A two-step approach to account for unobserved spatial heterogeneity

A two-step approach to account for unobserved spatial heterogeneity. Spatial Economic Analysis. Empirical analysis in economics often faces the difficulty that the data are correlated and heterogeneous in some unknown form. Spatial econometric models have been widely used to account for dependence structures, but the problem of directly dealing with unobserved spatial heterogeneity has been largely unexplored. The problem can be serious particularly if we have no prior information justified by economic theory. In this paper we propose a two-step procedure to identify endogenously spatial regimes in the first step and to account for spatial dependence in the second step. This procedure is applied to hedonic house price analysis.     

Proportional reversed hazard and frailty models

Reversed hazard rates are found to be very useful in survival analysis and reliability especially in study on parallel systems and in the analysis of left censored lifetime data. In this paper, we derive a class of bivariate distributions having marginal proportional reversed hazard rates. We, then, introduce a class of proportional reversed hazard rates frailty models and propose a multivariate correlated gamma frailty model. Bivariate reversed hazard rates and association measure are discussed in terms of frailty parameters.     

Testing for unobserved heterogeneity in exponential and Weibull duration models

We examine the use of the likelihood ratio (LR) statistic to test for unobserved heterogeneity in duration models, based on mixtures of exponential or Weibull distributions. We consider both the uncensored and censored duration cases. The asymptotic null distribution of the LR test statistic is not the standard chi-square, as the standard regularity conditions do not hold. Instead, there is a nuisance parameter identified only under the alternative, and a null parameter value on the boundary of the parameter space, as in Cho and White (2007a). We accommodate these and provide methods delivering consistent asymptotic critical values. We conduct a number of Monte Carlo simulations, comparing the level and power of the LR test statistic to an information matrix (IM) test due to Chesher (1984) and Lagrange multiplier (LM) tests of Kiefer (1985) and Sharma (1987). Our simulations show that the LR test statistic generally outperforms the IM and LM tests. We also revisit the work of van den Berg and Ridder (1998) on unemployment durations and of Ghysels et al. (2004) on interarrival times between stock trades, and, as it turns out, affirm their original informal inferences.     

Organizing customer-oriented service business in manufacturing

This study examines the organization of service business in manufacturing. Earlier literature has emphasized the positive effects of a separate service unit. Our comparative case study indicates that a separate unit as such does not guarantee success in service business. An essential issue is how customer interaction and the continuous flow of customer information have been secured. Sales personnel have often been regarded as the main actor in the creation of customer intelligence. Based on our study we argue that attention should also be paid to field technicians and other operative personnel as a channel for customer information.     

Pricing behaviour in UK manufacturing and service industries

This paper reports the findings related to pricing behaviour of 1775 manufacturing and service firms. Its objectives were to examine the nature of pricing objectives at differing stages of market evolution and for companies of differing size and to examine the association between pricing objectives and performance. Princing objectives were found to vary with stages of market evolution and firm size. Both positive and negative relationships between pricing objectives and performance were revealed.     

Computation in duration models with heterogeneity

This paper examines the use of Hermite polynomial quadrature to evaluate certain integrals in the maximum likelihood estimation of duration models.     

Unobserved heterogeneity in event history models

This paper demonstrates the effect of unobserved heterogeneity in event history models and discusses parametric methods to include unobserved factors into the models. Using data on career trajectories of German males, the application of models with unobserved heterogeneity is shown.     

Neglected heterogeneity in moment condition models

The central concern of this paper is parameter heterogeneity in models specified by a number of unconditional or conditional moment conditions and thereby the provision of a framework for the development of apposite optimal $m$-tests against its potential presence. We initially consider the unconditional moment restrictions framework. Optimal $m$-tests against moment condition parameter heterogeneity are derived with the relevant Jacobian matrix obtained in terms of the second order own derivatives of the moment indicator in a leading case. GMM and GEL tests of specification based on generalized information matrix equalities appropriate for moment-based models are described and their relation to optimal $m$-tests against moment condition parameter heterogeneity examined. A fundamental and important difference is noted between GMM and GEL constructions. The paper is concluded by a generalization of these tests to the conditional moment context and the provision of a limited set of simulation experiments to illustrate the efficacy of the proposed tests.     

A PageRank-based reputation model for personalised manufacturing service recommendation

The number of manufacturing services for cross-enterprise business collaborations is increasing rapidly because of the explosive growth of Web service technologies. This trend demands intelligent and robust models to address information overload in order to enable efficient discovery of manufacturing services. In this paper, we present a personalised manufacturing service recommendation approach, which combines a PageRank-based reputation model and a collaborative filtering technique in a unified framework for recommending the right manufacturing services to an active service user for supply chain deployment. The novel aspect of this research is adapting the PageRank algorithm to a network of service-oriented multi-echelon supply chain in order to determine both user reputation and service reputation. In addition, it explores the use of these methods in alleviating data sparsity and cold start problems that hinder traditional collaborative filtering techniques. A case study is conducted to validate the practicality and effectiveness of the proposed approach in recommending the right manufacturing services to active service users.     

Modeling node heterogeneity in latent space models for multidimensional networks

Multidimensional network data can have different levels of complexity, as nodes may be characterized by heterogeneous individual-specific features, which may vary across the networks. This article introduces a class of models for multidimensional network data, where different levels of heterogeneity within and between networks can be considered. The proposed framework is developed in the family of latent space models, and it aims to distinguish symmetric relations between the nodes and node-specific features. Model parameters are estimated via a Markov Chain Monte Carlo algorithm. Simulated data and an application to a real example, on fruits import/export data, are used to illustrate and comment on the performance of the proposed models.     

