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30. Oktober - 3. November 2023

Graduate Center Short Course

Transition and Duration Models


30. Oktober - 3. November 2023


DIW Berlin


Christian Schluter


Students will study models of transitions and durations, and learn how to estimate these using realworld data.



This course is an introduction to modelling transitions into a state of interest (such as the transition into employment from unemployment) and durations (such as unemployment, survival of patients after medical treatment or firms after a financial crash). We start with the basic building blocks (Poisson processes, Markovian transitions, hazard models). Since duration data might be censored (individuals might still be in the state of interest at the end of the observation window), classic ordinary least squares (OLS) is invalid, and we develop appropriate methods for estimation. Unobserved heterogeneity introduces fundamental identification challenges.

Throughout this course, all methods will be illustrated using examples in R and Python, and we will consider several papers from the established empirical literature.

Date and Time:
30 October 2023 to 3 November 2023

Mon, Tue, Wed, Fri:
09:30 – 13:00h

13:00 – 16:30h

Mon, Tue:                           Karl Popper, Room No. 2.3.020
Wed:                                   Ferdinand Friedensburg, Room No.2.3.001
Thu:                                    France D. Blau, Room No. 3.3.002C
Fri:                                      Elinor Ostrom Hall, Room No. 1.2.019

Topics and Ressources


  • Literate Programming, Replicability and Reproducibility
  • Introduction to Counting Processes: The Poisson Process
    • Exercise Set 1
    • Empirical exercise (Poisson regression): Bike rides
    • Empirical exercise (Poisson regression): Doctor visits
    • Empirical exercise (PWE): Criminal recidivism
  • Introduction to Markov Chains
    • Exercise Set 2
    • Coding: Unemployment transitions
    • Coding: Google’s PageRank
  • Duration and Survival Analysis: Hazard Models
    • Exercise Set 3
    • Empirical exercise: Criminal recidivism
    • Empirical exercise: Time to publication
    • Empirical exercise: Divorce in the US
    • Empirical exercise: Replication of Pebley and Stupp (1987) “Child Mortality in Guatemala”
    • Empirical exercise: The Cancer Genome Atlas (TCGA) data
  • The Mixed Proportional Hazard (MPH) Model
  • The Proportional Hazard (PH) Model and Grouped Data
  • Cox Partial Likelihood
  • Machine Learning and Survival Analysis: Random Survival Forests.
    • Empirical exercise: Training a Cox model
    • Empirical exercise: Random Survival Forests


About the instructor

Christian Schluter is a Professor of Economics at Aix-Marseille School of Economics.  His research is in the wider field of empirical labour economics / econometrics, and has been published in e.g. The Review of Economic Studies, The Review of Economics and Statistics, International Economic Review and Journal of Econometrics.


If you want to join this short course, please register with the Graduate Center on a first-come, first-serve basis: gradcenter@diw.de