prof.dr. (Richard) R Paap

Biography

Richard Paap is a professor of Econometrics at Econometric Institute, Erasmus School of Economics (ESE). He obtained his PhD from the same school in 1997. His research concerns the application of econometric models in marketing and macroeconomics using Bayesian and frequentist approaches. He has publications in several major econometric, economic and marketing journals and he is coauthor of the book Quantitative Models in Marketing Research. He is currently Academic Director of the Master Econometrics.

Erasmus School of Economics

Full professor | Econometrics
Email
paap@ese.eur.nl

Work

  • Richard Paap & Dick van Dijk (28 december 2022) - New Data from Koc University Illuminate Research in Economics (Modeling and estimation of synchronization in size-sorted portfolio returns)

  • Richard Paap (2008) - Computational Statistics & Data Analysis (Journal)
  • Richard Paap (2002) - Statistica Neerlandica (Journal)

Erasmus Q Intelligence

Start date approval
november 2022
End date approval
november 2025
Place
ROTTERDAM
Description
Consultancy voor EQI (Erasmus BV)

Bayesian Econometrics

Level
Master
Year Level
Master
Year
2024
Course Code
TIF20117

Bayesian Econometrics

Year
2024
Course Code
FEM21026

Bayesian Econometrics in Finance

Year
2024
Course Code
FEM21032

Econometrics 1

Year
2024
Course Code
FEB22004

Econometrics 1

Year
2024
Course Code
FEB22004X

  • Joost van Rosmalen

    Segmentation and Dimension Reduction: Exploratory and Model-Based Approaches
  • Dennis Fok

    Advanced Econometric Marketing Models
  • Karim Bannouh

    Measuring and Forecasting Financial Market Volatility using High-Frequency Data
  • Carlos Hernandez Mireles

    Marketing Modeling for New Products
  • Carlos Hernandez Mireles

    Marketing Modeling for New Products
  • Peter van der Zwan

    The Entrepreneurial Process: An International Analysis of Entry and Exit
  • Ronald de Vlaming

    Linear Mixed Models in Statistical Genetics
  • Bruno Jacobs

    Marketing Analytics for High-Dimensional Assortments
  • Bruno Jacobs

    Marketing Analytics for High-Dimensional Assortments
  • Bram van Os

    'Time Varying Risk and Dependence Structure of Financial Securities'.
  • Anoek Castelein

    Advanced individual response models
  • Sebastiaan Vermeulen

    bridging time series econometrics and machine learning
  • Xun Gong

    forecasting implied volatility surface
  • Jochem Oorschot

    Essays on extremes in Finance
  • Didier Nibbering

    The Gains from Dimensionality
  • Wei Li

    Competition in the Retail Market of Consumer Packaged Goods

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