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Invited and keynote lectures
Other seminars given
Courses
Ph.D. supervision

Invited and keynote lectures

  • Dynamic Predictive Density Combinations for Large Data Sets in Economics and Finance, EABCN Conference, Norway Central Bank, June 2015
  • Developments in Big Data and Advanced Computation for Economic Research: COEURE Workshop, Brussels, July 2-3, 2015.
  • Combined Density Nowcasting in an Uncertain Economic Environment, Central Bank of Portugal, September 2014;
  • Combined Density Nowcasting in an Uncertain Economic Environment, Central Bank of Poland, November 2014;
  • How Uncertainty founds its place in Bayesian Econometrics after Cowles Foundation Monographs 10,14, ESOBE Conference in Paris, November 2014.
  • Dynamic Predictive Density Combinations for Large Data Sets in Economics and Finance, (EC)2 Conference in Barcelona, December 2014.
  • Posterior and Predictive Evidence on US Inflation using Extended New Keynesian Phillips Curve Models and Non-filtered Data, Keynote Lecture at the Conference on Computational and Financial Econometrics, London, December 2013.
  • Parallel Sequential Monte Carlo for Efficient Density Combination, The Deco Matlab Toolbox, invited paper at the 40-th Macro-Models International Conference at Warsaw, October 2013.
  • Historical Developments in Bayesian Econometrics after Cowles Foundation Monographs 10,14,  special lecture at Workshop on DSGE Models at the Philadelphia Federal Reserve Bank, October 2013.
  • Parallel Sequential Monte Carlo for Efficient Density Combination, The Deco Matlab Toolbox, Keynote speaker at the 1st Vienna Workshop on High Dimensional Time Series in Macroeconomics and Finance, May 2013.
  • Simulation based Bayes Procedures for Three 21-st Century Key Research Issues, Invited keynote speaker at the XX Annual Congress of the Portuguese Statistical Society, September 26, 2012
  • Bayes Procedures for Optimal Measurement of Policy Effects and Risk, CFE and ERCIM Conference, London, December 2011
  • Direct Monte Carlo for SEM, IV and EV models, Seminar on Bayesian Inference in Econometrics and Statistics, SBIES, Washington University, Missouri, April 2011
  • Bayes’ procedures for 21-st Century Key Issues: ESOBE Conference, Rotterdam, November 5, 2010
  • Forecast Accuracy and Economic Gains from Bayesian Model Averaging using Time Varying Weights, Eurostat conference on Business Cycles, September, 2010
  • Forecast Accuracy and Economic Gains from Bayesian Model Averaging using Time Varying Weights, Central Bank of Italy in Rome, January, 2010
  • Forecast Accuracy and Economic Gains from Bayesian Model Averaging using Time Varying Weights, Federal Reserve Bank of Philadelphia, October 2009
  • Bayesian Averaging over Many Dynamic Model Structures with Evidence on the Great Ratios and Liquidity Trap Risk, Bormio, MCMSKI/IMS Conference, Jan. 2008
  • On Reliable and Efficient Simulation for Possibly Ill-behaved Econometric Posteriors: Some Experiments with Neural Network Sampling with Applications to IV Models, Mixture Processes and Option Evaluations, Second International Conference on Computational and Financial Econometrics, CFE '08, Neuchâtel, Switzerland, 19-21 June 2008.
  • On Reliable and Efficient Simulation for Possibly Ill-behaved Econometric Posteriors: Some Experiments with Neural Network Sampling with Applications to IV Models, Mixture Processes and Option Evaluations, Rimini Conference on Bayesian Econometrics, Rimini, Italy, 2-3 June 2008.
  • Bayesian Averaging over Many Dynamic Model Structures with Evidence on the Great Ratio’s and Liquidity Trap Risk, Special workshop at Monash University, Melbourne, July 2008.
  • Model uncertainty and Bayesian model averaging in VAR processes with applications to the stability of the great ratios in the USA and the probability of a liquidity trap in the UK, German Macro-econometric conference, Organizer, J.M. Dufour, Halle, December 7, 2007
  • On Reliable and Efficient Simulation for Possibly Ill-behaved Econometric Posteriors: Some Experiments with Neural Network Sampling with Applications to IV Models, Mixture Processes and Option Evaluations, ISI Conference, Lissabon, August 2007
  • On Reliable and Efficient Simulation for Possibly Ill-behaved Econometric Posteriors: Some Experiments with Neural Network Sampling with Applications to IV Models, Mixture Processes and Option Evaluations, Special Econometric Conference, Rome, June 2007
  • Model uncertainty and Bayesian model averaging in VAR processes with applications to the stability of the great ratios in the USA and the probability of a liquidity trap in the UK, Conference on Recent Advances in Applied Econometrics, 75th Anniversary Symposium of the Japan Statistical Society, Japan, September 2006
  • Model uncertainty and Bayesian model averaging in VAR processes with applications to the stability of the great ratios in the USA and the probability of a liquidity trap in the UK, Sveriges Riksbank, Sweden, September 2006
  • Searching for the optimal posterior simulation, Seminar on Bayesian Inference in Econometrics and Statistics, University of Iowa, April 2006
  • Neural network approximations to densities: A class of flexible sampling methods with application to reduced rank models, Conference at Kyoto, December 2005
  • Valuing structure, model uncertainty and model averaging in VAR processes, Conference on Scientific Applications of Bayesian Analysis, Israel, 3-8 December 2004
  • Functional approximations to posterior densities: a neural network approach to efficient sampling, keynote lecture at Conference on Computer and Management, Neuchatel, 2 - 5 April 2004
  • Valuing structure, model uncertainty and model averaging in VAR processes, Tokyo Metropolitan University, 21th Century COE Conference: International Symposium on Financial Time Series, February/March 2004
  • On the relative merits of some flexible models for determining turning points in economic time series using Bayesian inference, Eurostat Conference on Modern Tools for Business Cycle Analysis, Eurostat, Luxemburg, October 2003
  • Distribution and mobility of wealth of nations, Faculty seminar, Berkeley, USA, October 1997
  • Invited lecture at Australasian Meeting of the Econometric Society, Visiting Scholar University of Western Australia, Perth, June 1996
  • Bayesian analysis of simultaneous equation models using noninformative priors, Australian meeting of the Econometric Society, Armidale, Australia, July 1994
  • Distinguished guest lecture, University of Pennsylvania, April 1993
  • On the shape of the likelihood/posterior of cointegration models, Yale Conference on Bayes Methods and Unit Roots, USA, April 1992
  • SISAM and MIXIN, Two algorithms for the evaluation of posterior moments and densities using Monte Carlo integration, International Institute of Statistician’s conference Cairo, Egypt, September 1991
  • Some algorithms for the computation of posterior moments and densities using Monte Carlo integration, Invited address at the Franco-Belgian meeting of statisticians, Rouen, France, November 1986
  • Experiments with some alternatives for simple importance sampling in Monte Carlo integration, Second International Meeting on Bayesian Statistics, Valencia, Spain, June 1983.
  • Bayesian estimates of equation system parameters, An application of integration by Monte Carlo, First European Congress on foundations and applications of Bayesian methods, Fontainebleau, France, June 1976

