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Szabolcs Blazsek

Personal Details

First Name:Szabolcs
Middle Name:
Last Name:Blazsek
Suffix:
RePEc Short-ID:pbl111
[This author has chosen not to make the email address public]
https://www.researchgate.net/profile/Szabolcs-Blazsek
Stetson-Hatcher School of Business Mercer University 1511-1565 College St, Macon, GA 31201 United States
Terminal Degree:2007 Departamento de Economía; Universidad Carlos III de Madrid (from RePEc Genealogy)

Affiliation

School of Business and Economics
Mercer University

Atlanta/Macon, Georgia (United States)
http://www.mercer.edu/Business/
RePEc:edi:sbmerus (more details at EDIRC)

Research output

as
Jump to: Working papers Articles Chapters

Working papers

  1. Blazsek, Szabolcs Istvan & Kristof, Erzsebet, 2024. "Global, Arctic, and Antarctic sea ice volume predictions: using score-driven threshold climate models," UC3M Working papers. Economics 39546, Universidad Carlos III de Madrid. Departamento de Economía.
  2. Blazsek, Szabolcs, 2022. "Score-driven threshold ice-age models: benchmark models for long-run climate forecasts," UC3M Working papers. Economics 34757, Universidad Carlos III de Madrid. Departamento de Economía.
  3. Blazsek, Szabolcs, 2021. "Robust estimation and forecasting of climate change using score-driven ice-age models," UC3M Working papers. Economics 33453, Universidad Carlos III de Madrid. Departamento de Economía.
  4. Diego Aycinena & Szabolcs Blazsek & Lucas Rentschler & Charles Sprenger, 2020. "Intertemporal Choice Experiments and Large-Stakes Behavior," Working Papers 20-36, Chapman University, Economic Science Institute.
  5. Blazsek, Szabolcs & Licht, Adrian, 2020. "Prediction accuracy of bivariate score-driven risk premium and volatility filters: an illustration for the Dow Jones," UC3M Working papers. Economics 31339, Universidad Carlos III de Madrid. Departamento de Economía.
  6. Blazsek, Szabolcs & Licht, Adrian, 2020. "Dynamic stochastic general equilibrium inference using a score-driven approach," UC3M Working papers. Economics 30347, Universidad Carlos III de Madrid. Departamento de Economía.
  7. Blazsek, Szabolcs & Licht, Adrian, 2020. "Nonlinear common trends for the global crude oil market: Markov-switching score-driven models of the multivariate t-distribution," UC3M Working papers. Economics 30346, Universidad Carlos III de Madrid. Departamento de Economía.
  8. Blazsek, Szabolcs & Licht, Adrian, 2019. "Markov-switching score-driven multivariate models: outlier-robust measurement of the relationships between world crude oil production and US industrial production," UC3M Working papers. Economics 29030, Universidad Carlos III de Madrid. Departamento de Economía.
  9. Ayala, Astrid & Blazsek, Szabolcs, 2019. "Maximum likelihood estimation of score-driven models with dynamic shape parameters : an application to Monte Carlo value-at-risk," UC3M Working papers. Economics 28638, Universidad Carlos III de Madrid. Departamento de Economía.
  10. Blazsek, Szabolcs & Licht, Adrian, 2019. "Co-integration and common trends analysis with score-driven models : an application to the federal funds effective rate and US inflation rate," UC3M Working papers. Economics 28451, Universidad Carlos III de Madrid. Departamento de Economía.
  11. Ayala, Astrid & Blazsek, Szabolcs, 2019. "Score-driven time series models with dynamic shape : an application to the Standard & Poor's 500 index," UC3M Working papers. Economics 28133, Universidad Carlos III de Madrid. Departamento de Economía.
  12. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonal quasi-vector autoregressive models for macroeconomic data," UC3M Working papers. Economics 26316, Universidad Carlos III de Madrid. Departamento de Economía.
  13. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonality Detection in Small Samples using Score-Driven Nonlinear Multivariate Dynamic Location Models," UC3M Working papers. Economics 27483, Universidad Carlos III de Madrid. Departamento de Economía.
  14. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonal Quasi-Vector Autoregressive Models with an Application to Crude Oil Production and Economic Activity in the United States and Canada," UC3M Working papers. Economics 27484, Universidad Carlos III de Madrid. Departamento de Economía.
  15. Ayala, Astrid & Blazsek, Szabolcs, 2017. "Dynamic conditional score models with time-varying location, scale and shape parameters," UC3M Working papers. Economics 25043, Universidad Carlos III de Madrid. Departamento de Economía.
  16. Blazsek, Szabolcs & Licht, Adrian, 2017. "Score-driven non-linear multivariate dynamic location models," UC3M Working papers. Economics 25739, Universidad Carlos III de Madrid. Departamento de Economía.
  17. Blazsek, Szabolcs, 2016. "Score-driven dynamic patent count panel data models," UC3M Working papers. Economics 23458, Universidad Carlos III de Madrid. Departamento de Economía.
  18. Blazsek, Szabolcs, 2015. "Dynamic conditional score patent count panel data models," UC3M Working papers. Economics we1510, Universidad Carlos III de Madrid. Departamento de Economía.
  19. Blazsek, Szabolcs, 2014. "Propensity to patent, R&D and market competition : dynamic spillovers of innovation leaders and followers," UC3M Working papers. Economics we1412, Universidad Carlos III de Madrid. Departamento de Economía.
  20. Blazsek, Szabolcs, 2012. "Patents, secret innovations and firm's rate of return : differential effects of the innovation leader," UC3M Working papers. Economics we1202, Universidad Carlos III de Madrid. Departamento de Economía.
  21. Pedro Mendi & Nadia Ayari & Szabolcs Blazsek, 2011. "Renewable energy innovations in Europe: A dynamic panel data approach," Post-Print hal-00711448, HAL.
  22. Mr. Jerome Vandenbussche & Mr. Stanley B Watt & Szabolcs Blazsek, 2009. "The Liquidity and Liquidity Distribution Effects in Emerging Markets: The Case of Jordan," IMF Working Papers 2009/228, International Monetary Fund.
  23. Blazsek, Szabolcs, 2009. "Knowledge spillovers in U.S. patents: a dynamic patent intensity model with secret common innovation factors," UC3M Working papers. Economics we098951, Universidad Carlos III de Madrid. Departamento de Economía.
  24. Szabolcs Blazsek & Anna Downarowicz, 2008. "Regime switching models of hedge fund returns," Faculty Working Papers 12/08, School of Economics and Business Administration, University of Navarra.

