Quick consistency of quasi-maximum likelihood estimators in a multivariate poisson process

Recent results by the present author on quick consistency of quasi-maximum likelihood estimators of parameters in a multivariate Poisson process are strengthened at the cost of replacing the inverse continuity assumption with the strong uniform identifiability condition.     

Several efficient two-step estimators for the dynamic simultaneous equations model with autoregressive disturbances

Several asymptotically efficient methods are suggested on both the full and the limited information approach to estimate the simultaneous equations model in which the lagged endogenous variables and the autoregressive disturbances coexist. They are two-step procedures and do not involve iterations. A method is suggested also for the case where any portion of the autoregressive parameter matrix is specified to be zero. Since the consistency and efficiency depend upon the asymptotic, local identifiability, the necessary and sufficient condition is derived for it. It does not depend on the exclusion of the lagged endogenous variables.     

Two-stage non Gaussian QML estimation of GARCH models and testing the efficiency of the Gaussian QMLE

In generalized autoregressive conditional heteroskedastic (GARCH) models, the standard identifiability assumption that the variance of the iid process is equal to 1 can be replaced by an alternative moment assumption. We show that, for estimating the original specification based on the standard identifiability assumption, efficiency gains can be expected from using a quasi-maximum likelihood (QML) estimator based on a non Gaussian density and a reparameterization based on an alternative identifiability assumption. A test allowing to determine whether a reparameterization is needed, that is, whether the more efficient QMLE is obtained with a non Gaussian density, is proposed.     

Identification of binary choice models with social interactions

This paper provides a set of results on the econometric identifiability of binary choice models with social interactions. Our analysis moves beyond parametric identification results that have been obtained in the literature to consider the identifiability of model parameters when the distribution of random payoff terms is unknown. Further, we consider how identification is affected by the presence of unobservable payoff terms of various types as well as identification in the presence of certain forms of endogenous group membership. Our results suggest that at least partial identification may be achieved under assumptions that in certain contexts may be plausible.     

Global identification of the dynamic shock-error model

The paper gives (necessary and sufficient) conditions for the global identifiability of dynamic regression models with errors in the variables. The conditions are simple counting rules combining the order parameters of a model. They are counterparts of conditions previously established for local identifiability in a series of papers.     

Perceived identifiability,shared responsibility and innovative work behavior*

Based on social loafing theory, we develop and test the relationships between employee perceived identifiability, shared responsibility and innovative work behavior in the team context. Additionally, we investigate the moderating effect of coworker trust on these relationships. In a study of pair data from 142 ward heads and nurses in Indonesian hospitals, we find that perceived identifiability is positively associated with innovative work behaviors while perceived shared responsibility is negatively associated with the innovative work behaviors of employees. Meanwhile, employee perceived coworker trust moderates the negative relationship between perceived shared responsibility and innovative work behaviors. We discuss details of the relationships among these variables, and offer suggestions and implications.     

Identifiability criteria for Muth-rational expectations models

The authors deal with complete static linear models that contain current Muth-rational expectations. Rank, order and variety conditions for the identifiability of the structural parameter are derived under general restrictions. We also correct statements that appeared in the literature. Our main finding is that, in general, the standard rank and order conditions are sufficient also for the identifiability of the Muth-rational expectations model parameter, whenever there are enough not fully anticipated exogenous variables. If the number of imperfectly forecasted exogenous variables falls short of the number of endogenous variables by g, then g extra restrictions are needed on every equation and the restrictions must meet easily verifiable variety conditions as well as an augmented rank criterion.     

Determinacy in the Linear Model: Gauss to Bose and Koopmans

Gauss showed that least squares fails to produce a unique solution only when the problem is indeterminate. This note considers his argument and the notion of indeterminacy underlying it. It also relates the argument to twentieth-century discussions of estimability and identifiability.     

The Identifiability of Independent Competing Risks Models with Multiple Spells

Models of independent competing risks with multiple spells are becoming popular in the analysis of economic duration data. This paper considers their identifiability.     

The informative sample size for dynamic multiple equation systems with moving average errors

Abstract  The problem considered here, is that of finding suitable conditions for dynamic economic systems that exclude the existence of observationally equivalent structures. Here observational equivalence refers to equality of distributions or first and second moments of a small finite sample from the observable process. It is shown, that under these conditions we may act as if the lagged endogenous variables are nonrandom exogenous variables, when global identifiability is investigated.     

