Prof. dr. Herman K. van Dijk



	S election of most cited papers Books All journal papers Reports of the Econometric Institute / Discussion papers of the Tinbergen Institute Selection of most cited papers Further experience in Bayesian analysis using Monte Carlo integration HK Van Dijk, T Kloek, Journal of Econometrics 14 (3), 307-328, 1980. Time-varying combinations of predictive densities using nonlinear filtering M Billio, R Casarin, F Ravazzolo, HK Van Dijk Journal of Econometrics, 2013, 177 (2), 213-232. Bayesian forecasting of value at risk and expected shortfall using adaptive importance sampling L Hoogerheide, HK van Dijk International Journal of Forecasting 2010, vol. 26 (2), 231-247. Experiments with some alternatives for simple importance sampling in Monte Carlo integration HK Van Dijk, T Kloek A class of adaptive importance sampling weighted EM algorithms for efficient and robust posterior and predictive simulation L Hoogerheide, A Opschoor, HK Van Dijk Journal of Econometrics Vol. 171, 2012, (2), 101-120. A comparative study of Monte Carlo methods for efficient evaluation of marginal likelihood D Ardia, N Baştürk, L Hoogerheide, HK Van Dijk Computational Statistics & Data Analysis Vol. 56 (11), 2012, 3398-3414. Trends and cycles in economic time series: A Bayesian approach AC Harvey, TM Trimbur, HK Van Dijk Journal of Econometrics 140 (2), 618-649, 2007 download PDF Experiments with some alternatives for simple importance sampling in Monte Carlo integration HK Van Dijk, T Kloek Erasmus University, 1983 Bayes estimates of Markov trends in possibly cointegrated series R Paap, HK Van Dijk Journal of Business and Economic Statistics 21 (4), 547-563, 2003 download PDF Classical and Bayesian aspects of robust unit root inference H Hoek, A Lucas, HK Van Dijk Journal of Econometrics 69 (1), 27-59, 1995 download PDF Daily exchange rate behaviour and hedging of currency risk CS Bos, RJ Mahieu, HK Van Dijk Journal of Applied Econometrics 15 (6), 671-696, 2000 download PDF Natural conjugate priors for the instrumental variables regression model applied to the Angrist-Krueger data L Hoogerheide, F Kleibergen, HK Van Dijk Journal of Econometrics 138 (1), 63-103, 2007 download PDF Neural network pruning applied to real exchange rate analysis JF Kaashoek, HK Van Dijk Journal of Forecasting 21 (8), 559-5772, 2002 download PDF Direct cointegration testing in error correction models F Kleibergen, HK Van Dijk Journal of Econometrics 63 (1), 61-1032, 1994 download PDF Bayesian limited information analysis revisited L Bauwens, HK van Dijk In: JJ Gabszewicz, JF Richard and LA Wolsey (Eds), Economic Decision Making: Games, Econometrics and Optimisation. North-Holland, 1990 (pp 385-424) download PDF Posterior moments computed by mixed integration HK Van Dijk, T Kloek, CGE Boender Journal of Econometrics 29 (1-2), 3-18, 1985 download PDF back to top Books J.F. Geweke, G. Koop, and Van Dijk HK, eds., The Oxford Handbook of Bayesian Econometrics, Oxford University Press, 2011, translated in Japanese in 2012 C. Heij, P.M.C. de Boer, P.H. Franses, T. Kloek and Van Dijk HK, 2004, Econometric Methods with Applications in Business and Economics, Solution Manual, Oxford University Press, Oxford, 358 pages C. Heij, P.M.C. de Boer, P.H. Franses, T. Kloek and Van Dijk HK, 2004, Econometric Methods with Applications in Business and Economics, Oxford University Press, Oxford, 787 pages Van Dijk HK, A. Monfort, and B.W. Brown, eds., 1995, Econometric Inference using Simulation Techniques, J. Wiley, New York , 265 pages Van Dijk HK, R. Harkema, P. Kooiman, and P. Schotman, red., 1996, Kritisch en constructief, 40 jaar grensverkenningen in de econometrie, Liber Amicorum voor prof. dr. T. Kloek, Ridderkerk (Festschrift for T.Kloek) Van Dijk HK, 1984, Posterior Analysis of Econometric Models using Monte Carlo Integration, 207 pages, Rotterdam, Erasmus University Press back to top All journal papers 2020 Agnieszka Borowska, Lennart Hoogerheide, Siem Jan Koopman and Herman K. van Dijk, Partially Censored Posterior for Robust and Efficient Risk Evaluation, Journal of Econometrics. Volume 217, Issue 2, August 2020, Pages 335 - 355. https://www.sciencedirect.com/science/article/abs/pii/S0304407 2019 Sylvia Kaufmann, Sylvia Frühwirth-Schnatter, Herman K. van Dijk, Editorial introduction on complexity and big data in economics and finance: Recent developments from a Bayesian perspective, Journal of Econometrics, 2019, Vol. 210, Issue 1, 1-3. N. Baştürk, A. Borowska, S. Grassi, L. Hoogerheide, H.K. van Dijk, Forecast density combinations of dynamic models and data driven portfolio strategies, Journal of Econometrics, 2019, Vol. 210, Issue 1, 170-186. Knut Are Aastveit, James Mitchell, Francesco Ravazzolo, and Herman K. van Dijk, The Evolution of Forecast Density Combinations in Economics, Oxford Research Encyclopedia of Economics and Finance, 2019. https://oxfordre.com/economics/view/10.1093/acrefore/9780190625979.001.0001/acrefore-9780190625979-e-381?rskey=ZdTXfP&result=1 2018 Knut Are Aastvelt, Norges Bank, Francesco Ravazzolo, Norges Bank, and Herman K. van Dijk, 2018, Nowcasting the Business Cycle in an Uncertain Economic Environment, Journal of Business & Economic Statistics, Vol. 36, Issue 1, 131-145. https://doi.org/10.1080/07350015.2015.1137760. 2017 Nalan Basturk, Maastricht University , the Netherlands; Stefano Grassi, University of Kent, United Kingdom; Lennart Hoogerheide, VU University Amsterdam, the Netherlands; Anne Opschoor, VU University Amsterdam, the Netherlands; Herman K. van Dijk, VU University Amsterdam, Erasmus University Rotterdam, the Netherlands, The R Package MitISEM: Mixture of Student-t Distributions using Importance Sampling Weighted Expectation Maximization for Efficient and Robust Simulation, Journal of Statistical Software, 2017, Vol. 79, 1, 1- 40. https://www.jstatsoft.org/issue/view/v079. Nalan Basturk, Maastricht University, The Netherlands; Lennart Hoogerheide, VU Amsterdam and Tinbergen Institute, The Netherlands; Herman K. van Dijk, Erasmus University and Tinbergen Institute, The Netherlands and Norges Bank, Norway, Bayesian Analysis of Boundary and Near-Boundary Evidence in Econometric Models with Reduced Rank, Bayesian Analysis, Volume 12, Number 3 (2017), 879-917, https://projecteuclid.org/euclid.ba/1501120970. 2016 Christine DeMol, Eric Gautier, Domenico Giannone, Sendhil Mullainathan, Lucrezia Reichlin, Herman K Van Dijk, Jeffrey Wooldridge, 2016, Methods in Big Data Analysis, in Estelle Cantillon, Christine DeMol, Bram De Rock, Domenico Giannone, Georg Kirchsteiger, Laszlo Matyas, eds., Developments in Data and Methods for Economic Research, Cambridge University Press, Cambridge, UK. Monica Billio, University of Venice, Gretta Assoc. and School for Advanced Studies in Venice; Roberto Casarin, University of Venice, Gretta Assoc. and School for Advanced Studies In Venice; Francesco Ravazzolo, Norges Bank; Herman K. van Dijk, Erasmus University Rotterdam, VU University Amsterdam, 2016, Interactions between Eurozone and US Booms and Busts, A Bayesian Panel Markov-Switching VAR model, Journal of Applied Econometrics, http://onlinelibrary.wiley.com/doi/10.1002/jae.2501/pdf and online appendix: (http://onlinelibrary.wiley.com/doi/10.1002/jae.2501/suppinfo). Lukasz Gatarek, Erasmus University Rotterdam, Lennart Hoogerheide, VU University Amsterdam, Herman K. van Dijk, Erasmus University Rotterdam and VU University Amsterdam, Return and Risk of Pairs Trading using a Simulation-based Bayesian Procedure for Predicting Stable Ratios of Stock Prices, in Econometrics 2016, 4(1), 14; doi:10.3390/econometrics4010014. Nalan Basturk, Maastricht University, the Netherlands; Stefano Grassi, University of Kent, United Kingdom; Lennart Hoogerheide, VU University Amsterdam, the Netherlands; Herman K. van Dijk, VU University Amsterdam, Erasmus University Rotterdam, the Netherlands, 2016, Parallelization Experience with Four Canonical Econometric Models using ParMitISEM , in Econometrics 2016, 4(1), 11; doi:10.3390/econometrics4010011. Nalan Basturk, Maastricht University, the Netherlands; Roberto Casarin, University of Venice, Gretta Assoc. and School for AdvancedStudies In Venice; Francesco Ravazzolo, Norges Bank; Herman K. van Dijk, VU University Amsterdam, Erasmus University Rotterdam, the Netherlands, 2016, Computational Complexity and Parallelization in Bayesian Econometric Analysis, Econometrics 2016, 4(1), 9; doi:10.3390/econometrics4010009. 2015 Roberto Casarin, , University Ca' Foscari of Venice and GRETA; Stefano Grassi, Kent University; Francesco Ravazzolo, University of Bolzano; Herman K. van Dijk, Erasmus University Rotterdam, and VU University Amsterdam, 2015, Parallel Sequential Monte Carlo for Efficient Density Combination, The Deco Matlab Tool box, Journal of Statistical Software, Vol. 68, http://www.jstatsoft.org/article/view/v068i03. 2014 Arnold Zellner (posthumously), University of Chicago, USA; Tomohiro Ando, Keio University, Japan; Nalan Basturk, Erasmus University Rotterdam; Lennart Hoogerheide, VU University Amsterdam; Herman K. van Dijk, Erasmus University Rotterdam and VU University Amsterdam, 2014, Bayesian Analysis of Instrumental Variables Models: Acceptance-Rejection within Direct Monte Carlo, Econometric Reviews, 33:3-35. Nalan Basturk, Erasmus University Rotterdam; Cem Cakmakli, University of Amsterdam; Pinar Ceyhan, Erasmus University Rotterdam; Herman K. van Dijk, Erasmus University Rotterdam, and VU University Amsterdam, 2014, Posterior-Predictive Evidence on US Inflation using Extended New Keynesian Phillips Curve Models with Non-filtered Data, Journal of Applied Econometrics, vol. 29 (7), 1164-1181, http://onlinelibrary.wiley.com/doi/10.1002/jae.2411/abstract Nalan Basturk, Erasmus University Rotterdam; Cem Cakmakli, University of Amsterdam; S. Pinar Ceyhan, Erasmus University Rotterdam; Herman K. van Dijk, Erasmus University Rotterdam and VU University Amsterdam, 2014, On the rise of Bayesian Econometrics after Cowles Foundation Monographs 10,14, invited paper, Oeconomia, 4 (3), 381- 447, http://oeconomia.revues.org/913. Rodney W. Strachan, Australian National University, Australia; Herman K. van Dijk, Erasmus University Rotterdam, the Netherlands, 2014, Divergent Priors and well Behaved Bayes Factors, Central European Journal of Economic Modeling and Econometrics, Vol. 6:1-31. Fabio Canova, EUI, Frank Schorfheide, University of Pennsylvania, Herman K. van Dijk, Erasmus University Rotterdam and VU University Amsterdam, 2014, Introduction to recent advances in methods and applications of DSGE models, Journal of Applied Econometrics, vol. 29 (7), 1029-1030. 2013 Monica Billio, University of Venice, Gretta Assoc. and School for Advanced Studies in Venice; Roberto Casarin, University of Venice, Gretta Assoc. and School for Advanced Studies in Venice; Francesco Ravazzolo, Norges Bank; Herman K. van Dijk, Erasmus University Rotterdam, VU University Amsterdam, 2013, Time-varying combinations of predictive densities using nonlinear filtering, Journal of Econometrics, 177 (2), 213-232. Allan Timmermann University of California at San Diego and Herman K. van Dijk, Erasmus University Rotterdam, VU University Amsterdam, (2013), Dynamic Econometric Modeling and Forecasting in the presence of instability, Journal of Econometrics, 177 (2),1-3. Herman K. van Dijk, 2013, The Keynes-Tinbergen Debate on the Relevance of Estimating Econometric Models, TSEconomist, Issue 4, November 2013, 8-10. Herman K. van Dijk, 2013, Bridging Two Key Issues in Bayesian Inference: The relationship between the Lindley Paradox and Non-elliptical Credible Sets, in Nozer Singpurwalla, Philip Dawid, Tony O’Hagan and Peter Freeman, eds: A Book for Dennis, Festschrift for professor Dennis Lindley’s ninetieth-birthday, Burr online publisher, 4 pages. Strachan, RW, Van Dijk HK (2013) “Evidence on Features of a DSGE Business Cycle model from Bayesian Model Averaging”, The International Economic Review Volume 54, Number 1, 385-402. Schaap M, Lemmers RJLF, Maassen R, Van der Vliet PJ, Hoogerhide LF, Van Dijk HK, Bastürk N, De Knijff P and Van der Maarel SM, 2013,Genome-wide analysis of macrosatellite repeat copy number variation in worldwide populations: evidence for differences and commonalities in size distributions and size restrictions, BMC Genomics, 14:143 doi:10.1186/1471-2164-14-143 2012 Hoogerhide L, VU University Amsterdam; Opschoor A, Erasmus University Amsterdam; Van Dijk HK, Erasmus University Rotterdam, and VU University Amsterdam, 2012, A Class of Adaptive Importance Sampling Weighted EM Algorithms for Efficient and Robust Posterior and Predictive Simulation, Journal of Econometrics, Vol. 171 (2) 101–120 http://dx.doi:10.1016/j.jeconom. 