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Other seminars given

2016

  • Dynamic Predictive Density Combinations for Large Data Sets in Economics and Finance, 
    Brandeis University, USA, January 2016.

2015

  • Dynamic Predictive Density Combinations for Large Data Sets in Economics and Finance, CFE Conference, Birbeck College, London, December 2015.
  • Dynamic Predictive Density Combinations for Large Data Sets in Economics and Finance,  Econometric Institute, Rotterdam, November 2015.
  • Dynamic Predictive Density Combinations for Large Data Sets in Economics and Finance,  ESOBE Conference, Swiss Finance Institute, Gerzensee, October 2015.
  • Dynamic Predictive Density Combinations for Large Data Sets in Economics and Finance,  World Congress Econometric Society, Montreal, August 2015.
  • How Uncertainty founds its place in Bayesian Econometrics after Cowles Foundation Monographs 10,14, Workshop on Bayesian Econometric Forecasting and Policy Analysis, Rotterdam, June 2015.
  • Dynamic Predictive Density Combinations for Large Data Sets in Economics and Finance,  University of Technology Sydney; April 2015.
  • Dynamic Predictive Density Combinations for Large Data Sets in Economics and Finance, Monash University, Melbourne, April 2015.
  • Bayesian Estimation of Multimodal Density Features applied to DNA and Economic Data, University of Melbourne, Business School, April 2015.
  • Bayesian Estimation of Multimodal Density Features applied to DNA and Economic Data, Ca’Foscari University, Economics Department, Venice, March 2, 2015.

2014

  • Dynamic Predictive Density Combinations for Large Data Sets in Economics and Finance, Conference on Computational and Financial Econometrics, December 2014;
  • Combined Density Nowcasting in an Uncertain Economic Environment, Federal Reserve Bank of Philadelphia, October 2014;
  • On the Interaction of US and Eurozone Booms and Busts: A Bayesian Panel Markov-switching Model University of Pennsylvania, October 2014;
  • Combined Density Nowcasting in an Uncertain Economic Environment, Columbia University, October 2014;
  • On the Interaction of US and Eurozone Booms and Busts: A Bayesian Panel Markov-switching Model, ESEM Conference Toulouse, August 2014;
  • Combined Density Nowcasting in an Uncertain Economic Environment, Forecasting Conferen ce, Rotterdam, June 2014;
  • Combined Density Nowcasting in an Uncertain Economic Environment, IAAE Conference,  Queen Mary College,  London, June 2014.
  • Posterior and Predictive Evidence on US Inflation using Phillips Curve Models and Non-filtered series, University of Bern, February 2014.
  • Parallel Sequential Monte Carlo for Efficient Density Combination, The Deco Matlab, Harvard University, IQSS, March 2014.
  • Posterior and Predictive Evidence on US Inflation using Phillips Curve Models and Non-filtered series, Harvard University, Economics Department, March 2014.
  • Posterior and Predictive Evidence on US Inflation using Phillips Curve Models and Non-filtered series, Conference at Camp Econometrics, Watkins Glenn, April 2014.

2013

  • Posterior and Predictive Evidence on US Inflation using Phillips Curve Models and Non-filtered series, Federal Reserve Bank of Chicago, October 2013.
  • Parallel Sequential Monte Carlo for Efficient Density Combination, The Deco Matlab Toolbox, Booth School of Business, University of Chicago, October 2013.
  • Posterior and Predictive Evidence on US Inflation using Phillips Curve Models and Non-filtered series, Boston College, September 2013.
  • Posterior and Predictive Evidence on US Inflation using Phillips Curve Models and Non-filtered series, MIT, September 2013.
  • Parallel Sequential Monte Carlo for Efficient Density Combination, The Deco Matlab Toolbox, Harvard, September 2013.
  • Parallel Sequential Monte Carlo for Efficient Density Combination, The Deco Matlab Toolbox, at Conference on Forecasting Structure and Time Varying Patterns in Economics and Finance, Rotterdam, May 2013.
  • Posterior and Predictive Evidence on US Inflation using Phillips Curve Models and Non-filtered series, University of Venice, March 2013.
  • Posterior and Predictive Evidence on US Inflation using Phillips Curve Models and Non-filtered series, Tripartite Conference, Wharton School, Philadelphia, May 2013.

