Borowska, A., Hoogerheide, L., Koopman, S.J. and van Dijk, HermanK. (2020). Partially censored posterior for robust and efficient risk evaluation Journal of Econometrics, 217(2):335--355.
Herman van Dijk
University
Erasmus University Rotterdam
E-mail
Research field
Econometrics
Website
Biography
2023
• Casarin, R., S. Grassi, F. Ravazzolo, and H. K. van Dijk (2023). A flexible predictive density combination for large financial data sets in regular and crisis periods. Journal of Econometrics, Volume 237, Issue 2, Part C, December 2023, 105370. https://doi.org/10.1016/j.jeconom.2022.11.004
2022
• Aastveit, K. A., J. L. Cross, and H. K. van Dijk (2023). Quantifying time-varying forecast uncertainty and risk for the real price of oil. Journal of Business & Economic Statistics 41 (2), 523–537.DOI: 10.1080/07350015.2022.2039159.
Key publications
Baştürk, N., Borowska, A., Grassi, S., Hoogerheide, L. and van Dijk, H.K. (2019). Forecast density combinations of dynamic models and data driven portfolio strategies Journal of Econometrics, 210(1):170--186.
Aastveit, K.A., Ravazzolo, F. and H.K. van Dijk (2018). Combined Density Nowcasting in an Uncertain Economic Environment Journal of Business and Economic Statistics, 36(1):131-145.
Francesco Ravazzolo (2016). Interconnections Between Eurozone and us Booms and Busts Using a Bayesian Panel Markov-Switching VAR Model Journal of Applied Econometrics.
Basturk, N., Cakmakli, C.(., Ceyhan, P. and van Dijk, H. (2014). Posterior-predictive evidence on US inflation using extended New Keynesian Phillips Curve models with non-filtered data Journal of Applied Econometrics, 29(7):1164--1182.
Bilio, M., Casarin, R., Ravazzolo, F. and van Dijk, H. (2013). Time-varying combinations of predictive densities using nonlinear filtering Journal of Econometrics, 177(2):213--232.
Strachan, R. and van Dijk, H. (2013). Evidence on features of a dsge business cycle model from bayesian model averaging International Economic Review, 54(1):385--402.
Timmerman, A. and van Dijk, H. (2013). Dynamic econometric modeling and forecasting in the presence of instability Journal of Econometrics, 177(2):131--133.
Hoogerheide, L., Opschoor, A. and van Dijk, H.K. (2012). A class of adaptive importance sampling weighted EM algorithms for efficient and robust posterior and predictive simulation Journal of Econometrics, 171(2):101--120.
Hoogerheide, L., Ravazzolo, F. and van Dijk, H. (2012). Forecast rationality tests based on multi-horizon bounds: Comment Journal of Business and Economic Statistics, 30(1):30--33.
Chesher, A., Dhaene, G.(. and van Dijk, H. (2007). Endogeneity, Instruments and Identification, Guest Editorial Journal of Econometrics, 139(1):1--3.
Harvey, A., Trimbur, T. and van Dijk, H. (2007). Trends and cycles in economic time series: a Bayesian approach Journal of Econometrics, 140(2):618--649.
Hoogerheide, L., Kleibergen, F. and van Dijk, H.K. (2007). Natural conjugate priors for the instrumental variables regression model applied to the Angrist-Krueger data Journal of Econometrics, 138(1):63--103.
Hoogerheide, L., Kaashoek, J. and van Dijk, H.K. (2007). On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: an application of flexible sampling methods using neural networks Journal of Econometrics, 139(1):154--180.
Kleijn, R. and van Dijk, H. (2006). Bayes model averaging of cyclical decompositions in economic time series Journal of Applied Econometrics, 21(2):191--212.
van Dijk, D., van Dijk, H. and Franses, P.H. (2005). On the dynamics of business cycle analysis; Editors' introduction Journal of Applied Econometrics, 20(2):147--150.
Bauwens, L., Lubrano, M. and van Dijk, H. (2004). Recent advances in Bayesian econometrics Journal of Econometrics, 123(2):197--199.
Bos, C., Bauwens, L., van Dijk, H.K. and van Oest, R.D. (2004). Adaptive Radial-based Direction Sampling: Some Flexible and Robust Monte Carlo Integration Methods Journal of Econometrics, 123(2):201--225.
Paap, R. and van Dijk, H. (2003). Bayes estimates of Markov trends in possibly cointegrated series: an application to U.S. consumption and income Journal of Business and Economic Statistics, 21(4):547--563.
Geweke, J., Rust, J. and van Dijk, H. (2000). Inference and decision making, Introduction Journal of Applied Econometrics, 6:545--546.