2012.06.011 Billio M, University of Venice, Gretta Assoc. and School for Advanced Studies In Venice; Casarin R, University of Venice, Gretta Assoc. and School for Advanced Studies In Venice; Ravazzolo F, Norges Bank; Van Dijk HK, Erasmus University Rotterdam, VU University Amsterdam, Combination Schemes for Turning Point Predictions , 2012, The Quarterly Review of Economics and Finance , Vol. 52 (4), 402–412., http://www.sciencedirect.com/science/journal/10629769/52/4 Belsley, D.A., Kontoghiorghes, E.J., Van Dijk, H.K., Bauwens, L., Belsley, D.A., Kontoghiorghes, E.J., Koopman, S.J., McAleer, M., van Dijk, H.K., Amendola, A., Billio, M., Croux, C., Chen, C.W.S., Davidson, R., Duchesne, P., Foschi, P., Francq, C., Fuertes, A.-M., Koop, G., Khalaf, L., Paolella, M., Pollock, D.S.G., Ruiz, E., Paap, R., Proietti, T., Winker, P., Yu, P.L.H., Zakoian, J.-M., Zeileis, A., The Annals of Computational and Financial Econometrics 1st issue. Computational Statistics and Data Analysis (2012), doi:10.1016/j.csda.2012.04.004, 2991-2993 Belsley, D.A., Chen, C.W.S., Francq, C., Gallo, G., Khalaf, L., Kontoghiorghes, E.J., and Van Dijk, H.K. Introduction to the Sixth Special Issue on Computational Econometrics, Computational Statistics and Data Analysis, 56, 11, 2012, 3307-3309 Ardia, D., Basturk, N., Hoogerheide, L.F., Van Dijk, H.K., “ A Comparative Study of Monte Carlo Methods for Efficient Evaluation of Marginal Likelihoods”, Computational Statistics and Data Analysis 56, 3398-3415. Lennart F. Hoogerheide, VU University Amsterdam; Francesco Ravazzolo, Norges Bank; Herman K. van Dijk, Erasmus University Rotterdam, VU University Amsterdam., Backtesting Value-at-Risk using Forecasts for Multiple Horizons, a Comment on the Forecast Rationality Tests of A.J. Patton and A. Timmermann, appeared as : Comment in Journal of Business and Economic Statistics, 2012, 30 (1), 30-33. Herman K. van Dijk, Erasmus University Rotterdam and VU University Amsterdam, Some reflections at the Occasion of the Nobel Prize 2011, MET Journal, 2012, 18 (3), pp.2-3 Billio M, University of Venice, GRETA Assoc. and School for Advanced Studies in Venice; Roberto Casarin, University of Venice, GRETA Assoc. and School for Advanced Studies in Venice; Francesco Ravazzolo, Norges Bank; Herman K. van Dijk, Erasmus University Rotterdam, Bayesian Combinations of Stock Price Predictions with an Application to the Amsterdam Exchange Index, MET Journal, 2012, 18 (4), 1-9. 2011 Geweke, J.F., Koop, G., and Van Dijk HK, Introduction, Handbook of Bayesian Econometrics, Oxford University Press, 2011, 8 pages, 2010 David A. Belsley, Pierre Duchesne, George , Erricos John Kontoghiorghes, Marc Paolella, Herman K. van Dijk, editors, ‘Editorial for the Fifth Special Issue on Computational and Financial Econometrics, Computational Statistics and Data Analysis, 2 pages, 2010 Hoogerheide, L.F., Kleijn, R., Ravazzolo, F., Van Dijk, H.K, Verbeek, M. , “Forecast Accuracy and Economic Gains from Bayesian Model Averaging using Time Varying Weights”, Journal of Forecasting, 29, 251-269. Hoogerheide, L.F., Van Dijk, H.K., “Bayesian Forecasting of Value at Risk and Expected Shortfall using Adaptive Importance Sampling”, International Journal of Forecasting, 26(2), 231-247.. Hoogerheide, L.F., Van Dijk, H.K. “Simulation based Bayes Procedures for Model Structures with Non-Elliptical Posteriors”, Lexicon for Statistical Science, p. 1-2, Springer Verlag, 2010 Ardia, D., Hoogerheide, L.F., Van Dijk, H.K. ,“AdMit: Adaptive Mixtures of Student-t Distributions. The R Journal, 1(1), 25-30 Ardia, D., Hoogerheide, L.F., Van Dijk, H.K. “Adaptive mixture of Student-t distributions as a flexible candidate distribution for efficient simulation: the R package AdMit”, Journal of Statistical Software , 29(3), 1-32. Hoogerheide, L.F., Van Dijk, H.K., Van Oest, R.D. “Simulation based Bayesian econometric inference: principles and some recent computational advances”, Chapter 7 in Handbook of Computational Econometrics, J. Wiley & Sons, 215-280. Belsley, D.A., Davidson, R., Kontoghiorghes, E.J., MacKinnon, J.G., Van Dijk H.K. “Editorial of the fourth special issue on Computational Econometrics”, Computational Statistics and Data Analysis 53, 1923-1924. 2008 Peter A. Cornelisse & Herman K. van Dijk (2008). Tinbergen, Jan (1903-1994), The New Palgrave Dictionary of Economics 2, 1709-1719 Alessandra Amendola, David Belsley, Erricos Kontoghiorghes, Yasuhiro Omori, Herman K. van Dijk, and Eric Zivot, 2008, Introduction to Statistical & Computational Methods in Finance, Computational Statistics and Data Analysis, 2008, 1-5. R. Paap and Van Dijk HK, 2009, Distribution and mobility of wealth of nations, in Duangkamon Chotikapanich ed., Essays in Memory of Camilo Dagum, Springer Verlag, Ch. 5. 27 pages De Pooter, M., Ravazzolo, F., Segers, R., Van Dijk, H.K. (2008), Bayesian Near-Boundary Analysis in Basic Economic Time Series Models, in S. Chib, G. Koop, W. Griffiths and D. Terrell, eds., Advances in Econometrics, (Bayesian econometrics) 23, Emerald Group Publishing Limited, 331-402. Van Dijk HK, Why earn more than the prime minister? Tinbergen Magazine, December 2008 Van Dijk HK, De Balkenende norm faalt, ESB, 19 december 2008 (in Dutch) 2007 J.F. Geweke, P.J.F. Groenen, R. Paap and Van Dijk HK, Editorial: Computational techniques for applied econometric analysis of macroeconomic and financial processes, in: Computational Statistics & Data Analysis 51, 3506-3508 Philip Hans Franses and Herman K. van Dijk, Progress and Challenges in Econometrics, Guest Editorial, Journal of Econometrics, 138(1), 1-2 Lennart Hoogerheide, Frank Kleibergen and Herman K. van Dijk, Natural Conjugate priors for the instrumental variables regression model applied to the Angrist-Krueger data, Journal of Econometrics, 138(1), 63-103 Lennart F. Hoogerheide & Herman K. van Dijk, Note on neural network sampling for Bayesian inference of mixture processes, Bulletin of the International Statistical Institute, 8 pages Lennart F. Hoogerheide, Johan F. Kaashoek & Herman K. van Dijk, 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 Gary Koop and Herman K. van Dijk, Bayesian Dynamic Econometrics, Editor’s Introduction, Econometric Reviews, 26(2-3), 1-6 Andrew C. Harvey, Thomas M. Trimbur and Herman K. van Dijk, Trends and cycles in economic time series: A Bayesian approach, Journal of Econometrics, 140, 618-649 Andrew C. Harvey, Thomas M. Trimbur and Herman K. van Dijk, Bayes estimates of the cyclical component in twentieth century US gross domestic product, in: Growth and Cycle in the Eurozone, (eds. Gian Luigi Mazzi and Giovanni Savio), Palgrave MacMillan, New York, 76-89 Andrew Chesher, Geert Dhaene and Herman K. van Dijk, Endogeneity, Instruments and Identification, Guest Editorial, Journal of Econometrics, 139(1), 1-3. 2006 R.H. Kleijn and Van Dijk HK, Bayes model averaging of cyclical decomposition within economic time series, Journal of Applied Econometrics, 21: 191-212 Herman K. van Dijk, J. F. Kaashoek and Albert P.M. Wagelmans, ”Rotterdam econometrics”: An analysis of publications of the Econometric Institute 1956-2004, Statistica Neerlandica, 60(2), 85-111 Gary Koop, Rodney Strachan, Herman K. van Dijk & Mattias Villani, Bayesian approaches to cointegration, Chapter 25 in: T.C. Mills and K.P. Patterson, eds., Palgrave Handbook of Econometrics, 1: 871-898 2005 D.J.C van Dijk, Van Dijk HK and P.H.B.F. Franses, Editor’s Introduction to: Recent Developments in Business Cycle Analysis, Journal of Applied Econometrics, 20: 147-150. 2004 L. Bauwens, C.S. Bos, Van Dijk HK and R.D. van Oest, Adaptive radial-based direction sampling - Some flexible and robust Monte Carlo integration methods, Journal of Econometrics 123, 201-225 L. Bauwens, M. Lubrano and Van Dijk HK, Editor’s introduction to recent advances in Bayesian econometrics, Journal of Econometrics, 197-199 P.C. Cornelisse, H. Don and Van Dijk HK, Introduction to the Tinbergen Centennial Issue, De Economist, 161-165 Van Dijk HK, Twentieth Century Shocks, Trends and Cycles in Industrialized Nations, De Economist, 211-232 2003 Johan F. Kaashoek and Van Dijk HK, Neural networks as econometric tool, chapter 12, 351-385, in D. Giles, ed, Computer Aided Econometrics, Marcel Dekker, New York, 2003 Van Dijk HK, On Bayesian structural inference in a simultaneous equation model, chapter 25, 642-683, in B. Stigum, ed., Econometrics and the Philosophy of Economics, Princeton University Press, 2003 Van Dijk HK, On shocks, trends and cycles in industrialized countries in the Twentieth Century, Tinbergen Magazine, 2003, 7, 12-15 R. Paap and Van Dijk HK, Bayes estimates of Markov trends in possibly cointegrated series: an application to US consumption and income, Journal of Business & Economic Statistics, 21, 547-563. R.W. Strachan and Van Dijk HK, Bayesian model selection for a sharp null and a diffuse alternative with econometric applications, Oxford Bulletin of Economics and Statistics, 2003, 65 (supplement), 863-876 N. Haldrup, D.F. Hendry and Van Dijk HK, Guest editors introduction: Model Selection and Evaluation in Econometrics, Oxford Bulletin of Economics and Statistics, 2003, 65 (supplement), 681-688 L.F. Hoogerheide, J.F. Kaashoek and Van Dijk HK, Neural network approximations to posterior densities: An analytical approach, American Statistical Association 2003, Proceedings of the Section on Bayesian Statistical Science, 5 pages L. Bauwens, C.S. Bos, Van Dijk HK and R.D. van Oest, Explaining adaptive radialbased direction sampling, American Statistical Association 2003, Proceedings of the Section on Bayesian Statistical Science, 5 pages A.C. Harvey, Th.M. Trimbur and Van Dijk HK, Bayes estimates of the cyclical component in twentieth century US gross domestic product, Proceedings of the 4th Eurostat and DGECFIN Colloquium on Modern Tools for Business Cycle Analysis, Eurostat, 2003, 14 pages Kaashoek, J.F. and Van Dijk HK, Long term values of euro/dollar and European exchange rates: A neural network analysis, Medium Econometrische Toepassingen, 10(4), 26-29 2002 N. Terui, and Herman K. van Dijk, Combined forecasts from linear and nonlinear time series models, International Journal of Forecasting, 18(3), 421-438 J.F. Kaashoek and Van Dijk HK, Neural network analysis of varying trends in real exchange rates, Journal of Forecasting, 2002, 21, 559-577 2001 C.S. Bos, R.J. Mahieu and Van Dijk HK, On the variation of hedging decisions in daily currency risk management, in: I. Edward George ed., 2001, Bayesian methods with applications to science, policy and official statistics, Eurostat, 31-40 2000 G. Koop, and Van Dijk HK, Testing for integration using evolving trend and seasonal models: A Bayesian Approach, Journal of Econometrics 97(2), 261-291 Van Dijk HK, Comment on: Time series analysis of non-Gaussian observations based on state space models from both classical and Bayesian perspectives, by J. Durbin and S. Koopman, Journal of the Royal Statistical Society Series B, 62, 42 L. Bauwens, C.S. Bos and Van Dijk HK, Adaptive polar sampling: a new MCMC method for ill-behaved posterior surfaces, in W. Jansen and J.G. Bethlehem eds., Compstat 2000, Statistics Netherlands, 13-14 C.S. Bos, R.J. Mahieu and Van Dijk HK, Daily exchange rate behaviour and hedging of currency risk, Journal of Applied Econometrics, 15(6), 671-696 John Geweke, John Rust, Herman K. Van Dijk, Introduction: Inference and Decision making, Journal of Applied Econometrics, 15(6), 545-546 1999 Van Dijk HK, Some Remarks on the simulation revolution in Bayesian econometric inference, Econometric Reviews, 18(1), 105-112 F.R. Kleibergen, Van Dijk HK and J.P. Urbain, A cointegration study of aggregate imports using likelihood based testing principles, Annals of the Institute of Statistical Mathematics, 51(3), 399-417. R. Paap, and Van Dijk HK, Posterior evidence on the permanent income hypothesis, EU & US Inflation and Macroeconomic Analysis Bulletin, 58, July 1999 1998 R. Paap and Van Dijk HK, Distribution and mobility of wealth of nations, European Economic Review 42, 1269-1293. F.R. Kleibergen, Van Dijk HK, Bayesian simultaneous equations analysis using reduced rank structures, Econometric Theory 14, 701-743 1996 G. Koop, and Van Dijk HK, Testing for integration using evolving trend models, in: American Statistical Association 1996 Proceedings of the Section on Bayesian Statistical Science, 232-237 1996 L. Bauwens, W. Polasek, and H. K. van Dijk, Bayes, Bernoullis, and Basel, Editor’s introduction, Journal of Econometrics 75(1), 1-5 Van Dijk HK, De econometrie van simultane modellen, 1956-1997 (in Dutch) in Van Dijk HK et al, Kritisch en constructief, 40 jaar grensverkenningen in de econometrie, Liber Amicorum voor prof. dr. T. Kloek, Ridderkerk (Festschrift for T. Kloek) 1995 A. Monfort and Van Dijk HK, Simulation based econometrics, in: Van Dijk HK, Monfort and B.W. Brown, eds., 