計量経済学
計量経済学セミナーは、国内外の計量経済学研究者を招聘し、計量経済理論や実証分析に関する研究報告をお願いし、議論を通じて相互に理解を深めると共に、新たな研究テーマを模索する場を提供します。計量経済学に興味をもつ研究者、ポスドク、大学院、学部学生の皆さんのご参加を歓迎します。
15:10〜17:55
2) Counterfactual Identification and Latent Space Enumeration
Jiaying Gu (University of Toronto)
1) Daisuke Kurisu (U of Tokyo) 15:10 – 16:25
Title: Prediction and nonparametric inference on random objects
Abstract: In this presentation, I will talk about two topics on statistical analysis of non-Euclidean data.
Firstly, we extend the notion of model averaging for conventional regression models to Frechet regression, which has Euclidean predictors and a non-Euclidean output.
Specifically, we will introduce a cross-validation (CV) criterion for selecting model averaging weights and demonstrate its optimality in terms of the final prediction error.
Through simulation results, we will illustrate that CV outperforms AIC and BIC-type model averaging estimators.
Secondly, we consider statistical inference on the Frechet mean, which is a generalization of the conventional population mean.
In particular, we introduce empirical likelihood (EL) methods for the inference on Frechet means of Manifold-valued data and study asymptotic properties of the EL statistics.
We also discuss some extensions of our main results.
Simulation and real data analysis illustrate the usefulness of the proposed method.
2) Jiaying Gu (U of Toronto) 16:40 – 17:55
Title: Counterfactual Identification and Latent Space Enumeration (joint work with Thomas Russell and Thomas Stringham).
Abstract: This paper provides a unified framework for partial identification of counterfactual parameters in a general class of discrete outcome models allowing for endogenous regressors and multidimensional latent variables, all without parametric distributional assumptions. Our main theoretical result is that, when the covariates are discrete, the infinite-dimensional latent variable distribution can be replaced with a finite-dimensional version that is equivalent from an identification perspective. The finite-dimensional latent variable distribution is constructed in practice by enumerating regions of the latent variable space with a new and efficient cell enumeration algorithm for hyperplane arrangements. We then show that bounds on a certain class of counterfactual parameters can be computed by solving a sequence of linear programming problems, and show how the researcher can introduce additional assumptions as constraints in the linear programs. Finally, we apply the method to a mobile phone choice example with heterogeneous choice sets, as well as an airline entry game example.
16:45〜18:15
14:00〜17:20
Program
16:45〜18:15
（登録者のみ参加可能）
16:45〜18:15
Abstract: This study proposes a tying maximum likelihood estimation (TMLE) method to improve the performance of estimation of statistical and econometric models in which most time series have long sample periods, whereas the other time series are very short. The main idea of the TMLE is to tie the parameters of the long time series with those of the short time series together so that some useful information in the long time series which is related to the short time series can be transferred to the short time series. The information transferred from the long series can help improve the estimation accuracy of the parameters related to the short series. We first provide asymptotic properties of the TMLE and show its finite-sample risk bound with a fixed tuning parameter which determines the strength of tying. Further, we provide a method for selecting the tuning parameter based on a bootstrap procedure. A finite sample theory about this method is derived, which tells us how to conduct the bootstrap procedure effectively. Extensive artificial simulations and empirical applications show that the TMLE has an outstanding performance in point estimate and forecast.
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16:30〜18:00
応用ミクロ経済学セミナーと共催
https://www.econ.kyoto-u.ac.jp/about/seminars/seminars-cat/seminar-micro/
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16:30〜18:00
（登録者のみ参加可能）
18:30〜20:00
主催 TEDS (TRANSDISCIPLINARY ECONOMETRICS & DATA SCIENCE SEMINAR)
https://teds-datascience.github.io/seminars/
共催 共同利用・共同研究拠点プロジェクト研究 (Joint Research Program of KIER, Kyoto University)
共催 計量経済学セミナー(Econometrics Seminar of KIER, Kyoto University)
（登録者のみ参加可能）
18:00〜19:30
主催 TEDS (TRANSDISCIPLINARY ECONOMETRICS & DATA SCIENCE SEMINAR)
https://teds-datascience.github.io/seminars/
共催 共同利用・共同研究拠点プロジェクト研究 (Joint Research Program of KIER, Kyoto University)
共催 計量経済学セミナー(Econometrics Seminar of KIER, Kyoto University)
（登録者のみ参加可能）
10:00〜11:30
主催 TEDS (TRANSDISCIPLINARY ECONOMETRICS & DATA SCIENCE SEMINAR)
https://qingfeng-liu.github.io/Econometrics_seminar.html
共催 共同利用・共同研究拠点プロジェクト研究 (Joint Research Program of KIER, Kyoto University)
共催 計量経済学セミナー(Econometrics Seminar of KIER, Kyoto University)
（登録者のみ参加可能）