Resources by jona.frroku

EQSCORE: Composite Earnings Quality Indicators from Proprietary Research

EQSCORE: Composite Earnings Quality Indicators from Proprietary Research

jona.frroku
Open Dataset
Creators: Columbia Business School (hosted on Urooj Khan’s institutional website)
Publication Date: 2024
Creators: Columbia Business School (hosted on Urooj Khan’s institutional website)

This dataset supports the 2024 study by Urooj Khan, Venkat Peddireddy, and Shiva Rajgopal in Contemporary Accounting Research. The authors introduce a composite score (EQSCORE) to measure firm-year earnings quality, developed using 51 red-flag indicators derived from 613 proprietary research reports issued between 2004 and 2009. These reports cover aggressive accounting practices in 230 publicly traded firms. The score includes accounting, governance, audit, and cash-flow–related quality signals. EQSCORE is validated against SEC enforcement releases, restatements, and future returns.

Simulated Data and Code for Adversarial Estimation of Structural Models

Simulated Data and Code for Adversarial Estimation of Structural Models

jona.frroku
Open Dataset
Creators: Zenodo
Publication Date: 2023/09/01
Creators: Zenodo

This dataset accompanies the 2023 Econometrica paper by Tetsuya Kaji, Elena Manresa, and Guillaume Pouliot. The authors propose a novel adversarial estimation method for structural econometric models, framed as a minimax game between a data-generating model and a classifier. The dataset contains the simulated data and source code used to benchmark the estimator’s performance in several canonical structural model settings. The approach combines simulation-based estimation with neural network-based discriminators, enabling robust performance under both correct specification and model misspecification.

Urban Growth and Aggregate Productivity Model Data and Code

Urban Growth and Aggregate Productivity Model Data and Code

jona.frroku
Open Dataset
Creators: Diego Puga (hosted at diegopuga.org)
Publication Date: 2023/11/01
Creators: Diego Puga (hosted at diegopuga.org)

This dataset supports the Econometrica paper by Gilles Duranton and Diego Puga (2023), which develops a model of urban growth driven by human capital spillovers, constrained by planning regulations, and shaped by city-specific heterogeneity. The dataset includes simulation scripts and empirical data used to calibrate and validate the model. It allows replication of results on the impact of urban planning constraints and counterfactual policy changes on productivity and national output.

Administrative Data from Federal Disaster Recovery Loan Applications

Administrative Data from Federal Disaster Recovery Loan Applications

jona.frroku
Open Dataset
Creators: Federal recovery loan program data
Publication Date: 2023/11/16
Creators: Federal recovery loan program data

This dataset underlies the Econometrica paper by Benjamin Collier and Cameron Ellis (2024), which estimates a demand curve for disaster recovery loans using administrative records of over one million applicants. The data include household-level application records from a federal loan program offered after natural disasters, combined with exogenous variation in interest rates from 24 natural experiments. The dataset enables replication of results regarding credit demand sensitivity, interest rate elasticity, and the impact of credit scores on loan take-up.

Air Pollution and Labor Supply: Evidence from Mexico City

Air Pollution and Labor Supply: Evidence from Mexico City

jona.frroku
Open Dataset
Creators: Inter-American Development Bank (IDB) & Zenodo
Publication Date: 2024/04/24
Creators: Inter-American Development Bank (IDB) & Zenodo

This dataset supports the Econometrica article by Bridget Hoffmann and Juan Pablo Rud (2024), which investigates the effects of PM2.5 air pollution on daily labor supply in Mexico City. Using high-frequency locality-level pollution data and worker-level labor outcomes, the authors estimate nonlinear labor responses to pollution spikes. The dataset includes measurements of pollution, hourly labor supply indicators, and demographic differentiators (e.g., income level, job flexibility). It is used to analyze behavioral adjustments and inequalities in labor market impacts due to environmental stressors.

Experimental Data on Occupational Safety and Health Committees in Bangladeshi Apparel Factories

Experimental Data on Occupational Safety and Health Committees in Bangladeshi Apparel Factories

jona.frroku
Open Dataset
Creators: Columbia University, Laura Boudreau
Publication Date: 2024/05/28
Creators: Columbia University, Laura Boudreau

This dataset accompanies the 2024 Econometrica study by Laura Boudreau, which investigates the causal impact of Occupational Safety and Health (OSH) committees on workplace safety in Bangladeshi factories. The study was conducted via a large-scale field experiment involving 84 supplier factories and 29 multinational buyers. Half of the factories were randomly assigned to a treatment group that received enhanced OSH committee enforcement. The dataset includes factory-level compliance metrics, objective safety indicators, labor outcomes (wages, employment, productivity), and worker-reported satisfaction measures. It supports analysis of how international enforcement mechanisms interact with local managerial capacity.

Fiscal Capacity and State Consolidation Data for Territories in the Holy Roman Empire

Fiscal Capacity and State Consolidation Data for Territories in the Holy Roman Empire

jona.frroku
Open Dataset
Creators: Davide Cantoni, Cathrin Mohr, and Matthias Weigand
Publication Date: 2024/07/31
Creators: Davide Cantoni, Cathrin Mohr, and Matthias Weigand

This dataset supports the 2024 Econometrica study by Cantoni, Mohr, and Weigand on how early fiscal reforms shaped political survival, size, and compactness of territories within the Holy Roman Empire. The dataset includes novel administrative, fiscal, and geographic variables on territories and cities during the early modern period. Key indicators include the timing and type of fiscal reforms, Imperial tax burdens, revenue sources, military investments, and dynastic outcomes. The authors exploit quasi-random variation in Imperial taxation to establish causality. This dataset enables the replication of their empirical strategy and exploration of mechanisms such as administrative consolidation and absolutist transitions.

Lifestyle Choices and Wealth-Health Dynamics in Germany (Life-Cycle Model Data)

Lifestyle Choices and Wealth-Health Dynamics in Germany (Life-Cycle Model Data)

jona.frroku
Open Dataset
Creators: Lukas Mahler and Minchul Yum
Publication Date: 2024/07/12
Creators: Lukas Mahler and Minchul Yum

This dataset supports the Econometrica article by Mahler and Yum (2024), which examines the mechanisms behind observed wealth disparities across health statuses in Germany—a country with universal healthcare. The authors develop a heterogeneous-agent life-cycle model in which health and wealth co-evolve based on individual lifestyle efforts subject to adjustment costs. The dataset includes model simulation outputs, parameter estimates, and replication materials for decomposing wealth-health gaps into savings, earnings, and behavioral effort channels. The materials allow researchers to replicate and extend the structural estimation that attributes approximately one-quarter of the wealth gap to differential lifestyle behaviors.

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