Testing neoclassical production theory

In this paper we propose and carry out some tests that help us evaluate the neoclassical theory of production. First, we use the implied relationship between cost (production) and (inverse) derived demand equations to provide a test which can be interpreted as a test for the validity of the theory. Then, using the same relationships we provide a test for the internal consistency of the theory. Finally, we examine the extent to which the primal and dual models yield the same implications. We find that except for one case the theory does not pass the proposed tests and furthermore, the primal and dual do not yield the same implications.     

Estimation of a simultaneous equations model with an ordinal endogenous variable: The extent of teacher bargaining and the state legal environment

This paper presents a simple two-step estimator for a simultaneous equations model that contains an ordinal endogenous variable. The estimation rules are extensions of the Heckman (1978) estimators, also considered by Amemiya (1978). Asymptotic covariance matrices of the estimators also are derived. The estimator is applied to an economic model in which the statewide extent of teacher bargaining and teacherbargaining legislation are determined jointly.     

The specification and estimation of interrelated factor demands under uncertainty

This paper studies a model of the firm's interrelated demands for the factors of production incorporating exogenous variables with uncertain future values, multiple quasi-fixed factors, depreciation in use, and non-symmetric internal costs of adjustment. The inputs considered are production labor, non-production workers, capital, inventories of non-finished goods, and capacity and non-production worker utilization rates. A simultaneous system of factor demand equations with constraints is estimated and using U.S. manufacturing data. The model is shown to be tractable under certain assumptions. The results are encouraging given the complexity and the nature of the model.     

The modified second-round estimator in the general qualitative response model

This paper suggests a modification of the method of scoring in the general multivariate qualitative response model to attain simpler computation when there are many observations per cell. The paper shows that the proposed estimator is asymptotically efficient even in the cases when the generalized Berkson's estimator (see Amemiya, Journal of the American Statistical Association, June 1976) is not.     

Adverse effects of leverage and short-selling constraints in a financial market model with heterogeneous agents

This paper investigates the impact of leverage and short-selling constraints on financial market stability. Investors׳ demand is modelled in a well-known asset pricing model with heterogeneous beliefs. In particular, I generalise the heterogeneous agents model of Brock and Hommes (1998) and Anufriev and Tuinstra (2013) to allow for leverage constraints as well as a short-selling tax. I consider two examples of adaptive belief systems describing the coevolution of prices and investors׳ beliefs. First, if the market is inhabited by fundamentalist and chartist traders, demand constraints have potential adverse effects and may restrict the stabilising fundamentalist strategy such that mispricing and price volatility increase. Second, if the market is inhabited by fundamentalists, optimists and pessimists with fixed beliefs, demand constraints drive down price volatility, but mispricing remains. The results suggest the stabilising effects of demand constraints in financial markets are limited. Only if asset prices are too high compared to fundamentals, policy makers should consider constraining leverage ratios in order to deflate financial bubbles.     

On the estimation of multinomial logit models from relative frequency data

Standard estimators for the binomial logit model and for the multinomial logit model allow for an error arising from the use of relative frequencies instead of the true probabilities as the dependent variable. Recently Amemiya and Nold (1975) have considered the effect of the presence of an additional specification error in the binomial logit model and have proposed a modified logit estimation scheme to take the additional error variance into account. This paper extends their idea to the multinomial logit model and proposes an estimator that is consistent and asymptotically more efficient than the standard multinomial logit estimator. The paper presents a comparison of the results of applying the new estimator and existing estimators to a logit model for the choice of automobile ownership in the United States.     

Estimating multiple equation hybrid models with endogenous dummy regressors*

Estimating multiple equation hybrid models with endogenous dummy regressors is burdensome if the number of dummies and equations is large. Therefore, after clarifying model structure and identification issues the paper presents a generalization of the Amemiya principle. The new estimator reduces the computational costs and is flexible with regard to different types of variables. Furthermore, it is consistent and asymptotically normal distributed.     