Using learning networks to help improve manufacturing competitiveness

Innovation which requires the acquisition of new or improved technologies involves a technical and managerial learning process and it raises the policy question of how best to encourage and enable relevant learning. The absence or lack of experience in this domain is a particular problem for smaller firms (SMEs) and for enterprises in economies in transition—such as in the countries of the former Soviet Union or in eastern Europe. Successful technology transfer requires considerable management expertise as well as the availability of suitable solutions. This paper reports on one experimental approach used on a pilot basis in Romania to facilitate the absorption of `new' manufacturing practices, which involves the development of `learning networks' as an aid to this process.     

Testing for time-invariant unobserved heterogeneity in generalized linear models for panel data

Recent literature on panel data emphasizes the importance of accounting for time-varying unobservable individual effects, which may stem from either omitted individual characteristics or macro-level shocks that affect each individual unit differently. In this paper, we propose a simple specification test of the null hypothesis that the individual effects are time-invariant against the alternative that they are time-varying. Our test is an application of Hausman (1978) testing procedure and can be used for any generalized linear model for panel data that admits a sufficient statistic for the individual effect. This is a wide class of models which includes the Gaussian linear model and a variety of nonlinear models typically employed for discrete or categorical outcomes. The basic idea of the test is to compare two alternative estimators of the model parameters based on two different formulations of the conditional maximum likelihood method. Our approach does not require assumptions on the distribution of unobserved heterogeneity, nor it requires the latter to be independent of the regressors in the model. We investigate the finite sample properties of the test through a set of Monte Carlo experiments. Our results show that the test performs well, with small size distortions and good power properties. We use a health economics example based on data from the Health and Retirement Study to illustrate the proposed test.     

Adjustment and unobserved heterogeneity in dynamic stochastic frontier models

Stochastic frontier models with autocorrelated inefficiency have been proposed in the past as a way of addressing the issue of temporal variation in firm-level efficiency scores. They are justified using an underlying model of dynamic firm behavior. In this paper we argue that these models could have radically different implications for the expected long-run efficiency scores in the presence of unobserved heterogeneity. The possibility of accounting for unobserved heterogeneity is explored. Random- and correlated random-effects dynamic stochastic frontier models are proposed and applied to a panel of US electric utilities.     

Patterns and dynamics of population heterogeneity in mixtures models

Mixtures of distributions are a common modelling tool for durations of social phenomena, especially when the population is believed to be heterogeneous. We discuss heterogeneity patterns which can be captured by various mixing distributions in continuous and discrete time. Particular attention is given to recidivism data which Kaplan modeled by beta-mixtures of geometric distributions. We also investigate the dynamics of heterogeneity, measured via the variance of the mixing distribution, over the duration. It is shown that not all mixture models display decreasing heterogeneity over time.     

Reinforced urn processes for credit risk models

We propose a Bayesian nonparametric model to estimate rating migration matrices and default probabilities using the reinforced urn processes (RUP) introduced in Muliere et al. (2000). The estimated default probability becomes our prior information in a parametric model for the prediction of the number of bankruptcies, with the only assumption of exchangeability within rating classes. The Polya urn construction of the transition matrix justifies a Beta distributed de Finetti measure. Dependence among the processes is introduced through the dependence among the default probabilities, with the Bivariate Beta Distribution proposed in Olkin and Liu (2003) and its multivariate generalization.     

Planning processes for advanced manufacturing technology by large American manufacturers

In response to an increasingly competitive environment, many manufacturers have invested in advanced manufacturing technology (AMT). While many studies regarding the use of AMT have been performed, little is known about how firms plan and manage their AMT investments. This is surprising given the evidence about the impact such investments can have on an organization. To address this, a survey of large American manufacturing firms was conducted. Respondents were asked, among other questions, why their firms made such investments and the fit with their business strategy; which functional areas were involved in idea generation, the planning process, and proposal assessment; and what the anticipated risks, difficulties and benefits were from making such investments. The results from this survey are provided along with an analysis of the responses.     

Local linear M-estimation for spatial processes in fixed-design models

We investigate the local linear M-estimation for regression in a fixed-design model when the errors are from a strongly mixing random field. We establish the weak and strong consistency as well as the asymptotic normality of the local linear M-estimator. The conditions on ρ(·) used in this paper are mild and allow many important special cases such as the least square estimator and the least absolute distance estimator.     

Operational models for epidemics of problematic drug use: the Mover-Stayer approach to heterogeneity

A modified version of a susceptibles-infectives-removed (S-I-R) model for the HIV/AIDS epidemic, proposed at the beginning of the 1990s and recently generalized, is presented to mirror the epidemics of problematic drug use. The generalized model, which belongs to the susceptibles-infectives-susceptibles (S-I-S) class of epidemic models, can be used both to estimate interesting epidemic macro-parameters and to make scenario analyses. The model is a compartmental Mover-Stayer-type structure (Soc. Methods Res. 11 (1983) 345; Bull. Narcotics LIII (1-2) (2001) 39; Biometrics 55(4) (1999) 1252; Math. Biosci. 107 (1991) 521) and allows taking into account possible heterogeneous behaviours of the susceptibles. Such models, in fact, consider the susceptible population as subdivided into two main groups: the group of stayers, that is, the group of individuals who are considered not at risk of “infection”, and the group of movers (possibly divided into sub-groups with different risk behaviour) who are at risk of infection. Due to the interactions between infectious individuals and the susceptibles, some of these may pass to the drug user compartments and begin a “drug user career”. The model is presented and studied from a qualitative point of view using a Markov hybrid approximation. Some qualitative evaluation of the possible impact of interventions directed both towards susceptibles (primary prevention) and towards users (secondary prevention and/or law enforcement) are presented. Specific “what if” scenario analyses are obtained by simulation. Possible future developments are outlined.