4 citations · 5 across the 6 of their papers we have counts for
7 papers
How to deal with machine learning bias in economic history
Torben S. D. Johansen, Julius Koschnick, Christian Vedel
Machine learning (ML) has rapidly transformed economic history, lowering costs of digitization, data linkage, and imputation, and making information in historical text usable at sc…
Group-Level Treatment Effect Heterogeneity in Difference-in-Differences: A Balanced Approach
Nora Bearth, Nadja van 't Hoff, Torben S. D. Johansen
Understanding how treatment effects vary across groups is central to policy evaluation. In Difference-in-Differences designs, heterogeneity is often studied using subgroup or tripl…
Optimal Treatment Allocation under Constraints
Torben S. D. Johansen
In optimal policy problems where treatment effects vary at the individual level, optimally allocating treatments to recipients is complex even when potential outcomes are known. We…
Breaking the HISCO Barrier: Automatic Occupational Standardization with OccCANINE
Christian Møller Dahl, Torben Johansen, Christian Vedel
This paper introduces OccCANINE, an open-source tool that maps occupational descriptions to HISCO codes. Manual coding is slow and error-prone; OccCANINE replaces weeks of work wit…
DARE: A large-scale handwritten date recognition system
Christian M. Dahl, Torben S. D. Johansen, Emil N. Sørensen +2
Handwritten text recognition for historical documents is an important task but it remains difficult due to a lack of sufficient training data in combination with a large variabilit…
Applications of Machine Learning in Document Digitisation
Christian M. Dahl, Torben S. D. Johansen, Emil N. Sørensen +2
Data acquisition forms the primary step in all empirical research. The availability of data directly impacts the quality and extent of conclusions and insights. In particular, larg…
HANA: A HAndwritten NAme Database for Offline Handwritten Text Recognition
Christian M. Dahl, Torben Johansen, Emil N. Sørensen +1
Methods for linking individuals across historical data sets, typically in combination with AI based transcription models, are developing rapidly. Probably the single most important…