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Prof. dr. J.G. (Jan) de Gooijer

Faculty of Economics and Business
Section Quantitative Economics
Photographer: FEB

Visiting address
  • Roetersstraat 11
Postal address
  • Postbus 15867
    1001 NJ Amsterdam
Contact details
  • Profile

    Positions

    Professor of Economic Statistics

    Research programme

    UvA-Econometrics 

    Research interests

    Nonlinear Time Series Analysis; Change Point Problems; Forecasting; Model Identification, Nonparametric and semi-parametric statistics.

    Education

    M.Sc. in Mathematics and Statistics, Technical University Delft (1975);
    Ph.D. in Economics, Free University Amsterdam (1984)

    UvA-Econometrics

    See: www.fee.uva.nl/ke/UvA-Econometrics 

    Dissertation title

    Contributions to Univariate Time Series with an Application to Dutch Stock Market Prices 

    Prizes and honours

    Honorary Fellow of the International Institute of Forecasters (2008) Elected Fellow International Statistical Institute

    Curriculum Vitae 

  • Other activities

    Contributions (lectures) to conferences, workshops, seminars, summer schools

    • Detecting change-points in multidimensional stochastic processes, Department of Economics, University of Umeå, Sweden, October 7, 2005. (invited presentation) 
    • On the geometric conditional quantile, Joint Statistical Meetings, Toronto, Ontario, Canada, August 10, 2004. 
    • Multivariate conditional prediction, 24th International Symposium on Forecasting, Sydney, Australia, July 7, 2004 (invited presentation) 
    • Nonparametric multivariate conditional quantile prediction, 21st International Symposium on Forecasting, Pine Mountain, Georgia, USA, June 19, 2003. 
    • Modelling vector nonlinear time series using POLYMARS, Dipartimento di Scienze Economische e Statistische, Universita di Trieste, Italy, April 29, 2002 (invited presentation) 
    • On additive conditional quantiles with high-dimensional covariates, Conference: Current Advances and Trends in Nonparametric Statistics, Crete, Greece, July 19, 2002. 
    • Forecasting threshold cointegrated systems, Conference: Blending Theory and Practice in Research and the Evalaution of Economic Policy, Theil Memorial Conference, Amsterdam, The Netherlands, August 16, 2002 (invited presentation) 
    • Forecasting threshold cointegrated systems, Department of Economics, George Washington University, Washington DC, USA, September 26, 2002. 
    • Forecasting threshold cointegrated systems, McDonough School of Business, Georgetown University, Washington, DC, USA, September 25, 2002. 
    • Cross-validation criteria for selecting covariance structures and SETAR models, Department of Statistics and Actuarial Science, University of Stellenbosch, South Africa, March 28, 2001 (invited presentation) 
    • Multivariate conditional quantile prediction, Annual Meeting South-African Statistical Society, Stellenbosch, South Africa, March 30, 2001 (invited presentation) 
    • Modeling vector nonlinear time series using PMARS, UvA-Econometrics Weekly Lunch Seminar, Amsterdam, The Netherlands, December 3, 2001. 
    • Nonparametric Forecasting, School of Humanities and Social Sciences, Nanyang Technological University, Singapore, January 11, 2007 (invited presentation).
    • Time Series Forecasting: A Kind of (Historical) Overview , School of Humanities and Social Sciences, Nanyang Technological University, Singapore, January 15, 2007 (invited presentation). 
    • Semiparametric Regression with Kernel Error Model , 7th World Congres in Probability and Statistics, Singapore, July 16, 2008. 
    • Parametric and Nonparametric Granger Causality Testing , 28th International Symposium on Forecasting, Nice, France, June 23, 2008. 
    • Nonparametric Portmanteau Tests for Detecting Nonlinearities in High Dimensions, Institute for Advanced Studies, Vienna, March 22, 2012 (invited presentation).

     

    Membership editorial staff or referee activities

    • Associate Editor International Journal of Forecasting (till January 2012) 
    • Associate Editor Empirical Economics (till January 2012).

