IDEAS home Printed from https://ideas.repec.org/e/pbl111.html
   My authors  Follow this author

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 & Escribano, Álvaro & 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 & Escribano, Álvaro, 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 & Escribano, Álvaro, 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 & Escribano, Álvaro & 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 & Escribano, Álvaro & 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 & Escribano, Álvaro & 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. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 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.
  9. Blazsek, Szabolcs & Escribano, Álvaro & 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.
  10. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 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. Blazsek, Szabolcs & Escribano, Álvaro & 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.
  12. Blazsek, Szabolcs & Escribano, Álvaro & 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 & Escribano, Álvaro & Licht, Adrian, 2018. "Seasonal quasi-vector autoregressive models for macroeconomic data," UC3M Working papers. Economics 26316, Universidad Carlos III de Madrid. Departamento de Economía.
  14. Blazsek, Szabolcs & Escribano, Álvaro & 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 & Escribano, Álvaro, 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 & Escribano, Álvaro & 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 & Escribano, Álvaro, 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 & Escribano, Álvaro, 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 & Escribano, Álvaro, 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 & Escribano, Álvaro, 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. Blazsek, Szabolcs & Escribano, Álvaro, 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.
  23. 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.
  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 & Licht Adrian & Escribano Alvaro, 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.
  2. Szabolcs Blazsek & Richard Bowen, 2024. "Score-driven cryptocurrency and equity portfolios," Applied Economics, Taylor & Francis Journals, vol. 56(18), pages 2109-2128, April.
  3. 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.
  4. Blazsek, Szabolcs & Escribano, Alvaro, 2023. "Score-driven threshold ice-age models: Benchmark models for long-run climate forecasts," Energy Economics, Elsevier, vol. 118(C).
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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.
  11. 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.
  12. 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.
  13. 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.
  14. 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.
  15. 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.
  16. Blazsek Szabolcs & Licht Adrian & Escribano Alvaro, 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.
  17. 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.
  18. 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.
  19. 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.
  20. 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.
  21. 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.
  22. 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.
  23. 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.
  24. 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.
  25. 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.
  26. 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.
  27. Szabolcs Blazsek & Han-Chiang Ho, 2017. "Markov regime-switching Beta--EGARCH," Applied Economics, Taylor & Francis Journals, vol. 49(47), pages 4793-4805, October.
  28. 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.
  29. Blazsek, Szabolcs & Escribano, Alvaro, 2016. "Score-driven dynamic patent count panel data models," Economics Letters, Elsevier, vol. 149(C), pages 116-119.
  30. 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.
  31. 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.
  32. 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.
  33. 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.
  34. 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.
  35. 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.
  36. 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.
  37. 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.
  38. 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.
  39. 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 & Escribano, Álvaro, 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 & Escribano, Álvaro & 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 & Escribano, Álvaro, 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 & Escribano, Álvaro, 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 & Escribano, Álvaro & 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. 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.
    2. 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.

  4. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 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. Blazsek, Szabolcs & Escribano, Álvaro & 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.
    2. 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. Blazsek, Szabolcs & Escribano, Álvaro & 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 & Escribano, Álvaro & 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 & Escribano, Álvaro & 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.

  7. Blazsek, Szabolcs & Escribano, Álvaro & 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.

  8. Blazsek, Szabolcs & Escribano, Álvaro & 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 & Escribano, Álvaro & 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 & Escribano, Álvaro, 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. Blazsek, Szabolcs & Escribano, Álvaro & 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.
    2. Blazsek, Szabolcs & Escribano, Álvaro & 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.
    3. 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.

  10. Blazsek, Szabolcs & Escribano, Álvaro & 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 & Escribano, Álvaro & 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.
    2. Blazsek, Szabolcs & Escribano, Álvaro & 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 & Escribano, Álvaro & 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.
    4. Blazsek Szabolcs & Licht Adrian & Escribano Alvaro, 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.

  11. Blazsek, Szabolcs & Escribano, Álvaro, 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. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 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 & Escribano, Álvaro & 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, Álvaro & 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.
    4. Blazsek, Szabolcs & Escribano, Álvaro, 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.
    5. Blazsek, Szabolcs & Escribano, Álvaro & 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.
    6. Blazsek, Szabolcs Istvan & Escribano, Álvaro & 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.

  12. Blazsek, Szabolcs & Escribano, Álvaro, 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. 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.
    2. 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.

