini & Esfandiar Maasoumi & Estela Bee Dagum, 2015. "Entropy testing for nonlinear serial dependence in time series," Biometrika, Biometrika Trust, vol. 102(3), pages 661-675.

   Cited by:

   1. Omane-Adjepong, Maurice & Alagidede, Imhotep Paul, 2020. "High- and low-level chaos in the time and frequency market returns of leading cryptocurrencies and emerging assets," Chaos, Solitons & Fractals, Elsevier, vol. 132(C).
   2. Zacharias Psaradakis & Marián Vávra, 2015. "Portmanteau Tests for Linearity of Stationary Time Series," Birkbeck Working Papers in Economics and Finance 1514, Birkbeck, Department of Economics, Mathematics & Statistics.
      • Zacharias Psaradakis & Marian Vavra, 2016. "Portmanteau Tests for Linearity of Stationary Time Series," Working and Discussion Papers WP 1/2016, Research Department, National Bank of Slovakia.
      • Marian Vavra, 2012. "Testing Non-linearity Using a Modified Q Test," Birkbeck Working Papers in Economics and Finance 1204, Birkbeck, Department of Economics, Mathematics & Statistics.
      • Zacharias Psaradakis & Marián Vávra, 2019. "Portmanteau tests for linearity of stationary time series," Econometric Reviews, Taylor & Francis Journals, vol. 38(2), pages 248-262, February.
   3. Simone Giannerini & Greta Goracci, 2023. "Entropy-Based Tests for Complex Dependence in Economic and Financial Time Series with the R Package tseriesEntropy," Mathematics, MDPI, vol. 11(3), pages 1-27, February.
   4. Lei Jiang & Esfandiar Maasoumi & Jiening Pan & Ke Wu, 2018. "A test of general asymmetric dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 1026-1043, November.
   5. Kung-Sik Chan & Simone Giannerini & Greta Goracci & Howell Tong, 2020. "Testing for threshold regulation in presence of measurement error with an application to the PPP hypothesis," Papers 2002.09968, arXiv.org, revised Nov 2021.
   6. Renée Fry-McKibbin & Cody Yu-Ling Hsiao & Vance L. Martin, 2018. "Measuring financial interdependence in asset returns with an application to euro zone equities," CAMA Working Papers 2018-05, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
   7. Marian Vavra, 2016. "Testing the Validity of Assumptions of UC-ARIMA Models for Trend-Cycle Decompositions," Working and Discussion Papers WP 4/2016, Research Department, National Bank of Slovakia.
   8. Greta Goracci & Simone Giannerini & Kung-Sik Chan & Howell Tong, 2021. "Testing for threshold effects in the TARMA framework," Papers 2103.13977, arXiv.org.

2. Estela Bee Dagum & Silvia Bianconcini, 2013. "A Unified View of Nonparametric Trend-Cycle Predictors Via Reproducing Kernel Hilbert Spaces," Econometric Reviews, Taylor & Francis Journals, vol. 32(7), pages 848-867, October.

   Cited by:

   1. Anusha, "undated". "Evaluating reliability of some symmetric and asymmetric univariate filters," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2015-030, Indira Gandhi Institute of Development Research, Mumbai, India.

3. Theodore Alexandrov & Silvia Bianconcini & Estela Bee Dagum & Peter Maass & Tucker S. McElroy, 2012. "A Review of Some Modern Approaches to the Problem of Trend Extraction," Econometric Reviews, Taylor & Francis Journals, vol. 31(6), pages 593-624, November.

   Cited by:

   1. Vasilios Plakandaras & Theophilos Papadimitriou & Periklis Gogas, 2015. "Forecasting Daily and Monthly Exchange Rates with Machine Learning Techniques," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(7), pages 560-573, November.
      • Papadimitriou, Theophilos & Gogas, Periklis & Plakandaras, Vasilios, 2013. "Forecasting daily and monthly exchange rates with machine learning techniques," DUTH Research Papers in Economics 3-2013, Democritus University of Thrace, Department of Economics, revised 07 Apr 2015.
   2. Xu Huang & Hossein Hassani & Mansi Ghodsi & Zinnia Mukherjee & Rangan Gupta, 2016. "Do Trend Extraction Approaches Affect Causality Detection in Climate Change Studies?," Working Papers 201660, University of Pretoria, Department of Economics.
      • Huang, Xu & Hassani, Hossein & Ghodsi, Mansi & Mukherjee, Zinnia & Gupta, Rangan, 2017. "Do trend extraction approaches affect causality detection in climate change studies?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 604-624.
   3. Linh Nguyen & Vilém Novák & Soheyla Mirshahi, 2020. "Trend‐cycle Estimation Using Fuzzy Transform and Its Application for Identifying Bull and Bear Phases in Markets," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 27(3), pages 111-124, July.
   4. Jonathan Olusegun Famoroti & Omolade Adeleke, 2023. "Analysis of Wamz’s Economic Growth and Monetary Policy Using the Markov Switching Approach," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 7(4), pages 142-156, April.
   5. Michel Grun-Rehomme & OLGA VASYECHKO, 2013. "Methodes De Lissage D’Une Serie Temporelle :Le Probleme Des Extremites," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 56(2), pages 163-174.
   6. Huang, Xuan & An, Haizhong & Gao, Xiangyun & Hao, Xiaoqing & Liu, Pengpeng, 2015. "Multiresolution transmission of the correlation modes between bivariate time series based on complex network theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 493-506.
   7. Tung-Lam Dao, 2014. "Momentum Strategies with L1 Filter," Papers 1403.4069, arXiv.org.
   8. Herman O. Stekler & Yongchen Zhao, 2016. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Working Papers 2016-006, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
      • Herman Stekler & Yongchen Zhao, 2016. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Working Papers 2016-15, Towson University, Department of Economics, revised Sep 2016.
      • Yongchen Zhao, 2020. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 16(2), pages 77-97, November.
   9. Feliu Serra-Burriel & Pedro Delicado & Fernando M. Cucchietti, 2021. "Wildfires Vegetation Recovery through Satellite Remote Sensing and Functional Data Analysis," Mathematics, MDPI, vol. 9(11), pages 1-22, June.
   10. Elena Barton & Basad Al-Sarray & Stéphane Chrétien & Kavya Jagan, 2018. "Decomposition of Dynamical Signals into Jumps, Oscillatory Patterns, and Possible Outliers," Mathematics, MDPI, vol. 6(7), pages 1-13, July.
   11. Anusha, "undated". "Evaluating reliability of some symmetric and asymmetric univariate filters," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2015-030, Indira Gandhi Institute of Development Research, Mumbai, India.
   12. Riyadh Nazar Ali Algburi & Hongli Gao, 2019. "Health Assessment and Fault Detection System for an Industrial Robot Using the Rotary Encoder Signal," Energies, MDPI, vol. 12(14), pages 1-25, July.
   13. Cremaschini, Alessandro & Maruotti, Antonello, 2023. "A finite mixture analysis of structural breaks in the G-7 gross domestic product series," Research in Economics, Elsevier, vol. 77(1), pages 76-90.
   14. Bhaskar Jyoti Neog & Bimal Kishore Sahoo, 2020. "Job Reallocation Dynamics in India: Evidence from Large Manufacturing Plants," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(4), pages 934-959, August.
   15. Yoon, Gawon, 2015. "Locating change-points in Hodrick–Prescott trends with an application to US real GDP: A generalized unobserved components model approach," Economic Modelling, Elsevier, vol. 45(C), pages 136-141.
   16. McElroy, Tucker S. & Wildi, Marc, 2020. "The Multivariate Linear Prediction Problem: Model-Based and Direct Filtering Solutions," Econometrics and Statistics, Elsevier, vol. 14(C), pages 112-130.
   17. McElroy, Tucker S. & Jach, Agnieszka, 2023. "Identification of the differencing operator of a non-stationary time series via testing for zeroes in the spectral density," Computational Statistics & Data Analysis, Elsevier, vol. 177(C).
   18. Wildi Marc & McElroy Tucker, 2016. "Optimal Real-Time Filters for Linear Prediction Problems," Journal of Time Series Econometrics, De Gruyter, vol. 8(2), pages 155-192, July.
   19. Fritz, Marlon, 2019. "Steady state adjusting trends using a data-driven local polynomial regression," Economic Modelling, Elsevier, vol. 83(C), pages 312-325.
   20. Trimbur Thomas & McElroy Tucker, 2017. "Signal Extraction for Nonstationary Time Series with Diverse Sampling Rules," Journal of Time Series Econometrics, De Gruyter, vol. 9(1), pages 1-37, January.
   21. Vasilios Plakandaras & Periklis Gogas & Theophilos Papadimitriou, 2021. "Gold Against the Machine," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 5-28, January.