2012

  • Time-varying combinations of predictive densities using nonlinear filtering, EC2, Maastricht University, December 2012
  • Posterior and Predictive Evidence on US Inflation using Phillips Curve Models and Non-filtered series, Tinbergen Institute Amsterdam, November 2012
  • Posterior and Predictive Evidence on US Inflation using Phillips Curve Models and Non-filtered series, Atlanta Federal Reserve Bank, Workshop on DSGE Models, October 2012
  • Simulation based Bayes Procedure for Three 21-st Century Key Research Issues, Info-Metrics, American University, April 2012
  • Bayes Procedures for 21-st Century Key Issues, Finnish School of Economics, Helsinki, May, 2012
  • Key Issues of the 21-st Century, A Simulation-based Predictive Analysis, MIT, April 2012
  • Bayes Procedures for 21-st Century Key Issues, MIT Economics Department, April, 2012
  • Combining Predictive Densities using Nonlinear Filtering with an Applications to US Economics Data, Boston University, April 2012
  • Combining Predictive Densities using Nonlinear Filtering with an Applications to US Economics Data, Federal Reserve Bank of New York, April 2012
  • Key Issues of the 21-st Century, A Simulation-based Predictive Analysis, Info-Metrics, American University, April 2012.

2011

  • Discussant of Patton Timmerman JBES lecture at the ASSA meetings, Denver, January, 2011
  • Bayes Procedures for 21-st Century Key Issues, Albany University, April 2011
  • A predictive likelihood approach to possible endogeneity in IV models: Application using US Income-Education Data, Harvard Economics Department, April 2011
  • A predictive likelihood approach to possible endogeneity in IV models: Application using to US Income-Education Data, MIT Economics Department, April 2011
  • A class of adaptive EM based algorithms for efficient and robust posterior and predictive simulation, Harvard Statistics Department, April, 2011
  • A class of adaptive EM based algorithms for efficient and robust posterior and predictive simulation, Cowles Foundation Conference on Econometrics, June, 2011
  • Evidence on Features of DSGE Business Cycles Models using Bayesian Averaging, Cambridge Conference in Honor of Pesaran, July 2011
  • A predictive likelihood approach to possible endogeneity in IV models: Application using to US Income-Education Data, JeuBES, Norges Bank, August, 2011
  • Simulation based Bayes Procedures for Three 21-st Century Key Research Issues, Wharton School, Department of Statistics, October 2011
  • Combining Predictive Densities using Nonlinear Filtering with an Applications to US Economics Data, University of Pennsylvania, October 2011
  • A predictive likelihood approach to possible endogeneity in IV models: Application using to US Income-Education Data, Princeton University, October 2011,
  • A predictive likelihood approach to possible endogeneity in IV models: Application using to US Income-Education Data, Ecares, Brussel, November 2011

2010

  • Prior Ignorance, Normalization and Reduced Rank Probabilities in Cointegration Models, EC-2 Conference, December, Toulouse
  • A class of adaptive EM algorithms for efficient and robust posterior and predictive simulation, Econometric Society World Congress, Shanghai, August, 2010
  • A class of adaptive EM algorithms for efficient and robust posterior and predictive simulation, Cambridge University, June 2010
  • A class of adaptive EM algorithms for efficient and robust posterior and predictive simulation, Harvard University, April 2010
  • A class of adaptive EM algorithms for efficient and robust posterior and predictive simulation, MIT, April 2010
  • A class of adaptive EM algorithms for efficient and robust posterior and predictive simulation, Chicago Booth, April 2010

2009

  • Bayesian Averaging over Many Dynamic Model Structures with Evidence on the Great Ratio’s and Liquidity Trap Risk, IMF, October 2009, Washington
  • Possibly Ill-behaved Posteriors in Econometric Models: On the Connection between Model Structures, Non-elliptical Credible Sets and Neural Network Simulation Techniques, August, ESEM 2009, Barcelona
  • Possibly Ill-behaved Posteriors in Econometric Models: On the Connection between Model Structures, Non-elliptical Credible Sets and Neural Network Simulation Techniques, Journal of Applied Econometrics Conference, Lake Placid, March 2009
  • “Bayesian Forecasting of Value at Risk and Expected Shortfall using Adaptive Importance Sampling, April 2009, University of Pennsylvania
  • “Bayesian Forecasting of Value at Risk and Expected Shortfall using Adaptive Importance Sampling, Netherlands Day of Econometrics, University of Amsterdam, June, 2009

2008

  • Bayesian Averaging over Many Dynamic Model Structures with Evidence on the Great Ratio’s and Liquidity Trap Risk, 3M workshop, March 2008, Rotterdam
  • Bayesian Averaging over Many Dynamic Model Structures with Evidence on the Great Ratio’s and Liquidity Trap Risk. ECB, April 2008, Frankfurt
  • Possibly Ill-behaved Posteriors in Econometric Models: On the Connection between Model Structures, Non-elliptical Credible Sets and Neural Network Simulation Techniques, GSB Chicago, April 2008
  • Bayesian Averaging over Many Dynamic Model Structures with Evidence on the Great Ratio’s and Liquidity Trap Risk. SBIES, May 2008
  • Possibly Ill-behaved Posteriors in Econometric Models: On the Connection between Model Structures, Non-elliptical Credible Sets and Neural Network Simulation Techniques, Rimini, June 2008
  • Changing distributions using nonlinear state space models, Paris, Comp. Econ Conference, June 2008
  • Possibly Ill-behaved Posteriors in Econometric Models: On the Connection between Model Structures, Non-elliptical Credible Sets and Neural Network Simulation Techniques, ISBA, July 2008
  • Bayesian Averaging over Many Dynamic Model Structures with Evidence on the Great Ratio’s and Liquidity Trap Risk, Brisbane, July 2008
  • Bayesian Averaging over Many Dynamic Model Structures with Evidence on the Great Ratio’s and Liquidity Trap Risk, New York Fed, 11 sept. 2008
  • Forecasting Value at Risk, University of Venice, October 2008,
  • Bayesian Averaging over Many Dynamic Model Structures with Evidence on the Great Ratio’s and Liquidity Trap Risk, EUI, November 21, 2008

