Asymptotic comparison at optimal levels of reduced‐bias extreme value index estimators

In this article we are interested in the asymptotic comparison, at optimal levels, of a set of semi‐parametric reduced‐bias extreme value (EV) index estimators, valid for a wide class of heavy‐tailed models, underlying the available data. Again, as in the classical case, there is not any estimator that can always dominate the alternatives, but interesting clear‐cut patterns are found. Consequently, and in practice, a suitable choice of a set of EV index estimators will jointly enable us to better estimate the EV index γ, the primary parameter of extreme events.     

Properties of Census Dual System Population Size Estimators

We study parametric and non‐parametric approaches for assessing the accuracy and coverage of a population census based on dual system surveys. The two parametric approaches being considered are post‐stratification and logistic regression, which have been or will be implemented for the US Census dual system surveys. We show that the parametric model‐based approaches are generally biased unless the model is correctly specified. We then study a local post‐stratification approach based on a non‐parametric kernel estimate of the Census enumeration functions. We illustrate that the non‐parametric approach avoids the risk of model mis‐specification and is consistent under relatively weak conditions. The performances of these estimators are evaluated numerically via simulation studies and an empirical analysis based on the 2000 US Census post‐enumeration survey data.     

A reference-dependent representation with subjective tastes

Experimental and empirical evidence documents instances where the presence of an inferior option in a menu increases the attractiveness of the better options from that menu and thus distorts the normative ranking across menus. We analyze the case when in addition to this so called context-effects bias there is also a concern for flexibility, in the spirit of the literature initiated by Kreps (1979) and Dekel et al. (2001). Since the context-effects bias and the desire for flexibility both increase the inclination of a decision maker to choose larger menus, our analysis allows the disentangling of the effect of the behavioral bias from the effect of the rational desire from flexibility. We find a weak condition on the set of ex post preferences under which the two effects are identifiable. We show that our representation is essentially unique. From a methodological viewpoint, our paper provides a novel technique of identifying probabilities on the state space of subjective uncertainty introduced by Dekel et al. (2001) when this state space is infinite. This method renders the infinite state space essentially finite with respect to a certain salient property.     

Housing demand in Russia: Rationing and reform1

In a number of articles Alexeev (1988a) and (1988b) shows that in the former Soviet Union the administrative rationing of housing was partially replaced by market forces acting through the second economy. This paper uses a much richer dataset to update his analysis for Russia to consider housing demand in 1992, the last year of the administrative allocation system. Almost immediately after the survey used for this analysis Russia began to privatize the housing stock as part of its movement towards a market economy. The questions we ask are: Were households really able to beat the system, as argued by Alexeev and, if so, were they still able to do so in 1992? Our answer to the second question is that in 1992 households were not able to beat the system. Income had no observable effect on housing demand. Furthermore, we do not think that the difference in our empirical results and Alexeev's is due only to the broader economic changes that occurred since his estimation or the richer dataset available to us. Indeed, our answer to the first question is that there are good reasons for arguing that Alexeev's estimates of the income elasticity of housing demand are biased upwards.     

基于终极产权论的股权结构与公司绩效研究

文章依据终极产权理论,对我国制造业上市公司股权进行重新划分,分为国有终极控制权和非国有终极控制权.采用面板数据方法,在控制样本选择偏差和股权内生变量的前提下研究股权结构对公司绩效的影响.实证结果表明,终极控制权比例与国有控股公司绩效CFOA、M/B呈显著的倒U性关系,而与传统绩效指标ROE、ROA无显著关系,在非国有终极控股公司中则不存在上述关系.流通A股比例与公司绩效关系不确定.样本选择偏差、机构投资者和外资股对公司绩效也有不同的影响.     

Biases in demand analysis due to variation in retail distribution

Aggregate demand models typically assume that consumers choose between all available products. Since consumers may be unwilling to search across every store in a given market for a particular item, this assumption is problematic when product assortments vary across stores. Using supermarket scanner data for five product categories we demonstrate that approximately one third of products have limited retail distribution, which account for one fourth of dollar sales. Monte Carlo analysis demonstrates that the level of limited product availability observed in the data can significantly bias the results of aggregate demand models that incorrectly assume all consumers in a given market face the same choice set.     

Real effects of financial market integration: does lower home bias lead to welfare benefits?

This paper proposes equity home bias as a proxy for financial integration in the ongoing empirical debate on the impact of financial integration on economic growth. In integrated markets, investors are expected to take full advantage of the potential for international diversification. The extent of equity home bias (i.e. overinvesting in domestic stocks and foregoing gains from international diversification) provides a relevant quantity-based measure of financial integration. Using different techniques to compute home bias, this paper investigates whether countries with lower home bias experience faster economic growth. Additionally, the analysis extends to the link between (decreasing) home bias and international risk sharing and income inequality. The results suggest that financial integration, proxied by the decreasing equity home bias, is positively associated with economic growth and international risk sharing. At the same time, it appears that higher financial integration pairs with higher income inequality.     

Incorporating heterogeneity with store-level aggregate data

This paper introduces a methodology to incorporate heterogeneity in the analysis of store level aggregate data. The proposed model is validated using two sets of scanner panel data, for tuna and ketchup, and their corresponding weekly aggregate data. The model recovers the true parameters with acceptable accuracy.The model has several advantages over the previous aggregate models, such as the linear model, the semilog model, and the log-log model. First, the cross-price elasticities estimated from the model show the asymmetric responses to the price promotions very close to those from the logit model applied to the panel data. Second, the model shows better prediction performance.