1995, Econometric Inference using Simulation Techniques (Wiley, New York), 1-20 H. Hoek, A. Lucas and Van Dijk HK, Classical and Bayesian aspects of robust unit root Inference, Journal of Econometrics 69, 27-59 1994 F.R. Kleibergen and Van Dijk HK, On the shape of the likelihood/posterior of cointegration models, Econometric Theory 10, 514-551 J.F. Kaashoek and Van Dijk HK, A neural network applied to the calculation of Lyapunov exponents, Econometric Reviews, 13(1), 123-137 M. Ooms and Van Dijk HK, Comment on ’Estimating systems of trending variables’, estimating pushing trends and pulling equilibria, Econometric Reviews 13(3), 395-422 F.R. Kleibergen and Van Dijk HK, Direct cointegration testing in error-correction models, Journal of Econometrics 63, 61-103 J.F. Kiviet and Van Dijk HK, Structure and dynamics in Econometrics, Editor’s Introduction, Journal of Econometrics 63, 1-5 P.C.B. Phillips and Van Dijk HK, Bayes methods and unit roots, Editor’s Introduction, Econometric Theory 10, 453-460 Van Dijk HK, Dynamiek in de Econometrie, (Dynamics In Econometrics, Inaugural Lecture), 1994, 26 pages 1993 P. Schotman and Van Dijk HK, Posterior analysis of possibly integrated time series with an application to real GNP, in: P. Caines, J. Geweke and M. Taqqu., eds., New Directions in Time Series Analysis part II, IMA Volumes in Mathematics and its Applications 46, Springer Verlag, Heidelberg, 341-361 C.G.E. Boender and Van Dijk HK, Bayes estimates of multi-criteria decision alternatives using Monte Carlo integration, Statistica Neerlandica, 47, 2, 127-151 F.R. Kleibergen and Van Dijk HK, Efficient computer generation of matric-variatet drawings with an application to Bayesian estimation of simple market models, in: W. Hardle and L. Simar, eds., Statistics & Computing: Computer Intensive Methods in Statistics, Springer Verlag, 1993, 30-46 F.R. Kleibergen and Van Dijk HK, Non-stationarity in GARCH models: A Bayesian analysis, Journal of Applied Econometrics, vol. 8, S41-S61 B.W. Brown, A. Monfort, Van Dijk HK, Introduction to econometric inference using simulation techniques, Journal of Applied Econometrics, vol. 8, S1-S3 1992 J.P. Hop and Van Dijk HK, SISAM and MIXIN, Two algorithms for the evaluation of posterior moments and densities using Monte Carlo integration, Computer Science in Economics and Management, (now Computational Economics) vol. 5, 183-220; reprinted in Bulletin of the International Statistical Institute, Cairo, vol. LIV, book 3, 29 pages 1991 P. Schotman and Van Dijk HK, A Bayesian analysis of the unit root in real exchange rates, Journal of Econometrics 49, 195-238 Van Dijk HK, Comment on G.E. Mizon, Modelling relative price variability and aggregate inflation in the United Kingdom, Scandinavian Journal of Economics, 93, 213-217. Reprinted in: S. Hylleberg and M. Paldam, eds., New approaches to empirical macroeconomics, Basil Blackwell, 85-89. J.F. Kaashoek and Van Dijk HK, A note on the detection of chaos in medium sized time series, in: R. Seydel, F.W. Schneider, T. Kupper, H. Troger, eds., Bifurcation and Chaos: Analysis, Algorithms, Applications, International Series of Numerical Mathematics 97, Basel: Birkhauser, 162-166 P. Schotman and Van Dijk HK, On Bayesian routes to unit roots, Journal of Applied Econometrics, 6, 387-401 1990 L. Bauwens and Van Dijk HK, Bayesian limited information analysis revisited, in: J. Gabszewicz, J.F. Richard and L. Wolsey, eds., Economic decision-making: Games, Econometrics, and Decision-making, Contributions in honour of Jacques Dreze, North-Holland, Amsterdam, 385-424 1988 A. Zellner, L. Bauwens and Van Dijk HK, Bayesian specification analysis and estimation of simultaneous equation models using Monte Carlo methods, Journal of Econometrics, 38, 39-72 1987 Van Dijk HK, J.P. Hop and A.S. Louter, An algorithm for the computation of posterior moments and densities using simple importance sampling, The Statistician 36, 83-90 Van Dijk HK, A product of multivariate t densities as upper bound for the posterior kernel of simultaneous equation model parameters, in: R. Viertl, ed., Probability and Bayesian Statistics (Plenum, New York), 129-138 Van Dijk HK, Some advances in Bayesian analysis using Monte Carlo integration, in: T.B. Fomby and C. Rhodes, eds., Advances in Econometrics, Vol 6, JAI Press, 215-261 Van Dijk HK, Comment on Computation in Bayesian statistics, in J.M. Bernardo, M.H. de Groot, D.V. Lindley and R.F.M. Smith, Bayesian Statistics 3, North Holland, Amsterdam, 435 1986 Van Dijk HK and T. Kloek, Posterior moments of the Klein-Goldberger Model, in: P.K. Goel and A. Zellner, eds., Bayesian inference and decision techniques with application: Essays in honor of Bruno de Finetti, (North-Holland, Amsterdam), 95-108 1985 Van Dijk HK and T. Kloek, Experiments with some alternatives for simple importance sampling in Monte Carlo integration (with discussion), in: J.M. Bernardo, M.H. DeGroot, D.V. Lindley and A.F.M. Smith, eds., Bayesian Statistics 2, (North Holland, Amsterdam), 511-530 Van Dijk HK, Editor’s Introduction to Bayesian analysis of some econometric and statistical models, Journal of Econometrics 29, 1-2 Van Dijk HK, T. Kloek, and G. Boender, Posterior moments computed by mixed integration, Journal of Econometrics 29, 3-18 P. Kooiman, Van Dijk HK, and A.R. Thurik, Likelihood diagnostics and Bayesian analysis of a micro-economic disequilibrium model for retail services, Journal of Econometrics 29, 212-248 download PDF 1983 Van Dijk HK and T. Kloek, Monte Carlo analysis of skew posterior distributions: An econometric example, The Statistician 32, 216-223 download PDF Van Dijk HK, Bayesian estimation methods and Bayesian statistics, in: Encyclopedia of Business Economics (in Dutch), Kluwer, Deventer 1980 Van Dijk HK and T. Kloek, Further experience in Bayesian analysis using Monte Carlo integration, Journal of Econometrics 14, 307-328 Van Dijk HK and T. Kloek, Inferential procedures in stable distributions for class frequency data on incomes, Econometrica 48, 1139-1148 download PDF 1978 T. Kloek and Van Dijk HK, Bayesian estimates of equation system parameters, An application of integration by Monte Carlo, Econometrica 46, 1-19. Reprinted in: A. Zellner ed., 1980, Bayesian analysis in econometrics and statistics, Essays in honor of Harold Jeffreys (North Holland, Amsterdam), 311-329 T. Kloek and Van Dijk HK, Efficient estimation of income distribution parameters, Journal of Econometrics 8, 61-74. Van Dijk HK and T. Kloek, Posterior analysis of Klein’s Model I, Szigma, Hungarian Journal of Mathematical Economics, 121-143 1977 Van Dijk HK and T. Kloek, Predictive moments of simultaneous econometric models, A Bayesian Approach, in: A. Aykac and C. Brumat, eds., New developments in the applications of Bayesian methods, (North-Holland, Amsterdam), 243-260 T. Kloek and Van Dijk HK, Further results on efficient estimation of income distribution parameters, Economie Applique 30, 439-459 back to top Reports of the Econometric Institute / Discussion papers of the Tinbergen Institute 2019 Agnieszka Borowska, Vrije Universiteit Amsterdam & University of Glasgow; Lennart Hoogerheide, Vrije Universiteit Amsterdam; Siem Jan Koopman, Vrije Universiteit Amsterdam & CREATES, Aarhus University; Herman K. van Dijk, Erasmus University Rotterdam & Norges Bank, Partially Censored Posterior for Robust and Efficient Risk Evaluation, Tinbergen DP https://www.tinbergen.nl/discussion-paper/2898/0000 Roberto Casarin, University Ca' Foscari of Venice; Stefano Grassi , University of Rome `Tor Vergata'; Francesco Ravazzollo , BI Norwegian Business School; Herman K. van Dijk , Erasmus University Rotterdam , Forecast Density Combinations with Dynamic Learning for Large Data Sets in Economics and Finance, Tinbergen DP https://www.tinbergen.nl/discussion-paper/2866/19-025 2018 Lennart (L.F.) Hoogerheide, VU University Amsterdam; Herman (H.K.) van Dijk, Erasmus University, Norges Bank, Learning to Average Predictively over Good and Bad: Comment on: Using Stacking to Average Bayesian Predictive Distributions, Tinbergen DP, https://www.tinbergen.nl/discussion-paper/1675/18-06 Knut Are Aastveit, Norges Bank; James Mitchell, Warwick Business School; Francesco Ravazzolo, Free University of Bozen/Bolzano; Herman van Dijk, Erasmus University,Norges Bank,The Evolution of Forecast Density Combinations in Economics, Tinbergen DP, https://www.tinbergen.nl/discussion-paper/2810/18-069 2017 Nalan Basturk, Maastricht University, The Netherlands; Lennart Hoogerheide, VU Amsterdam and Tinbergen Institute, The Netherlands; Herman K. van Dijk, Erasmus University and Tinbergen Institute, The Netherlands and Norges Bank, Norway, Bayesian Analysis of Boundary and Near-Boundary Evidence in Econometric Models with Reduced Rank, Tinbergen DP, https://www.tinbergen.nl/discussion-paper/604/17-058 2016 Nalan Basturk, Maastricht University, the Netherlands; Stefano Grassi, University of Kent, United Kingdom; Lennart Hoogerheide, VU University Amsterdam, the Netherlands; Herman K. van Dijk, VU University Amsterdam, Erasmus University Rotterdam, the Netherlands, 16-005/III - Parallelization Experience with Four Canonical Econometric Models using ParMitISEM, Tinbergen DP, https://www.tinbergen.nl/discussion-paper/2455/16-005. Nalan Basturk, Maastricht University, The Netherlands; Stefano Grassi, University of Kent, United Kingdom; Lennart Hoogerheide, VU University Amsterdam, The Netherlands; Herman K. van Dijk, Erasmus University Rotterdam, The Netherlands, Time-varying Combinations of Bayesian Dynamic Models and Equity Momentum Strategies, Tinbergen DP , https://www.tinbergen.nl/discussion-paper/1705/16-099. 2015 Roberto Casarin, University Ca’ Foscari of Venice, Italy; Stefano Grassi,University of Kent, United Kingdom; Francesco Ravazzolo, Norges Bank and Centre for Applied Macro and Petroleum Economics, Norway; Herman K. van Dijk, Erasmus University Rotterdam, VU University Amsterdam, the Netherlands, Dynamic Predictive Density Combinations for Large Data Sets in Economics and Finance, Tinbergen DP, http://www.tinbergen.nl/discussionpaper/?paper=2513 2014 Nalan Basturk , Maastricht University, the Netherlands; Pinar Ceyhan , Erasmus University Rotterdam; Herman K. van Dijk Erasmus University Rotterdam, VU University Amsterdam, the Netherlands, 2014, Bayesian Forecasting of US Growth using Basic Time-Varying Parameter Models and Expectations Data. Tinbergen DP: http://www.tinbergen.nl/discussionpaper/?paper=2381. 2013 Lukasz Gatarek, Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam; Lennart Hoogerheide, VU University Amsterdam; Koen Hooning, Delft University of Technology; Herman K. van Dijk, Econometric Institute, Erasmus University Rotterdam, and VU University Amsterdam, Censored Posterior and Predictive Likelihood in Bayesian Left-Tail Prediction for Accurate Value at Risk Estimation, 2013-04-15. Nalan Basturk, Erasmus University Rotterdam; Cem Cakmakli, University of Amsterdam; Pinar Ceyhan, Erasmus University Rotterdam; Herman K. van Dijk, Erasmus University Rotterdam, and VU University Amsterdam, 2014, Posterior-Predictive Evidence on US Inflation using Phillips Curve Models with Non-filtered Time Series, TI-Discussion Paper. 