4. Estela Bee Dagum, 2010. "Time Series Modelling and Decomposition," Statistica, Department of Statistics, University of Bologna, vol. 70(4), pages 433-457.

   Cited by:

   1. Luis Arismendy & Carlos Cárdenas & Diego Gómez & Aymer Maturana & Ricardo Mejía & Christian G. Quintero M., 2020. "Intelligent System for the Predictive Analysis of an Industrial Wastewater Treatment Process," Sustainability, MDPI, vol. 12(16), pages 1-19, August.

5. Estela Bee Dagum & Alessandra Luati, 2009. "A Cascade Linear Filter to Reduce Revisions and False Turning Points for Real Time Trend-Cycle Estimation," Econometric Reviews, Taylor & Francis Journals, vol. 28(1-3), pages 40-59.

   Cited by:

   1. Luis J. Álvarez, 2017. "Business cycle estimation with high-pass and band-pass local polynomial regression," Working Papers 1702, Banco de España.
      • Luis J. Álvarez, 2017. "Business Cycle Estimation with High-Pass and Band-Pass Local Polynomial Regression," Econometrics, MDPI, vol. 5(1), pages 1-11, January.
   2. Tommaso Proietti & Alessandra Luati, 2008. "Real Time Estimation in Local Polynomial Regression, with Application to Trend-Cycle Analysis," CEIS Research Paper 112, Tor Vergata University, CEIS, revised 14 Jul 2008.

6. Elena Rusticelli & Richard Ashley & Estela Bee Dagum & Douglas Patterson, 2009. "A New Bispectral Test for NonLinear Serial Dependence," Econometric Reviews, Taylor & Francis Journals, vol. 28(1-3), pages 279-293.

   Cited by:

   1. Simone Giannerini & Esfandiar Maasoumi & Estela Bee Dagum, 2015. "Entropy testing for nonlinear serial dependence in time series," Biometrika, Biometrika Trust, vol. 102(3), pages 661-675.
   2. Harvill, Jane L. & Ravishanker, Nalini & Ray, Bonnie K., 2013. "Bispectral-based methods for clustering time series," Computational Statistics & Data Analysis, Elsevier, vol. 64(C), pages 113-131.

7. Dagum, Estela Bee & Bianconcini, Silvia, 2008. "The Henderson Smoother in Reproducing Kernel Hilbert Space," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 536-545.

   Cited by:

   1. Michel Grun-Rehomme & OLGA VASYECHKO, 2013. "Methodes De Lissage D’Une Serie Temporelle :Le Probleme Des Extremites," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 56(2), pages 163-174.
   2. Anusha, "undated". "Evaluating reliability of some symmetric and asymmetric univariate filters," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2015-030, Indira Gandhi Institute of Development Research, Mumbai, India.
   3. McElroy, Tucker S. & Wildi, Marc, 2020. "The Multivariate Linear Prediction Problem: Model-Based and Direct Filtering Solutions," Econometrics and Statistics, Elsevier, vol. 14(C), pages 112-130.
   4. McElroy, Tucker S. & Jach, Agnieszka, 2023. "Identification of the differencing operator of a non-stationary time series via testing for zeroes in the spectral density," Computational Statistics & Data Analysis, Elsevier, vol. 177(C).

8. Dagum, Estela Bee & Giannerini, Simone, 2006. "A critical investigation on detrending procedures for non-linear processes," Journal of Macroeconomics, Elsevier, vol. 28(1), pages 175-191, March.

   Cited by:

   1. Kauermann Goeran & Krivobokova Tatyana & Semmler Willi, 2011. "Filtering Time Series with Penalized Splines," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(2), pages 1-28, March.
   2. Blöchl, Andreas, 2014. "Penalized Splines as Frequency Selective Filters - Reducing the Excess Variability at the Margins," Discussion Papers in Economics 20687, University of Munich, Department of Economics.
   3. Anusha, "undated". "Evaluating reliability of some symmetric and asymmetric univariate filters," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2015-030, Indira Gandhi Institute of Development Research, Mumbai, India.
   4. Kugiumtzis Dimitris, 2008. "Evaluation of Surrogate and Bootstrap Tests for Nonlinearity in Time Series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(1), pages 1-26, March.
   5. Esfandiar Maasoumi & Jeffrey Racine, 2009. "A Robust Entropy-Based Test of Asymmetry for Discrete and Continuous Processes," Econometric Reviews, Taylor & Francis Journals, vol. 28(1-3), pages 246-261.
   6. José A. Tapia Granados & Edward L. Ionides, 2011. "Mortality and Macroeconomic Fluctuations in Contemporary Sweden [Mortalité et fluctuations macroéconomiques dans la Suède contemporaine]," European Journal of Population, Springer;European Association for Population Studies, vol. 27(2), pages 157-184, May.

