IDEAS home Printed from https://ideas.repec.org/e/pvi12.html
   My authors  Follow this author

Antoni Vidiella-I-Anguera

Personal Details

First Name:Antoni
Middle Name:
Last Name:Vidiella-I-Anguera
Suffix:
RePEc Short-ID:pvi12
http://www.ub.es/mecfi/AVidiella.html
Virtut 6, principal 08012 Barcelona Catalonia, Spain

Research output

as
Jump to: Articles

Articles

  1. Jan G. De Gooijer & Antoni Vidiella-i-Anguera, 2005. "Estimating threshold cointegrated systems," Economics Bulletin, AccessEcon, vol. 3(8), pages 1-7.
  2. De Gooijer, Jan G. & Vidiella-i-Anguera, Antoni, 2004. "Forecasting threshold cointegrated systems," International Journal of Forecasting, Elsevier, vol. 20(2), pages 237-253.
  3. De Gooijer, Jan G. & Vidiella-i-Anguera, Antoni, 2003. "Nonlinear stochastic inflation modelling using SEASETARs," Insurance: Mathematics and Economics, Elsevier, vol. 32(1), pages 3-18, February.

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.

Articles

  1. De Gooijer, Jan G. & Vidiella-i-Anguera, Antoni, 2004. "Forecasting threshold cointegrated systems," International Journal of Forecasting, Elsevier, vol. 20(2), pages 237-253.

    Cited by:

    1. David Hendry & Andrew B. Martinez, 2016. "Evaluating Multi-Step System Forecasts with Relatively Few Forecast-Error Observations," Economics Series Working Papers 784, University of Oxford, Department of Economics.
    2. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2015. "Was the recent downturn in US real GDP predictable?," Applied Economics, Taylor & Francis Journals, vol. 47(28), pages 2985-3007, June.
    3. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen Miller, 2010. "Forecasting Nevada Gross Gaming Revenue and Taxable Sales Using Coincident and Leading Employment Indexes," Working Papers 15-01, Eastern Mediterranean University, Department of Economics.
    4. Pawel Milobedzki, 2010. "The Term Structure of the Polish Interbank Rates. A Note on the Symmetry of their Reversion to the Mean," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 10, pages 81-95.
    5. Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
    6. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2012. "Was the Recent Downturn in US GDP Predictable?," Working papers 2012-38, University of Connecticut, Department of Economics, revised Dec 2013.
    7. Terasvirta, Timo, 2006. "Forecasting economic variables with nonlinear models," Handbook of Economic Forecasting, Elsevier.
    8. Clements, Michael P. & Galvao, Ana Beatriz, 2004. "A comparison of tests of nonlinear cointegration with application to the predictability of US interest rates using the term structure," International Journal of Forecasting, Elsevier, vol. 20(2), pages 219-236.
    9. Michael P. Clements & Philip Hans Franses & Norman R. Swanson, 2003. "Forecasting economic and financial time-series with non-linear models," Departmental Working Papers 200309, Rutgers University, Department of Economics.
    10. Michael J. Dueker & Zacharias Psaradakis & Martin Sola & Fabio Spagnolo, 2007. "Multivariate contemporaneous threshold autoregressive models," Working Papers 2007-019, Federal Reserve Bank of St. Louis.
    11. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    12. Jumah, Adusei & Kunst, Robert M., 2008. "Optimizing Time-series Forecasts for Inflation and Interest Rates Using Simulation and Model Averaging," Economics Series 231, Institute for Advanced Studies.
    13. Jan G. De Gooijer & Antoni Vidiella-i-Anguera, 2005. "Estimating threshold cointegrated systems," Economics Bulletin, AccessEcon, vol. 3(8), pages 1-7.
    14. Roula Inglesi-Lotz & Mehmet Balcilar & Rangan Gupta, 2014. "Time-varying causality between research output and economic growth in US," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(1), pages 203-216, July.

  2. De Gooijer, Jan G. & Vidiella-i-Anguera, Antoni, 2003. "Nonlinear stochastic inflation modelling using SEASETARs," Insurance: Mathematics and Economics, Elsevier, vol. 32(1), pages 3-18, February.

    Cited by:

    1. Li, Johnny Siu-Hang & Ng, Andrew C.Y. & Chan, Wai-Sum, 2015. "Managing financial risk in Chinese stock markets: Option pricing and modeling under a multivariate threshold autoregression," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 217-230.
    2. Chan, W.S. & Cheung, S.H., 2005. "A bivariate threshold time series model for analyzing Australian interest rates," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 68(5), pages 429-437.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

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, Antoni Vidiella-I-Anguera 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 hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.