2007

  • Bayesian near-boundary analysis of basic economic time series model, International Workshop on Computational and Financial Econometrics, Geneva, April 20-22, 2007
  • Predictive gains from forecast combinations using time-varying model weights, CEF conference, Neuchatel, April 2007
  • Diffuse priors and well defined Bayes factors applied in Bayesian model averaging in econometrics, The Sixth International Workshop on Objective Bayes Methodology, Rome, June 9-12, 2007
  • Searching for perfect candidate densities using neural networks in Bayesian econometric models, Conference on ”Parametric and non parametric estimation and prevision of the dynamics of conditional moments of time series”, Rome, June 14-16, 2007
  • 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, and Weakly informative priors and well behaved Bayes Factors, O’Bayes Conference, Rome, June 2007
  • 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, ESEM 2007, Budapest, August 2007
  • On Reliable and Efficient Simulation for Possibly Ill-behaved Econometric Posteriors: Some Experiments with Neural Network Sampling with Applications to IV Models, Mixture Processes and Option Evaluations, Montreal, October 2007
  • On Reliable and Efficient Simulation for Possibly Ill-behaved Econometric Posteriors: Some Experiments with Neural Network Sampling with Applications to IV Models, Mixture Processes and Option Evaluations, Lunch Seminar, Harvard, October 2007
  • On Reliable and Efficient Simulation for Possibly Ill-behaved Econometric Posteriors: Some Experiments with Neural Network Sampling with Applications to IV Models, Mixture Processes and Option Evaluations, Louisiana State University, November 2007

2006

  • A Bayesian perspective on estimating returns to education: A reconsideration of the Angrist-Krueger Analysis, Brown University, April 2006
  • A Bayesian perspective on estimating returns to education: A reconsideration of the Angrist-Krueger Analysis, Seminar on Bayesian Inference in Econometrics and Statistics, University of Iowa, April 2006
  • A Bayesian perspective on estimating returns to education: A reconsideration of the Angrist-Krueger Analysis, Princeton University, May 2006
  • Searching for the optimal posterior simulator, 8-th Valencia Meeting, May/June 2006
  • Neural networks and option pricing, 12-th Conference on Computational Economics and Finance, Cyprus, June 2006
  • Bayesian perspective on estimating returns to education: A reconsideration of the Angrist-Krueger Analysis, Hitotsubashi University, Tokyo, September 2006
  • Bayesian perspective on estimating returns to education: A reconsideration of the Angrist-Krueger Analysis, NAKE Research Day, Netherland Central Bank, Amsterdam, October 2006
  • Bayesian near-boundary analysis of basic economic time series model, International Workshop on Computational and Financial Econometrics, Geneva, April 20-22, 2007

2005

  • Functional approximations to posterior densities: a neural network approach to efficient sampling, Convegno Statistica, Bormio, Italy, 11-15 January 2005
  • Cyclical components in economic time series: a Bayesian approach, Sveriges Riksbank,
  • February 2005
  • Model uncertainty and Bayesian model averaging in vector autoregressive processes, CORE, February 2005
  • 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, Econometric Society World Meeting, London, August 2005
  • 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, London School of Economics, October 2005
  • Gibbs sampling in econometric practice, World Meeting of International Association of Scientific Computing, Cyprus, October 2005
  • Model uncertainty and Bayesian model averaging in vector autoregressive processes, Tokyo University, December 2005

2004

  • Functional approximations to posterior densities: a neural network approach to efficient sampling, School of Economics, Stockholm, January 2004
  • Bayesian Cyclical Decompositions with Applications, Tohuku University, Sendai, Japan, March 2004
  • Cyclical components in economic time series: a Bayesian approach ESAM, Melbourne, 10-12 July 2004
  • Cyclical components in economic time series: a Bayesian approach ISF Conference, Sydney, 4-7 July 2004
  • Improper priors with well defined Bayes factors, ESEM Madrid, 20-24 August 2004
  • Valuing structure, model uncertainty and model averaging in VAR processes, EUI, Florence, 14-19 October 2004
  • Neural network approximations to densities: A class of flexible sampling methods with applications to reduced rank models, Katholieke Universiteit Leuven, November 2004

2003

  • On Radial-based adaptive direction sampling, section on Bayesian statistical science, American Statistical Association Meeting, San Francisco, August 2003
  • Functional approximations to posterior densities: a neural network approach to efficient sampling, Econometric Society European Meeting, Stockholm, August 2003
  • Bayesian Cyclical Decompositions with Applications, Conference on Econometric Time Series, Linz, October 2003
  • Functional approximations to posterior densities: a neural network approach to efficient sampling, (EC)2 Conference, London, December 2003