2012 Nalan Basturk, Erasmus University Rotterdam, Lennart Hoogerheide, VU University Amsterdam; Anne Opschoor, Erasmus University Rotterdam; Herman K. van Dijk, Erasmus University Rotterdam, and VU University Amsterdam, The R Package MitISEM: Mixture of Student-t Distributions using Importance Sampling Weighted Expectation Maximization for Efficient and Robust Simulation. Under review at Journal of Statistical Software. Basturk N, Cakmakli C, Ceyhan P, Van Dijk HK. Posterior-Predictive Evidence on US Inflation using Phillips Curve Models with Non-Filtered Time Series 13-011/III (2013-01-10), Tinbergen Institute Billio M, Casarin R, Francesco R, Van Dijk HK. Time-varying Combinations of Predictive Densities using Nonlinear Filtering 12-118/III (2012-11-07), Tinbergen Institute Zellner A(posthumously), Ando T, Basturk N, Hoogerheide LF, Van Dijk HK.Bayesian Analysis of Instrumental Variable Models: Acceptance-Rejection within Direct Monte Carlo 12-098/III (2012-09-24), Tinbergen Institute Basturk N, Hoogerheide LF, Opschoor A, Van Dijk HK. The R Package MitISEM: Mixture of Student-t Distributions using Importance Sampling Weighted Expectation Maximization for Efficient and Robust Simulation 12-096/III (2012-09-20), Tinbergen Institute Hoogerheide LF, Opschoor A, Van Dijk HK. A Class of Adaptive Importance Sampling Weighted EM Algorithms for Efficient and Robust Posterior and Predictive Simulation 11-082/4 (2011-05-17), Tinbergen Institute Strachan R, Herman K. van Dijk, Evidence on Features of a DSGE Business Cycle Model from Bayesian Model Averaging 12-025/4 (2012-03-20), Tinbergen Institute 2011 Hoogerheide LF, Van Dijk HK. Backtesting Value-at-Risk using Forecasts for Multiple Horizons, a Comment on the Forecast Rationality Tests of A.J. Patton and A. Timmermann 11-131/4 (2011-09-20), Tinbergen Institute Billio M, Casarin R, Ravazzolo F, Van Dijk HK. Combination Schemes for Turning Point Predictions 11-123/4 (2011-08-22), Tinbergen Institute Billio M, Casarin R, Ravazzolo F, Van Dijk HK, Bayesian Combinations of Stock Price Predictions with an Application to the Amsterdam Exchange Index 11-082/4 (2011-05-17), Tinbergen Institute Arnold Zellner, (posthumously) Booth School of Business, University of Chicago, USA; Tomohiro Ando, Graduate School of Business Administration, Keio University, Japan; Nalan Basturk, Econometric Institute, Erasmus University Rotterdam, The Netherlands; The Rimini Centre for Economic Analysis, Rimini, Italy; Lennart Hoogerheide, VU University Amsterdam, The Netherlands; Herman K. van Dijk, Econometric Institute, Erasmus University Rotterdam, and VU University Amsterdam, Instrumental Variables, Errors in Variables, and Simultaneous Equations Models: Applicability and Limitations of Direct Monte Carlo (2011-09-27) Rodney W. Strachan, Australian National University, Australia; Herman K. van Dijk, Erasmus University Rotterdam, the Netherlands, Divergent Priors and well Behaved Bayes Factors, Report 11-006/4 from the Tinbergen Institute. Lennart Hoogerheide, VU University Amsterdam; Anne Opschoor, Erasmus University Rotterdam; Herman K. van Dijk, Erasmus University Rotterdam, A Class of Adaptive EM-based Importance Sampling Algorithms for Efficient and Robust Posterior and Predictive Simulation, Report 11-004/4 of the Tinbergen Institute, submitted for publication Billio M, University Ca'Foscari di Venezia; Roberto Casarin, University Ca'Foscari di Venezia; Francesco Ravazzolo, Norges Bank; Herman K. van Dijk, Erasmus University Rotterdam, Combining Predictive Densities using Bayesian Filtering with Applications to US Economics Data, Report 11-003/4 of the Tinbergen Institute, submitted for publication 2010 Rodney W. Strachan, The Australian National University; Herman K. van Dijk, Erasmus University Rotterdam, Evidence on a Real Business Cycle Model with Neutral and Investment-Specific Technology Shocks using Bayesian Model Averaging , Report 10-050/4 of the Tinbergen Institute, under revision for publication 2009 David Ardia, University of Fribourg, Switzerland; Lennart Hoogerheide, Erasmus University Rotterdam; Herman K. van Dijk, Erasmus University Rotterdam, To Bridge, to Warp or to Wrap? A Comparative Study of Monte Carlo Methods for Efficient Evaluation of Marginal Likelihoods, Report 09-017/4 from the Tinbergen Institute Arco van Oord, Erasmus University Rotterdam; Martin Martens, Erasmus University Rotterdam; Herman K. van Dijk, Erasmus University Rotterdam, Robust Optimization of the Equity Momentum Strategy, Report 09-011/4 of the Tinbergen Institute 2008 Lennart Hoogerheide, Erasmus University Rotterdam; Herman K. van Dijk, Erasmus University Rotterdam, Possibly Ill-behaved Posteriors in Econometric Models, On the Connection between Model Structures, Non-elliptical Credible Sets and Neural Network Simulation Techniques. Report 08-036/4 of the Tinbergen Institute, 45 pages abstract with link to full text pdf Strachan, R.W., Van Dijk, H.K. (2008). Bayesian Averaging over Many Dynamic Model Structures with Evidence on the Great Ratio’s and Liquidity Trap Risk, Tinbergen Institute Discussion Paper. abstract with link to full text pdf 2007 Lennart F. Hoogerheide, Herman K. van Dijk and Rutger D. van Oest, Simulation based Bayesian econometric inference: principles and some recent computational advances, report 2007-03 of the Econometric Institute, 70 pages Rodney W. Strachan and Herman K. van Dijk, Bayesian model averaging in vector autoregressive processes with an investigation of stability of the US great ratios and risk of a liquidity trap in the USA, UK and Japan, report 2007-11 of the Econometric Institute, 47 pages Francesco Ravazzolo, Herman K. van Dijk and Marno Verbeek, Predictive gains from forecast combinations using time-varying model weights, report 2007-26, 40 pages Lennart F. Hoogerheide and Herman K. van Dijk, Note on neutral network sampling for Bayesian inference of mixture processes, report 2007-15 of the Econometric Institute, 8 pages 2006 Herman K. van Dijk, J.F. Kaashoek and Albert P.M.Wagelmans (2006), ”Rotterdam econometrics”: publications of the Econometric Institute 1956-2005, report 2006-00 of the Econometric Institute, 102 pages (electronic data) Michiel D. de Pooter, Rene Segers and Herman K. van Dijk (2006), Gibbs sampling in econometric practice, report 2006-13 of the Econometric Institute, 36 pages (electronic data) Lennart F. Hoogerheide and Herman K. van Dijk, A reconsideration of the Angrist/Krueger analysis returns to education, report 2006-15 of the Econometric Institute, 35 pages RodneyW. Strachan and Herman K. van Dijk (2006), Model uncertainty and Bayesian Model averaging in vector autoregressive processes, report 2006-08 of the Econometric Institute, 38 pages (electronic data), under revision for publication Rodney W. Strachan & Herman K. van Dijk (2005), Weakly informative priors and well behaved Bayes Factors, report 2005-40 of the Econometric Institute, 55 pages 2004 Herman K. van Dijk , Twentieth century shocks, trends and cycles in industrialized nations, report 2004-01 of the Econometric Institute, 19 pages R.W. Strachan and Van Dijk HK, Improper priors with well defined Bayes factors, report 2004-18 of the Econometric Institute, 24 pages L.F. Hoogerheide, J.F. Kaashoek, and Van Dijk HK, Neural network approximations to posterior densities: A class of flexible sampling methods with applications to reduced rank models, report 2004-19 of the Econometric Institute, 42 pages R.W. Strachan and Van Dijk HK, Valuing structure, model uncertainty and model averaging in vector autoregressive processes, report 2004-23 of the Econometric Institute, 47 pages 2003 Rodney W. Strachan and Herman K. van Dijk, The value of structural information in the VAR model, report 2003-17 of the Econometric Institute, 38 pages R.H. Kleijn and Van Dijk HK, Rationalizing the unit root in real exchanges rates, a Bayesian procedure using expectational mechanisms, manuscript, 2003, 13 pages 2002 A.C. Harvey, Th.M. Trimbur and Van Dijk HK, Cyclical components in economic time series: a Bayesian approach, report 2002-20 of the Econometric Institute, 48 pages L. Bauwens, C. Bos and Van Dijk HK, Adaptive Polar sampling, a flexible and robust Monte Carlo method report 2002-27 of the Econometric Institute 2001 R.H. Kleijn and Van Dijk HK, A Bayesian analysis of the PPP puzzle using an unobserved components model, report 2001-35 of the Econometric Institute, 20 pages Charles S. Bos, Erasmus University Rotterdam; Ronald J. Mahieu, Erasmus University Rotterdam; Herman K. van Dijk, Erasmus University Rotterdam, On the Variation of Hedging Decisions in Daily Currency Risk Management, report 01-018/4 L.F. Hoogerheide and Van Dijk HK, Comparison of the Anderson-Rubin test for overidentification and the Johansen test for cointegration, Report 2001-04 of the Econometric Institute, 14 pages, 1999 Luc Bauwens, CORE, Université Catholique de Louvain; Charles S. Bos, Erasmus University Rotterdam; Herman K. van Dijk, Econometric Institute, Erasmus University Rotterdam, Adaptive Polar Sampling with an Application to a Bayes Measure of Value-at-Risk, report 99-082/4 of the Econometric Institute, 29 pages Charles S. Bos, Erasmus University Rotterdam; Ronald J. Mahieu, Rotterdam School of Management; Herman K. van Dijk, Econometric Institute, Erasmus University Rotterdam, Daily Exchange Rate Behaviour and Hedging of Currency Risk, 99-078/4 Gary Koop, University of Edinburgh; Herman K. van Dijk, Erasmus University Rotterdam, Testing for Integration using Evolving Trend and Seasonals Models: A Bayesian Approach, 99-072/4 Richard Paap, RIBES; Herman K. van Dijk, Econometric Institute, Erasmus University Rotterdam, Bayes Estimates of Markov Trends in Possibly Cointegrated Series: An Application to US Consumption and Income, report 99-024/4 of the Econometric Institute, 29 pages 1998 L. Bauwens, C. Bos and Van Dijk HK, Adaptive polar sampling: A New MC technique for the analysis of Ill-behaved surfaces, report 9822 of the Econometric Institute, 8 pages J.F. Kaashoek and Herman K. van Dijk, A simple strategy to prune neural networks with an application to economic time series, report 9854 of the Econometric Institute, 29 pages 1997 F.R. Kleibergen, J.-P. Urbain, and Van Dijk HK, Oil price shocks and long run price and import demands behavior, report 9708 of the Econometric Institute, 37 pages G. Koop, Van Dijk HK and H. Hoek, Testing for integration using evolving trend and seasonal models: A Bayesian Approach, report 9732 of the Econometric Institute, 34 pages 1995 G. Draisma, J.F. Kaashoek, and Van Dijk HK, A neural network applied to embedded economic data, discussion paper 95-20 of the Tinbergen Institute 1994 F.R. Kleibergen and Van Dijk HK, Bayesian analysis of simultaneous equation models using noninformative priors, discussion paper 94-134 of the Tinbergen Institute 1992 F.R. Kleibergen and Van Dijk HK, Bayesian simultaneous equation model analysis: On the existence of structural posterior moments, report 9269 of the Econometric Institute, 62 pages, discussion paper 93-25 of the Tinbergen Institute 1990 J.P. Hop and Van Dijk HK, SISAM and MIXIN: two algorithms for the computation of posterior moments and densities using Monte Carlo integration, report 9031 of the Econometric Institute, 150 pages J.F. Kaashoek and Van Dijk HK, On the use of descriptive measures for chaos in economic time series, report 9064 of the Econometric Institute, 13 pages 1989 P. Schotman and Van Dijk HK, Bayesian analysis of the unit root hypothesis, report 8953 of the Econometric Institute, 39 pages1988 Van Dijk HK and J.P. Hop, PMMC: A set of computer programs for the computation of posterior moments and densities using Monte Carlo integration, report 8810 of the Econometric Institute, 10 pages 1986 Van Dijk HK, J.P. Hop and A.S. Louter, Some algorithms for the computation of posterior moments and densities using Monte Carlo integration, report 8625 of the Econometric Institute, 61 pages 1985 H.K. van Dijk and T. Kloek, Monte Carlo analysis of skew posterior distributions: An econometric example, The Statistician 32, 216-223 download PDF H.K. van Dijk, Bayesian estimation methods and Bayesian statistics, in: Encyclopedia of Business Economics (in Dutch), Kluwer, Deventer H.K. van Dijk and T. Kloek, Monte Carlo analysis of skew posterior distributions: An econometric example, The Statistician 32, 216-223 download PDF H.K. van Dijk, Bayesian estimation methods and Bayesian statistics, in: Encyclopedia of Business Economics (in Dutch), Kluwer, Deventer H.K. van Dijk and T. Kloek, Monte Carlo analysis of skew posterior distributions: An econometric example, The Statistician 32, 216-223 download PDF H.K. van Dijk, Bayesian estimation methods and Bayesian statistics, in: Encyclopedia of Business Economics (in Dutch), Kluwer, Deventer 1983 H.K. van Dijk and T. Kloek, Monte Carlo analysis of skew posterior distributions: An econometric example, The Statistician 32, 216-223 download PDF H.K. van Dijk, Bayesian estimation methods and Bayesian statistics, in: Encyclopedia of Business Economics (in Dutch), Kluwer, Deventer 1978 Van Dijk HK and T. Kloek, Posterior analysis of Klein’s Model I, report 7824 of the Econometric Institute, 26 pages Van Dijk HK and T. Kloek, Empirical evidence on Pareto-Levy and log stable income distributions, report 7812 of the Econometric Institute, 28 pages 1975 T. Kloek and Van Dijk HK, Bayesian estimates of equation system parameters: An unorthodox application of Monte Carlo, report 7511 of the Econometric Institute, 21 pages Electronic versions are provided as a professional courtesy to ensure timely dissemination of academic work for individual, noncommercial purposes. Copyright and all rights therein reside with the respective copyright holders, as stated within each paper. These files may not be reposted without permission. back to top Copyright Notice: The documents distributed here have been provided to ensure timely dissemination of scholarly work. Copyright and all rights therein are maintained by the authors or by other copyright holders. These works may not be reposted or reproduced without the explicit permission of the copyright holders.
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S election of most cited papers
Books
All journal papers
Reports of the Econometric Institute / Discussion papers of the Tinbergen Institute

