Updated on 2026/07/27

写真a

 
UTAMARU, Rentaro
 
Affiliation
Faculty of Political Science and Economics, Waseda Institute of Political Economy
Job title
Junior Researcher(Assistant Professor)
Degree
Ph.D. in Public Policy ( The University of Tokyo )
Master of Economics ( The University of Tokyo )
Bachelor of Arts in Economics ( Waseda University )
Homepage URL
https://r-utamaru.github.io/

Research Experience

  • 2026.04
    -
    Now

    Waseda University   Waseda Institute of Political Economy   Junior Researcher (Assistant Professor)   JSPS Postdoctoral Research Fellow

  • 2025.04
    -
    2026.03

    Japan Society for the Promotion of Science   Research Fellowship for Young Scientists DC2

  • 2021.09
    -
    2024.03

    UTokyo Economic Consulting Inc   Intern Analyst

Education Background

  • 2023.04
    -
    2026.03

    The University of Tokyo   Graduate School of Public Policy  

  • 2021.04
    -
    2023.03

    The University of Tokyo   Division of Economics, Graduate School  

  • 2017.04
    -
    2021.03

    Waseda University   School of Political Science and Economics   Economics  

Professional Memberships

  • 2023
    -
    Now

    The Japanese Economic Association

Research Areas

  • Economic policy

Research Interests

  • Empirical Industrial Organization

  • Applied Econometrics

Awards

  • Representative of the Doctoral Graduating Class

    2026.03   Graduate School of Public Policy, The University of Tokyo  

    Winner： Rentaro Utamaru

  • GraSPP's BEST Student Award

    2026.03   Graduate School of Public Policy, The University of Tokyo  

    Winner： Rentaro Utamaru

  • Best Paper Award

    2025.11   The 20th Applied Econometrics Conference  

    Winner： Rentaro Utamaru

  • Fine work

    2020.02   AY2019 20th Thesis Competition of the Waseda Society of Political Science and Economics  

    Winner： Rentaro Utamaru

 

Papers

  • Nonparametric Identification and Estimation of Production Functions Invariant to Productivity Dynamics

    Rentaro Utamaru

    Working Paper    2026.04

    　View Summary

    Production function estimates underpin the measurement of firm-level markups, allocative efficiency, and the productivity effects of policy interventions. Since Olley and Pakes (1996), every major proxy variable estimator has identified the production function through a first-order Markov assumption on unobserved productivity; I show that misspecification of this assumption generates persistent upward bias in the materials elasticity that propagates into overestimated markups and inflated treatment effects. I replace the Markov restriction with conditional independence across three intermediate input demands, a static condition grounded in input market segmentation, and establish nonparametric identification from a single cross-section. I develop a GMM estimator and establish consistency and asymptotic normality. Monte Carlo simulations confirm that the proposed estimator is unbiased across Markov and non-Markov environments, while the standard estimator exhibits persistent bias of up to 63 percent of the true materials elasticity. In 502 Japanese manufacturing industries, the proposed method yields systematically lower markups than the standard method across the entire distribution (median 0.93 vs. 1.03), reducing the share of industries with markups above unity from 54 to 37 percent. In a difference-in-differences analysis of the 2011 Tohoku earthquake, the standard method overstates the productivity loss by 0.40 percentage points, roughly $3.6 billion (400 billion yen) per year.

    DOI

Presentations

  • Nonparametric Identification and Estimation of Production Functions Invariant to Productivity Dynamics

    Rentaro Utamaru

    The Symposium on Econometric Theory and Applications (SETA) 

    Presentation date： 2026.06

    Event date：
    2026.06
    　
    　

  • Restoring Identification in the Olley-Pakes Estimator: A Timing Assumption Approach

    Rentaro Utamaru

    Japanese Economic Association 2026 Spring Meeting 

    Presentation date： 2026.05

    Event date：
    2026.05
    　
    　

  • Nonparametric Identification and Estimation of Production Functions Invariant to Productivity Dynamics

    International Industrial Organization Conference (IIOC) 

    Presentation date： 2026.04

  • Nonparametric Identification of Production Functions without a Markov Assumption

    Rentaro Utamaru

    関西計量経済学研究会 

    Presentation date： 2026.01

    Event date：
    2026.01
    　
    　

  • Nonparametric Identification of Production Functions without a Markov Assumption

    Rentaro Utamaru

    Japan Empirical Industrial Organization Workshop 

    Presentation date： 2025.11

  • From Reduced to Structural: A New Identification Strategy for Production Functions

    Rentaro Utamaru

    The 20th Applied Econometrics Conference 

    Presentation date： 2025.11

  • Nonparametric Identification of Production Functions with Nonseparable Productivity

    Rentaro Utamaru

    Japanese Economic Association 2024 Autumn Meeting 

    Presentation date： 2024.10

  • Estimating Civic Culture: An Application to Tax Revenue and Welfare Analysis

    Rentaro Utamaru

    Japanese Economic Association 2023 Spring Meeting 

    Presentation date： 2023.05

  • Estimating Civic Culture: An Application to Tax Revenue and Welfare Analysis

    Rentaro Utamaru

    Empirical Micro Research Seminar 

    Presentation date： 2023.01

  • Civic Culture

    Rentaro Utamaru

    Japan Empirical Industrial Organization Workshop 

    Presentation date： 2022.11

▼display all

Research Projects

  • 市場支配力と生産性の推定：仮定に依拠しない新たな生産関数推定法の開発と実証分析

    日本学術振興会  科学研究費助成事業

    Project Year :

    2026.04
    -
    2029.03
     

    哥丸 連太朗

  • 環境イノベーションの測定手法開発と環境規制が環境イノベーションに与える影響の解明

    日本学術振興会  科学研究費助成事業

    Project Year :

    2025.04
    -
    2026.03
     

    哥丸 連太朗

  • Developing Measurement Methods for Environmental Innovation and Analyzing the Impact of Environmental Regulations on Environmental Innovation

    Hitotsubashi University Institute of Economic Research  Joint Usage and Research Center Project

    Project Year :

    2024.06
    -
    　
     

 

Syllabus