Articles

  1. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrián, 2024. "Non-Gaussian score-driven conditionally heteroskedastic models with a macroeconomic application," Macroeconomic Dynamics, Cambridge University Press, vol. 28(1), pages 32-50, January.
  2. Astrid Loretta Ayala & Szabolcs Blazsek & Adrian Licht, 2024. "Score function scaling for QAR plus Beta-t-EGARCH: an empirical application to the S&P 500," Applied Economics, Taylor & Francis Journals, vol. 56(31), pages 3684-3697, July.
  3. Blazsek Szabolcs & Escribano Alvaro & Licht Adrian, 2024. "Score-driven location plus scale models: asymptotic theory and an application to forecasting Dow Jones volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(1), pages 61-82, February.
  4. Blazsek, Szabolcs & Escribano, Alvaro & Kristof, Erzsebet, 2024. "Global, Arctic, and Antarctic sea ice volume predictions using score-driven threshold climate models," Energy Economics, Elsevier, vol. 134(C).
  5. Szabolcs Blazsek & Richard Bowen, 2024. "Score-driven cryptocurrency and equity portfolios," Applied Economics, Taylor & Francis Journals, vol. 56(18), pages 2109-2128, April.
  6. Szabolcs Blazsek & William M. Dos Santos & Andreco S. Edwards, 2024. "Score-Driven Interactions for “Disease X” Using COVID and Non-COVID Mortality," Econometrics, MDPI, vol. 12(3), pages 1-24, September.
  7. Blazsek Szabolcs & Haddad Michel Ferreira Cardia, 2023. "Score-driven multi-regime Markov-switching EGARCH: empirical evidence using the Meixner distribution," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(4), pages 589-634, September.
  8. Blazsek, Szabolcs & Escribano, Alvaro, 2023. "Score-driven threshold ice-age models: Benchmark models for long-run climate forecasts," Energy Economics, Elsevier, vol. 118(C).
  9. Blazsek Szabolcs & Blazsek Virag & Kobor Adam, 2023. "Conservatorship, quantitative easing, and mortgage spreads: a new multi-equation score-driven model of policy actions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(2), pages 237-264, April.
  10. Blazsek, Szabolcs & Escribano, Alvaro & Licht, Adrian, 2023. "Co-integration with score-driven models: an application to US real GDP growth, US inflation rate, and effective federal funds rate," Macroeconomic Dynamics, Cambridge University Press, vol. 27(1), pages 203-223, January.
  11. Ayala Astrid & Blazsek Szabolcs & Escribano Alvaro, 2023. "Anticipating extreme losses using score-driven shape filters," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(4), pages 449-484, September.
  12. Michel Ferreira Cardia Haddad & Szabolcs Blazsek & Philip Arestis & Franz Fuerst & Hsia Hua Sheng, 2023. "The two-component Beta-t-QVAR-M-lev: a new forecasting model," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(4), pages 379-401, December.
  13. Ayala Astrid & Blazsek Szabolcs & Licht Adrian, 2023. "Comparison of Score-Driven Equity-Gold Portfolios During the COVID-19 Pandemic Using Model Confidence Sets," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(5), pages 705-731, December.
  14. Astrid Ayala & Szabolcs Blazsek & Adrian Licht, 2022. "Score-driven stochastic seasonality of the Russian rouble: an application case study for the period of 1999 to 2020," Empirical Economics, Springer, vol. 62(5), pages 2179-2203, May.
  15. Szabolcs Blazsek & Adrian Licht, 2022. "Prediction accuracy of volatility using the score-driven Meixner distribution: an application to the Dow Jones," Applied Economics Letters, Taylor & Francis Journals, vol. 29(2), pages 111-117, January.
  16. Aycinena, Diego & Blazsek, Szabolcs & Rentschler, Lucas & Sprenger, Charles, 2022. "Intertemporal choice experiments and large-stakes behavior," Journal of Economic Behavior & Organization, Elsevier, vol. 196(C), pages 484-500.
  17. Blazsek Szabolcs & Escribano Alvaro & Licht Adrian, 2022. "Multivariate Markov-switching score-driven models: an application to the global crude oil market," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 26(3), pages 313-335, June.
  18. Szabolcs Blazsek & Alvaro Escribano, 2022. "Robust Estimation and Forecasting of Climate Change Using Score-Driven Ice-Age Models," Econometrics, MDPI, vol. 10(1), pages 1-29, February.
  19. Sergio Contreras-Espinoza & Francisco Novoa-Muñoz & Szabolcs Blazsek & Pedro Vidal & Christian Caamaño-Carrillo, 2022. "COVID-19 Active Case Forecasts in Latin American Countries Using Score-Driven Models," Mathematics, MDPI, vol. 11(1), pages 1-17, December.
  20. Astrid Loretta Ayala & Szabolcs Blazsek, 2021. "Score-driven panel data models of the capital structure of US firms," Applied Economics Letters, Taylor & Francis Journals, vol. 28(19), pages 1666-1670, November.
  21. Blazsek Szabolcs & Escribano Alvaro & Licht Adrian, 2021. "Identification of Seasonal Effects in Impulse Responses Using Score-Driven Multivariate Location Models," Journal of Econometric Methods, De Gruyter, vol. 10(1), pages 53-66, January.
  22. Szabolcs Blazsek & Adrian Licht, 2020. "Dynamic conditional score models: a review of their applications," Applied Economics, Taylor & Francis Journals, vol. 52(11), pages 1181-1199, March.
  23. Astrid Ayala & Szabolcs Blazsek, 2019. "Score-driven currency exchange rate seasonality as applied to the Guatemalan Quetzal/US Dollar," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(1), pages 65-92, March.
  24. Diego Aycinena & Szabolcs Blazsek & Lucas Rentschler & Betzy Sandoval, 2019. "Smoothing, discounting, and demand for intra-household control for recipients of conditional cash transfers," Journal of Applied Economics, Taylor & Francis Journals, vol. 22(1), pages 219-242, January.
  25. Astrid Ayala & Szabolcs Blazsek, 2019. "Score-driven models of stochastic seasonality in location and scale: an application case study of the Indian rupee to USD exchange rate," Applied Economics, Taylor & Francis Journals, vol. 51(37), pages 4083-4103, August.
  26. Astrid Ayala & Szabolcs Blazsek, 2018. "Equity market neutral hedge funds and the stock market: an application of score-driven copula models," Applied Economics, Taylor & Francis Journals, vol. 50(37), pages 4005-4023, August.
  27. Astrid Ayala & Szabolcs Blazsek, 2018. "Score-driven copula models for portfolios of two risky assets," The European Journal of Finance, Taylor & Francis Journals, vol. 24(18), pages 1861-1884, December.
  28. Szabolcs Blazsek & Hector Hernández, 2018. "Analysis of electricity prices for Central American countries using dynamic conditional score models," Empirical Economics, Springer, vol. 55(4), pages 1807-1848, December.
  29. Blazsek, Szabolcs & Carrizo, Daniela & Eskildsen, Ricardo & Gonzalez, Humberto, 2018. "Forecasting rate of return after extreme values when using AR-t-GARCH and QAR-Beta-t-EGARCH," Finance Research Letters, Elsevier, vol. 24(C), pages 193-198.
  30. Szabolcs Blazsek & Han-Chiang Ho & Su-Ping Liu, 2018. "Score-driven Markov-switching EGARCH models: an application to systematic risk analysis," Applied Economics, Taylor & Francis Journals, vol. 50(56), pages 6047-6060, December.
  31. Szabolcs Blazsek & Luis Antonio Monteros, 2017. "Event-study analysis by using dynamic conditional score models," Applied Economics, Taylor & Francis Journals, vol. 49(45), pages 4530-4541, September.
  32. Szabolcs Blazsek & Han-Chiang Ho, 2017. "Markov regime-switching Beta--EGARCH," Applied Economics, Taylor & Francis Journals, vol. 49(47), pages 4793-4805, October.
  33. Szabolcs Blazsek & Luis Antonio Monteros, 2017. "Dynamic conditional score models of degrees of freedom: filtering with score-driven heavy tails," Applied Economics, Taylor & Francis Journals, vol. 49(53), pages 5426-5440, November.
  34. Blazsek, Szabolcs & Escribano, Alvaro, 2016. "Score-driven dynamic patent count panel data models," Economics Letters, Elsevier, vol. 149(C), pages 116-119.
  35. Szabolcs Blazsek & Helmuth Chavez & Carlos Mendez, 2016. "Model stability and forecast performance of Beta--EGARCH," Applied Economics Letters, Taylor & Francis Journals, vol. 23(17), pages 1219-1223, November.
  36. Blazsek, Szabolcs & Escribano, Alvaro, 2016. "Patent propensity, R&D and market competition: Dynamic spillovers of innovation leaders and followers," Journal of Econometrics, Elsevier, vol. 191(1), pages 145-163.
  37. Szabolcs Blazsek & Vicente Mendoza, 2016. "QARMA-Beta- t -EGARCH versus ARMA-GARCH: an application to S&P 500," Applied Economics, Taylor & Francis Journals, vol. 48(12), pages 1119-1129, March.
  38. Astrid Ayala & Szabolcs Blazsek & Juncal Cuñado & Luis Albériko Gil-Alana, 2016. "Regime-switching purchasing power parity in Latin America: Monte Carlo unit root tests with dynamic conditional score," Applied Economics, Taylor & Francis Journals, vol. 48(29), pages 2675-2696, June.
  39. Szabolcs Blazsek & Marco Villatoro, 2015. "Is Beta- t -EGARCH(1,1) superior to GARCH(1,1)?," Applied Economics, Taylor & Francis Journals, vol. 47(17), pages 1764-1774, April.
  40. Szabolcs Blazsek & Anna Downarowicz, 2013. "Forecasting hedge fund volatility: a Markov regime-switching approach," The European Journal of Finance, Taylor & Francis Journals, vol. 19(4), pages 243-275, April.
  41. Ayala, Astrid & Blazsek, Szabolcs, 2013. "Structural breaks in public finances in Central and Eastern European countries," Economic Systems, Elsevier, vol. 37(1), pages 45-60.
  42. Nadia Ayari & Szabolcs Blazsek & Pedro Mendi, 2012. "Renewable energy innovations in Europe: a dynamic panel data approach," Applied Economics, Taylor & Francis Journals, vol. 44(24), pages 3135-3147, August.
  43. Astrid Ayala & Szabolcs Blazsek, 2012. "How has the financial crisis affected the fiscal convergence of Central and Eastern Europe to the Eurozone?," Applied Economics Letters, Taylor & Francis Journals, vol. 19(5), pages 471-476, March.
  44. Blazsek, Szabolcs & Escribano, Alvaro, 2010. "Knowledge spillovers in US patents: A dynamic patent intensity model with secret common innovation factors," Journal of Econometrics, Elsevier, vol. 159(1), pages 14-32, November.