Selection of most cited papers

Further experience in Bayesian analysis using Monte Carlo integration
HK Van Dijk, T Kloek, Journal of Econometrics 14 (3), 307-328, 1980.

Time-varying combinations of predictive densities using nonlinear filtering
M Billio, R Casarin, F Ravazzolo, HK Van Dijk
Journal of Econometrics, 2013, 177 (2), 213-232.

Bayesian forecasting of value at risk and expected shortfall using adaptive importance sampling
L Hoogerheide, HK van Dijk
International Journal of Forecasting 2010, vol. 26 (2), 231-247.

Experiments with some alternatives for simple importance sampling in Monte Carlo integration
HK Van Dijk, T Kloek

A class of adaptive importance sampling weighted EM algorithms for efficient and robust posterior and predictive simulation
L Hoogerheide, A Opschoor, HK Van Dijk
Journal of Econometrics Vol. 171, 2012, (2), 101-120.

A comparative study of Monte Carlo methods for efficient evaluation of marginal likelihood
D Ardia, N Baştürk, L Hoogerheide, HK Van Dijk
Computational Statistics & Data Analysis Vol. 56 (11), 2012, 3398-3414.

Trends and cycles in economic time series: A Bayesian approach
AC Harvey, TM Trimbur, HK Van Dijk
Journal of Econometrics 140 (2), 618-649, 2007
download PDF

Experiments with some alternatives for simple importance sampling in Monte Carlo integration
HK Van Dijk, T Kloek
Erasmus University, 1983

Bayes estimates of Markov trends in possibly cointegrated series
R Paap, HK Van Dijk
Journal of Business and Economic Statistics 21 (4), 547-563, 2003
download PDF

Classical and Bayesian aspects of robust unit root inference
H Hoek, A Lucas, HK Van Dijk
Journal of Econometrics 69 (1), 27-59, 1995
download PDF

Daily exchange rate behaviour and hedging of currency risk
CS Bos, RJ Mahieu, HK Van Dijk
Journal of Applied Econometrics 15 (6), 671-696, 2000
download PDF

Natural conjugate priors for the instrumental variables regression model applied to the Angrist-Krueger data
L Hoogerheide, F Kleibergen, HK Van Dijk
Journal of Econometrics 138 (1), 63-103, 2007
download PDF

Neural network pruning applied to real exchange rate analysis
JF Kaashoek, HK Van Dijk
Journal of Forecasting 21 (8), 559-5772, 2002
download PDF

Direct cointegration testing in error correction models
F Kleibergen, HK Van Dijk
Journal of Econometrics 63 (1), 61-1032, 1994
download PDF

Bayesian limited information analysis revisited
L Bauwens, HK van Dijk
In: JJ Gabszewicz, JF Richard and LA Wolsey (Eds), Economic Decision Making: Games, Econometrics and Optimisation. North-Holland, 1990 (pp 385-424)
download PDF

Posterior moments computed by mixed integration
HK Van Dijk, T Kloek, CGE Boender
Journal of Econometrics 29 (1-2), 3-18, 1985
download PDF

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Books

J.F. Geweke, G. Koop, and Van Dijk HK, eds., The Oxford Handbook of Bayesian Econometrics, Oxford University Press, 2011, translated in Japanese in 2012

C. Heij, P.M.C. de Boer, P.H. Franses, T. Kloek and Van Dijk HK, 2004, Econometric Methods with Applications in Business and Economics, Solution Manual, Oxford University Press, Oxford, 358 pages

C. Heij, P.M.C. de Boer, P.H. Franses, T. Kloek and Van Dijk HK, 2004, Econometric Methods with Applications in Business and Economics, Oxford University Press, Oxford, 787 pages

Van Dijk HK, A. Monfort, and B.W. Brown, eds., 1995, Econometric Inference using Simulation Techniques, J. Wiley, New York , 265 pages

Van Dijk HK, R. Harkema, P. Kooiman, and P. Schotman, red., 1996, Kritisch en constructief, 40 jaar grensverkenningen in de econometrie, Liber Amicorum voor prof. dr. T. Kloek, Ridderkerk (Festschrift for T.Kloek)

Van Dijk HK, 1984, Posterior Analysis of Econometric Models using Monte Carlo Integration, 207 pages, Rotterdam, Erasmus University Press

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All journal papers

2020

Agnieszka Borowska, Lennart Hoogerheide, Siem Jan Koopman and Herman K. van Dijk, Partially Censored Posterior for Robust and Efficient Risk Evaluation, Journal of Econometrics. Volume 217, Issue 2, August 2020, Pages 335 - 355. https://www.sciencedirect.com/science/article/abs/pii/S0304407

2019

Sylvia Kaufmann, Sylvia Frühwirth-Schnatter, Herman K. van Dijk, Editorial introduction on complexity and big data in economics and finance: Recent developments from a Bayesian perspective, Journal of Econometrics, 2019, Vol. 210, Issue 1, 1-3.

N. Baştürk, A. Borowska, S. Grassi, L. Hoogerheide, H.K. van Dijk, Forecast density combinations of dynamic models and data driven portfolio strategies, Journal of Econometrics, 2019, Vol. 210, Issue 1, 170-186.

Knut Are Aastveit, James Mitchell, Francesco Ravazzolo, and Herman K. van Dijk, The Evolution of Forecast Density Combinations in Economics, Oxford Research Encyclopedia of Economics and Finance, 2019.
https://oxfordre.com/economics/view/10.1093/acrefore/9780190625979.001.0001/acrefore-9780190625979-e-381?rskey=ZdTXfP&result=1

2018

Knut Are Aastvelt, Norges Bank, Francesco Ravazzolo, Norges Bank, and Herman K. van Dijk, 2018, Nowcasting the Business Cycle in an Uncertain Economic Environment, Journal of Business & Economic Statistics, Vol. 36, Issue 1, 131-145. https://doi.org/10.1080/07350015.2015.1137760.

2017

Nalan Basturk, Maastricht University , the Netherlands; Stefano Grassi, University of Kent, United Kingdom; Lennart Hoogerheide, VU University Amsterdam, the Netherlands; Anne Opschoor, VU University Amsterdam, the Netherlands; Herman K. van Dijk, VU University Amsterdam, Erasmus University Rotterdam, the Netherlands, The R Package MitISEM: Mixture of Student-t Distributions using Importance Sampling Weighted Expectation Maximization for Efficient and Robust Simulation, Journal of Statistical Software, 2017, Vol. 79, 1, 1- 40. https://www.jstatsoft.org/issue/view/v079.

Nalan Basturk, Maastricht University, The Netherlands; Lennart Hoogerheide, VU Amsterdam and Tinbergen Institute, The Netherlands; Herman K. van Dijk, Erasmus University and Tinbergen Institute, The Netherlands and Norges Bank, Norway, Bayesian Analysis of Boundary and Near-Boundary Evidence in Econometric Models with Reduced Rank, Bayesian Analysis, Volume 12, Number 3 (2017), 879-917, https://projecteuclid.org/euclid.ba/1501120970.

2016

Christine DeMol, Eric Gautier, Domenico Giannone, Sendhil Mullainathan, Lucrezia Reichlin, Herman K Van Dijk, Jeffrey Wooldridge, 2016, Methods in Big Data Analysis, in Estelle Cantillon, Christine DeMol, Bram De Rock, Domenico Giannone, Georg Kirchsteiger, Laszlo Matyas, eds., Developments in Data and Methods for Economic Research, Cambridge University Press, Cambridge, UK.

Monica Billio, University of Venice, Gretta Assoc. and School for Advanced Studies in Venice; Roberto Casarin, University of Venice, Gretta Assoc. and School for Advanced Studies In Venice; Francesco Ravazzolo, Norges Bank; Herman K. van Dijk, Erasmus University Rotterdam, VU University Amsterdam, 2016, Interactions between Eurozone and US Booms and Busts, A Bayesian Panel Markov-Switching VAR model, Journal of Applied Econometrics, http://onlinelibrary.wiley.com/doi/10.1002/jae.2501/pdf and online appendix: (http://onlinelibrary.wiley.com/doi/10.1002/jae.2501/suppinfo).

Lukasz Gatarek, Erasmus University Rotterdam, Lennart Hoogerheide, VU University Amsterdam, Herman K. van Dijk, Erasmus University Rotterdam and VU University Amsterdam, Return and Risk of Pairs Trading using a Simulation-based Bayesian Procedure for Predicting Stable Ratios of Stock Prices, in Econometrics 2016, 4(1), 14; doi:10.3390/econometrics4010014.

Nalan Basturk, Maastricht University, the Netherlands; Stefano Grassi, University of Kent, United Kingdom; Lennart Hoogerheide, VU University Amsterdam, the Netherlands; Herman K. van Dijk, VU University Amsterdam, Erasmus University Rotterdam, the Netherlands, 2016, Parallelization Experience with Four Canonical Econometric Models using ParMitISEM , in  Econometrics 2016, 4(1), 11; doi:10.3390/econometrics4010011.

Nalan Basturk, Maastricht University, the Netherlands; Roberto Casarin, University of Venice, Gretta Assoc. and School for AdvancedStudies In Venice; Francesco Ravazzolo, Norges Bank; Herman K. van Dijk, VU University Amsterdam, Erasmus University Rotterdam, the Netherlands, 2016, Computational Complexity and Parallelization in Bayesian Econometric Analysis,  Econometrics  2016, 4(1), 9; doi:10.3390/econometrics4010009.

2015

Roberto Casarin, , University Ca' Foscari of Venice and GRETA; Stefano Grassi, Kent University; Francesco Ravazzolo, University of Bolzano; Herman K. van Dijk, Erasmus University Rotterdam, and VU University Amsterdam, 2015, Parallel Sequential Monte Carlo for Efficient Density Combination, The Deco Matlab Tool box, Journal of Statistical Software, Vol. 68, http://www.jstatsoft.org/article/view/v068i03.

2014

Arnold Zellner (posthumously), University of Chicago, USA; Tomohiro Ando, Keio University, Japan; Nalan Basturk, Erasmus University Rotterdam; Lennart Hoogerheide, VU University Amsterdam; Herman K. van Dijk, Erasmus University Rotterdam and VU University Amsterdam, 2014, Bayesian Analysis of Instrumental Variables Models: Acceptance-Rejection within Direct Monte Carlo, Econometric Reviews, 33:3-35.

Nalan Basturk, Erasmus University Rotterdam; Cem Cakmakli, University of Amsterdam; Pinar Ceyhan, Erasmus University Rotterdam; Herman K. van Dijk, Erasmus University Rotterdam, and VU University Amsterdam, 2014, Posterior-Predictive Evidence on US Inflation using Extended New Keynesian Phillips Curve Models with Non-filtered Data, Journal of Applied Econometrics, vol. 29 (7), 1164-1181, http://onlinelibrary.wiley.com/doi/10.1002/jae.2411/abstract

Nalan Basturk, Erasmus University Rotterdam; Cem Cakmakli, University of Amsterdam; S. Pinar Ceyhan, Erasmus University Rotterdam; Herman K. van Dijk, Erasmus University Rotterdam and VU University Amsterdam, 2014, On the rise of Bayesian Econometrics after Cowles Foundation Monographs 10,14, invited paper, Oeconomia, 4 (3), 381- 447, http://oeconomia.revues.org/913.

Rodney W. Strachan, Australian National University, Australia; Herman K. van Dijk, Erasmus University Rotterdam, the Netherlands, 2014, Divergent Priors and well Behaved Bayes Factors, Central European Journal of Economic Modeling and Econometrics, Vol. 6:1-31.

Fabio Canova, EUI, Frank Schorfheide, University of Pennsylvania, Herman K. van Dijk, Erasmus University Rotterdam and VU University Amsterdam, 2014, Introduction to recent advances in methods and applications of DSGE models, Journal of Applied Econometrics, vol. 29 (7), 1029-1030.

2013

Monica Billio, University of Venice, Gretta Assoc. and School for Advanced Studies in Venice; Roberto Casarin, University of Venice, Gretta Assoc. and School for Advanced Studies in Venice; Francesco Ravazzolo, Norges Bank; Herman K. van Dijk, Erasmus University Rotterdam, VU University Amsterdam, 2013, Time-varying combinations of predictive densities using nonlinear filtering, Journal of Econometrics, 177 (2), 213-232.

Allan Timmermann University of California at San Diego and Herman K. van Dijk, Erasmus University Rotterdam, VU University Amsterdam, (2013), Dynamic Econometric Modeling and Forecasting in the presence of instability, Journal of Econometrics, 177 (2),1-3.

Herman K. van Dijk, 2013, The Keynes-Tinbergen Debate on the Relevance of Estimating Econometric Models, TSEconomist, Issue 4, November 2013, 8-10.

Herman K. van Dijk, 2013, Bridging Two Key Issues in Bayesian Inference: The relationship between the Lindley Paradox and Non-elliptical Credible Sets, in Nozer Singpurwalla, Philip Dawid, Tony O’Hagan and Peter Freeman, eds: A Book for Dennis, Festschrift for professor Dennis Lindley’s ninetieth-birthday, Burr online publisher, 4 pages.

Strachan, RW, Van Dijk HK (2013) “Evidence on Features of a DSGE Business Cycle model from Bayesian Model Averaging”, The International Economic Review Volume 54, Number 1, 385-402.

