📐 On Bessel’s Correction: Unbiased Sample Variance, the Bariance, and a Novel Runtime-Optimized Estimator
Derives a fast unbiased estimator for sample variance and introduces a new concept, the “Bariance.”
🏊♂️ Using COVID-19 Response Policy to Estimate Open Water and Swim Drafting Effects in Triathlon
Uses staggered triathlon starts during COVID to estimate causal drafting effects in open water swimming.
📊 Strategic Effort and Bandwagon Effects in Finite Multi-Stage Games with Non-Linear Externalities: Evidence from Triathlon using a Leave-One-Out IV Strategy
Analyzes group size and bandwagon effects in triathlons using a leave-one-out IV strategy.
🛒 Spatial Competition on Psychological Pricing Strategies: Preliminary Evidence from an Online Marketplace
Examines strategic .99 pricing and spatial clustering using scraped data from online bike markets.
🧃 Evaluation of Political Interventions to Reduce Single-Use Plastics (SUPs) and subsequent SUP Littering: An Event-Study for Austria and Germany
Investigates if political interventions under EU Directive 2019/904 caused observable price changes in Austria and Germany. Results support effective pass-through of externalities in line with the polluter-pays principle (PPP) using aggregated monthly price data and robustness checks.
🧪 alpha-miner 0.1.3 (WIP)
Implements the α-algorithm for automated process discovery using event logs. Lightweight algorithm. Useful for high-level process mining in industrial settings. Hosted on PyPI.
austrian-cpi
A lightweight, zero-dependency helper for working with Austrian CPI tables from Statistik Austria — perfect for dashboards, data-science notebooks, web applications, Node.js backend services, or quick inflation adjustments. Hosted on npm.
Statistically Significant Linear Regression Coefficients Solely Driven by Outliers in Finite-Sample Inference
Demonstrates how a single outlier can cause a linear regression coefficient to appear statistically significant in small samples. Compares OLS to Robust, and alternative regression methods and emphasizes diagnostic methods for detecting influential observations.
Chaos in Dynamic Systems, Measuring Dimensionality, Entropy and the Hidden Dynamics of Residuals
Uses dynamical systems theory to show that regression residuals—especially from misspecified models—can follow deterministic yet chaotic paths. Includes formal derivations of entropy and fractal dimensions, with examples informed by nonlinear time series analysis and chaos theory in economic systems.
