JP

Events

Econometrics

Category
Date
Title
Presenter/Location
Details
2013/12/25 Wed
16:30〜18:00
Are University Admissions Academically Fair?
金谷 信 (Aarhus University)
第一共同研究室 (4F北側)
2013/12/04 Wed
16:30〜18:00
Partial Identification of Treatment Effects Using Instrumental Variables
崔 庭敏 (京都大学・院)
第一共同研究室 (4F北側)
2013/12/04 Wed
16:30〜18:00
Nonparametric tests for the effect of the treatment on conditional variance
金 燕春 (京都大学・院)
第一共同研究室 (4F北側)
2013/10/09 Wed
16:30〜18:00
修士論文中間発表会 Decomposition of Difference in Mean under Weak Conditions
崔 庭敏 (京都大学・院)
第一共同研究室 (4F北側)
2013/10/09 Wed
16:30〜18:00
修士論文中間発表会 Nonparametric tests for the effect of the treatment on conditional variance
金 燕春 (京都大学・院)
第一共同研究室 (4F北側)
2013/09/18 Wed
16:30〜18:00
Do Siblings Free-Ride in ‘Being There’ for Parents?
丸山 士行 (University of New South Wales)
第一共同研究室 (4F北側)
2013/09/11 Wed
16:30〜18:00
Set Identification of the Censored Quantile Regression Model for Short Panels with Fixed Effects(Tong Liとの共著)
岡 達志 (National University of Singapore)
第一共同研究室 (4F北側)
2013/07/26 Fri
16:30〜18:00
Finite Sample Bias and MSE of Fully Aggregated Estimator for AR(1) model with a General Error Distribution
永田 修一 (同志社大学)
第一共同研究室 (4F北側)

[Abstract]
 We derive the finite sample bias and mean squared error of the fully aggregated estimator (FAE) for the stationary AR(1) model with intercept, which is proposed by Han, Phillips, and Sul (2011, Econometric Theory). Our analytical results show why the FAE is less biased than the ordinary least square estimator in finite sample case and is not biased by non-normality of error distribution and by intercept term at least O(1/T ), where T is sample size. We also propose a second order unbiased FAE using the analytical result. Finally, we examine the Monte Carlo simulation and show that it is consistent with the theoretical results.

2013/07/17 Wed
16:30〜18:00
Quasi Bayesian Model Selection(新谷元嗣との共著)
井上 篤 (North Carolina State University)
第一共同研究室 (4F北側)
2013/07/03 Wed
16:30〜18:00
A nonparametric Bayesian approach for counterfactual prediction with an application to the Japanese private nursing home market
菅原 慎矢 (東京大学)
第一共同研究室 (4F北側)

[Abstract]
 This paper analyzes impacts of an outdated but sticky economic circumstance in the Japanese private nursing home market. Under this circumstance, homes cover all longevity risks of the residents. To measure its impacts, I compare consumers’ lifetime payments with and without this circumstance. This analysis provides implications for consumer welfare as a policy evaluation and longevity risk premium that homes assume. For the prediction analysis, I construct a structural econometric model that fits industrial organization of the nursing home market. Then, I propose a flexible prediction technique using a nonparametric Bayesian approach. My prediction analysis finds an excess payment under the circumstance that can be compensate only if a consumer live longer than thirty years in a nursing home. This results indicate rich policy implications for sustainable policy of elderly care in Japan.

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