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「くるみんマーク」取得企業から探る労働者のワークライフバランスの改善策
Get PDF申請代表者： 法学部国際公共政策学科2年 濱口 陸アドバイザー教員： 法学部国際公共政策研究科 松繁 寿和共同研究者： 法学部国際公共政策学科4年 椿 真美, 2年 南部 未玖, 山口 理香採択番号: 法-1
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No full text「文化」の解読(19) : 文化とメディ
Multiproduct Firms, Consumer Search, and Demand Heterogeneity
No full textMarch 2018. Revised October 2019.This study constructs a consumer search model in which some consumers search for multiple products, whereas others search for a single product. A price difference arises because of a difference in the price elasticity for each group. We show that a positive demand shock to one of the products decreases the price of another product, whereas it increases its own price, and a negative correlation between the demands for each product strengthens these tendencies. Both prices decrease, however, following a positive demand shock when the demands for each product are positively correlated. We also show that multiproduct firms set a relatively high price for a more demanded product, as such a product's price tends to be more elastic with respect to search costs. A price difference between products increases as the demand gap between products increases or as economies of scale in search increase
A robust approach to heteroskedasticity, error serial correlation and slope heterogeneity for large linear panel data models with interactive effects
No full textJuly 2018. Revised June 2019.In this paper, we propose a robust approach against heteroskedasticity, error serial correlation and slope heterogeneity for large linear panel data models. First, we establish the asymptotic validity of the Wald test based on the widely used panel heteroskedasticity and autocorrelation consistent (HAC) variance estimator of the pooled estimator under random coefficient models. Then, we show that a similar result holds with the proposed bias-corrected Bai's (2009) estimator for models with unobserved interactive e¤ects. Our new theoretical result justifies the use of the same slope estimator and the variance estimator, both for slope homogeneous and heterogeneous models. This robust approach can significantly reduce the model selection uncertainty for applied researchers. In addition, we propose a novel test for the correlation and dependence of the random coefficient with covariates. The test is of great importance, since the widely used estimators and/or its variance estimators can become inconsistent when the variation of coefficients depends on covariates, in general. The finite sample evidence supports the usefulness and reliability of our approach