Journal of Economic Literature
ISSN 0022-0515 (Print) | ISSN 2328-8175 (Online)
Data Engineering for Cognitive Economics
Journal of Economic Literature
(pp. 164–96)
Abstract
Cognitive economics studies imperfect information and decision-making mistakes. A central scientific challenge is that these can't be identified in standard choice data. Overcoming this challenge calls for data engineering, in which new data forms are introduced to separately identify preferences, beliefs, and other model constructs. I present applications to traditional areas of economic research, such as wealth accumulation, earnings, and consumer spending. I also present less traditional applications to assessment of decision-making skills, and to human-AI interactions. Methods apply both to individual and to collective decisions. I make the case for broader application of data engineering beyond cognitive economics. It allows symbiotic advances in modeling and measurement. It cuts across existing boundaries between disciplines and styles of research.Citation
Caplin, Andrew. 2025. "Data Engineering for Cognitive Economics." Journal of Economic Literature 63 (1): 164–96. DOI: 10.1257/jel.20241351Additional Materials
JEL Classification
- C45 Neural Networks and Related Topics
- C80 Data Collection and Data Estimation Methodology; Computer Programs: General
- D15 Intertemporal Household Choice; Life Cycle Models and Saving
- D80 Information, Knowledge, and Uncertainty: General
- D91 Micro-Based Behavioral Economics: Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
- G50 Household Finance: General
- J24 Human Capital; Skills; Occupational Choice; Labor Productivity