Schaap M, Lemmers RJLF, Maassen R, Van der Vliet PJ, Hoogerhide LF, Van Dijk HK, Bastürk N, De Knijff P and Van der Maarel SM, 2013,Genome-wide analysis of macrosatellite repeat copy number variation in worldwide populations: evidence for differences and commonalities in size distributions and size restrictions, BMC Genomics, 14:143 doi:10.1186/1471-2164-14-143

2012

Hoogerhide L, VU University Amsterdam; Opschoor A, Erasmus University Amsterdam; Van Dijk HK, Erasmus University Rotterdam, and VU University Amsterdam, 2012, A Class of Adaptive Importance Sampling Weighted EM Algorithms for Efficient and Robust Posterior and Predictive Simulation, Journal of Econometrics, Vol. 171 (2) 101–120 http://dx.doi:10.1016/j.jeconom. 2012.06.011

Billio M, University of Venice, Gretta Assoc. and School for Advanced Studies In Venice; Casarin R, University of Venice, Gretta Assoc. and School for Advanced Studies In Venice; Ravazzolo F, Norges Bank; Van Dijk HK, Erasmus University Rotterdam, VU University Amsterdam, Combination Schemes for Turning Point Predictions , 2012, The Quarterly Review of Economics and Finance , Vol. 52 (4), 402–412., http://www.sciencedirect.com/science/journal/10629769/52/4

Belsley, D.A., Kontoghiorghes, E.J., Van Dijk, H.K., Bauwens, L., Belsley, D.A., Kontoghiorghes, E.J., Koopman, S.J., McAleer, M., van Dijk, H.K., Amendola, A., Billio, M., Croux, C., Chen, C.W.S., Davidson, R., Duchesne, P., Foschi, P., Francq, C., Fuertes, A.-M., Koop, G., Khalaf, L., Paolella, M., Pollock, D.S.G., Ruiz, E., Paap, R., Proietti, T., Winker, P., Yu, P.L.H., Zakoian, J.-M., Zeileis, A., The Annals of Computational and Financial Econometrics 1st issue. Computational Statistics and Data Analysis (2012), doi:10.1016/j.csda.2012.04.004, 2991-2993

Belsley, D.A., Chen, C.W.S., Francq, C., Gallo, G., Khalaf, L., Kontoghiorghes, E.J., and Van Dijk, H.K. Introduction to the Sixth Special Issue on Computational Econometrics, Computational Statistics and Data Analysis, 56, 11, 2012, 3307-3309

Ardia, D., Basturk, N., Hoogerheide, L.F., Van Dijk, H.K., “ A Comparative Study of Monte Carlo Methods for Efficient Evaluation of Marginal Likelihoods”, Computational Statistics and Data Analysis 56, 3398-3415.

Lennart F. Hoogerheide, VU University Amsterdam; Francesco Ravazzolo, Norges Bank; Herman K. van Dijk, Erasmus University Rotterdam, VU University Amsterdam., Backtesting Value-at-Risk using Forecasts for Multiple Horizons, a Comment on the Forecast Rationality Tests of A.J. Patton and A. Timmermann, appeared as : Comment in Journal of Business and Economic Statistics, 2012, 30 (1), 30-33.

Herman K. van Dijk, Erasmus University Rotterdam and VU University Amsterdam, Some reflections at the Occasion of the Nobel Prize 2011, MET Journal, 2012, 18 (3), pp.2-3

Billio M, University of Venice, GRETA Assoc. and School for Advanced Studies in Venice; Roberto Casarin, University of Venice, GRETA Assoc. and School for Advanced Studies in Venice; Francesco Ravazzolo, Norges Bank; Herman K. van Dijk, Erasmus University Rotterdam, Bayesian Combinations of Stock Price Predictions with an Application to the Amsterdam Exchange Index, MET Journal, 2012, 18 (4), 1-9.

2011

Geweke, J.F., Koop, G., and Van Dijk HK, Introduction, Handbook of Bayesian Econometrics, Oxford University Press, 2011, 8 pages,

2010

David A. Belsley, Pierre Duchesne, George , Erricos John Kontoghiorghes, Marc Paolella, Herman K. van Dijk, editors, ‘Editorial for the Fifth Special Issue on Computational and Financial Econometrics, Computational Statistics and Data Analysis, 2 pages, 2010

Hoogerheide, L.F., Kleijn, R., Ravazzolo, F., Van Dijk, H.K, Verbeek, M. , “Forecast Accuracy and Economic Gains from Bayesian Model Averaging using Time Varying Weights”, Journal of Forecasting, 29, 251-269.

Hoogerheide, L.F., Van Dijk, H.K., “Bayesian Forecasting of Value at Risk and Expected Shortfall using Adaptive Importance Sampling”, International Journal of Forecasting, 26(2), 231-247..

Hoogerheide, L.F., Van Dijk, H.K. “Simulation based Bayes Procedures for Model Structures with Non-Elliptical Posteriors”, Lexicon for Statistical Science, p. 1-2, Springer Verlag, 2010

Ardia, D., Hoogerheide, L.F., Van Dijk, H.K. ,“AdMit: Adaptive Mixtures of Student-t Distributions. The R Journal, 1(1), 25-30

Ardia, D., Hoogerheide, L.F., Van Dijk, H.K. “Adaptive mixture of Student-t distributions as a flexible candidate distribution for efficient simulation: the R package AdMit”, Journal of Statistical Software , 29(3), 1-32.

Hoogerheide, L.F., Van Dijk, H.K., Van Oest, R.D. “Simulation based Bayesian econometric inference: principles and some recent computational advances”, Chapter 7 in Handbook of Computational Econometrics, J. Wiley & Sons, 215-280.

Belsley, D.A., Davidson, R., Kontoghiorghes, E.J., MacKinnon, J.G., Van Dijk H.K. “Editorial of the fourth special issue on Computational Econometrics”, Computational Statistics and Data Analysis 53, 1923-1924.

2008

Peter A. Cornelisse & Herman K. van Dijk (2008). Tinbergen, Jan (1903-1994), The New Palgrave Dictionary of Economics 2, 1709-1719

Alessandra Amendola, David Belsley, Erricos Kontoghiorghes, Yasuhiro Omori, Herman K. van Dijk, and Eric Zivot, 2008, Introduction to Statistical & Computational Methods in Finance, Computational Statistics and Data Analysis, 2008, 1-5.

R. Paap and Van Dijk HK, 2009, Distribution and mobility of wealth of nations, in Duangkamon Chotikapanich ed., Essays in Memory of Camilo Dagum, Springer Verlag, Ch. 5. 27 pages

De Pooter, M., Ravazzolo, F., Segers, R., Van Dijk, H.K. (2008), Bayesian Near-Boundary Analysis in Basic Economic Time Series Models, in S. Chib, G. Koop, W. Griffiths and D. Terrell, eds., Advances in Econometrics, (Bayesian econometrics) 23, Emerald Group Publishing Limited, 331-402.

Van Dijk HK, Why earn more than the prime minister? Tinbergen Magazine, December 2008

Van Dijk HK, De Balkenende norm faalt, ESB, 19 december 2008 (in Dutch)

2007

J.F. Geweke, P.J.F. Groenen, R. Paap and Van Dijk HK, Editorial: Computational techniques for applied econometric analysis of macroeconomic and financial processes, in: Computational Statistics & Data Analysis 51, 3506-3508

Philip Hans Franses and Herman K. van Dijk, Progress and Challenges in Econometrics, Guest Editorial, Journal of Econometrics, 138(1), 1-2

Lennart Hoogerheide, Frank Kleibergen and Herman K. van Dijk, Natural Conjugate priors for the instrumental variables regression model applied to the Angrist-Krueger data, Journal of Econometrics, 138(1), 63-103

Lennart F. Hoogerheide & Herman K. van Dijk, Note on neural network sampling for Bayesian inference of mixture processes, Bulletin of the International Statistical Institute, 8 pages

Lennart F. Hoogerheide, Johan F. Kaashoek & Herman K. van Dijk, 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

Gary Koop and Herman K. van Dijk, Bayesian Dynamic Econometrics, Editor’s Introduction, Econometric Reviews, 26(2-3), 1-6

Andrew C. Harvey, Thomas M. Trimbur and Herman K. van Dijk, Trends and cycles in economic time series: A Bayesian approach, Journal of Econometrics, 140, 618-649

Andrew C. Harvey, Thomas M. Trimbur and Herman K. van Dijk, Bayes estimates of the cyclical component in twentieth century US gross domestic product, in: Growth and Cycle in the Eurozone, (eds. Gian Luigi Mazzi and Giovanni Savio), Palgrave MacMillan, New York, 76-89

Andrew Chesher, Geert Dhaene and Herman K. van Dijk, Endogeneity, Instruments and Identification, Guest Editorial, Journal of Econometrics, 139(1), 1-3.

2006

R.H. Kleijn and Van Dijk HK, Bayes model averaging of cyclical decomposition within economic time series, Journal of Applied Econometrics, 21: 191-212

Herman K. van Dijk, J. F. Kaashoek and Albert P.M. Wagelmans, ”Rotterdam econometrics”: An analysis of publications of the Econometric Institute 1956-2004, Statistica Neerlandica, 60(2), 85-111

Gary Koop, Rodney Strachan, Herman K. van Dijk & Mattias Villani, Bayesian approaches to cointegration, Chapter 25 in: T.C. Mills and K.P. Patterson, eds., Palgrave Handbook of Econometrics, 1: 871-898

2005

D.J.C van Dijk, Van Dijk HK and P.H.B.F. Franses, Editor’s Introduction to: Recent Developments in Business Cycle Analysis, Journal of Applied Econometrics, 20: 147-150.

2004

L. Bauwens, C.S. Bos, Van Dijk HK and R.D. van Oest, Adaptive radial-based direction sampling - Some flexible and robust Monte Carlo integration methods, Journal of Econometrics 123, 201-225

L. Bauwens, M. Lubrano and Van Dijk HK, Editor’s introduction to recent advances in Bayesian econometrics, Journal of Econometrics, 197-199

P.C. Cornelisse, H. Don and Van Dijk HK, Introduction to the Tinbergen Centennial Issue, De Economist, 161-165

Van Dijk HK, Twentieth Century Shocks, Trends and Cycles in Industrialized Nations, De Economist, 211-232

2003

Johan F. Kaashoek and Van Dijk HK, Neural networks as econometric tool, chapter 12, 351-385, in D. Giles, ed, Computer Aided Econometrics, Marcel Dekker, New York, 2003

Van Dijk HK, On Bayesian structural inference in a simultaneous equation model, chapter 25, 642-683, in B. Stigum, ed., Econometrics and the Philosophy of Economics, Princeton University Press, 2003

Van Dijk HK, On shocks, trends and cycles in industrialized countries in the Twentieth Century, Tinbergen Magazine, 2003, 7, 12-15

R. Paap and Van Dijk HK, Bayes estimates of Markov trends in possibly cointegrated series: an application to US consumption and income, Journal of Business & Economic Statistics, 21, 547-563.

R.W. Strachan and Van Dijk HK, Bayesian model selection for a sharp null and a diffuse alternative with econometric applications, Oxford Bulletin of Economics and Statistics, 2003, 65 (supplement), 863-876

N. Haldrup, D.F. Hendry and Van Dijk HK, Guest editors introduction: Model Selection and Evaluation in Econometrics, Oxford Bulletin of Economics and Statistics, 2003, 65 (supplement), 681-688

L.F. Hoogerheide, J.F. Kaashoek and Van Dijk HK, Neural network approximations to posterior densities: An analytical approach, American Statistical Association 2003, Proceedings of the Section on Bayesian Statistical Science, 5 pages

L. Bauwens, C.S. Bos, Van Dijk HK and R.D. van Oest, Explaining adaptive radialbased direction sampling, American Statistical Association 2003, Proceedings of the Section on Bayesian Statistical Science, 5 pages

A.C. Harvey, Th.M. Trimbur and Van Dijk HK, Bayes estimates of the cyclical component in twentieth century US gross domestic product, Proceedings of the 4th Eurostat and DGECFIN Colloquium on Modern Tools for Business Cycle Analysis, Eurostat, 2003, 14 pages

Kaashoek, J.F. and Van Dijk HK, Long term values of euro/dollar and European exchange rates: A neural network analysis, Medium Econometrische Toepassingen, 10(4), 26-29

2002

N. Terui, and Herman K. van Dijk, Combined forecasts from linear and nonlinear time series models, International Journal of Forecasting, 18(3), 421-438

J.F. Kaashoek and Van Dijk HK, Neural network analysis of varying trends in real exchange rates, Journal of Forecasting, 2002, 21, 559-577

2001

C.S. Bos, R.J. Mahieu and Van Dijk HK, On the variation of hedging decisions in daily currency risk management, in: I. Edward George ed., 2001, Bayesian methods with applications to science, policy and official statistics, Eurostat, 31-40

2000

G. Koop, and Van Dijk HK, Testing for integration using evolving trend and seasonal models: A Bayesian Approach, Journal of Econometrics 97(2), 261-291

Van Dijk HK, Comment on: Time series analysis of non-Gaussian observations based on state space models from both classical and Bayesian perspectives, by J. Durbin and S. Koopman, Journal of the Royal Statistical Society Series B, 62, 42

L. Bauwens, C.S. Bos and Van Dijk HK, Adaptive polar sampling: a new MCMC method for ill-behaved posterior surfaces, in W. Jansen and J.G. Bethlehem eds., Compstat 2000, Statistics Netherlands, 13-14

C.S. Bos, R.J. Mahieu and Van Dijk HK, Daily exchange rate behaviour and hedging of currency risk, Journal of Applied Econometrics, 15(6), 671-696

John Geweke, John Rust, Herman K. Van Dijk, Introduction: Inference and Decision making, Journal of Applied Econometrics, 15(6), 545-546

1999

Van Dijk HK, Some Remarks on the simulation revolution in Bayesian econometric inference, Econometric Reviews, 18(1), 105-112

F.R. Kleibergen, Van Dijk HK and J.P. Urbain, A cointegration study of aggregate imports using likelihood based testing principles, Annals of the Institute of Statistical Mathematics, 51(3), 399-417.