    RePEc:taf:apfiec:v:22:y:2012:i:3:p:231-242 is not listed on IDEAS

Chapters

  1. Astrid Ayala & Szabolcs Blazsek & Raúl B. González Paz, 2015. "Default Risk of Sovereign Debt in Central America," Palgrave Macmillan Books, in: Nigel Finch (ed.), Emerging Markets and Sovereign Risk, chapter 2, pages 18-44, Palgrave Macmillan.

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. Blazsek, Szabolcs, 2022. "Score-driven threshold ice-age models: benchmark models for long-run climate forecasts," UC3M Working papers. Economics 34757, Universidad Carlos III de Madrid. Departamento de Economía.

    Cited by:

    1. Blazsek, Szabolcs Istvan & Kristof, Erzsebet, 2024. "Global, Arctic, and Antarctic sea ice volume predictions: using score-driven threshold climate models," UC3M Working papers. Economics 39546, Universidad Carlos III de Madrid. Departamento de Economía.

  2. Blazsek, Szabolcs, 2021. "Robust estimation and forecasting of climate change using score-driven ice-age models," UC3M Working papers. Economics 33453, Universidad Carlos III de Madrid. Departamento de Economía.

    Cited by:

    1. Blazsek, Szabolcs, 2022. "Score-driven threshold ice-age models: benchmark models for long-run climate forecasts," UC3M Working papers. Economics 34757, Universidad Carlos III de Madrid. Departamento de Economía.
    2. Blazsek, Szabolcs Istvan & Kristof, Erzsebet, 2024. "Global, Arctic, and Antarctic sea ice volume predictions: using score-driven threshold climate models," UC3M Working papers. Economics 39546, Universidad Carlos III de Madrid. Departamento de Economía.

  3. Diego Aycinena & Szabolcs Blazsek & Lucas Rentschler & Charles Sprenger, 2020. "Intertemporal Choice Experiments and Large-Stakes Behavior," Working Papers 20-36, Chapman University, Economic Science Institute.

    Cited by:

    1. Stephen L. Cheung & Agnieszka Tymula & Xueting Wang, 2022. "Present bias for monetary and dietary rewards," Experimental Economics, Springer;Economic Science Association, vol. 25(4), pages 1202-1233, September.
    2. James Andreoni & Christina Gravert & Michael A. Kuhn & Silvia Saccardo & Yang Yang, 2018. "Arbitrage Or Narrow Bracketing? On Using Money to Measure Intertemporal Preferences," NBER Working Papers 25232, National Bureau of Economic Research, Inc.
    3. David J. Freeman & Kevin Laughren, 2024. "Task completion without commitment," Experimental Economics, Springer;Economic Science Association, vol. 27(2), pages 273-298, April.

  4. Ayala, Astrid & Blazsek, Szabolcs, 2019. "Maximum likelihood estimation of score-driven models with dynamic shape parameters : an application to Monte Carlo value-at-risk," UC3M Working papers. Economics 28638, Universidad Carlos III de Madrid. Departamento de Economía.

    Cited by:

    1. Ayala Astrid & Blazsek Szabolcs & Escribano Alvaro, 2023. "Anticipating extreme losses using score-driven shape filters," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(4), pages 449-484, September.
    2. Blazsek, Szabolcs & Licht, Adrian, 2019. "Markov-switching score-driven multivariate models: outlier-robust measurement of the relationships between world crude oil production and US industrial production," UC3M Working papers. Economics 29030, Universidad Carlos III de Madrid. Departamento de Economía.

  5. Blazsek, Szabolcs & Licht, Adrian, 2019. "Co-integration and common trends analysis with score-driven models : an application to the federal funds effective rate and US inflation rate," UC3M Working papers. Economics 28451, Universidad Carlos III de Madrid. Departamento de Economía.

    Cited by:

    1. Giacomo Bormetti & Fulvio Corsi, 2021. "A Lucas Critique Compliant SVAR model with Observation-driven Time-varying Parameters," Papers 2107.05263, arXiv.org, revised Feb 2022.

  6. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonal quasi-vector autoregressive models for macroeconomic data," UC3M Working papers. Economics 26316, Universidad Carlos III de Madrid. Departamento de Economía.

    Cited by:

    1. Astrid Ayala & Szabolcs Blazsek, 2019. "Score-driven currency exchange rate seasonality as applied to the Guatemalan Quetzal/US Dollar," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(1), pages 65-92, March.

  7. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonality Detection in Small Samples using Score-Driven Nonlinear Multivariate Dynamic Location Models," UC3M Working papers. Economics 27483, Universidad Carlos III de Madrid. Departamento de Economía.

    Cited by:

    1. Blazsek, Szabolcs & Licht, Adrian, 2019. "Co-integration and common trends analysis with score-driven models : an application to the federal funds effective rate and US inflation rate," UC3M Working papers. Economics 28451, Universidad Carlos III de Madrid. Departamento de Economía.

  8. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonal Quasi-Vector Autoregressive Models with an Application to Crude Oil Production and Economic Activity in the United States and Canada," UC3M Working papers. Economics 27484, Universidad Carlos III de Madrid. Departamento de Economía.

    Cited by:

    1. Blazsek, Szabolcs & Licht, Adrian, 2019. "Co-integration and common trends analysis with score-driven models : an application to the federal funds effective rate and US inflation rate," UC3M Working papers. Economics 28451, Universidad Carlos III de Madrid. Departamento de Economía.

  9. Ayala, Astrid & Blazsek, Szabolcs, 2017. "Dynamic conditional score models with time-varying location, scale and shape parameters," UC3M Working papers. Economics 25043, Universidad Carlos III de Madrid. Departamento de Economía.

    Cited by:

    1. Astrid Ayala & Szabolcs Blazsek, 2019. "Score-driven currency exchange rate seasonality as applied to the Guatemalan Quetzal/US Dollar," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(1), pages 65-92, March.
    2. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonal Quasi-Vector Autoregressive Models with an Application to Crude Oil Production and Economic Activity in the United States and Canada," UC3M Working papers. Economics 27484, Universidad Carlos III de Madrid. Departamento de Economía.
    3. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonality Detection in Small Samples using Score-Driven Nonlinear Multivariate Dynamic Location Models," UC3M Working papers. Economics 27483, Universidad Carlos III de Madrid. Departamento de Economía.

  10. Blazsek, Szabolcs & Licht, Adrian, 2017. "Score-driven non-linear multivariate dynamic location models," UC3M Working papers. Economics 25739, Universidad Carlos III de Madrid. Departamento de Economía.