The relationship between employee performance management and civil servants’ turnover intentions: a test of the mediating roles of system satisfaction and affective commitment

In search of maximizing efficiency, public organizations found solace in the adoption of employee performance management (EPM) systems. While research supports that managing employees’ performance has favourable outcomes, it is still unclear why and under which conditions. Moreover, EPM systems might even create additional pressures and therefore increase turnover intentions and undermine public organization’s quest to maximize efficiency. We argue that when EPM systems are carried out consistently (i.e. internal consistency) and when they link civil servants’ individual goals to the organization’s strategic goals (i.e. vertical alignment), civil servants will be less likely to leave the organization. Hierarchical linear regression analysis shows that internal consistency relates to increased satisfaction with the EPM system and affective commitment to the organization. Vertical alignment relates to lower levels of turnover intentions. This relationship was mediated by EPM system satisfaction and affective commitment. These findings that contribute to our understanding of EPM systems can lead to favourable outcomes.     

The nonlinear limited-information maximum- likelihood estimator and the modified nonlinear two-stage least-squares estimator

Several limited-information type estimators of the nonlinear simultaneous equation model are considered and their asymptotic covariance matrices are compared. Amemiya (1974) proposed the general class of nonlinear two-stage least-squares estimators. In this paper, its two specific members are considered and, in addition, the nonlinear limited-information maximum- likelihood estimator and the modified nonlinear two-stage least-squares estimator are proposed. Both are shown to be asymptotically more efficient than the nonlinear two-stage least-squares estimator, and the second has the advantage of being computationally simple.     

The use of advance order data in demand forecasting

This paper uses advance order data and historical demand data from a manufacturing shop and from a service operation to develop and test a forecasting methodology for predicting customer demand over a forecast horizon. The proposed methodology uses simple linear regression to model the relationship between a total demand ratio and a partial demand ratio. Comparison of the proposed model to a standard regression approach and a commonly used multiplicative model showed that the proposed model exhibited the greatest forecast accuracy.     

The structure of simultaneous equations estimators: A comment

This comment presents a generalised derivation of the maximum likelihood estimator of the parameters in a simultaneous equation model which incorporates an important class of models not included in Hendry (1976), namely those which have singular error covariance matrices. In so doing it conveniently brings under the scope of Hendry's analysis those models associated with systems of demand equations, models with identities and the joint structural and reduced form formulations proposed by Court (1974).     

Semiparametric estimation of a bivariate Tobit model

The existing semiparametric estimation literature has mainly focused on univariate Tobit models and no semiparametric estimation has been considered for bivariate Tobit models. In this paper, we consider semiparametric estimation of the bivariate Tobit model proposed by Amemiya (1974), under the independence condition without imposing any parametric restriction on the error distribution. Our estimator is shown to be consistent and asymptotically normal, and simulation results show that our estimator performs well in finite samples. It is also worth noting that while Amemiya’s (1974) instrumental variables estimator (IV) requires the normality assumption, our semiparametric estimator actually outperforms his IV estimator even when normality holds. Our approach can be extended to higher dimensional multivariate Tobit models.     

BENCHMARKING LARGE ACCOUNTING FRAMEWORKS: A GENERALIZED MULTIVARIATE MODEL

We present a multivariate benchmarking model for achieving consistency between large quarterly and annual accounting frameworks. The method is based on a quadratic optimization problem, for which many efficient numeric solvers exist. The method combines several features, such as linear constraints, ratio constraints, weights, and inequalities, in one model. Therefore, a wide range of modelling possibilities is supported. This method is especially interesting for national statistical offices, to simplify their processes to achieve consistency between publications.     

The Lowry Model Revisited: Incorporating a Multizonal Input-Output Model into an Urban Land Use Allocation Model

This paper formulates a new generation of Lowry-style models that combine a multizonal input-output model and an urban land use allocation model. Three different types of models are proposed: 1) an unconstrained model, 2) a primal of a linear programming approach that includes land supply constraints, and 3) a modified dual of the linear programming approach that allocates land based on additional conditions of economic efficiency. The modified dual formulation improves upon the limitations of Lowry models and their derivatives. First, the proposed model has sound theoretical underpinnings that incorporate the production theory of input-output models and the behavioral theory of optimization models. Second, the proposed model allocates land on the basis of economic efficiency by imposing a procedure that equalizes shadow prices. And third, the proposed model is an optimization model that fully accounts for the spatial and sectoral relationships of multiplier effects determining land use demand.     