2002

  • On the value of structural information in a VAR model, ESEM meeting, Venice, August 2002
  • On Adaptive Polar sampling: a flexible and robust Monte Carlo method, SAMSI, Triangle Research Park, North Carolina, October 2002
  • On Bayes estimates of Markov trends in possibly cointegrated series: an application to US consumption and income, Aarhus, October 2002

2001

  • Comparison of the Anderson-Rubin test for overidentification and the Johansen test for cointegration, EC-2, March 2001, Cambridge
  • Daily exchange rate behaviour and hedging of currency risk, Cambridge (UK), March 2001
  • Adaptive polar sampling: a new MCMC method for ill-behaved posterior surfaces, March 2001, Cambridge
  • Bayes estimates of Markov trends in possibly cointegrated series: an application to US consumption and income, University of Liverpool, May 2001
  • Bayes estimates of Markov trends in possibly cointegrated series: an application to US consumption and income, Marseille, June 2001
  • On Bayesian structural inference in a simultaneous equation model, October 2001, Liverpool

2000

  • Daily exchange rate behavior and hedging of currency risk, UCLA, USA, April 2000
  • Daily exchange rate behavior and hedging of currency risk, UC-Irvine, USA, April 2000
  • Daily exchange rate behavior and hedging of currency risk, UC-San Diego, USA, May 2000.
  • Daily exchange rate behavior and hedging of currency risk, ISBA Meeting, Crete, May 2000
  • Adaptive polar sampling: a new MCMC method for ill-behaved posterior surfaces, Computing in Economics and Finance, Barcelona, July 2000
  • Adaptive polar sampling: a new MCMC method for ill-behaved posterior surfaces, COMPSTAT, 14th Symposium, Utrecht, August 2000
  • Comparison of the Anderson-Rubin test for overidentification and the Johansen test for cointegration, EC-2, December 2000, Dublin

1999

  • Bayes estimates of Markov trends in possibly cointegrated series: an application to US consumption and income, Carlos III, April 1999
  • Bayes estimates of Markov trends in possibly cointegrated series: an application to US consumption and income, Universit'e Libre de Bruxelles, May 1999
  • Bayes estimates of Markov trends in possibly cointegrated series: an application to US consumption and income, ESEM, Santiago di Compostella, 1999
  • Daily exchange rate behaviour and hedging of currency risk, EC2, Madrid, December 1999

1998

  • Testing for integration using evolving trend and seasonal models: A Bayesian Approach, Oslo, June, 1998
  • Bayes estimates of Markov trends in possibly cointegrated series: an application to US consumption and income, Stockholm, June, 1998
  • Bayes estimates of Markov trends in possibly cointegrated series: an application to US consumption and income, ESEM, Berlin, 1998
  • Testing for integration using evolving trend and seasonal models: A Bayesian Approach, Edinburgh, April 1998
  • Neural network analysis of varying trends in real exchange rates, (EC)2, Stockholm, December 1998

1997

  • Bayesian analysis of stochastic trends in structural time series models, Stockholm, April 1997
  • Testing for integration using evolving trend and seasonal models: A Bayesian Approach, ESEM, Toulouse, August 1997.
  • Bayesian simultaneous equations analysis using reduced rank structures, Montreal, Canada, October 1997
  • Distribution and mobility of wealth of nations, Washington, Seattle, October 1997

1996

  • Bayesian analysis of stochastic trends in structural time series models, Chicago, ISBA meeting, August 1996
  • Distribution and mobility of wealth of nations, Australian Meeting, 1996
  • Bayesian analysis of stochastic trends in structural time series models, ESEM, Istanbul, August 1996

1995

  • Distribution and mobility of wealth of nations, Workshop on Time Series Econometrics, Aarhus, Denmark, 1995
  • Distribution and mobility of wealth of nations, World Congress of the Econometric Society, Tokyo, Japan, 1995
  • Distribution and mobility of wealth of nations, European University Institute, Florence, Italy, 1995
  • Distribution and mobility of wealth of nations, (EC)2 Conference, Aarhus, Denmark, 1995

1994

  • On the shape of the likelihood/posterior of cointegration models; Direct cointegration testing in error-correction models, University of Bristol, UK, May 1994
  • On the shape of the likelihood/posterior of cointegration models; Direct cointegration testing in error-correction models, University of Exeter, UK, May 1994
  • On the shape of the likelihood/posterior of cointegration models; Direct cointegration testing in error-correction models, University of Lausanne, Switzerland, May 1994
  • On the shape of the likelihood/posterior of cointegration models, Fourth international meeting on Bayesian statistics, Valencia, Spain, June 1994
  • Classical and Bayesian aspects of robust unit root Inference, Meeting of International Society of Forecasting, Stockholm, Sweden, June 1994
  • A Bayesian analysis of the unit root in real exchange rates, University of New England, Armidale, Australia, July 1994
  • On the shape of the likelihood/posterior of cointegration models; Direct cointegration testing in error-correction models, University of New England, Armidale, Australia, July 1994
  • SISAM and MIXIN, Two algorithms for the evaluation of posterior moments and densities using Monte Carlo integration, University of New South Wales, Sydney, Australia, July 1994
  • A Bayesian analysis of the unit root in real exchange rates, University of New South Wales, Sydney, Australia, August 1994
  • Direct cointegration testing in error-correction models, University of New South Wales, Sydney, Australia, August 1994
  • On the shape of the likelihood/posterior of cointegration models; Direct cointegration testing in error-correction models, Australian National University, Canberra, Australia, July 1994
  • On the shape of the likelihood/posterior of cointegration models; Direct cointegration testing in error-correction models, Monash University, Melbourne, Australia, August 1994
  • On the shape of the likelihood/posterior of cointegration models; Direct cointegration testing in error-correction models, University of Sydney, Sydney, Australia, August 1994
  • On the shape of the likelihood/posterior of cointegration models; Direct cointegration testing in error-correction models, University of Western Australia, Perth, Australia, September 1994
  • Distribution and mobility of wealth of nations, (EC)2 Conference, Berlin, December 1994