    Cited by:

    1. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonal quasi-vector autoregressive models for macroeconomic data," UC3M Working papers. Economics 26316, Universidad Carlos III de Madrid. Departamento de Economía.
    2. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonal Quasi-Vector Autoregressive Models with an Application to Crude Oil Production and Economic Activity in the United States and Canada," UC3M Working papers. Economics 27484, Universidad Carlos III de Madrid. Departamento de Economía.
    3. Blazsek Szabolcs & Escribano Alvaro & Licht Adrian, 2021. "Identification of Seasonal Effects in Impulse Responses Using Score-Driven Multivariate Location Models," Journal of Econometric Methods, De Gruyter, vol. 10(1), pages 53-66, January.
    4. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonality Detection in Small Samples using Score-Driven Nonlinear Multivariate Dynamic Location Models," UC3M Working papers. Economics 27483, Universidad Carlos III de Madrid. Departamento de Economía.

  11. Blazsek, Szabolcs, 2016. "Score-driven dynamic patent count panel data models," UC3M Working papers. Economics 23458, Universidad Carlos III de Madrid. Departamento de Economía.

    Cited by:

    1. Blazsek, Szabolcs, 2022. "Score-driven threshold ice-age models: benchmark models for long-run climate forecasts," UC3M Working papers. Economics 34757, Universidad Carlos III de Madrid. Departamento de Economía.
    2. Blazsek, Szabolcs Istvan & Kristof, Erzsebet, 2024. "Global, Arctic, and Antarctic sea ice volume predictions: using score-driven threshold climate models," UC3M Working papers. Economics 39546, Universidad Carlos III de Madrid. Departamento de Economía.
    3. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonal Quasi-Vector Autoregressive Models with an Application to Crude Oil Production and Economic Activity in the United States and Canada," UC3M Working papers. Economics 27484, Universidad Carlos III de Madrid. Departamento de Economía.
    4. Blazsek, Szabolcs & Licht, Adrian, 2019. "Markov-switching score-driven multivariate models: outlier-robust measurement of the relationships between world crude oil production and US industrial production," UC3M Working papers. Economics 29030, Universidad Carlos III de Madrid. Departamento de Economía.
    5. Ayala, Astrid & Blazsek, Szabolcs, 2019. "Score-driven time series models with dynamic shape : an application to the Standard & Poor's 500 index," UC3M Working papers. Economics 28133, Universidad Carlos III de Madrid. Departamento de Economía.
    6. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonality Detection in Small Samples using Score-Driven Nonlinear Multivariate Dynamic Location Models," UC3M Working papers. Economics 27483, Universidad Carlos III de Madrid. Departamento de Economía.

  12. Blazsek, Szabolcs, 2014. "Propensity to patent, R&D and market competition : dynamic spillovers of innovation leaders and followers," UC3M Working papers. Economics we1412, Universidad Carlos III de Madrid. Departamento de Economía.

    Cited by:

    1. Sara Alonso-Muñoz & Eva Pelechano-Barahona & Rocío González-Sánchez, 2020. "Participation in Group Companies as a Source of External Knowledge in Obtaining and Making Profitable Radical Innovations," Sustainability, MDPI, vol. 12(18), pages 1-19, September.
    2. Blazsek, Szabolcs & Escribano, Alvaro, 2016. "Patent propensity, R&D and market competition: Dynamic spillovers of innovation leaders and followers," Journal of Econometrics, Elsevier, vol. 191(1), pages 145-163.

  13. Blazsek, Szabolcs, 2012. "Patents, secret innovations and firm's rate of return : differential effects of the innovation leader," UC3M Working papers. Economics we1202, Universidad Carlos III de Madrid. Departamento de Economía.

    Cited by:

    1. Blazsek, Szabolcs, 2014. "Propensity to patent, R&D and market competition : dynamic spillovers of innovation leaders and followers," UC3M Working papers. Economics we1412, Universidad Carlos III de Madrid. Departamento de Economía.

  14. Pedro Mendi & Nadia Ayari & Szabolcs Blazsek, 2011. "Renewable energy innovations in Europe: A dynamic panel data approach," Post-Print hal-00711448, HAL.

    Cited by:

    1. Pedro Mendi & Nadia Ayari & Szabolcs Blazsek, 2011. "Renewable energy innovations in Europe: A dynamic panel data approach," Post-Print hal-00711448, HAL.
    2. Bongsuk Sung & Myung-Bae Yeom & Hong-Gi Kim, 2017. "Eco-Efficiency of Government Policy and Exports in the Bioenergy Technology Market," Sustainability, MDPI, vol. 9(9), pages 1-18, September.
    3. Mai Miyamoto & Kenji Takeuchi, 2018. "Explaining Trade Flows in Renewable Energy Products: The Role of Technological Development," Discussion Papers 1819, Graduate School of Economics, Kobe University.
    4. Wang, Qiang & Li, Shuyu & Pisarenko, Zhanna, 2020. "Heterogeneous effects of energy efficiency, oil price, environmental pressure, R&D investment, and policy on renewable energy -- evidence from the G20 countries," Energy, Elsevier, vol. 209(C).
    5. Zastempowski, Maciej, 2023. "Analysis and modeling of innovation factors to replace fossil fuels with renewable energy sources - Evidence from European Union enterprises," Renewable and Sustainable Energy Reviews, Elsevier, vol. 178(C).
    6. Su, Hsin-Ning & Moaniba, Igam M., 2017. "Does innovation respond to climate change? Empirical evidence from patents and greenhouse gas emissions," Technological Forecasting and Social Change, Elsevier, vol. 122(C), pages 49-62.
    7. Bruns, Stephan B. & Kalthaus, Martin, 2020. "Flexibility in the selection of patent counts: Implications for p-hacking and evidence-based policymaking," Research Policy, Elsevier, vol. 49(1).
    8. Modhurima Dey Amin & Syed Badruddoza & Jill J. McCluskey, 2021. "Does conventional energy pricing induce innovation in renewable energy? New evidence from a nonlinear approach," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 43(2), pages 659-679, June.
    9. Kruse, Juergen, 2016. "Innovation in Green Energy Technologies and the Economic Performance of Firms," EWI Working Papers 2016-2, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).

  15. Mr. Jerome Vandenbussche & Mr. Stanley B Watt & Szabolcs Blazsek, 2009. "The Liquidity and Liquidity Distribution Effects in Emerging Markets: The Case of Jordan," IMF Working Papers 2009/228, International Monetary Fund.

    Cited by:

    1. Poghosyan, Tigran, 2011. "Slowdown of credit flows in Jordan in the wake of the global financial crisis: Supply or demand driven?," Economic Systems, Elsevier, vol. 35(4), pages 562-573.

  16. Blazsek, Szabolcs, 2009. "Knowledge spillovers in U.S. patents: a dynamic patent intensity model with secret common innovation factors," UC3M Working papers. Economics we098951, Universidad Carlos III de Madrid. Departamento de Economía.

    Cited by:

    1. Astrid Ayala & Szabolcs Blazsek, 2019. "Score-driven currency exchange rate seasonality as applied to the Guatemalan Quetzal/US Dollar," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(1), pages 65-92, March.
    2. Blazsek, Szabolcs, 2016. "Score-driven dynamic patent count panel data models," UC3M Working papers. Economics 23458, Universidad Carlos III de Madrid. Departamento de Economía.
    3. Klein, Michael A., 2022. "The reward and contract theories of patents in a model of endogenous growth," European Economic Review, Elsevier, vol. 147(C).
    4. Waters, James, 2011. "The effect of the Sarbanes-Oxley Act on innovation," MPRA Paper 28072, University Library of Munich, Germany.
    5. Blazsek, Szabolcs, 2015. "Dynamic conditional score patent count panel data models," UC3M Working papers. Economics we1510, Universidad Carlos III de Madrid. Departamento de Economía.
    6. Rodolphe Desbordes & Markus Eberhardt, 2024. "Climate change and economic prosperity: Evidence from a flexible damage function," Discussion Papers 2024-01, University of Nottingham, GEP.
    7. Blazsek, Szabolcs & Escribano, Alvaro, 2016. "Patent propensity, R&D and market competition: Dynamic spillovers of innovation leaders and followers," Journal of Econometrics, Elsevier, vol. 191(1), pages 145-163.
    8. Blazsek, Szabolcs & Licht, Adrian, 2019. "Markov-switching score-driven multivariate models: outlier-robust measurement of the relationships between world crude oil production and US industrial production," UC3M Working papers. Economics 29030, Universidad Carlos III de Madrid. Departamento de Economía.
    9. Ben Angelo & Mitchell Johnston, 2023. "Technological innovation and stock returns: Innovative skill versus innovative luck," The Financial Review, Eastern Finance Association, vol. 58(4), pages 811-832, November.
    10. Jesús Manuel Plaza Llorente, 2012. "Innovación y caos determinista: un modelo predictivo para Europa," EKONOMIAZ. Revista vasca de Economía, Gobierno Vasco / Eusko Jaurlaritza / Basque Government, vol. 80(02), pages 260-289.
    11. Blazsek, Szabolcs, 2012. "Patents, secret innovations and firm's rate of return : differential effects of the innovation leader," UC3M Working papers. Economics we1202, Universidad Carlos III de Madrid. Departamento de Economía.
    12. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonality Detection in Small Samples using Score-Driven Nonlinear Multivariate Dynamic Location Models," UC3M Working papers. Economics 27483, Universidad Carlos III de Madrid. Departamento de Economía.
    13. Blazsek, Szabolcs, 2014. "Propensity to patent, R&D and market competition : dynamic spillovers of innovation leaders and followers," UC3M Working papers. Economics we1412, Universidad Carlos III de Madrid. Departamento de Economía.

  17. Szabolcs Blazsek & Anna Downarowicz, 2008. "Regime switching models of hedge fund returns," Faculty Working Papers 12/08, School of Economics and Business Administration, University of Navarra.

    Cited by:

    1. Heidari , Hassan & Refah-Kahriz, Arash & Hashemi Berenjabadi, Nayyer, 2018. "Dynamic Relationship between Macroeconomic Variables and Stock Return Volatility in Tehran Stock Exchange: Multivariate MS ARMA GARCH Approach," Quarterly Journal of Applied Theories of Economics, Faculty of Economics, Management and Business, University of Tabriz, vol. 5(2), pages 223-250, August.
    2. Luo, Cuicui & Seco, Luis & Wu, Lin-Liang Bill, 2015. "Portfolio optimization in hedge funds by OGARCH and Markov Switching Model," Omega, Elsevier, vol. 57(PA), pages 34-39.
    3. Diteboho Xaba & Ntebogang Dinah Moroke & Ishmael Rapoo, 2019. "Modeling Stock Market Returns of BRICS with a Markov-Switching Dynamic Regression Model," Journal of Economics and Behavioral Studies, AMH International, vol. 11(3), pages 10-22.
    4. Slavutskaya, Anna, 2013. "Short-term hedge fund performance," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4404-4431.

Articles

  1. Blazsek, Szabolcs & Escribano, Alvaro, 2023. "Score-driven threshold ice-age models: Benchmark models for long-run climate forecasts," Energy Economics, Elsevier, vol. 118(C).
    See citations under working paper version above.
  2. Astrid Ayala & Szabolcs Blazsek & Adrian Licht, 2022. "Score-driven stochastic seasonality of the Russian rouble: an application case study for the period of 1999 to 2020," Empirical Economics, Springer, vol. 62(5), pages 2179-2203, May.

    Cited by:

    1. Alanya-Beltran Willy, 2023. "Modelling volatility dependence with score copula models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(5), pages 649-668, December.
    2. Sergio Contreras-Espinoza & Francisco Novoa-Muñoz & Szabolcs Blazsek & Pedro Vidal & Christian Caamaño-Carrillo, 2022. "COVID-19 Active Case Forecasts in Latin American Countries Using Score-Driven Models," Mathematics, MDPI, vol. 11(1), pages 1-17, December.

  3. Szabolcs Blazsek & Adrian Licht, 2022. "Prediction accuracy of volatility using the score-driven Meixner distribution: an application to the Dow Jones," Applied Economics Letters, Taylor & Francis Journals, vol. 29(2), pages 111-117, January.

    Cited by:

    1. Michel Ferreira Cardia Haddad & Szabolcs Blazsek & Philip Arestis & Franz Fuerst & Hsia Hua Sheng, 2023. "The two-component Beta-t-QVAR-M-lev: a new forecasting model," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(4), pages 379-401, December.

  4. Aycinena, Diego & Blazsek, Szabolcs & Rentschler, Lucas & Sprenger, Charles, 2022. "Intertemporal choice experiments and large-stakes behavior," Journal of Economic Behavior & Organization, Elsevier, vol. 196(C), pages 484-500.
    See citations under working paper version above.
  5. Blazsek Szabolcs & Escribano Alvaro & Licht Adrian, 2022. "Multivariate Markov-switching score-driven models: an application to the global crude oil market," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 26(3), pages 313-335, June.

    Cited by:

    1. Sergio Contreras-Espinoza & Francisco Novoa-Muñoz & Szabolcs Blazsek & Pedro Vidal & Christian Caamaño-Carrillo, 2022. "COVID-19 Active Case Forecasts in Latin American Countries Using Score-Driven Models," Mathematics, MDPI, vol. 11(1), pages 1-17, December.

  6. Szabolcs Blazsek & Alvaro Escribano, 2022. "Robust Estimation and Forecasting of Climate Change Using Score-Driven Ice-Age Models," Econometrics, MDPI, vol. 10(1), pages 1-29, February.
    See citations under working paper version above.
  7. Szabolcs Blazsek & Adrian Licht, 2020. "Dynamic conditional score models: a review of their applications," Applied Economics, Taylor & Francis Journals, vol. 52(11), pages 1181-1199, March.

    Cited by:

    1. Petra Tomanová & Vladimír Holý, 2021. "Clustering of arrivals in queueing systems: autoregressive conditional duration approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(3), pages 859-874, September.
    2. Astrid Ayala & Szabolcs Blazsek & Adrian Licht, 2022. "Score-driven stochastic seasonality of the Russian rouble: an application case study for the period of 1999 to 2020," Empirical Economics, Springer, vol. 62(5), pages 2179-2203, May.
    3. Giuseppe Orlando & Michele Bufalo, 2021. "Empirical Evidences on the Interconnectedness between Sampling and Asset Returns’ Distributions," Risks, MDPI, vol. 9(5), pages 1-35, May.
    4. Sergio Contreras-Espinoza & Francisco Novoa-Muñoz & Szabolcs Blazsek & Pedro Vidal & Christian Caamaño-Carrillo, 2022. "COVID-19 Active Case Forecasts in Latin American Countries Using Score-Driven Models," Mathematics, MDPI, vol. 11(1), pages 1-17, December.

  8. Astrid Ayala & Szabolcs Blazsek, 2019. "Score-driven currency exchange rate seasonality as applied to the Guatemalan Quetzal/US Dollar," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(1), pages 65-92, March.

    Cited by:

    1. Aknouche, Abdelhakim & Almohaimeed, Bader & Dimitrakopoulos, Stefanos, 2024. "Noising the GARCH volatility: A random coefficient GARCH model," MPRA Paper 120456, University Library of Munich, Germany, revised 15 Mar 2024.
    2. Blazsek, Szabolcs & Licht, Adrian, 2019. "Markov-switching score-driven multivariate models: outlier-robust measurement of the relationships between world crude oil production and US industrial production," UC3M Working papers. Economics 29030, Universidad Carlos III de Madrid. Departamento de Economía.
    3. Song, Shijia & Li, Handong, 2022. "Predicting VaR for China's stock market: A score-driven model based on normal inverse Gaussian distribution," International Review of Financial Analysis, Elsevier, vol. 82(C).
    4. Ayala, Astrid & Blazsek, Szabolcs, 2019. "Score-driven time series models with dynamic shape : an application to the Standard & Poor's 500 index," UC3M Working papers. Economics 28133, Universidad Carlos III de Madrid. Departamento de Economía.