Koop, G. and van Dijk, H. (2000). Testing for integration using evolving trend and seasonals model: a Bayesian approach Journal of Econometrics, 97:261--291.
Bauwens, L., Polasek, W. and van Dijk, H. (1996). Bayes, Bernoullis and Basel, editors' introduction Journal of Econometrics, 75:1--5.
Hoek, H., Lucas, A.(. and van Dijk, H. (1995). Classical and Bayesian aspects of robust unit root inference Journal of Econometrics, 69:27--59.
Kiviet, J. and van Dijk, H. (1994). Structure and dynamics in econometrics, editor's introduction Journal of Econometrics, 63:1--5.
Kleibergen, F.(. and van Dijk, H. (1994). Direct cointegration testing in error-correction models Journal of Econometrics, 63:61--103.
Schotman, P. and van Dijk, H. (1991). On Bayesian routes to unit roots Journal of Applied Econometrics, 6:387--401.
Kooiman, P., van Dijk, H. and Thurik, R. (1985). Likelihood diagnostics and Bayesian analysis of a micro-economic disequilibrium model for retail services Journal of Econometrics, 29(1-2):121--148.
List of publications
Borowska, A., Hoogerheide, L., Koopman, S.J. and van Dijk, HermanK. (2020). Partially censored posterior for robust and efficient risk evaluation Journal of Econometrics, 217(2):335--355.
Baştürk, N., Borowska, A., Grassi, S., Hoogerheide, L. and van Dijk, H.K. (2019). Forecast density combinations of dynamic models and data driven portfolio strategies Journal of Econometrics, 210(1):170--186.
Aastveit, K.A., Ravazzolo, F. and H.K. van Dijk (2018). Combined Density Nowcasting in an Uncertain Economic Environment Journal of Business and Economic Statistics, 36(1):131-145.
Francesco Ravazzolo (2016). Interconnections Between Eurozone and us Booms and Busts Using a Bayesian Panel Markov-Switching VAR Model Journal of Applied Econometrics.
Basturk, N., Cakmakli, C.(., Ceyhan, P. and van Dijk, H. (2014). Posterior-predictive evidence on US inflation using extended New Keynesian Phillips Curve models with non-filtered data Journal of Applied Econometrics, 29(7):1164--1182.
Zellner, A., Ando, T., Basturk, N., Hoogerheide, L. and van Dijk, H.K. (2014). Bayesian Analysis of Instrumental Variable Models: Acceptance-Rejection within Direct Monte Carlo Econometric Reviews, 33(1-4):3--35.
Bilio, M., Casarin, R., Ravazzolo, F. and van Dijk, H. (2013). Time-varying combinations of predictive densities using nonlinear filtering Journal of Econometrics, 177(2):213--232.
Strachan, R. and van Dijk, H. (2013). Evidence on features of a dsge business cycle model from bayesian model averaging International Economic Review, 54(1):385--402.
Timmerman, A. and van Dijk, H. (2013). Dynamic econometric modeling and forecasting in the presence of instability Journal of Econometrics, 177(2):131--133.
Hoogerheide, L., Opschoor, A. and van Dijk, H.K. (2012). A class of adaptive importance sampling weighted EM algorithms for efficient and robust posterior and predictive simulation Journal of Econometrics, 171(2):101--120.
Hoogerheide, L., Ravazzolo, F. and van Dijk, H. (2012). Forecast rationality tests based on multi-horizon bounds: Comment Journal of Business and Economic Statistics, 30(1):30--33.
Hoogerheide, L. and van Dijk, H.K. (2010). Bayesian Forecasting of Value at Risk and Expected Shortfall using Adaptive Importance Sampling International Journal of Forecasting, 26(2):231--247.
Hoogerheide, L., Kleijn, R., Ravazzolo, F., van Dijk, H.K. and Verbeek, M. (2010). Forecast Accuracy and Economic Gains from Bayesian Model Averaging using Time Varying Weights Journal of Forecasting, 29:251--269.
Chesher, A., Dhaene, G.(. and van Dijk, H. (2007). Endogeneity, Instruments and Identification, Guest Editorial Journal of Econometrics, 139(1):1--3.
Harvey, A., Trimbur, T. and van Dijk, H. (2007). Trends and cycles in economic time series: a Bayesian approach Journal of Econometrics, 140(2):618--649.
Hoogerheide, L., Kleibergen, F. and van Dijk, H.K. (2007). Natural conjugate priors for the instrumental variables regression model applied to the Angrist-Krueger data Journal of Econometrics, 138(1):63--103.
Hoogerheide, L., Kaashoek, J. and van Dijk, H.K. (2007). On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: an application of flexible sampling methods using neural networks Journal of Econometrics, 139(1):154--180.