居住小区公共建筑设计研究

本文就如何在居住小区环境中合理配置和设计公共建筑,使其与小区环境有机结合,提高小区的可识别性和归属感等一系列问题进行了阐述,从而能够满足居民更高层次的需求。     

Identification of the dynamic shock-error model with autocorrelated errors

The paper gives (necessary and sufficient) conditions for the local identifiability of dynamic regression models with autocorrelated errors in the variables. The conditions are simple counting rules combining the order parameters of a model and directly generalize the results of Maravall and Aigner. A new method of identification is presented allowing a compact derivation of the results.     

Testing the proportional hazards assumption in the presence of unmeasured heterogeneity

This paper develops a discrete-time hazard model which accounts for unmeasured hetergeneity while allowing the coefficients of the regressors to vary over time. Sufficient conditions for nonparametric identifiability of the unmeasured heterogeneity distribution are derived. Testing for time-varying coefficients in this model is, under suitable conditions, equivalent to testing the proportionality assumption of the underlying continuous-time hazard model. Some Monte Carlo evidence is presented regarding the small-sample properties of this test. As an illustration, these tests are applied to the joblessness durations of displaced workers.     

Local identifiability of the factor analysis and measurement error model parameter

Measurement error regression models are factor analysis models, the latent ‘correct’ regressors are the factors. There is however no common statistical method between the factor analysis and the regression model, because the covariance elements that are known identifying constituents of the former model are unknown in the latter. Instead, the idea that the data come from the same regression model, as with panel data, but can be grouped in two or more groups, each group having its own different regrressor generating process, is shown to supply credible restrictions. We generalize and compare relevant identifiability criteria and corresponding asymptotically efficient estimators that are recursive in the number of overidentifying restrictions.     

Interdependent preferences: an econometric analysis

The theoretical model of Gaertner (1974) and Pollak (1976) for the interdependence of preferences in the Linear Expenditure System is estimated for a cross-section of households. The interdependence of consumption of different households has implications for the stochastic structure of the model and for the identifiability of its parameters. Both aspects are dealt with. The empirical results indicate a significant role played by the interdependence of preferences. One of its implications is that predictions of the effects of changes in a household's exogenous variables differ according to whether the exogenous variable only changes for this household or for all households jointly. © 1997 John Wiley & Sons, Ltd.     

Identification structure of linear structural models

In this paper identification problems in linear structural models are discussed. A special but practically important form of these problems, the structural identifiability, is defined. Thereafter it is shown that this problem can be studied — without empirical data — by a set system defined on the set of free parameters of a model. This set system is the identification structure, or the matroid, of the model. It gives insight into the dependence of unidentified parameters. The advantages of this approach in research planning and in correcting nonidentifiable models is demonstrated. Finally we introduce the FORTRAN program LISRAN, which is designed to analyze a given linear structural model and to provide its identification structure.     

基于Pareto遗传算法的仓库箱装军用物资垛位优化

垛位是否合理是影响后方仓库中箱装军用物资供应保障能力的一个重要因素。首先根据后方仓库中箱装军用物资堆垛优化原则和储存策略,建立了基于收发频率和同一性原则的多目标优化模型—箱装军用物资垛位优化数学模型;然后通过分析模型,提出采用Pareto遗传算法对垛位优化问题进行了求解,并给出求解的详细步骤;最后选用一个实例进行了应用,证明了该模型的合理性和算法的有效性。     

Identification and estimation of a class of household production models

We consider a class of household production models characterized by a dichotomy property. In these models the amount of time spent on household production does not depend on the household utility function, conditional on household members having a paid job. We analyse the (non‐parametric) identifiability of the production function and the so‐called jointness function (a function describing which part of household production time is counted as pure leisure). It is shown that the models are identified in the two‐adult case, but not in the single‐adult case. We present an empirical application to Swedish time‐allocation data. The estimates satisfy regularity conditions that were violated in previous studies and pass various specification tests. For this data set we find that male and female home production time are q‐substitutes. Copyright © 2003 John Wiley & Sons, Ltd.     

Consistency of assessments in infinite signaling games

In this paper we investigate possible ways to define consistency of assessments in infinite signaling games, i.e. signaling games in which the sets of types, messages and answers are complete, separable metric spaces. Roughly speaking, a consistency concept is called appropriate if it implies Bayesian consistency and copies the original idea of consistency in finite extensive form games as introduced by ^{Kreps and Wilson (Econometrica 1982, 50, 863–894)}. We present a particular appropriate consistency concept, which we call strong consistency and give a characterization of strongly consistent assessments. It turns out that all appropriate consistency concepts are refinements of strong consistency. Finally, we define and characterize structurally consistent assessments in infinite signaling games.