  9. Diego Aycinena & Szabolcs Blazsek & Lucas Rentschler & Betzy Sandoval, 2019. "Smoothing, discounting, and demand for intra-household control for recipients of conditional cash transfers," Journal of Applied Economics, Taylor & Francis Journals, vol. 22(1), pages 219-242, January.

    Cited by:

    1. David J. Freeman & Kevin Laughren, 2024. "Task completion without commitment," Experimental Economics, Springer;Economic Science Association, vol. 27(2), pages 273-298, April.
    2. Giuseppe Arcangelis & Majlinda Joxhe, 2021. "Intra-household allocation with shared expenditure choices: experimental evidence from Filipino migrants," Review of Economics of the Household, Springer, vol. 19(4), pages 1245-1274, December.

  10. Astrid Ayala & Szabolcs Blazsek, 2019. "Score-driven models of stochastic seasonality in location and scale: an application case study of the Indian rupee to USD exchange rate," Applied Economics, Taylor & Francis Journals, vol. 51(37), pages 4083-4103, August.

    Cited by:

    1. Song, Shijia & Li, Handong, 2023. "A method for predicting VaR by aggregating generalized distributions driven by the dynamic conditional score," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 203-214.
    2. Blazsek, Szabolcs & Licht, Adrian, 2019. "Markov-switching score-driven multivariate models: outlier-robust measurement of the relationships between world crude oil production and US industrial production," UC3M Working papers. Economics 29030, Universidad Carlos III de Madrid. Departamento de Economía.
    3. Hang Lin & Lixin Liu & Zhengjun Zhang, 2023. "Tail Risk Signal Detection through a Novel EGB2 Option Pricing Model," Mathematics, MDPI, vol. 11(14), pages 1-32, July.
    4. Giuseppe Orlando & Michele Bufalo, 2021. "Empirical Evidences on the Interconnectedness between Sampling and Asset Returns’ Distributions," Risks, MDPI, vol. 9(5), pages 1-35, May.
    5. Sergio Contreras-Espinoza & Francisco Novoa-Muñoz & Szabolcs Blazsek & Pedro Vidal & Christian Caamaño-Carrillo, 2022. "COVID-19 Active Case Forecasts in Latin American Countries Using Score-Driven Models," Mathematics, MDPI, vol. 11(1), pages 1-17, December.
    6. Ayala, Astrid & Blazsek, Szabolcs, 2019. "Score-driven time series models with dynamic shape : an application to the Standard & Poor's 500 index," UC3M Working papers. Economics 28133, Universidad Carlos III de Madrid. Departamento de Economía.

  11. Astrid Ayala & Szabolcs Blazsek, 2018. "Equity market neutral hedge funds and the stock market: an application of score-driven copula models," Applied Economics, Taylor & Francis Journals, vol. 50(37), pages 4005-4023, August.

    Cited by:

    1. Ayala, Astrid & Blazsek, Szabolcs, 2019. "Score-driven time series models with dynamic shape : an application to the Standard & Poor's 500 index," UC3M Working papers. Economics 28133, Universidad Carlos III de Madrid. Departamento de Economía.
    2. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonality Detection in Small Samples using Score-Driven Nonlinear Multivariate Dynamic Location Models," UC3M Working papers. Economics 27483, Universidad Carlos III de Madrid. Departamento de Economía.

  12. Astrid Ayala & Szabolcs Blazsek, 2018. "Score-driven copula models for portfolios of two risky assets," The European Journal of Finance, Taylor & Francis Journals, vol. 24(18), pages 1861-1884, December.

    Cited by:

    1. Alanya-Beltran Willy, 2023. "Modelling volatility dependence with score copula models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(5), pages 649-668, December.
    2. Ayala, Astrid & Blazsek, Szabolcs, 2019. "Score-driven time series models with dynamic shape : an application to the Standard & Poor's 500 index," UC3M Working papers. Economics 28133, Universidad Carlos III de Madrid. Departamento de Economía.
    3. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonality Detection in Small Samples using Score-Driven Nonlinear Multivariate Dynamic Location Models," UC3M Working papers. Economics 27483, Universidad Carlos III de Madrid. Departamento de Economía.

  13. Szabolcs Blazsek & Hector Hernández, 2018. "Analysis of electricity prices for Central American countries using dynamic conditional score models," Empirical Economics, Springer, vol. 55(4), pages 1807-1848, December.

    Cited by:

    1. Astrid Ayala & Szabolcs Blazsek, 2019. "Score-driven currency exchange rate seasonality as applied to the Guatemalan Quetzal/US Dollar," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(1), pages 65-92, March.
    2. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonal quasi-vector autoregressive models for macroeconomic data," UC3M Working papers. Economics 26316, Universidad Carlos III de Madrid. Departamento de Economía.
    3. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonal Quasi-Vector Autoregressive Models with an Application to Crude Oil Production and Economic Activity in the United States and Canada," UC3M Working papers. Economics 27484, Universidad Carlos III de Madrid. Departamento de Economía.
    4. Rehman, Mobeen Ur & Owusu Junior, Peterson & Ahmad, Nasir & Vo, Xuan Vinh, 2022. "Time-varying risk analysis for commodity futures," Resources Policy, Elsevier, vol. 78(C).
    5. Owusu Junior, Peterson & Alagidede, Imhotep, 2020. "Risks in emerging markets equities: Time-varying versus spatial risk analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    6. Andr s Oviedo-G mez & Sandra Milena Londo o-Hern ndez & Diego Fernando Manotas-Duque, 2021. "Electricity Price Fundamentals in Hydrothermal Power Generation Markets Using Machine Learning and Quantile Regression Analysis," International Journal of Energy Economics and Policy, Econjournals, vol. 11(5), pages 66-77.

  14. Blazsek, Szabolcs & Carrizo, Daniela & Eskildsen, Ricardo & Gonzalez, Humberto, 2018. "Forecasting rate of return after extreme values when using AR-t-GARCH and QAR-Beta-t-EGARCH," Finance Research Letters, Elsevier, vol. 24(C), pages 193-198.

    Cited by:

    1. Astrid Ayala & Szabolcs Blazsek, 2019. "Score-driven currency exchange rate seasonality as applied to the Guatemalan Quetzal/US Dollar," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(1), pages 65-92, March.
    2. Carlos Henrique Dias Cordeiro de Castro & Fernando Antonio Lucena Aiube, 2023. "Forecasting inflation time series using score‐driven dynamic models and combination methods: The case of Brazil," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 369-401, March.

  15. Szabolcs Blazsek & Han-Chiang Ho & Su-Ping Liu, 2018. "Score-driven Markov-switching EGARCH models: an application to systematic risk analysis," Applied Economics, Taylor & Francis Journals, vol. 50(56), pages 6047-6060, December.

    Cited by:

    1. Chang, Kuang-Liang, 2023. "The low-magnitude and high-magnitude asymmetries in tail dependence structures in international equity markets and the role of bilateral exchange rate," Journal of International Money and Finance, Elsevier, vol. 133(C).
    2. Astrid Ayala & Szabolcs Blazsek, 2019. "Score-driven currency exchange rate seasonality as applied to the Guatemalan Quetzal/US Dollar," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(1), pages 65-92, March.
    3. Prelorentzos, Arsenios-Georgios N. & Konstantakis, Konstantinos N. & Michaelides, Panayotis G. & Xidonas, Panos & Goutte, Stephane & Thomakos, Dimitrios D., 2024. "Introducing the GVAR-GARCH model: Evidence from financial markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    4. Ayala Astrid & Blazsek Szabolcs & Escribano Alvaro, 2023. "Anticipating extreme losses using score-driven shape filters," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(4), pages 449-484, September.
    5. Astrid Ayala & Szabolcs Blazsek & Adrian Licht, 2022. "Score-driven stochastic seasonality of the Russian rouble: an application case study for the period of 1999 to 2020," Empirical Economics, Springer, vol. 62(5), pages 2179-2203, May.
    6. Blazsek, Szabolcs & Licht, Adrian, 2019. "Markov-switching score-driven multivariate models: outlier-robust measurement of the relationships between world crude oil production and US industrial production," UC3M Working papers. Economics 29030, Universidad Carlos III de Madrid. Departamento de Economía.
    7. Shaojie Liu & Jing Teng & Yue Gong, 2020. "Extraction Method and Integration Framework for Perception Features of Public Opinion in Transportation," Sustainability, MDPI, vol. 13(1), pages 1-17, December.
    8. Alanya-Beltran Willy, 2023. "Modelling volatility dependence with score copula models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(5), pages 649-668, December.
    9. Ayala, Astrid & Blazsek, Szabolcs, 2019. "Score-driven time series models with dynamic shape : an application to the Standard & Poor's 500 index," UC3M Working papers. Economics 28133, Universidad Carlos III de Madrid. Departamento de Economía.
    10. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonality Detection in Small Samples using Score-Driven Nonlinear Multivariate Dynamic Location Models," UC3M Working papers. Economics 27483, Universidad Carlos III de Madrid. Departamento de Economía.
    11. Ayala, Astrid & Blazsek, Szabolcs, 2019. "Maximum likelihood estimation of score-driven models with dynamic shape parameters : an application to Monte Carlo value-at-risk," UC3M Working papers. Economics 28638, Universidad Carlos III de Madrid. Departamento de Economía.