Make and Use Approaches to Regional and Interregional Accounts and Models

Institutional, or sector-by-sector input–output tables have traditionally been used in regional and interregional modelling. This paper examines the origins of this tradition and argues instead, both theoretically and empirically, for the integration of make and use submodels within models of production, demand and interregional trade, outlining the manner in which they can be integrated. Further, it is argued that structural rather than reduced-form models represent a sounder theoretical base. Finally, a Danish interregional model (LINE) based on a social accounting matrix framework that employs these principles is presented. The paper also deals with the issue of data construction at the regional and interregional levels, based on the make and use approach. It is argued that when data are constructed at a low level of sectoral and spatial aggregation under accounting consistency constraints, data quality and validity are high.     

The empirical determination of technology and expectations: A simplified procedure

This paper makes three principal contributions to the growing body of empirically oriented research on dynamic factor demand systems that are based on the adjustment cost model of the firm. First, a simplified procedure is described for deriving demand and supply functions which are amenable to empirical estimation and which are consistent with intertemporal expected profit maximization and a general expectations formation process for future prices. Second, it is pointed out that estimation of a complete system of demand and supply functions permits the empirical identification of both the firm's technology and its expectations formation process. Finally, the procedure is applied to aggregate annual U.S. manufacturing data for the 1947-1977 period and the consistency of the data with the theoretical framework is investigated.     

Siting a facility in continuous space to maximize coverage of a region

Siting facilities in continuous space such that continuously distributed demand within a region is optimally served is a challenging location problem. This problem is further complicated by the non-convexity of regions typically encountered in practice. In this paper a model for maximizing the service coverage of continuously distributed demand through the location of a single service facility in continuous space is proposed. To address this problem, theoretical conditions are established and associated methods are proposed for optimally siting a service facility in a region (convex or non-convex) with uniformly distributed demand. Through the use of geographic information systems (GIS), the developed approach is applied to identify facility sites that maximize regional coverage provided limitations on facility service ability.     

School Finance Reform and Private School Enrollment: Evidence from California

Abstract: This paper uses the school finance reforms in California in the 1970s to examine whether the constraints such reforms impose on school districts lead to switching to private schools. Misspecifications of demand in previous work have led to understatement of reform effects. An empirical model of schooling share equations is derived from a discrete choice framework. Large biases are shown to result from failure to account for heterogeneity of demanders and school-district-specific fixed effects. Simulations indicate that the changes in public provision potentially resulting from reform explain a sizeable portion of the growth in the private school share.     

Nonlinear dynamical systems and inventory management

Surprisingly, deterministic time series can generate highly irregular, random-appearing trajectories. These deterministic time series result from nonlinear dynamical systems of differential or difference equations. The random appearance displayed by these systems is called nonlinear dynamical complexity. Properties of nonlinear complex systems include aperiodic random appearance, sensitive dependence on initial conditions and model parameters, and nonstationarity. Experiments involving the operation of simulated business environments and theoretical nonlinear dynamical models for inventory are reviewed to explore motivating factors that can give rise to demand with nonlinear complexities. The experimental and theoretical evidence reviewed indicates that nonlinear complexities in demand have significant implications for inventory management. Thus, researchers and practitioners in inventory management need to consider these properties when choosing inventory management methods. Characteristics of nonlinear dynamical systems and their implications for inventory management are presented in this paper. The use of the Brock, Dechert, and Scheinkman (1987) (BDS) test for nonlinear dependence is demonstrated on actual demand data.     

基于系统动力学的短生命周期产品供应链牛鞭效应研究

通过因果关系分析构建了短生命周期产品供应链订货、发货子系统的系统动力学模型结构图及方程,Vensim的模拟环境下,运行模型并对结果进行分析,提出消减牛鞭效应的对策建议。