FACULTY
SUSUMU IMAI
Graduate School of Social Data Science/Professor
Field of Study
Labor Economics
Industrial Organization
Applied Econometrics
INTERVIEW
Unique Appeal of the Social Data Science Program
Education:
1. In data science, students learn how to do data analysis respecting the core principles of science, such as reproducibility and refutability.
2. In social data science, we use data to analyze issues in social science. Students appreciate the benefits that those data bring to the social science analysis, that the construction of those data required the efforts and cooperation of large numbers of individuals and firms, and that manipulation of those datasets results in irreversible loss of reproducibility and refutability.
Research:
Empirical analysis of economic models of workers and firms using microdata.
1. In data science, students learn how to do data analysis respecting the core principles of science, such as reproducibility and refutability.
2. In social data science, we use data to analyze issues in social science. Students appreciate the benefits that those data bring to the social science analysis, that the construction of those data required the efforts and cooperation of large numbers of individuals and firms, and that manipulation of those datasets results in irreversible loss of reproducibility and refutability.
Research:
Empirical analysis of economic models of workers and firms using microdata.
CLASS
- (U)Micro Economics and Data Science
- (U)Causal Inference
- (U)Qualitative Data Analysis
- (G)Econometric Analysis of Policy Evalution
RESEARCH
Research details: Empirical analysis of occupational mobility and skill formation. Estimation of demand and cost function, firm entry behavior without exogeneity assumptions.
Keywords
- occupational mobility
- skill formation
- demand function
- cost function
- exogeneity