  16. Szabolcs Blazsek & Luis Antonio Monteros, 2017. "Event-study analysis by using dynamic conditional score models," Applied Economics, Taylor & Francis Journals, vol. 49(45), pages 4530-4541, September.

    Cited by:

    1. Astrid Ayala & Szabolcs Blazsek, 2019. "Score-driven currency exchange rate seasonality as applied to the Guatemalan Quetzal/US Dollar," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(1), pages 65-92, March.
    2. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonal Quasi-Vector Autoregressive Models with an Application to Crude Oil Production and Economic Activity in the United States and Canada," UC3M Working papers. Economics 27484, Universidad Carlos III de Madrid. Departamento de Economía.
    3. Ayala Astrid & Blazsek Szabolcs & Escribano Alvaro, 2023. "Anticipating extreme losses using score-driven shape filters," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(4), pages 449-484, September.
    4. Ayala, Astrid & Blazsek, Szabolcs, 2019. "Score-driven time series models with dynamic shape : an application to the Standard & Poor's 500 index," UC3M Working papers. Economics 28133, Universidad Carlos III de Madrid. Departamento de Economía.
    5. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonality Detection in Small Samples using Score-Driven Nonlinear Multivariate Dynamic Location Models," UC3M Working papers. Economics 27483, Universidad Carlos III de Madrid. Departamento de Economía.

  17. Szabolcs Blazsek & Han-Chiang Ho, 2017. "Markov regime-switching Beta--EGARCH," Applied Economics, Taylor & Francis Journals, vol. 49(47), pages 4793-4805, October.

    Cited by:

    1. Chang, Kuang-Liang, 2023. "The low-magnitude and high-magnitude asymmetries in tail dependence structures in international equity markets and the role of bilateral exchange rate," Journal of International Money and Finance, Elsevier, vol. 133(C).
    2. Astrid Ayala & Szabolcs Blazsek, 2019. "Score-driven currency exchange rate seasonality as applied to the Guatemalan Quetzal/US Dollar," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(1), pages 65-92, March.
    3. Blazsek, Szabolcs & Licht, Adrian, 2019. "Markov-switching score-driven multivariate models: outlier-robust measurement of the relationships between world crude oil production and US industrial production," UC3M Working papers. Economics 29030, Universidad Carlos III de Madrid. Departamento de Economía.
    4. Ayala, Astrid & Blazsek, Szabolcs, 2019. "Score-driven time series models with dynamic shape : an application to the Standard & Poor's 500 index," UC3M Working papers. Economics 28133, Universidad Carlos III de Madrid. Departamento de Economía.
    5. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonality Detection in Small Samples using Score-Driven Nonlinear Multivariate Dynamic Location Models," UC3M Working papers. Economics 27483, Universidad Carlos III de Madrid. Departamento de Economía.

  18. Szabolcs Blazsek & Luis Antonio Monteros, 2017. "Dynamic conditional score models of degrees of freedom: filtering with score-driven heavy tails," Applied Economics, Taylor & Francis Journals, vol. 49(53), pages 5426-5440, November.

    Cited by:

    1. Ayala Astrid & Blazsek Szabolcs & Escribano Alvaro, 2023. "Anticipating extreme losses using score-driven shape filters," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(4), pages 449-484, September.
    2. Ayala, Astrid & Blazsek, Szabolcs, 2019. "Score-driven time series models with dynamic shape : an application to the Standard & Poor's 500 index," UC3M Working papers. Economics 28133, Universidad Carlos III de Madrid. Departamento de Economía.
    3. Palumbo, D., 2021. "Testing and Modelling Time Series with Time Varying Tails," Cambridge Working Papers in Economics 2111, Faculty of Economics, University of Cambridge.

  19. Blazsek, Szabolcs & Escribano, Alvaro, 2016. "Score-driven dynamic patent count panel data models," Economics Letters, Elsevier, vol. 149(C), pages 116-119.
    See citations under working paper version above.
  20. Szabolcs Blazsek & Helmuth Chavez & Carlos Mendez, 2016. "Model stability and forecast performance of Beta--EGARCH," Applied Economics Letters, Taylor & Francis Journals, vol. 23(17), pages 1219-1223, November.

    Cited by:

    1. Carlos Henrique Dias Cordeiro de Castro & Fernando Antonio Lucena Aiube, 2023. "Forecasting inflation time series using score‐driven dynamic models and combination methods: The case of Brazil," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 369-401, March.

  21. Blazsek, Szabolcs & Escribano, Alvaro, 2016. "Patent propensity, R&D and market competition: Dynamic spillovers of innovation leaders and followers," Journal of Econometrics, Elsevier, vol. 191(1), pages 145-163.

    Cited by:

    1. Blazsek, Szabolcs, 2022. "Score-driven threshold ice-age models: benchmark models for long-run climate forecasts," UC3M Working papers. Economics 34757, Universidad Carlos III de Madrid. Departamento de Economía.
    2. Shuo Han & Weijun Cui & Jin Chen & Yu Fu, 2019. "Female CEOs and Corporate Innovation Behaviors—Research on the Regulating Effect of Gender Culture," Sustainability, MDPI, vol. 11(3), pages 1-22, January.
    3. Blazsek, Szabolcs, 2016. "Score-driven dynamic patent count panel data models," UC3M Working papers. Economics 23458, Universidad Carlos III de Madrid. Departamento de Economía.
    4. Sisi Zheng & Shanyue Jin, 2023. "Can Enterprises in China Achieve Sustainable Development through Green Investment?," IJERPH, MDPI, vol. 20(3), pages 1-25, January.
    5. Arnold, Denis G. & Amato, Louis H. & Troyer, Jennifer L. & Stewart, Oscar Jerome, 2022. "Innovation and misconduct in the pharmaceutical industry," Journal of Business Research, Elsevier, vol. 144(C), pages 1052-1063.
    6. Wang, Weilong & Wang, Jianlong & Wu, Haitao, 2024. "The impact of energy-consuming rights trading on green total factor productivity in the context of digital economy: Evidence from listed firms in China," Energy Economics, Elsevier, vol. 131(C).
    7. Sara Alonso-Muñoz & Eva Pelechano-Barahona & Rocío González-Sánchez, 2020. "Participation in Group Companies as a Source of External Knowledge in Obtaining and Making Profitable Radical Innovations," Sustainability, MDPI, vol. 12(18), pages 1-19, September.
    8. Zhang, Meiyang & Zhu, Xuezhong & Liu, Rui, 2024. "Patent length and innovation: Novel evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    9. Fang, Guanfu & Gao, Tiantian & Xu, Peng, 2024. "Beyond the borders: Estimating the effect of China's Bonded Zones on innovation and its spillovers," China Economic Review, Elsevier, vol. 83(C).
    10. Suzuki, Keishun, 2017. "Competition, Patent Protection, and Innovation in an Endogenous Market Structure," MPRA Paper 77133, University Library of Munich, Germany.
    11. AIVAZ Kamer-Ainur & TOFAN Ionela, 2022. "The Synergy Between Digitalization And The Level Of Research And Business Development Allocations At Eu Level," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 17(3), pages 5-17, December.
    12. Xin Sheng & Wenya Chen & Decai Tang & Bright Obuobi, 2023. "Impact of Digital Finance on Manufacturing Technology Innovation: Fixed-Effects and Panel-Threshold Approaches," Sustainability, MDPI, vol. 15(14), pages 1-24, July.
    13. Michaela Kotkova Striteska & Viktor Prokop, 2020. "Dynamic Innovation Strategy Model in Practice of Innovation Leaders and Followers in CEE Countries—A Prerequisite for Building Innovative Ecosystems," Sustainability, MDPI, vol. 12(9), pages 1-20, May.
    14. Yuanyuan Dong & Zepeng Wei & Tiansen Liu & Xinpeng Xing, 2020. "The Impact of R&D Intensity on the Innovation Performance of Artificial Intelligence Enterprises-Based on the Moderating Effect of Patent Portfolio," Sustainability, MDPI, vol. 13(1), pages 1-17, December.
    15. Chen, Chao & Gu, Junjian & Luo, Rongxi, 2022. "Corporate innovation and R&D expenditure disclosures," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    16. Nestor Duch-Brown & Andrea de Panizza & Ibrahim Kholilul Rohman, 2016. "Innovation and productivity in a S&T intensive sector: the case of Information industries in Spain," JRC Research Reports JRC101847, Joint Research Centre.