1993

  • On the shape of the likelihood/posterior of cointegration models, Malinvaud Seminar, CREST/INSEE, Paris, February 1993
  • Direct cointegration testing in error-correction models; Bayesian simultaneous equation model analysis: On the existence of structural posterior moments, The University of Michigan, USA, March 1993
  • On the shape of the likelihood/posterior of cointegration models; Direct cointegration testing in error-correction models, University of Southern California, USA, March 1993
  • On the shape of the likelihood/posterior of cointegration models; Direct cointegration testing in error-correction models, University of California, San Diego, March 1993
  • On the shape of the likelihood/posterior of cointegration models, University of Pennsylvania, Philadelphia, USA, March/April 1993
  • On the shape of the likelihood/posterior of cointegration models, Erasmus University, Dept. of Mathematics, March 1993
  • On the shape of the likelihood/posterior of cointegration models; Direct cointegration testing in error-correction models, Brown University, Providence, USA, April 1993
  • Direct cointegration testing in error-correction models, Harvard/MIT, Cambridge, USA, April 1993
  • On the shape of the likelihood/posterior of cointegration models, First Multinational Conference on Bayesian Econometrics and Statistics, Basel-Amsterdam, April/May 1993
  • On the shape of the likelihood/posterior of cointegration models, Nuffield College, Oxford, May 1993
  • On the shape of the likelihood/posterior of cointegration models; Direct cointegration testing in error-correction models, University of Groningen, June 1993
  • Direct cointegration testing in error-correction models, ESEM, Uppsala, Sweden, August 1993
  • Direct cointegration testing in error-correction models, NBER/NSF Time Series Seminar, Vienna, Austria, October 1993
  • Direct cointegration testing in error-correction models, Real Time Econometrics, XXXIXth Conference, Eurostat Luxemburg, October 1993
  • On the shape of the likelihood/posterior of cointegration models, International Symposium on Exploration of Informational Aspects of Bayesian Statistics, Yamanashi, Japan, December 1993

1992

  • Bayes Estimates of multi-criteria decision alternatives using Monte Carlo integration, University of Basel, Switzerland, February 1992
  • Bayesian simultaneous equation model analysis: On the existence of structural posterior moments, CORE, University Catholique de Louvain, Belgium, March, 1992
  • Non-stationarity in GARCH models: A Bayesian analysis, Conference on Econometric Inference using Simulation Techniques, Rotterdam, The Netherlands, June 1992
  • On the shape of the likelihood/posterior of cointegration models, Conference on Classical and Bayesian Analysis of Dynamic Econometric Models, Marseille, France, June 1992
  • On Bayesian routes to unit roots; Bayesian simultaneous equation model analysis: On the existence of structural posterior moments, Yale Econometrics Seminar, USA, May 1992
  • On Bayesian routes to unit roots; Bayesian simultaneous equation model analysis: On the existence of structural posterior moments, Yale Graduate Students Seminar, USA, May 1992
  • On the shape of the likelihood/posterior of cointegration models, Econometrics and Statistics Colloquium, University of Chicago, USA, May 1992
  • Bayesian simultaneous equation model analysis: On the existence of structural posterior moments, ESEM, Brussels, Belgium, September 1992
  • On Bayesian routes to unit roots; On the shape of the likelihood/posterior of cointegration models, University of Kopenhagen, Denmark, November 1992
  • On Bayesian routes to unit roots; On the shape of the likelihood/posterior of cointegration models, (EC), Paris, December 1992

1991

  • On Bayesian routes to unit roots, JOG; Dutch research group, February 1991, CBS, The Hague, The Netherlands; On Bayesian routes to unit roots, University of Amsterdam; Katholieke Universiteit Leuven; CORE; University of Limburg in Maastricht, all in March 1991
  • On Bayesian routes to unit roots, Econometric analysis of Unit Roots, Paris, France, May 1991
  • On Bayesian routes to unit roots; SISAM and MIXIN, Two algorithms for the evaluation of posterior moments and densities using Monte Carlo integration; Bayesian simultaneous equation model analysis: On the existence of structural posterior moments, Conference of Society of economics, dynamics and control, Capri, Italy, June 1991
  • A neural network applied to the calculation of Lyapunov exponents, Meeting of the European Economic Association, Cambridge, UK, September 1991
  • Efficient computer generation of matric-variate t drawings with an application to Bayesian estimation of simple market model, Franco-Belgian meeting of statisticians, CORE, Louvain-la-Neuve, Belgium, November 1991
  • On Bayesian routes to unit roots, CentER, Catholic University Brabant, Tilburg, The Netherlands, November 1991

1990

  • Bayesian analysis of the unit root hypothesis, report 8953 of the Econometric Institute London School of Economics, United Kingdom, January 1990
  • A Bayesian analysis of the unit root in real exchange rates, GREQE-EHESS Marseille, France, February 1990
  • A Bayesian analysis of the unit root in real exchange rates, National research day in economics, Groningen, The Netherlands, May 1990
  • A Bayesian analysis of the unit root in real exchange rates; Bayes Estimates of multicriteria decision alternatives using Monte Carlo integration, GREQE/EHESS, Marseille, France, November 1990
  • A Bayesian analysis of the unit root in real exchange rates; Bayes Estimates of multicriteria decision alternatives using Monte Carlo integration, GREMAQ, University of Toulouse, France, November 1990
  • Bayes Estimates of multi-criteria decision alternatives using Monte Carlo integration, and A Bayesian analysis of the unit root in real exchange rates, University of Aarhus, Denmark, May 1990
  • Modelling relative price variability and aggregate inflation in the United Kingdom 51 Conference on macro-economic modelling, Ebeltoft, Denmark, May 1990
  • Bayes Estimates of multi-criteria decision alternatives using Monte Carlo integration, and A Bayesian analysis of the unit root in real exchange rates, University of Minnesota, USA, IMA conference on Time Series, July 1990
  • On Bayesian routes to unit roots, (EC)2 Conference, December 1990, Amsterdam, The Netherlands