     

  • Links
  • Publications

    2021

    2020

    2019

    2018

    2017

    2016

    2014

    2012

    • Brännäs, K., de Gooijer, J. G., Lönnbark, C., & Soultanaeva, A. (2012). Simultaneity and asymmetry of returns and volatilities: the emerging Baltic States' stock exchanges. Studies in Nonlinear Dynamics and Econometrics, 16(1), [4]. https://doi.org/10.1515/1558-3708.1855 [details]
    • de Gooijer, J. G., Diks, C. G. H., & Gatarek, L. T. (2012). Information flows around the globe: predicting opening gaps from overnight foreign stock price patterns. Central European Journal of Economic Modelling and Econometrics, 4(1), 23-44. [details]

    2011

    2009

    2008

    2007

    2006

    2005

    • de Gooijer, J. G., & Vidiella-i-Anguera, A. (2005). Estimating threshold cointegrated systems. Economics Bulletin, 3(8), 1-7.

    2004

    2003

    2002

    • de Gooijer, J. G., Gannoun, A., & Larramendy, I. (2002). Nonparametric regression with serially correlated errors. Pub. Inst. Stat. Univ. Paris, XXXXVI(1-2), 17-41. [details]
    • de Gooijer, J. G., Gannoun, A., & Zerom Godefay, D. (2002). Mean squared error properties of the kernel-based multi-stage median predictor for time series. Statistics & Probability Letters, 56, 51-56. https://doi.org/10.1016/S0167-7152(01)00169-9 [details]

    2001

    2000

    • de Gooijer, J. G., & Zerom Godefay, D. (2000). Kernel-based multistep-ahead predictions of the US short-term interest rate. Journal of Forecasting, (19), 335-353. [details]
    • de Gooijer, J. G., & Zerom Godefay, D. (2000). Nonparametric conditional predictive regions for time series. Computational Statistics and Data Analysis, (33), 259-275. https://doi.org/10.1016/S0167-9473(99)00056-0 [details]

    1999

    • de Gooijer, J. G., & Knotters, M. (1999). TARSO modeling of water table depths. Water Resources Research, (35), 695-705. [details]
    • de Gooijer, J. G., & Macneill, I. B. (1999). Lagged regression residuals and serial-correlation tests. Journal of Business & Economic Statistics, (17), 236-247. [details]

    1998

    1997

    • de Gooijer, J. G., & Franses, P. H. (1997). Forecasting and seasonality. International Journal of Forecasting, 13, 303-305. https://doi.org/10.1016/S0169-2070(97)00018-6 [details]
    • van Casteren, P. H. F. M., & de Gooijer, J. G. (1997). Model selection by maximum entropy. Advances in Econometrics, 12, 135-161. [details]

    1996

    • Akman, I., & de Gooijer, J. G. (1996). Component extraction analysis of multivariate time series. Computational Statistics and Data Analysis, 21, 487-499. https://doi.org/10.1016/0167-9473(95)00031-3 [details]
    • Klein, A. A. B., & de Gooijer, J. G. (1996). Cumulated prediction errors of multivariate time series models. Random Operators and Stochastic Equations, 4, 111-117. [details]

    1995

    1994

    • de Gooijer, J. G., & Brannas, K. (1994). Autoregressive - asymmetric moving average models for business cycle data. Journal of Forecasting, 13, 529-544.
    • de Gooijer, J. G., & Pukkila, T. (1994). On the expectation of estimators for general ARMA processes. Statistica, LIV, 39-50.
    • de Gooijer, J. G., Bretschneider, S., & Koveos, P. (1994). Estimating market model betas using least absolute deviations estimation: Does it make a difference? Kwantitatieve Methoden, 15, 77-89.

