projects
Research projects by Johannes Bleher in econometrics, data science, finance, and computational social science.
Selected current and recent projects. Short descriptions emphasize the problem, method, and current output.
economics
Administrative Reform Options in Baden-Wuerttemberg
Ranks Baden-Wuerttemberg county reform options with a reproducible cost-frontier screen, producing a cautious prioritization tool for institutional review.
Hydrological Shocks and Fuel-Supply Resilience
Combines river gauges, AIS tanker data, and fuel prices to measure waterway-shock pass-through and supply-chain resilience.
Local Implementation-Capacity Frictions in Baden-Wuerttemberg
Builds a county-year index of local implementation-capacity frictions using official regional, fiscal, labor-market, and infrastructure data.
econometrics
Dynamic Generator Inversion for Observable Conditional Distributions
Builds a Doi-Peliti-style generator framework and empirical-characteristic-function estimator for observable conditional distributions.
financial econometrics
Systemic Tail-Risk Contributions in European Banking
Estimates hierarchical Bayesian CoVaR for European banks, producing a broad bank-level ranking of systemic tail-risk contributions.
Expected-Shortfall Envelopes and Hansen-Jagannathan Kernels
Uses regularized conditional quantiles to compare downside-risk envelopes and admissible Hansen-Jagannathan kernels across asset universes.
Using Exact Simulation of Order Book Dynamics for Bayesian Estimates of Structural Parameters
Uses exact simulation of limit-order-book dynamics to support Bayesian estimation of structural market-microstructure parameters.
statistical methodology
Algorithmic Evidence Processes
Formalizes inference from repeated randomized algorithm runs using sequential evidence processes, producing diagnostics for stability and reproducibility.
Bayes-Factor-Guided Post-Double Selection with Bootstrapped Multiple Imputation
Aggregates variable-selection evidence across bootstrap and multiple-imputation runs with Bayes-factor-style stopping and inclusion rules.
Fast Non-parametric Test on the Equivalence of Multivariate Empirical Distributions
Develops a fast non-parametric test for equivalence of multivariate empirical distributions in high-dimensional settings.
data science
FAIR Data Science
Book project on reproducible, findable, accessible, interoperable, and reusable data-science workflows for empirical research.
computational social science
Political Sentiment in German Newspapers over Time -- Using LLMs to Model Political Sentiment
Uses LLM-based text measurement to track political sentiment in German newspapers over time.
computational finance
Using Symbolic Regression to Describe Order Book Dynamics
Uses symbolic regression to discover interpretable equations for order-book dynamics from high-frequency market data.
computational chemistry
Optimizing Catalysts - Machine Learning-Driven Discovery from Crystal Structure Data
Applies machine learning to crystal-structure data to screen catalyst candidates and accelerate materials discovery.