  13. Blazsek, Szabolcs & Escribano, Álvaro, 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 & Escribano, Álvaro, 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. 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).
    3. 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.
    4. 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).
    5. 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.
    6. 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).
    7. 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.
    8. 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.
    9. 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).

  15. Blazsek, Szabolcs & Escribano, Álvaro, 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. Klein, Michael A., 2022. "The reward and contract theories of patents in a model of endogenous growth," European Economic Review, Elsevier, vol. 147(C).
    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.
    3. Blazsek, Szabolcs & Escribano, Alvaro, 2016. "Score-driven dynamic patent count panel data models," Economics Letters, Elsevier, vol. 149(C), pages 116-119.
    4. Blazsek, Szabolcs & Escribano, Álvaro & 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.
    5. Waters, James, 2011. "The effect of the Sarbanes-Oxley Act on innovation," MPRA Paper 28072, University Library of Munich, Germany.
    6. Blazsek, Szabolcs & Escribano, Álvaro & 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. Rodolphe Desbordes & Markus Eberhardt, 2022. "Climate change and economic prosperity: Evidence from a flexible damage function," Discussion Papers 2022-06, University of Nottingham, GEP.
    8. Blazsek, Szabolcs & Escribano, Álvaro, 2015. "Dynamic conditional score patent count panel data models," UC3M Working papers. Economics we1510, Universidad Carlos III de Madrid. Departamento de Economía.
    9. 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.
    10. 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.
    11. Blazsek, Szabolcs & Escribano, Álvaro, 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 & Escribano, Álvaro, 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.
    13. 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.

  16. 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.

  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. 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. 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.
    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. 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.
  3. 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.

  4. 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.

  5. 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.
  6. 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.

  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. 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.
    2. 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.
    3. 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.
    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.

  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. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 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. 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).
    3. Blazsek, Szabolcs & Escribano, Álvaro & 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. 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. 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. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 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 & Escribano, Álvaro & 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. 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.
    5. 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.
    6. 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.

  11. 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. Blazsek, Szabolcs & Escribano, Álvaro & 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.
    2. Blazsek, Szabolcs & Escribano, Álvaro & 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. 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).
    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. 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.
    6. 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.

  12. 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. 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.
    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.

  13. 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 & Escribano, Álvaro, 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 & Escribano, Álvaro & 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. 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. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 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 & Escribano, Álvaro & 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.
    3. 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.

  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. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 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. 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. Blazsek, Szabolcs & Escribano, Álvaro & 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.
    4. 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.
    5. Blazsek, Szabolcs & Escribano, Álvaro & 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.
    6. 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.
    7. 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).
    8. 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.
    9. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 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. 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.

  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. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 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 & Escribano, Álvaro & 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, Álvaro & 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.
    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, 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.

  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. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 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 & Escribano, Álvaro & 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.
    3. Blazsek, Szabolcs & Escribano, Álvaro & 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. 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).
    5. 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.

  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, Álvaro, 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. 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.
    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. 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. Blazsek, Szabolcs & Escribano, Álvaro & 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.
    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.

  22. 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. 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.
    2. Blazsek, Szabolcs & Escribano, Alvaro, 2016. "Score-driven dynamic patent count panel data models," Economics Letters, Elsevier, vol. 149(C), pages 116-119.
    3. Sisi Zheng & Shanyue Jin, 2023. "Can Enterprises in China Achieve Sustainable Development through Green Investment?," IJERPH, MDPI, vol. 20(3), pages 1-25, January.
    4. Chen, Chao & Gu, Junjian & Luo, Rongxi, 2022. "Corporate innovation and R&D expenditure disclosures," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    5. 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.
    6. Blazsek, Szabolcs & Escribano, Álvaro, 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. Suzuki, Keishun, 2017. "Competition, Patent Protection, and Innovation in an Endogenous Market Structure," MPRA Paper 77133, University Library of Munich, Germany.
    12. 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.
    13. 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.

  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. Blazsek, Szabolcs & Escribano, Álvaro & 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.
    2. Amélie Charles & Olivier Darné, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Post-Print hal-01598141, HAL.
    3. 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.
    4. Trucíos, Carlos, 2019. "Forecasting Bitcoin risk measures: A robust approach," International Journal of Forecasting, Elsevier, vol. 35(3), pages 836-847.

  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. 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.

  26. 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.
  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.

Chapters

    Sorry, no citations of chapters recorded.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

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

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Szabolcs Blazsek should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.