    1992

    • Does, R. J. M. M., & de Gooijer, J. G. (1992). Statistische kwaliteitsbeheersing binnen de Nederlandse industrie. Sigma, 92(6), 23-25.
    • Molenaar, P. C. M., de Gooijer, J. G., & Schmitz, B. (1992). Dynamic factor analysis of nonstationary multivariate time series. Psychometrika, 57(3), 333-349. https://doi.org/10.1007/BF02295422 [details]
    • de Gooijer, J. G., & Anderson, O. D. (1992). Discriminating between nonstationary and nearly nonstationary time series models: A simulation study. Journal of Computational and Applied Mathematics, 41, 265-280.
    • de Gooijer, J. G., & Klein, A. A. B. (1992). On the cumulated multi-step-ahead predictions of vector autoregressive moving average processes. International Journal of Forecasting, 7(4), 501-513. https://doi.org/10.1016/0169-2070(92)90034-7
    • de Gooijer, J. G., & Kumar, K. (1992). Some recent developments in non-linear time series modelling, testing, and forecasting. International Journal of Forecasting, 8(2), 135-156. https://doi.org/10.1016/0169-2070(92)90115-P

    1990

    • de Gooijer, J. G. (1990). The role of time series analysis in forecasting: A personal view. International Journal of Forecasting, 6, 449-451.
    • de Gooijer, J. G., & Anderson, O. D. (1990). Discrimination between nonstationary processes, and its effect on forecasting. Operations Research, 24, 67-91.

    1989

    • de Gooijer, J. G. (1989). Testing non-linearities in world stock market prices. Economics Letters, 31, 31- 34.
    • de Gooijer, J. G., & Klein, A. A. B. (1989). Forecasting the Antwerp Maritime Steel Traffic Flow: A case study. Journal of Forecasting, 8(4), 381-398. https://doi.org/10.1002/for.3980080404
    • de Gooijer, J. G., & Stoica, P. (1989). A min-max optimal variable estimation method for multivariate linear time series systems. The International Journal of Control, 50, 955-976.
    • de Gooijer, J. G., & van Nieuwburg, M. J. T. J. (1989). Indexnumber Theory with Economic Applications. Boom Uitgeverij.

    1988

    • de Gooijer, J. G., & Anderson, O. D. (1988). Sampled autocovariance and autocorrelation results for linear time processes. Communications in Statistics: Simulation and Computation, 17(2), 489-513.
    • de Gooijer, J. G., & Koopman, S. J. (1988). Cross-validation criteria and the analysis of covariance structures. In M. G. H. Jansen, & W. H. Schuur (Eds.), The Many Faces of Multivariate Analysis: Proceedings of the SMABS-88 conference in Groningen (pp. 263-311). RION Groningen.
    • de Gooijer, J. G., & Saikkonen, P. (1988). A specification strategy for order determination in ARMA models. Communications in Statistics: Theory and Methods, 17(3), 1037-1054.

    1987

    • de Gooijer, J. G. (1987). Correlations in stock returns: Some statistical comments. In A. B. Dorsman, J. van der Hilst, & R. T. Wymenga (Eds.), The Amsterdam Stock Exchange (pp. 47-55). Samsom Uitgeverij.
    • de Gooijer, J. G. (1987). Non-linearities in world stock market prices. In J. G. de Gooijer, M. J. T. J. van Nieuwburg, & J. A. M. Wesseling (Eds.), Economic Statistics: Recent Developments in Quantitative Research Boom Uitgeverij.
    • de Gooijer, J. G., & Heuts, R. M. J. (1987). Higher order moments of bilinear time series processes with symmetrically distributed errors. In T. Pukkila, & S. Puntanen (Eds.), Proceedings of the Second International Tampere Conference in Statistics (pp. 467-476).
    • de Gooijer, J. G., van Nieuwburg, M. J. T. J., & Wesseling, J. A. M. (1987). Economic Statistics: Recent Developments in Quantitative Research. Boom Uitgeverij.

    1985

    • de Gooijer, J. G. (1985). A Monte Carlo study of the small-sample properties of some estimators for ARMA models. Computational Statistics Quarterly, 2, 245-266.
    • de Gooijer, J. G. (1985). Time series model selection and financial market efficiency. In R. Henn (Ed.), Methods of Operations Research (pp. 205-224). Hain Verlag.
    • de Gooijer, J. G., & Anderson, O. D. (1985). Moments of the sampled space-time autocovariance and autocorrelation function. Biometrika, 72, 689-693.
    • de Gooijer, J. G., Abrahma, B., Gould, A., & Robinson, L. (1985). Methods for determining the order of an autoregressive moving average process: A survey. International Statistical Review, 53(3), 301-329.

