Patrick W. Schmidt

Welcome to my website! I am a PhD Candidate at the Graduate School for Economics, Finance and Management (GSEFM) at Goethe University Frankfurt and a member of the Computational Statistics Group at the Heidelberg Institute for Theoretical Studies (HITS).

I work on uncertainty quantification in forecasting, surveys, laboratory experiments, and economic modelling. My work lies at the crossroad between decision science, computational statistics, and experimental economics. The applications of my work range from development and behavioral economics to financial risk measurement and macroeconomic forecasting.


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Working Papers

with Markus Eyting (GSEFM Frankfurt)

Online Supplement

with Matthias Katzfuss (Texas A&M) and Tilmann Gneiting (HITS, KIT)

Online Supplement

with Andrew J. Patton (Duke) and Timo Dimitriadis (HITS)



Discussion of "Elicitability and backtesting: Perspectives for banking regulation". The Annals of Applied Statistics, 11(4):1883-1885, 2017.

Work in Progress

An income expectation panel of Indian fishers: Uncertainty perception and consumption

with Xavier Giné (World Bank)

Inference on information sets: Estimation and testing of information sources

Beyond simulations: Stratified randomization and regression adjustments for experimental data (draft available upon request)

with Simon Heß (Goethe University)

Optimal state-dependent forecasting for Value-at-Risk under the Basel Accord (slides available upon request)

Software Package in R

PointFore (available on CRAN):

Estimate specification models for the state-dependent level of an optimal quantile/expectile forecast. Wald Tests and the test of overidentifying restrictions are implemented. Plotting of the estimated specification model is possible. The package contains two data sets with forecasts and realizations: the daily accumulated precipitation at London, UK from the high-resolution model of the European Centre for Medium-Range Weather Forecasts (ECMWF) and GDP growth Greenbook data by the US Federal Reserve. See Schmidt, Katzfuss and Gneiting (2017) for more details on the identification and estimation of a directive behind a point forecast.

Further R-Packages are currently available upon request and will be uploaded when research papers are finished. Please get in contact.