Koop, G. and van Dijk, H. (2007). Editors' introduction to the special issue of econometric reviews on Bayesian dynamic econometrics Econometric Reviews, 26(2-4):107--112.
Kleijn, R. and van Dijk, H. (2006). Bayes model averaging of cyclical decompositions in economic time series Journal of Applied Econometrics, 21(2):191--212.
van Dijk, D., van Dijk, H. and Franses, P.H. (2005). On the dynamics of business cycle analysis; Editors' introduction Journal of Applied Econometrics, 20(2):147--150.
Bauwens, L., Lubrano, M. and van Dijk, H. (2004). Recent advances in Bayesian econometrics Journal of Econometrics, 123(2):197--199.
Cornelisse, P., van Dijk, H. and Don, H. (2004). Economics with a purpose. (Tinbergen centennial issue) De Economist, 152(2):161--165.
Bos, C., Bauwens, L., van Dijk, H.K. and van Oest, R.D. (2004). Adaptive Radial-based Direction Sampling: Some Flexible and Robust Monte Carlo Integration Methods Journal of Econometrics, 123(2):201--225.
van Dijk, H. (2004). Twentieth century shocks, trends and cycles in industrialized nations De Economist, 152(2):211--232.
Haldrup, N., Hendry, D. and van Dijk, H. (2003). Introduction: Time series concepts for conditional distributions Oxford Bulletin of Economics and Statistics, 65(Supplement):681--688.
Paap, R. and van Dijk, H. (2003). Bayes estimates of Markov trends in possibly cointegrated series: an application to U.S. consumption and income Journal of Business and Economic Statistics, 21(4):547--563.
Strachan, R. and van Dijk, H. (2003). Bayesian model selection with an uninformative prior Oxford Bulletin of Economics and Statistics, 65(Supplement):863--876.
Kaashoek, J.(. and van Dijk, H. (2002). Neural network pruning applied to real exchange rate analysis Journal of Forecasting, 21:559--577.
Terui, N. and van Dijk, H. (2002). Combined forecasts from linear and nonlinear time series models International Journal of Forecasting, 18(3):421--438.
Geweke, J., Rust, J. and van Dijk, H. (2000). Inference and decision making, Introduction Journal of Applied Econometrics, 6:545--546.
Koop, G. and van Dijk, H. (2000). Testing for integration using evolving trend and seasonals model: a Bayesian approach Journal of Econometrics, 97:261--291.
van Dijk, H. (1999). Some remarks on the simulation revolution in Bayesian econometric inference Econometric Reviews, 18(1):105--112.
Kleibergen, F.(. and van Dijk, H. (1998). Bayesian simultaneous equations analysis using reduced rank structures Econometric Theory, 14:701--743.
Paap, R. and van Dijk, H. (1998). Distribution and mobility of wealth of nations European Economic Review, 42:1269--1293.
Bauwens, L., Polasek, W. and van Dijk, H. (1996). Bayes, Bernoullis and Basel, editors' introduction Journal of Econometrics, 75:1--5.
Hoek, H., Lucas, A.(. and van Dijk, H. (1995). Classical and Bayesian aspects of robust unit root inference Journal of Econometrics, 69:27--59.
Kaashoek, J.(. and van Dijk, H. (1994). A neural network applied to the calculation of Lyapunov exponents Econometric Reviews, 13(1):123--137.
Kaashoek, J.(. and van Dijk, H. (1994). Evaluation and application of numerical procedures to calculate Lyapunov exponents Econometric Reviews, 13:123--137.
Kiviet, J. and van Dijk, H. (1994). Structure and dynamics in econometrics, editor's introduction Journal of Econometrics, 63:1--5.
Kleibergen, F.(. and van Dijk, H. (1994). Direct cointegration testing in error-correction models Journal of Econometrics, 63:61--103.
Kleibergen, F.(. and van Dijk, H. (1994). On the shape of the likelihood/posterior of cointegration models Econometric Theory, 10:514--551.
Kleibergen, F.(. and van Dijk, H. (1994). On the shape of the likelihood/posterior in cointegration models Econometric Theory, 10:514--551.
Ooms, M.(. and van Dijk, H. (1994). Comment on estimating systems of trending variables: estimating pushing trends and pulling equilibra Econometric Reviews, 13(3):395--423.
Phillips, P. and van Dijk, H. (1994). Bayes methods and unit roots, editors' introduction Econometric Theory, 10:453--460.
Schotman, P. and van Dijk, H. (1991). On Bayesian routes to unit roots Journal of Applied Econometrics, 6:387--401.
Kooiman, P., van Dijk, H. and Thurik, R. (1985). Likelihood diagnostics and Bayesian analysis of a micro-economic disequilibrium model for retail services Journal of Econometrics, 29(1-2):121--148.