    1984

    • de Gooijer, J. G., & Dorsman, A. B. (1984). On the behavior of Dutch stock market prices and the random walk hypothesis. In G. Hawawini, & P. Michel (Eds.), European Equity Markets: Risk, Return and Efficiency (pp. 185-214). Garland Publishing Company.
    • de Gooijer, J. G., & Dorsman, A. B. (1984). On the strong form efficiency hypothesis and the behavior of stock prices on the Amsterdam Stock Exchange (1). Bedrijfskunde: Tijdschrift voor Modern Management, 56, 86-96.
    • de Gooijer, J. G., & Dorsman, A. B. (1984). On the strong form efficiency hypothesis and the behavior of stock prices on the Amsterdam Stock Exchange (2). Bedrijfskunde: Tijdschrift voor Modern Management, 56, 202-208.

    1983

    • de Gooijer, J. G., & Anderson, O. D. (1983). Formulae for the covariance structure of the sampled autocovariances from series generated by general autoregressive integrated moving average processes of order (p,d,q), d=0 or 1. Sankhya B, 45, 249-256.
    • de Gooijer, J. G., & Dorsman, A. B. (1983). The relationship between the New York and Amsterdam Stock Exchange. Bedrijfskunde: Tijdschrift voor Modern Management, 55, 95-98.

    1982

    • de Gooijer, J. G., & Anderson, O. D. (1982). The covariances between sampled autocovariances and between serial correlations for finite realizations from ARUMA time series models. In O. D. Anderson (Ed.), Time Series Analysis: Theory and Practice 1 (pp. 7-22). Elsevier.
    • de Gooijer, J. G., & Dorsman, A. B. (1982). On the behavior of stock prices on the Amsterdam Stock Exchange and the random walk hypothesis. Bedrijfskunde: Tijdschrift voor Modern Management, 54, 370-378.
    • de Gooijer, J. G., & Godolphin, E. J. (1982). On the maximum likelihood estimation of the parameters of a Gaussian moving average process. Biometrika, 69, 443-451.

    1981

    • de Gooijer, J. G. (1981). An investigation of the moments of the sample autocovariances and autocorrelations for general ARMA processes. Journal of Statistical Computation and Simulation, 12, 175-192.
    • de Gooijer, J. G., & Heuts, R. M. J. (1981). The corner method: An investigation of an order discrimination procedure for general ARMA processes. Journal of the Operational Research Society, 32, 1039-1042.

    1980

    • de Gooijer, J. G. (1980). A comparative study of some sample autocovariance and autocorrelation functions. Cahiers du Centre d'Etudes de Recherche Operationelle , 22, 325-343.
    • de Gooijer, J. G. (1980). A comparative study of the moments of the first lag serial correlation coefficient. Statistica, XL, 345-362.
    • de Gooijer, J. G. (1980). Exact moments of the sample autocorrelations from series generated by general ARIMA processes of order (p,d,q), d=0 or 1. Journal of Econometrics, 14, 365-379.
    • de Gooijer, J. G., & Anderson, O. D. (1980). Classifying series realizations from IMA(1,1) and ARMA(1,1) processes. In O. D. Anderson (Ed.), Time Series (pp. 5-13). Elsevier.
    • de Gooijer, J. G., & Anderson, O. D. (1980). Distinguishing between IMA(1,1) and ARMA(1,1) models: A large scale simulation study of two particular time processes. In O. D. Anderson (Ed.), Time Series (pp. 15-40). Elsevier.
    • de Gooijer, J. G., & Anderson, O. D. (1980). Distinguishing certain stationary time series from their nonstationary approximations and improved Box-Jenkins forecasting. In O. D. Anderson (Ed.), Analysing Time Series (pp. 21-42). Elsevier.