9. Dagum Estela Bee & Luati Alessandra, 2004. "Relationship between Local and Global Nonparametric Estimators Measures of Fitting and Smoothing," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(2), pages 1-18, May.

   Cited by:

   1. Silvia Bianconcini, 2008. "A Reproducing Kernel Perspective of Smoothing Spline Estimators," Quaderni di Dipartimento 3, Department of Statistics, University of Bologna.

10. Dagum, Estela Bee & Quenneville, Benoit, 1993. "Dynamic linear models for time series components," Journal of Econometrics, Elsevier, vol. 55(1-2), pages 333-351.

    Cited by:

    1. Stefano Grassi & Tommaso Proietti, 2011. "Stochastic trends and seasonality in economic time series: new evidence from Bayesian stochastic model specification search," CREATES Research Papers 2011-30, Department of Economics and Business Economics, Aarhus University.
       • Grassi, Stefano & Proietti, Tommaso, 2011. "Stochastic trends and seasonality in economic time series: new evidence from Bayesian stochastic model specification search," Working Papers 07/2011, University of Sydney Business School, Discipline of Business Analytics.
       • Tommaso Proietti & Stefano Grassi, 2015. "Stochastic trends and seasonality in economic time series: new evidence from Bayesian stochastic model specification search," Empirical Economics, Springer, vol. 48(3), pages 983-1011, May.
    2. Tommaso, Proietti & Stefano, Grassi, 2010. "Bayesian stochastic model specification search for seasonal and calendar effects," MPRA Paper 27305, University Library of Munich, Germany.
       • Stefano Grassi & Tommaso Proietti, 2011. "Bayesian stochastic model specification search for seasonal and calendar effects," CREATES Research Papers 2011-08, Department of Economics and Business Economics, Aarhus University.

11. Dagum, Estela Bee, 1989. "The future of the forecasting profession," International Journal of Forecasting, Elsevier, vol. 5(2), pages 155-157.

    Cited by:

    1. Ord, Keith, 1995. "The future of the International Journal of Forecasting," International Journal of Forecasting, Elsevier, vol. 11(2), pages 197-198, June.

12. Dagum, Estela Bee & Laniel, Normand, 1987. "Revisions of Trend-Cycle Estimators of Moving Average Seasonal Adjustment Methods," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(2), pages 177-189, April.

    Cited by:

    1. Hotta, Luiz Koodi, 1988. "Seasonal adjustment of brazilian time series," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 8(1), June.
    2. Sana Souaid Jad, 2011. "The use of surveys to measure sentiment and expected behaviour of key sectors in the economy: evidence from the business survey conducted by the Central Bank of Lebanon," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Proceedings of the IFC Conference on "Initiatives to address data gaps revealed by the financial crisis", Basel, 25-26 August 2010, volume 34, pages 248-277, Bank for International Settlements.
    3. Pfeffermann, Danny & Morry, Marietta & Wong, Paul, 1995. "Estimation of the variances of X-11 ARIMA seasonally adjusted estimators for a multiplicative decomposition and heteroscedastic variances," International Journal of Forecasting, Elsevier, vol. 11(2), pages 271-283, June.

13. Dagum, Estela Bee & Laniel, Normand J D, 1984. "Issues Involved with the Seasonal Adjustment of Economic Time Series: Comment," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 328-332, October.

    Cited by:

    1. William R. Bell & Eric Ghysels & Hahn Shik Lee, 1997. "Seasonal Time Series and Autocorrelation Function Estimation," CIRANO Working Papers 97s-35, CIRANO.
       • Hahn Shik Lee & Eric Ghysels & William R. Bell, 2002. "Seasonal Time Series and Autocorrelation Function Estimation," Manchester School, University of Manchester, vol. 70(5), pages 651-665, September.

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