R. Paap, and Van Dijk HK, Posterior evidence on the permanent income hypothesis, EU & US Inflation and Macroeconomic Analysis Bulletin, 58, July 1999

1998

R. Paap and Van Dijk HK, Distribution and mobility of wealth of nations, European Economic Review 42, 1269-1293.

F.R. Kleibergen, Van Dijk HK, Bayesian simultaneous equations analysis using reduced rank structures, Econometric Theory 14, 701-743

1996

G. Koop, and Van Dijk HK, Testing for integration using evolving trend models, in: American Statistical Association 1996 Proceedings of the Section on Bayesian Statistical Science, 232-237

1996

L. Bauwens, W. Polasek, and H. K. van Dijk, Bayes, Bernoullis, and Basel, Editor’s introduction, Journal of Econometrics 75(1), 1-5

Van Dijk HK, De econometrie van simultane modellen, 1956-1997 (in Dutch) in Van Dijk HK et al, Kritisch en constructief, 40 jaar grensverkenningen in de econometrie, Liber Amicorum voor prof. dr. T. Kloek, Ridderkerk (Festschrift for T. Kloek)

1995

A. Monfort and Van Dijk HK, Simulation based econometrics, in: Van Dijk HK, Monfort and B.W. Brown, eds., 1995, Econometric Inference using Simulation Techniques (Wiley, New York), 1-20

H. Hoek, A. Lucas and Van Dijk HK, Classical and Bayesian aspects of robust unit root Inference, Journal of Econometrics 69, 27-59

1994

F.R. Kleibergen and Van Dijk HK, On the shape of the likelihood/posterior of cointegration models, Econometric Theory 10, 514-551

J.F. Kaashoek and Van Dijk HK, A neural network applied to the calculation of Lyapunov exponents, Econometric Reviews, 13(1), 123-137

M. Ooms and Van Dijk HK, Comment on ’Estimating systems of trending variables’, estimating pushing trends and pulling equilibria, Econometric Reviews 13(3), 395-422

F.R. Kleibergen and Van Dijk HK, Direct cointegration testing in error-correction models, Journal of Econometrics 63, 61-103

J.F. Kiviet and Van Dijk HK, Structure and dynamics in Econometrics, Editor’s Introduction, Journal of Econometrics 63, 1-5

P.C.B. Phillips and Van Dijk HK, Bayes methods and unit roots, Editor’s Introduction, Econometric Theory 10, 453-460

Van Dijk HK, Dynamiek in de Econometrie, (Dynamics In Econometrics, Inaugural Lecture), 1994, 26 pages

1993

P. Schotman and Van Dijk HK, Posterior analysis of possibly integrated time series with an application to real GNP, in: P. Caines, J. Geweke and M. Taqqu., eds., New Directions in Time Series Analysis part II, IMA Volumes in Mathematics and its Applications 46, Springer Verlag, Heidelberg, 341-361

C.G.E. Boender and Van Dijk HK, Bayes estimates of multi-criteria decision alternatives using Monte Carlo integration, Statistica Neerlandica, 47, 2, 127-151

F.R. Kleibergen and Van Dijk HK, Efficient computer generation of matric-variatet drawings with an application to Bayesian estimation of simple market models, in: W. Hardle and L. Simar, eds., Statistics & Computing: Computer Intensive Methods in Statistics, Springer Verlag, 1993, 30-46

F.R. Kleibergen and Van Dijk HK, Non-stationarity in GARCH models: A Bayesian analysis, Journal of Applied Econometrics, vol. 8, S41-S61

B.W. Brown, A. Monfort, Van Dijk HK, Introduction to econometric inference using simulation techniques, Journal of Applied Econometrics, vol. 8, S1-S3

1992

J.P. Hop and Van Dijk HK, SISAM and MIXIN, Two algorithms for the evaluation of posterior moments and densities using Monte Carlo integration, Computer Science in Economics and Management, (now Computational Economics) vol. 5, 183-220; reprinted in Bulletin of the International Statistical Institute, Cairo, vol. LIV, book 3, 29 pages

1991

P. Schotman and Van Dijk HK, A Bayesian analysis of the unit root in real exchange rates, Journal of Econometrics 49, 195-238

Van Dijk HK, Comment on G.E. Mizon, Modelling relative price variability and aggregate inflation in the United Kingdom, Scandinavian Journal of Economics, 93, 213-217. Reprinted in: S. Hylleberg and M. Paldam, eds., New approaches to empirical macroeconomics, Basil Blackwell, 85-89.

J.F. Kaashoek and Van Dijk HK, A note on the detection of chaos in medium sized time series, in: R. Seydel, F.W. Schneider, T. Kupper, H. Troger, eds., Bifurcation and Chaos: Analysis, Algorithms, Applications, International Series of Numerical Mathematics 97, Basel: Birkhauser, 162-166

P. Schotman and Van Dijk HK, On Bayesian routes to unit roots, Journal of Applied Econometrics, 6, 387-401

1990

L. Bauwens and Van Dijk HK, Bayesian limited information analysis revisited, in: J. Gabszewicz, J.F. Richard and L. Wolsey, eds., Economic decision-making: Games, Econometrics, and Decision-making, Contributions in honour of Jacques Dreze, North-Holland, Amsterdam, 385-424

1988

A. Zellner, L. Bauwens and Van Dijk HK, Bayesian specification analysis and estimation of simultaneous equation models using Monte Carlo methods, Journal of Econometrics, 38, 39-72

1987

Van Dijk HK, J.P. Hop and A.S. Louter, An algorithm for the computation of posterior moments and densities using simple importance sampling, The Statistician 36, 83-90

Van Dijk HK, A product of multivariate t densities as upper bound for the posterior kernel of simultaneous equation model parameters, in: R. Viertl, ed., Probability and Bayesian Statistics (Plenum, New York), 129-138

Van Dijk HK, Some advances in Bayesian analysis using Monte Carlo integration, in: T.B. Fomby and C. Rhodes, eds., Advances in Econometrics, Vol 6, JAI Press, 215-261

Van Dijk HK, Comment on Computation in Bayesian statistics, in J.M. Bernardo, M.H. de Groot, D.V. Lindley and R.F.M. Smith, Bayesian Statistics 3, North Holland, Amsterdam, 435

1986

Van Dijk HK and T. Kloek, Posterior moments of the Klein-Goldberger Model, in: P.K. Goel and A. Zellner, eds., Bayesian inference and decision techniques with application: Essays in honor of Bruno de Finetti, (North-Holland, Amsterdam), 95-108

1985

Van Dijk HK and T. Kloek, Experiments with some alternatives for simple importance sampling in Monte Carlo integration (with discussion), in: J.M. Bernardo, M.H. DeGroot, D.V. Lindley and A.F.M. Smith, eds., Bayesian Statistics 2, (North Holland, Amsterdam), 511-530

Van Dijk HK, Editor’s Introduction to Bayesian analysis of some econometric and statistical models, Journal of Econometrics 29, 1-2

Van Dijk HK, T. Kloek, and G. Boender, Posterior moments computed by mixed integration, Journal of Econometrics 29, 3-18

P. Kooiman, Van Dijk HK, and A.R. Thurik, Likelihood diagnostics and Bayesian analysis of a micro-economic disequilibrium model for retail services, Journal of Econometrics 29, 212-248 download PDF

1983

Van Dijk HK and T. Kloek, Monte Carlo analysis of skew posterior distributions: An econometric example, The Statistician 32, 216-223 download PDF

Van Dijk HK, Bayesian estimation methods and Bayesian statistics, in: Encyclopedia of Business Economics (in Dutch), Kluwer, Deventer

1980

Van Dijk HK and T. Kloek, Further experience in Bayesian analysis using Monte Carlo integration, Journal of Econometrics 14, 307-328

Van Dijk HK and T. Kloek, Inferential procedures in stable distributions for class frequency data on incomes, Econometrica 48, 1139-1148 download PDF

1978

T. Kloek and Van Dijk HK, Bayesian estimates of equation system parameters, An application of integration by Monte Carlo, Econometrica 46, 1-19. Reprinted in: A. Zellner ed., 1980, Bayesian analysis in econometrics and statistics, Essays in honor of Harold Jeffreys (North Holland, Amsterdam), 311-329

T. Kloek and Van Dijk HK, Efficient estimation of income distribution parameters, Journal of Econometrics 8, 61-74.

Van Dijk HK and T. Kloek, Posterior analysis of Klein’s Model I, Szigma, Hungarian Journal of Mathematical Economics, 121-143

1977

Van Dijk HK and T. Kloek, Predictive moments of simultaneous econometric models, A Bayesian Approach, in: A. Aykac and C. Brumat, eds., New developments in the applications of Bayesian methods, (North-Holland, Amsterdam), 243-260

T. Kloek and Van Dijk HK, Further results on efficient estimation of income distribution parameters, Economie Applique 30, 439-459

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Reports of the Econometric Institute / Discussion papers of the Tinbergen Institute

2019

Agnieszka Borowska, Vrije Universiteit Amsterdam & University of Glasgow; Lennart Hoogerheide, Vrije Universiteit Amsterdam; Siem Jan Koopman, Vrije Universiteit Amsterdam & CREATES, Aarhus University; Herman K. van Dijk, Erasmus University Rotterdam & Norges Bank, Partially Censored Posterior for Robust and Efficient Risk Evaluation, Tinbergen DP https://www.tinbergen.nl/discussion-paper/2898/0000

Roberto Casarin, University Ca' Foscari of Venice; Stefano Grassi , University of Rome `Tor Vergata'; Francesco Ravazzollo , BI Norwegian Business School; Herman K. van Dijk , Erasmus University Rotterdam , Forecast Density Combinations with Dynamic Learning for Large Data Sets in Economics and Finance, Tinbergen DP https://www.tinbergen.nl/discussion-paper/2866/19-025

2018

Lennart (L.F.) Hoogerheide, VU University Amsterdam; Herman (H.K.) van Dijk, Erasmus University, Norges Bank, Learning to Average Predictively over Good and Bad: Comment on: Using Stacking to Average Bayesian Predictive Distributions, Tinbergen DP, https://www.tinbergen.nl/discussion-paper/1675/18-06

Knut Are Aastveit, Norges Bank; James Mitchell, Warwick Business School; Francesco Ravazzolo, Free University of Bozen/Bolzano; Herman van Dijk, Erasmus University,Norges Bank,The Evolution of Forecast Density Combinations in Economics, Tinbergen DP, https://www.tinbergen.nl/discussion-paper/2810/18-069

2017

Nalan Basturk, Maastricht University, The Netherlands; Lennart Hoogerheide, VU Amsterdam and Tinbergen Institute, The Netherlands; Herman K. van Dijk, Erasmus University and Tinbergen Institute, The Netherlands and Norges Bank, Norway, Bayesian Analysis of Boundary and Near-Boundary Evidence in Econometric Models with Reduced Rank, Tinbergen DP, https://www.tinbergen.nl/discussion-paper/604/17-058

2016

Nalan Basturk, Maastricht University, the Netherlands; Stefano Grassi, University of Kent, United Kingdom; Lennart Hoogerheide, VU University Amsterdam, the Netherlands; Herman K. van Dijk, VU University Amsterdam, Erasmus University Rotterdam, the Netherlands, 16-005/III - Parallelization Experience with Four Canonical Econometric Models using ParMitISEM, Tinbergen DP, https://www.tinbergen.nl/discussion-paper/2455/16-005.

Nalan Basturk, Maastricht University, The Netherlands; Stefano Grassi, University of Kent, United Kingdom; Lennart Hoogerheide, VU University Amsterdam, The Netherlands; Herman K. van Dijk, Erasmus University Rotterdam, The Netherlands, Time-varying Combinations of Bayesian Dynamic Models and Equity Momentum Strategies, Tinbergen DP , https://www.tinbergen.nl/discussion-paper/1705/16-099.

2015

Roberto Casarin, University Ca’ Foscari of Venice, Italy; Stefano Grassi,University of Kent, United Kingdom; Francesco Ravazzolo, Norges Bank and Centre for Applied Macro and Petroleum Economics, Norway; Herman K. van Dijk, Erasmus University Rotterdam, VU University Amsterdam, the Netherlands, Dynamic Predictive Density Combinations for Large Data Sets in Economics and Finance, Tinbergen DP, http://www.tinbergen.nl/discussionpaper/?paper=2513

2014

Nalan Basturk , Maastricht University, the Netherlands; Pinar Ceyhan , Erasmus University Rotterdam; Herman K. van Dijk Erasmus University Rotterdam, VU University Amsterdam, the Netherlands, 2014, Bayesian Forecasting of US Growth using Basic Time-Varying Parameter Models and Expectations Data. Tinbergen DP: http://www.tinbergen.nl/discussionpaper/?paper=2381.

2013

Lukasz Gatarek, Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam; Lennart Hoogerheide, VU University Amsterdam; Koen Hooning, Delft University of Technology; Herman K. van Dijk, Econometric Institute, Erasmus University Rotterdam, and VU University Amsterdam, Censored Posterior and Predictive Likelihood in Bayesian Left-Tail Prediction for Accurate Value at Risk Estimation, 2013-04-15.

Nalan Basturk, Erasmus University Rotterdam; Cem Cakmakli, University of Amsterdam; Pinar Ceyhan, Erasmus University Rotterdam; Herman K. van Dijk, Erasmus University Rotterdam, and VU University Amsterdam, 2014, Posterior-Predictive Evidence on US Inflation using Phillips Curve Models with Non-filtered Time Series, TI-Discussion Paper.

2012

Nalan Basturk, Erasmus University Rotterdam, Lennart Hoogerheide, VU University Amsterdam; Anne Opschoor, Erasmus University Rotterdam; Herman K. van Dijk, Erasmus University Rotterdam, and VU University Amsterdam, The R Package MitISEM: Mixture of Student-t Distributions using Importance Sampling Weighted Expectation Maximization for Efficient and Robust Simulation. Under review at Journal of Statistical Software.