    1979

    • de Gooijer, J. G. (1979). On a recurrence relation for a special type of determinant. The matrix and tensor quarterly, 30, 55-60.
    • de Gooijer, J. G., & Anderson, O. D. (1979). On discriminating between IMA(1,1) and ARMA(1,1) processes: some extensions to a paper by Wichern. Statistician, 28, 119-133.

    1978

    • de Gooijer, J. G. (1978). On the inverse of the autocovariance matrix for a general mixed autoregressive moving process. Statistical Papers, 19, 114-123.

    1977

    • de Gooijer, J. G. (1977). Modelling of multivariate time series processes. Cahiers du Centre d'Etudes de Recherche Operationelle , 19, 349-355.

    2010

    • Cheng, Y., de Gooijer, J. G., & Zerom, D. (2010). Efficient estimation of an additive quantile regression model. (UvA-Econometrics discussion paper; No. 2010/05). Amsterdam: Amsterdam School of Economics, Department of Quantitative Economics. [details]
    • de Gooijer, J. G., & Yuan, A. (2010). Some exact tests for manifest properties of latent trait models. (Tinbergen Institute discussion paper; No. TI 2010-044/4). Amsterdam: Tinbergen Institute. [details]

    2009

    • Cheng, Y., de Gooijer, J. G., & Zerom, D. (2009). Efficient estimation of an additive quantile regression model. (Tinbergen Institute Discussion Paper; No. TI 2009-104/4). Amsterdam: Faculteit Economie en Bedrijfskunde. [details]

    2008

    • de Gooijer, J. G., & Sivarajasingham, S. (2008). Parametric and nonparametric Granger causality testing: linkages between international stock markets. In Proceedings of the 28th International Symposium on Forecasting (pp. 1-22). Nice, France. [details]
    • de Gooijer, J. G., & Yuan, A. (2008). Exact tests for some latent traits. (UvA-Econometrics discussion papers; No. 2008/01). onbekend: Afdeling Kwantitatieve Economie. [details]

    2006

    • de Gooijer, J. G. (2006). Power of the Neyman smooth test for evaluating multivariate forecast densities. (UvA-Econometrics Working Paper; No. 2006/05). Amsterdam: Faculteit Economie en Bedrijfskunde.
    • de Gooijer, J. G., & Yuan, A. (2006). Semiparametric regression with kernel error model. (Tinbergen Institute Discussion Paper; No. 06-058/4). Amsterdam: Faculteit Economie en Bedrijfskunde.

    2005

    • Cheng, Y., & de Gooijer, J. G. (2005). On the geometric conditional quantile. In Proceedings of the Joint Statistical meetings (pp. 1971-1974)
    • de Gooijer, J. G., Garcia-Ferrer, A., Poncela, P., & Ruiz, E. (2005). Introduction to nonlinearities, business cycles, and forecasting. International Journal of Forecasting, 21, 623-625. https://doi.org/10.1016/j.ijforecast.2005.04.001

    2002

    2001

    • de Gooijer, J. G., Gannoun, A., & Zerom Godefay, D. (2001). Multi-stage conditional quantile prediction. In Proceedings of the Statistical Computing Section and the Section on Statistical Graphics of the American Statistical Association 2000 meeting (pp. 32-37) [details]

    1998

    • de Bruin, P. T., & de Gooijer, J. G. (1998). A comparison of ARMA and SETAR forecasts. AE-report, 6/98. [details]

    1996

    • Brannas, K., de Gooijer, J. G., & Terasvirta, T. (1996). Testing linearity against nonlinear moving average models. Report AE, 96(8). [details]
    • Klein, A. A. B., & de Gooijer, J. G. (1996). Cumulated prediction errors of multivariate time series. (TI discussion paper; No. 96-34/7). Amsterdam: Tinbergen Institute. [details]
    • van Casteren, P. H. F. M., & de Gooijer, J. G. (1996). Model selection by maximum entropy. (TI discussion paper; No. 96-160/7). Amsterdam: Tinbergen Institute. [details]

    1995

    • Akman, I., & de Gooijer, J. G. (1995). Component extraction analysis of multivariate time series. (TI discussion paper; No. TI 95-125). Amsterdam: vakgroep kwantitatieve methoden. [details]
    • de Gooijer, J. G. (1995). Oliver Duncan Anderson: 1940-1995. International Journal of Forecasting, 11(1), 195-196.

