Resources by jona.frroku

Firm-Level Data on IT Capital, Factor Substitution, and Returns to Scale in France

Creators: French Institute of Statistics and Economic Studies (INSEE)
Publication Date: 2024/03/18
Creators: French Institute of Statistics and Economic Studies (INSEE)

This dataset provides firm-level information from France on capital input, labor, IT expenditures, and output over time. It was used by Danial Lashkari, Arthur Bauer, and Jocelyn Boussard in their 2024 American Economic Review paper to analyze how declining IT prices affect factor demand and returns to scale. The authors identify a novel channel whereby IT shocks influence not only factor substitution but also endogenous shifts in the scale of production, contributing to aggregate changes in market concentration and labor share.

Global Historical Data on Long-Maturity Real Interest Rates

Creators: Bank of England
Publication Date: 2024/02/04
Creators: Bank of England

This dataset contains annual real interest rate data spanning over 700 years across multiple countries. It was used by Kenneth S. Rogoff, Barbara Rossi, and Paul Schmelzing in their 2024 American Economic Review paper to investigate the long-term statistical properties and historical inflection points of long-maturity real interest rates. The data incorporates archival sources, reconstructed bond yields, and modern government bond data to provide a continuous view of rate trends and structural breaks since the 14th century.

Administrative Electricity Billing Data and Election Outcomes in Indian Constituencies

Creators: West Bengal State Electricity Distribution Corporation Limited (WBSEDCL)
Publication Date: 2024/07/08
Creators: West Bengal State Electricity Distribution Corporation Limited (WBSEDCL)

This dataset contains administrative electricity billing records from the Indian state of Tamil Nadu, linked with election outcomes at the constituency level. It was used by Meera Mahadevan in her 2024 American Economic Review paper to study the effect of political favoritism on electricity billing practices. By combining the data with night-time satellite imagery and close-election regression discontinuities, the author identifies significant covert bill manipulation that favors constituencies of winning party candidates and imposes large welfare losses.

Historical Data on French Administrative Reforms, Local Capitals, and Long-Run Development (1790–1900)

Creators: Old Administrative Functions, Police Force, Matricules Napoléoniens, Conseil des Bâtiments Civils
Publication Date: 2024/07/22
Creators: Old Administrative Functions, Police Force, Matricules Napoléoniens, Conseil des Bâtiments Civils

This dataset includes historical administrative, demographic, and economic data from France between 1790 and 1900. It was used by Cédric Chambru, Emeric Henry, and Benjamin Marx in their 2024 American Economic Review paper to study the long-run effects of administrative reforms enacted during the French Revolution. The data tracks the assignment of departmental capitals, taxation, law enforcement, public good provision, and urban growth across French communes, some of which became capitals through plausibly exogenous decisions by the 1790 Assembly.

Branch Banking, Credit Growth, and Economic Recovery in 1930s California

Creators: Bank of America (historical records) and U.S. Census Bureau (linked individual data)
Publication Date: 2024/06/10
Creators: Bank of America (historical records) and U.S. Census Bureau (linked individual data)

This dataset combines archival data from Bank of America’s branch operations with property value, employment, and credit flow data across California cities during the Great Depression. It was used by Sarah Quincy in her 2024 American Economic Review paper to study how branching mitigated local economic shocks by creating an internal capital market. The dataset includes bank-level loan activity, narrative documentation from archives, and linked individual-level census records to analyze structural labor market shifts and urban recovery trajectories between 1929 and 1940.

Citation Database Coverage and Academic Careers: Evidence from the Introduction of Citation Metrics

Creators: National Science Foundation (NSF), Institute for Scientific Information (ISI)
Publication Date: 2024/10/11
Creators: National Science Foundation (NSF), Institute for Scientific Information (ISI)

This dataset includes historical citation data, publication metadata, NSF funding records, and academic employment outcomes used by Sebastian Hager, Carlo Schwarz, and Fabian Waldinger in their 2024 American Economic Reviewpaper. The dataset exploits the introduction of the first citation database (ISI’s Science Citation Index) to analyze how the visibility of scientific work affects the allocation of academic talent. It includes visible and invisible citation data, author affiliations, career progression metrics, and grant awards, enabling an investigation of performance metrics on promotion, mobility, and funding outcomes.

Technological Peer Pressure and Job Posting Skill Disclosure

Creators: Burning Glass, Compustat
Publication Date: 2023
Creators: Burning Glass, Compustat

This dataset was used by Yi Cao, Shijun Cheng, Jennifer Wu Tucker, and Chi Wan in their 2023 Contemporary Accounting Research study. It includes firm-level job posting data with skill requirement specificity, matched with technological peer pressure measures derived from patent similarity and competition. The dataset allows analysis of how firms alter job descriptions for tech positions under varying levels of innovation pressure. It combines data from Burning Glass job postings, Compustat, and patent databases, covering thousands of firm-year observations across U.S. industries.

Creators: Compustat

This dataset supports the 2024 study by Katie W. Lem in Contemporary Accounting Research. It combines textual analysis of corporate disclosures with firm characteristics to measure data analytics strategy adoption. Supplementary materials include variable construction files, robustness checks, and extracted job postings. The data are used to examine whether firms that disclose a data analytics strategy also demonstrate improved internal information quality, such as increased operating efficiency and forecast accuracy.

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