Basturk N, Cakmakli C, Ceyhan P, Van Dijk HK. Posterior-Predictive Evidence on US Inflation using Phillips Curve Models with Non-Filtered Time Series 13-011/III (2013-01-10), Tinbergen Institute
Billio M, Casarin R, Francesco R, Van Dijk HK. Time-varying Combinations of Predictive Densities using Nonlinear Filtering 12-118/III (2012-11-07), Tinbergen Institute

Zellner A(posthumously), Ando T, Basturk N, Hoogerheide LF, Van Dijk HK.Bayesian Analysis of Instrumental Variable Models: Acceptance-Rejection within Direct Monte Carlo 12-098/III (2012-09-24), Tinbergen Institute

Basturk N, Hoogerheide LF, Opschoor A, Van Dijk HK. The R Package MitISEM: Mixture of Student-t Distributions using Importance Sampling Weighted Expectation Maximization for Efficient and Robust Simulation 12-096/III (2012-09-20), Tinbergen Institute

Hoogerheide LF, Opschoor A, Van Dijk HK. A Class of Adaptive Importance Sampling Weighted EM Algorithms for Efficient and Robust Posterior and Predictive Simulation 11-082/4 (2011-05-17), Tinbergen Institute

Strachan R, Herman K. van Dijk, Evidence on Features of a DSGE Business Cycle Model from Bayesian Model Averaging 12-025/4 (2012-03-20), Tinbergen Institute

2011

Hoogerheide LF, Van Dijk HK. Backtesting Value-at-Risk using Forecasts for Multiple Horizons, a Comment on the Forecast Rationality Tests of A.J. Patton and A. Timmermann 11-131/4 (2011-09-20), Tinbergen Institute

Billio M, Casarin R, Ravazzolo F, Van Dijk HK. Combination Schemes for Turning Point Predictions 11-123/4 (2011-08-22), Tinbergen Institute

Billio M, Casarin R, Ravazzolo F, Van Dijk HK, Bayesian Combinations of Stock Price Predictions with an Application to the Amsterdam Exchange Index 11-082/4 (2011-05-17), Tinbergen Institute

Arnold Zellner, (posthumously) Booth School of Business, University of Chicago, USA; Tomohiro Ando, Graduate School of Business Administration, Keio University, Japan; Nalan Basturk, Econometric Institute, Erasmus University Rotterdam, The Netherlands; The Rimini Centre for Economic Analysis, Rimini, Italy; Lennart Hoogerheide, VU University Amsterdam, The Netherlands; Herman K. van Dijk, Econometric Institute, Erasmus University Rotterdam, and VU University Amsterdam, Instrumental Variables, Errors in Variables, and Simultaneous Equations Models: Applicability and Limitations of Direct Monte Carlo (2011-09-27)

Rodney W. Strachan, Australian National University, Australia; Herman K. van Dijk, Erasmus University Rotterdam, the Netherlands, Divergent Priors and well Behaved Bayes Factors, Report 11-006/4 from the Tinbergen Institute.

Lennart Hoogerheide, VU University Amsterdam; Anne Opschoor, Erasmus University Rotterdam; Herman K. van Dijk, Erasmus University Rotterdam, A Class of Adaptive EM-based Importance Sampling Algorithms for Efficient and Robust Posterior and Predictive Simulation, Report 11-004/4 of the Tinbergen Institute, submitted for publication

Billio M, University Ca'Foscari di Venezia; Roberto Casarin, University Ca'Foscari di Venezia; Francesco Ravazzolo, Norges Bank; Herman K. van Dijk, Erasmus University Rotterdam, Combining Predictive Densities using Bayesian Filtering with Applications to US Economics Data, Report 11-003/4 of the Tinbergen Institute, submitted for publication

2010

Rodney W. Strachan, The Australian National University; Herman K. van Dijk, Erasmus University Rotterdam, Evidence on a Real Business Cycle Model with Neutral and Investment-Specific Technology Shocks using Bayesian Model Averaging , Report 10-050/4 of the Tinbergen Institute, under revision for publication

2009

David Ardia, University of Fribourg, Switzerland; Lennart Hoogerheide, Erasmus University Rotterdam; Herman K. van Dijk, Erasmus University Rotterdam, To Bridge, to Warp or to Wrap? A Comparative Study of Monte Carlo Methods for Efficient Evaluation of Marginal Likelihoods, Report 09-017/4 from the Tinbergen Institute

Arco van Oord, Erasmus University Rotterdam; Martin Martens, Erasmus University Rotterdam; Herman K. van Dijk, Erasmus University Rotterdam, Robust Optimization of the Equity Momentum Strategy, Report 09-011/4 of the Tinbergen Institute

2008

Lennart Hoogerheide, Erasmus University Rotterdam; Herman K. van Dijk, Erasmus University Rotterdam, Possibly Ill-behaved Posteriors in Econometric Models, On the Connection between Model Structures, Non-elliptical Credible Sets and Neural Network Simulation Techniques. Report 08-036/4 of the Tinbergen Institute, 45 pages abstract with link to full text pdf

Strachan, R.W., Van Dijk, H.K. (2008). Bayesian Averaging over Many Dynamic Model Structures with Evidence on the Great Ratio’s and Liquidity Trap Risk, Tinbergen Institute Discussion Paper. abstract with link to full text pdf

2007

Lennart F. Hoogerheide, Herman K. van Dijk and Rutger D. van Oest, Simulation based Bayesian econometric inference: principles and some recent computational advances, report 2007-03 of the Econometric Institute, 70 pages

Rodney W. Strachan and Herman K. van Dijk, Bayesian model averaging in vector autoregressive processes with an investigation of stability of the US great ratios and risk of a liquidity trap in the USA, UK and Japan, report 2007-11 of the Econometric Institute, 47 pages

Francesco Ravazzolo, Herman K. van Dijk and Marno Verbeek, Predictive gains from forecast combinations using time-varying model weights, report 2007-26, 40 pages

Lennart F. Hoogerheide and Herman K. van Dijk, Note on neutral network sampling for Bayesian inference of mixture processes, report 2007-15 of the Econometric Institute, 8 pages

2006

Herman K. van Dijk, J.F. Kaashoek and Albert P.M.Wagelmans (2006), ”Rotterdam econometrics”: publications of the Econometric Institute 1956-2005, report 2006-00 of the Econometric Institute, 102 pages (electronic data)

Michiel D. de Pooter, Rene Segers and Herman K. van Dijk (2006), Gibbs sampling in econometric practice, report 2006-13 of the Econometric Institute, 36 pages (electronic data)

Lennart F. Hoogerheide and Herman K. van Dijk, A reconsideration of the Angrist/Krueger analysis returns to education, report 2006-15 of the Econometric Institute, 35 pages

RodneyW. Strachan and Herman K. van Dijk (2006), Model uncertainty and Bayesian Model averaging in vector autoregressive processes, report 2006-08 of the Econometric Institute, 38 pages (electronic data), under revision for publication

Rodney W. Strachan & Herman K. van Dijk (2005), Weakly informative priors and well behaved Bayes Factors, report 2005-40 of the Econometric Institute, 55 pages

2004

Herman K. van Dijk , Twentieth century shocks, trends and cycles in industrialized nations, report 2004-01 of the Econometric Institute, 19 pages

R.W. Strachan and Van Dijk HK, Improper priors with well defined Bayes factors, report 2004-18 of the Econometric Institute, 24 pages

L.F. Hoogerheide, J.F. Kaashoek, and Van Dijk HK, Neural network approximations to posterior densities: A class of flexible sampling methods with applications to reduced rank models, report 2004-19 of the Econometric Institute, 42 pages

R.W. Strachan and Van Dijk HK, Valuing structure, model uncertainty and model averaging in vector autoregressive processes, report 2004-23 of the Econometric Institute, 47 pages

2003

Rodney W. Strachan and Herman K. van Dijk, The value of structural information in the VAR model, report 2003-17 of the Econometric Institute, 38 pages

R.H. Kleijn and Van Dijk HK, Rationalizing the unit root in real exchanges rates, a Bayesian procedure using expectational mechanisms, manuscript, 2003, 13 pages

2002

A.C. Harvey, Th.M. Trimbur and Van Dijk HK, Cyclical components in economic time series: a Bayesian approach, report 2002-20 of the Econometric Institute, 48 pages

L. Bauwens, C. Bos and Van Dijk HK, Adaptive Polar sampling, a flexible and robust Monte Carlo method report 2002-27 of the Econometric Institute

2001

R.H. Kleijn and Van Dijk HK, A Bayesian analysis of the PPP puzzle using an unobserved components model, report 2001-35 of the Econometric Institute, 20 pages

Charles S. Bos, Erasmus University Rotterdam; Ronald J. Mahieu, Erasmus University Rotterdam; Herman K. van Dijk, Erasmus University Rotterdam, On the Variation of Hedging Decisions in Daily Currency Risk Management, report 01-018/4

L.F. Hoogerheide and Van Dijk HK, Comparison of the Anderson-Rubin test for overidentification and the Johansen test for cointegration, Report 2001-04 of the Econometric Institute, 14 pages,

1999

Luc Bauwens, CORE, Université Catholique de Louvain; Charles S. Bos, Erasmus University Rotterdam; Herman K. van Dijk, Econometric Institute, Erasmus University Rotterdam, Adaptive Polar Sampling with an Application to a Bayes Measure of Value-at-Risk, report 99-082/4 of the Econometric Institute, 29 pages

Charles S. Bos, Erasmus University Rotterdam; Ronald J. Mahieu, Rotterdam School of Management; Herman K. van Dijk, Econometric Institute, Erasmus University Rotterdam, Daily Exchange Rate Behaviour and Hedging of Currency Risk, 99-078/4

Gary Koop, University of Edinburgh; Herman K. van Dijk, Erasmus University Rotterdam, Testing for Integration using Evolving Trend and Seasonals Models: A Bayesian Approach, 99-072/4

Richard Paap, RIBES; Herman K. van Dijk, Econometric Institute, Erasmus University Rotterdam, Bayes Estimates of Markov Trends in Possibly Cointegrated Series: An Application to US Consumption and Income, report 99-024/4 of the Econometric Institute, 29 pages

1998

L. Bauwens, C. Bos and Van Dijk HK, Adaptive polar sampling: A New MC technique for the analysis of Ill-behaved surfaces, report 9822 of the Econometric Institute, 8 pages

J.F. Kaashoek and Herman K. van Dijk, A simple strategy to prune neural networks with an application to economic time series, report 9854 of the Econometric Institute, 29 pages

1997

F.R. Kleibergen, J.-P. Urbain, and Van Dijk HK, Oil price shocks and long run price and import demands behavior, report 9708 of the Econometric Institute, 37 pages

G. Koop, Van Dijk HK and H. Hoek, Testing for integration using evolving trend and seasonal models: A Bayesian Approach, report 9732 of the Econometric Institute, 34 pages

1995

G. Draisma, J.F. Kaashoek, and Van Dijk HK, A neural network applied to embedded economic data, discussion paper 95-20 of the Tinbergen Institute

1994

F.R. Kleibergen and Van Dijk HK, Bayesian analysis of simultaneous equation models using noninformative priors, discussion paper 94-134 of the Tinbergen Institute

1992

F.R. Kleibergen and Van Dijk HK, Bayesian simultaneous equation model analysis: On the existence of structural posterior moments, report 9269 of the Econometric Institute, 62 pages, discussion paper 93-25 of the Tinbergen Institute

1990

J.P. Hop and Van Dijk HK, SISAM and MIXIN: two algorithms for the computation of posterior moments and densities using Monte Carlo integration, report 9031 of the Econometric Institute, 150 pages

J.F. Kaashoek and Van Dijk HK, On the use of descriptive measures for chaos in economic time series, report 9064 of the Econometric Institute, 13 pages

1989

P. Schotman and Van Dijk HK, Bayesian analysis of the unit root hypothesis, report 8953 of the Econometric Institute, 39 pages1988

Van Dijk HK and J.P. Hop, PMMC: A set of computer programs for the computation of posterior moments and densities using Monte Carlo integration, report 8810 of the Econometric Institute, 10 pages

1986

Van Dijk HK, J.P. Hop and A.S. Louter, Some algorithms for the computation of posterior moments and densities using Monte Carlo integration, report 8625 of the Econometric Institute, 61 pages

1985

H.K. van Dijk and T. Kloek, Monte Carlo analysis of skew posterior distributions: An econometric example, The Statistician 32, 216-223 download PDF

H.K. van Dijk, Bayesian estimation methods and Bayesian statistics, in: Encyclopedia of Business Economics (in Dutch), Kluwer, Deventer

H.K. van Dijk and T. Kloek, Monte Carlo analysis of skew posterior distributions: An econometric example, The Statistician 32, 216-223 download PDF

H.K. van Dijk, Bayesian estimation methods and Bayesian statistics, in: Encyclopedia of Business Economics (in Dutch), Kluwer, Deventer

H.K. van Dijk and T. Kloek, Monte Carlo analysis of skew posterior distributions: An econometric example, The Statistician 32, 216-223 download PDF

H.K. van Dijk, Bayesian estimation methods and Bayesian statistics, in: Encyclopedia of Business Economics (in Dutch), Kluwer, Deventer

1983

H.K. van Dijk and T. Kloek, Monte Carlo analysis of skew posterior distributions: An econometric example, The Statistician 32, 216-223 download PDF

H.K. van Dijk, Bayesian estimation methods and Bayesian statistics, in: Encyclopedia of Business Economics (in Dutch), Kluwer, Deventer

1978

Van Dijk HK and T. Kloek, Posterior analysis of Klein’s Model I, report 7824 of the Econometric Institute, 26 pages

Van Dijk HK and T. Kloek, Empirical evidence on Pareto-Levy and log stable income distributions, report 7812 of the Econometric Institute, 28 pages

1975

T. Kloek and Van Dijk HK, Bayesian estimates of equation system parameters: An unorthodox application of Monte Carlo, report 7511 of the Econometric Institute, 21 pages

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