    1992

    • de Gooijer, J. G. (1992). Lies, big lies, and quantitative forecasts. Kwantitatieve Methoden, 40, 115-128.

    1988

    • Molenaar, P. C. M., & de Gooijer, J. G. (1988). On the identification of the latent covariance structure in dynamic nonstationary factor models. In M. G. H. Jansen, & W. H. van Schuur (Eds.), The many faces of multivariate analysis (pp. 196-209). Groningen: Society for multivariate analysis in the behavioral sciences. [details]

    2011

    • Yuan, A., & de Gooijer, J. G. (2011). Asymptotically informative prior for Bayesian analysis. (Tinbergen Institute discussion paper; No. TI2011-130/4). Amsterdam: Tinbergen Institute. [details]
    • de Gooijer, J. G., & Yuan, A. (2011). Kernel-smoothed conditional quantiles of correlated bivariate discrete data. (Tinbergen Institute Discussion Paper; No. TI2011-011/4). Amsterdam/Rotterdam: Tinbergen Institute. [details]

    2009

    • de Gooijer, J. G., Diks, C. G. H., & Gatarek, L. T. (2009). Information flows around the globe: predicting opening gaps from overnight foreign stock price patterns. (CeNDEF working paper; No. 09-13). Amsterdam: CeNDEF. [details]
    • de Gooijer, J. G., Diks, C. G. H., & Gatarek, L. T. (2009). Information flows around the globe: predicting opening gaps from overnight foreign stock price patterns. (Tinbergen Institute discussion paper; No. TI 2009-107/4). Amsterdam [etc.]: Tinbergen Institute. [details]
    • de Gooijer, J. G., Diks, C. G. H., & Gatarek, L. T. (2009). Information flows around the globe: predicting opening gaps from overnight foreign stock price patterns. (UvA-Econometrics discussion paper; No. 2009/02). Amsterdam: Faculteit Economie en Bedrijfskunde. [details]

    2007

    • Brännäs, K., de Gooijer, J. G., Lönnbark, C., & Soultanaeva, A. (2007). Simultaneity and asymmetry of returns and volatilities in the emerging Baltic stock exchanges. (Umeå Economic Studies; No. 725). Umeå University. https://ideas.repec.org/p/hhs/umnees/0725.html
    • de Gooijer, J. G. (2007). Partial sums of lagged cross-products of AR residuals and a test for white noise. (UvA - Econometrics Working Paper; No. 2007/02). Amsterdam: Faculteit Economie en Bedrijfskunde.

    2000

    • Brännäs, K., & de Gooijer, J. G. (2000). Asymmetries in conditional mean and variance: Modelling stock returns by asMA-asQGARCH. (Tinbergen Institute Discussion Paper; No. TI 2000-049/4). Amsterdam / Rotterdam: Tinbergen Institute. [details]
    • de Gooijer, J. G., & Vidiella-i-Anguera, A. (2000). Modelling seasonalities in nonlinear inflation rates using SEASETERs. (Tinbergen Institute Discussion Paper; No. TI 2000-098/4). Amsterdam / Rotterdam: Discussion paper - Tinbergen Institute. [details]

    1999

    • de Gooijer, J. G., & Zerom Godefay, D. (1999). Kernel-based multistep-ahead predictions of the U.S. short-term interest rate. (Tinbergen Institute Discussion Paper; No. TI 1999-015/4). Amsterdam / Rotterdam: Tinbergen Institute. [details]
    • de Gooijer, J. G., Gannoun, A., & Larramendy, I. (1999). Nonparametric regression with serially correlated errors. (Tinbeergen Institute Discussion Paper; No. TI 1999-063/4). Amsterdam / Rotterdam: Tinbergen Institute. [details]
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  • Ancillary activities
    No known ancillary activities