Abstract: This paper develops semiparametric Bayesian methods for estimating the average treatment effect on the treated (ATT) in difference-in-differences (DiD) designs. We propose two Bayesian procedures with frequentist validity. The first places a Gaussian process prior on the conditional mean function of the control group. The second is a double-robust Bayesian approach that adjusts the prior on the conditional mean function and then corrects the posterior distribution of the ATT. We establish a semiparametric Bernstein¨Von Mises theorem, showing the asymptotic equivalence between our Bayesian procedures and efficient frequentist estimators. For the second approach, the result holds under double-robust smoothness conditions: the lack of smoothness in the conditional mean function can be compensated by high regularity of the propensity score, and vice versa. Monte Carlo simulations and an empirical application demonstrate strong finite-sample performance of our Bayesian DiD methods. We also extend the Bayesian framework to staggered DiD designs.

Abstract：In low- and middle-income country cities, poor households often reside in unattractive locations, including flood-prone areas. This can be due to poor information about flood risks or acceptance of these risks in the face of lower housing prices. Poor households are also more vulnerable to floods than richer households given the low-quality housing they occupy. Does information on flood risks help households make better location and housing choices? To what extent will these choices be revised with increased flood risks from climate change? To answer these questions, we develop a polycentric land use model with heterogeneous income groups, formal and informal housing, and flood risks. The model is calibrated to the city of Cape Town (South Africa) and simulations are run to assess the impact of flood risks on land values and income segregation within the city, distinguishing between the effects of three types of flooding (fluvial, pluvial, and coastal). Although total damages from floods are greater for rich households, they represent a larger relative share of poor households’ incomes. Better information encourages the adaptation of poor households up to a certain point, and this allows them to mitigate most of the adverse consequences from climate change. Considering the different nature of flood types is key to understanding their responses.

KIER Seminar（Joint with Applied Microeconomics Seminar)

Abstract：

Bullying is a widespread form of aggression that emerges early in childhood and is

common in school settings. Using Italian data from the National Institute for the Evaluation
of Education and Training on primary school students, we document
gender differences in self-reported bullying, both as victims and perpetrators, across multiple
dimensions. Bullying is more prevalent among boys on both fronts. Exploiting the
quasi-random allocation of students to classes within schools, we show that a higher share
of boys increases reported victimization among girls, particularly in forms such as mockery
and verbal insults. These effects are associated with lower well-being among girls.
The findings point to a spillover of violence from boys to girls as the share of male peers
increases, highlighting the role of classroom gender composition in shaping early peer 

interactions and the need for caution when managing gender imbalances in elementary
education.

【参考資料】

Masaki Nakabayashi (2025) “Legislating filial obligations: Property rights and filial piety in shogunate Japan,” Journal of Asian Economics, 98, 101923.

要旨：We first provide an overview of the latest estimates of Japan’s population from the eighth century to the mid-nineteenth century and confirm that Japan experienced a sharp fall in population from the ninth to the twelfth centuries and a modest decrease in the early eighteenth century. We next review institutional changes that accompanied population growth from the fourteenth century and the population stagnation in the eighteenth century, and conclude that the current stem family system in Japan, where the duty of support is mutual between parents and children, was formed in the eighteenth century as a response to aging.

Distributional Effects with Two-Sided Measurement Error: An Application to Intergenerational Income Mobility∗ (joint with Brantly Callaway, Irina Murtazashvili, Emmanuel S. Tsyawo)

Abstract: This paper considers identification and estimation of distributional effect parameters that depend on the
joint distribution of an outcome and another variable of interest (“treatment”) in a setting with “two-
sided” measurement error — that is, where both variables are possibly measured with error. Examples
of these parameters in the context of intergenerational income mobility include transition matrices, rank-
rank correlations, and the poverty rate of children as a function of their parents’ income, among others.
Building on recent work on quantile regression (QR) with measurement error in the outcome (particu-
larly, Hausman, Liu, Luo, and Palmer (2021)), we show that, given (i) two linear QR models separately
for the outcome and treatment conditional on other observed covariates and (ii) assumptions about the
measurement error for each variable, one can recover the joint distribution of the outcome and the treat-
ment. Besides these conditions, our approach does not require an instrument, repeated measurements,
or distributional assumptions about the measurement error. Using recent data from the 1997 National
Longitudinal Study of Youth, we find that accounting for measurement error notably reduces several
estimates of intergenerational mobility parameters.