1989

  • Bayesian analysis of the unit root hypothesis, report 8953 of the Econometric Institute CORE, Louvain-la-Neuve, Belgium, April 1989
  • Bayesian analysis of the unit root hypothesis, report 8953 of the Econometric Institute GREQE/EHESS, Marseille, France, April 1989
  • Bayesian analysis of the unit root hypothesis, report 8953 of the Econometric Institute Cornell, Ithaca, USA, July 1989
  • Bayesian analysis of the unit root hypothesis, report 8953 of the Econometric Institute ESEM, Munich, Germany, September 1989

1988

  • Bayesian specification analysis and estimation of simultaneous equation models using Monte Carlo method, Institute of Statistics and Decision Sciences, Duke University, USA, February 1988
  • Bayesian specification analysis and estimation of simultaneous equation models using Monte Carlo method, Econometrics and Statistics Colloquium University of Chicago, USA, April 1988
  • Bayesian specification analysis and estimation of simultaneous equation models using Monte Carlo method, NBER/NSF, Seminar on Bayesian inference in econometrics, University of Michigan, USA, April 1988
  • Bayesian estimation of the weights of a multicriteria decision model using Monte Carlo integration, Fuqua School of Business, Duke University, USA, April 1988
  • A set of computer programs for the computation of posterior moments and densities using Monte Carlo integration, Dutch Research group on computer software, November 1988

1987

  • Bayesian specification analysis and estimation of simultaneous equation models using Monte Carlo method; Comment on Computation in Bayesian statistics, Valencia meeting on Bayesian statistics, Spain, June 1987
  • National Research Day, University of Amsterdam, The Netherlands, May 1987
  • Some advances in Bayesian analysis using Monte Carlo integration, ESEM, Kopenhagen, Denmark, August 1987
  • Bayesian specification analysis and estimation of simultaneous equation models using Monte Carlo methods, ESEM, Kopenhagen, Denmark, August 1987
  • Bayesian specification analysis and estimation of simultaneous equation models using Monte Carlo method, CORE, Louvain-la-Neuve, Belgium, October 1987

1986

  • Likelihood diagnostics and Bayesian analysis of a micro-economic disequilibrium model for retail services; Bayesian specification analysis and estimation of simultaneous equation models using Monte Carlo methods, Research meeting on equilibrium and disequilibrium analysis, University of Amsterdam, The Netherlands, April 1986
  • A note on simple algebraic relations between structural and reduced form parameters, Econometric Institute, April 1986
  • Existence conditions for posterior moments of simultaneous equation model parameters, CORE, Louvain-la-Neuve, Belgium, April 1986
  • Existence conditions for posterior moments of simultaneous equation model parameters, National research day in economics, Tilburg University, The Netherlands, May 1986
  • Some algorithms for the computation of posterior moments and densities using Monte Carlo integration, ISI’s second international conference on practical Bayesian Statistics, Cambridge, UK, July 1986
  • A product of multivariate t densities as upper bound for the posterior kernel of simultaneous equation model parameters, International Symposium on Probability and Bayesian Statistics, Cambridge, UK, July 1986
  • Existence conditions for posterior moments of simultaneous equation model parameters; A note on simple algebraic relations between structural and reduced form parameters, ESEM, Budapest, Hungary, September 1986

1985

  • Posterior moments computed by mixed integration, NBER-NSF Seminar on Bayesian Inference in Econometrics, May 1985, Federal Reserve Bank, Minneapolis, USA
  • Likelihood diagnostics and Bayesian analysis of a micro-economic disequilibrium model for retail services, Econometrics and Statistics Colloquium, University of Chicago, USA, May 1985
  • Posterior moments computed by mixed integration; Likelihood diagnostics and Bayesian analysis of a micro-economic disequilibrium model for retail services, Cornell University, Ithaca, USA, October 1985
  • Posterior moments computed by mixed integration; Likelihood diagnostics and Bayesian analysis of a micro-economic disequilibrium model for retail services, Princeton University, USA, October 1985
  • Posterior moments computed by mixed integration; Likelihood diagnostics and Bayesian analysis of a micro-economic disequilibrium model for retail services, Carnegie Mellon University, Pittsburgh, USA, November 1985
  • Posterior moments computed by mixed integration; Likelihood diagnostics and Bayesian analysis of a micro-economic disequilibrium model for retail services, State University of New York at Albany, USA, November 1985
  • Existence conditions for posterior moments of simultaneous equation model parameters, Harvard-MIT econometrics seminar, USA, November 1985
  • A note on simple algebraic relations between structural and reduced form parameters, Econometrics and Statistics Colloquium, University of Chicago, USA, November 1985
  • Existence conditions for posterior moments of simultaneous equation model parameters, University of Michigan at Ann Harbor, USA, December 1985

1984

  • Experiments with some alternatives for simple importance sampling in Monte Carlo integration, University of Manchester, UK, June 1984

