【日時】
2025年11月8日(土) 14:00～17:00（開場 13:30）

【場所】
京都大学百周年時計台記念館 国際交流ホールⅢ（定員 80名）

【講演者】

・基調講演：「パリ協定から10年―気候変動政策はどう変わったのか」
　高村 ゆかり　東京大学未来ビジョン研究センター教授
・基調講演：「脱炭素に向けた日本の取組」
　大井 通博　環境省大臣官房審議官
・基調講演：「日本企業が目指すべきサステナビリティ経営による企業価値向上」
　八林 公平　株式会社エスプールブルードットグリーン取締役社長

【パネルディスカッション】

　高村 ゆかり　東京大学未来ビジョン研究センター教授
　大井 通博　環境省大臣官房審議官
　八林 公平　株式会社エスプールブルードットグリーン取締役社長
　五十嵐 祐介　京都大学経済研究所先端政策分析研究センター特定准教授（コーディネーター）

【詳細】
入場無料、申込制
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Flyerはこちら

【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.