  22. Szabolcs Blazsek & Vicente Mendoza, 2016. "QARMA-Beta- t -EGARCH versus ARMA-GARCH: an application to S&P 500," Applied Economics, Taylor & Francis Journals, vol. 48(12), pages 1119-1129, March.

    Cited by:

    1. Astrid Ayala & Szabolcs Blazsek, 2019. "Score-driven currency exchange rate seasonality as applied to the Guatemalan Quetzal/US Dollar," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(1), pages 65-92, March.
    2. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonality Detection in Small Samples using Score-Driven Nonlinear Multivariate Dynamic Location Models," UC3M Working papers. Economics 27483, Universidad Carlos III de Madrid. Departamento de Economía.

  23. Szabolcs Blazsek & Marco Villatoro, 2015. "Is Beta- t -EGARCH(1,1) superior to GARCH(1,1)?," Applied Economics, Taylor & Francis Journals, vol. 47(17), pages 1764-1774, April.

    Cited by:

    1. Petra Tomanová & Vladimír Holý, 2021. "Clustering of arrivals in queueing systems: autoregressive conditional duration approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(3), pages 859-874, September.
    2. Charles, Amélie & Darné, Olivier, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Energy Economics, Elsevier, vol. 67(C), pages 508-519.
    3. Trucíos, Carlos, 2019. "Forecasting Bitcoin risk measures: A robust approach," International Journal of Forecasting, Elsevier, vol. 35(3), pages 836-847.
    4. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonality Detection in Small Samples using Score-Driven Nonlinear Multivariate Dynamic Location Models," UC3M Working papers. Economics 27483, Universidad Carlos III de Madrid. Departamento de Economía.

  24. Szabolcs Blazsek & Anna Downarowicz, 2013. "Forecasting hedge fund volatility: a Markov regime-switching approach," The European Journal of Finance, Taylor & Francis Journals, vol. 19(4), pages 243-275, April.

    Cited by:

    1. Luo, Cuicui & Seco, Luis & Wu, Lin-Liang Bill, 2015. "Portfolio optimization in hedge funds by OGARCH and Markov Switching Model," Omega, Elsevier, vol. 57(PA), pages 34-39.
    2. Li, Xiafei & Liang, Chao & Chen, Zhonglu & Umar, Muhammad, 2022. "Forecasting crude oil volatility with uncertainty indicators: New evidence," Energy Economics, Elsevier, vol. 108(C).

  25. Nadia Ayari & Szabolcs Blazsek & Pedro Mendi, 2012. "Renewable energy innovations in Europe: a dynamic panel data approach," Applied Economics, Taylor & Francis Journals, vol. 44(24), pages 3135-3147, August.
    See citations under working paper version above.
  26. Astrid Ayala & Szabolcs Blazsek, 2012. "How has the financial crisis affected the fiscal convergence of Central and Eastern Europe to the Eurozone?," Applied Economics Letters, Taylor & Francis Journals, vol. 19(5), pages 471-476, March.

    Cited by:

    1. Nikolay Nenovsky & Kiril Tochkov, 2013. "The Distribution Dynamics of Income in Central and Eastern Europe relative to the EU: A Nonparametric Analysis," William Davidson Institute Working Papers Series wp1063, William Davidson Institute at the University of Michigan.
    2. Athanasios Anastasiou & Nicholas Apergis & Athina Zervoyianni, 2024. "Convergence of public expenditures and revenues in EU28 during 2002–2019: Evidence from club‐clustering analysis before and after the European debt crisis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 1856-1876, April.

  27. Blazsek, Szabolcs & Escribano, Alvaro, 2010. "Knowledge spillovers in US patents: A dynamic patent intensity model with secret common innovation factors," Journal of Econometrics, Elsevier, vol. 159(1), pages 14-32, November.
    See citations under working paper version above.

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 24 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (15) 2008-12-01 2015-12-08 2016-08-14 2017-08-06 2017-11-12 2018-03-05 2018-10-15 2018-10-15 2019-03-11 2019-06-10 2019-07-29 2019-10-28 2020-05-18 2020-05-18 2020-11-16. Author is listed
  2. NEP-ETS: Econometric Time Series (11) 2008-12-01 2018-03-05 2018-10-15 2018-10-15 2019-03-11 2019-06-10 2019-07-29 2019-10-28 2020-05-18 2020-05-18 2020-11-16. Author is listed
  3. NEP-ENE: Energy Economics (5) 2018-10-15 2019-10-28 2020-05-18 2021-10-25 2022-05-23. Author is listed
  4. NEP-INO: Innovation (5) 2010-01-16 2012-02-20 2014-07-05 2015-12-08 2016-08-14. Author is listed
  5. NEP-IPR: Intellectual Property Rights (5) 2010-01-16 2012-02-20 2014-07-05 2015-12-08 2016-08-14. Author is listed
  6. NEP-RMG: Risk Management (4) 2008-12-01 2019-03-11 2019-07-29 2020-11-16
  7. NEP-CSE: Economics of Strategic Management (3) 2010-01-16 2012-02-20 2014-07-05
  8. NEP-DCM: Discrete Choice Models (3) 2020-09-21 2020-10-05 2021-03-22
  9. NEP-ENV: Environmental Economics (3) 2021-10-25 2022-05-23 2024-02-12
  10. NEP-EXP: Experimental Economics (3) 2020-09-21 2020-10-05 2021-03-22
  11. NEP-FOR: Forecasting (3) 2008-12-01 2021-10-25 2022-05-23
  12. NEP-ORE: Operations Research (3) 2019-07-29 2019-10-28 2020-05-18
  13. NEP-UPT: Utility Models and Prospect Theory (3) 2020-09-21 2020-10-05 2021-03-22
  14. NEP-MAC: Macroeconomics (2) 2018-03-05 2018-10-15
  15. NEP-SBM: Small Business Management (2) 2010-01-16 2012-02-20
  16. NEP-TID: Technology and Industrial Dynamics (2) 2010-01-16 2014-07-05
  17. NEP-BEC: Business Economics (1) 2016-08-14
  18. NEP-COM: Industrial Competition (1) 2014-07-05
  19. NEP-DGE: Dynamic General Equilibrium (1) 2020-05-18
  20. NEP-HIS: Business, Economic and Financial History (1) 2021-10-25
  21. NEP-KNM: Knowledge Management and Knowledge Economy (1) 2010-01-16

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