1983

  • Experiments with some alternatives for simple importance sampling in Monte Carlo integration, National research day in economics, Leiden, The Netherlands, March, 1983
  • Experiments with some alternatives for simple importance sampling in Monte Carlo integration, JOG research group, Free University, Amsterdam, The Netherlands, September 1983

1981

  • Some alternatives for simple importance sampling in Monte Carlo integration, ESEM, Amsterdam, The Netherlands, August/September 1981

1980

  • Further experience in Bayesian analysis using Monte Carlo integration, World meeting of the Econometric Society, Aix-en-Provence, France, August/September 1980

1978

  • Further experience in Bayesian analysis using Monte Carlo integration, ESEM, Geneva, Switzerland, 1978

1977

  • Likelihood diagnostics and posterior analysis of Klein’s Model I, ESEM, Vienna, Austria, September 1977
  • Likelihood diagnostics and posterior analysis of Klein’s Model I, NBER-NSF Seminar on Bayesian Inference in Econometrics, Wisconsin, USA, October 1977

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Courses

  • PhD course in Simulation-based Bayesian Econometrics, Econometric and Tinbergen Institutes, June 2015.
  • PhD course in Simulation-based Bayesian Econometrics, University of Bern, February, 2014.
  • PhD course in Simulation-based Bayesian Econometrics, Finnish Doctoral Program, May 2012
  • PhD course in Simulation-based Bayesian Econometrics, Tinbergen Institute, June, 2012Introduction to Bayesian Macro-econometrics, Tinbergen Institute, June, 2012
  • Simulation based Bayesian Econometrics, Finnish Doctoral Program, Helsinki, May 2012
  • Simulation based Bayesian Econometric inference, European University Institute, November, 2008
  • Simulation based Bayesian Econometric inference, Princeton University Press/Econometric Institute Lectures, June, 2008
  • Kalman Filters and Dynamic Stochastic General Equilibrium Models, Princeton University Press/Econometric Institute Lectures, June, 2007
  • Simulation based Bayesian Econometric inference, Master program Econometrics and Management Science, Econometric Institute, Fall 2004
  • Graduate course on Bayesian Analysis of Dynamic Econometric Models using Monte Carlo, NAKE, Spring 2002
  • Graduate course on Bayesian Analysis of Dynamic Econometric Models using Monte Carlo, Tinbergen Institute, Fall 2001, Fall 2002, 2003
  • Mphil course on Bayesian analysis of dynamic econometric models using Monte Carlo integration methods, Faculty of Economics and Political Science, University of Cambridge, Lent term 2001
  • Undergraduate course in introductory econometrics, Faculty of Economics and Political Science, University of Cambridge, Lent term 2001
  • Graduate course on Limited Dependent Variables Models, Tinbergen Institute, Fall 2000
  • Graduate course on Markov chain Monte Carlo, Tinbergen Institute, Spring 1999
  • Graduate course in financial econometrics, Tinbergen Institute, Spring 1998 (jointly with F. Kleibergen and H.P. Boswijk)
  • Graduate course in applied dynamic models, Tinbergen Institute, 1997 (jointly which H.P. Boswijk)
  • Graduate course in Inference in dynamic econometric models, Dutch Ph.D. program, spring 1995 (jointly with H.P. Boswijk)
  • Course in applied econometrics University of New South Wales, summer 1994
  • Course in Bayesian econometrics at the Italian Summer School in econometrics, June 1990
  • Graduate course in Bayesian econometrics at the Dutch Ph.D. program in Quantitative Economics, April-May 1990; May 1994
  • Course in intermediate mathematical statistics at Cornell University, USA, 1989
  • Course in intermediate mathematical statistics at the Institute of Statistics and Decision Sciences, Duke University and an introductory course in econometrics in the Economics Department at Duke, 1988
  • Graduate courses in econometrics at the Universite Catholique de Louvain in Belgium, 1986-1989
  • Undergraduate and graduate courses in statistical methods of econometrics, applied econometrics and workshop courses in econometrics at Erasmus University, 1972-2005
  • Introductory macro- and micro-economics, money and banking, intermediate microeconomics courses at SUNY at Buffalo (USA), 1970-1972

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Ph.D. supervision

  • A. van Oord, Essays on Momentum Strategies in Finance, May 2016.
  • R.H. Kleijn, Essays on Bayesian Model Averaging using Economic Time Series, January 2016.
  • Lukasz Gatarek, Econometric Contributions to Financial Trading, Hedging and Risk Measurement, Tinbergen PhD thesis, May 2014.S.
  • Pinar Ceyhan, Essays on Bayesian Analysis of Time Varying Patterns in Economics,  Tinbergen PhD thesis, September 2014.
  • N. Basturk, Essays on Parameter Heterogeneity and Model Uncertainty, October 2010, supervisor on 2 chapters.
  • F. Ravazzolo, Forecasting Financial Time Series using Model Averaging, November 2007
  • L.F. Hoogerheide, Essays on Neural Network Sampling Methods and Instrumental Variables, 2006
  • R. van Oest, Essays on Quantitative Marketing and Monte Carlo Integration Methods, 2005
  • C.Bos, 2001, ’Time Varying Parameter Models in Inflation and Exchange Rates’
  • J.J.J. Groen, 2000, ‘Testing Multi-Country Exchange Rate Models’
  • R. Paap, 1997, ’Markov Trends in Macroeconomic Time Series’
  • H. Hoek, 1997, ’Variable Trends - A Bayesian Perspective’
  • F.R. Kleibergen, 1994, ’Identifiability and Nonstationarity in Classical and Bayesian Econometrics’
  • J.P. Urbain, 1992, ’Exogeneity in Error Correction Models’

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