Selection of influential variables in ordinal data with preponderance of zeros

Presence of excess zero in ordinal data is pervasive in areas like medical and social sciences. Unfortunately, analysis of such kind of data has so far hardly been looked into, perhaps for the reason that the underlying model that fits such data, is not a generalized linear model. Obviously some methodological developments and intensive computations are required. The current investigation is concerned with the selection of variables in such models. In many occasions where the number of predictors is quite large and some of them are not useful, the maximum likelihood approach is not the automatic choice. As, apart from the messy calculations involved, this approach fails to provide efficient estimates of the underlying parameters. The proposed penalized approach includes ?₁ penalty (LASSO) and the mixture of ?₁ and ?₂ penalties (elastic net). We propose a coordinate descent algorithm to fit a wide class of ordinal regression models and select useful variables appearing in both the ordinal regression and the logistic regression based mixing component. A rigorous discussion on the selection of predictors has been made through a simulation study. The proposed method is illustrated by analyzing the severity of driver injury from Michigan upper peninsula road accidents.     

Measuring the Impact of Socio-Economic Factors on School Efficiency in Australia

This paper examines the productive efficiency of government schools in New South Wales (NSW) in Australia. The study uses a technical inefficiency effects model applied to a unique three-year panel dataset containing 1235 primary and 371 secondary schools in NSW. A stochastic frontier production function and an inefficiency effects function that control for school socioeconomic and environmental factors are estimated. The dataset contains information on various school inputs, school expenditures by major functional area, parental socioeconomic characteristics, student characteristics, and standardized test scores. We examine the degree to which school and non-school educational inputs influence student achievement scores and find that, overall, primary schools are 88.6% and secondary schools 96.4% efficient. The index describing community socio-educational advantage has the most significant influence on students’ achievement scores.     

The mitigating effect of matching regulatory focus with arousal-inducing stimuli in service failure situations

Service failures are pivotal touchpoints that can reduce customer satisfaction, encourage negative word-of-mouth, and ultimately impact a firm's market share. We advance a novel perspective that after a service failure occurs, matching incidental arousal-inducing stimuli to one's regulatory orientation can make the negative experience stemming from the service failure less deleterious. In three experiments (two stock out scenarios and one involving a rude salesperson), after a service failure, promotion-focused and prevention-focused individuals were exposed to high versus low arousal-inducing stimuli. Three approaches available to retailers were used to manipulate arousal levels: background pictures (Study 1), colors (Study 2), and music (Study 3). When high (low) incidental arousal-inducing stimuli were presented to those with a promotion (prevention) focus, this raised satisfaction, loyalty, and referral for brands compared to when promotion (prevention)-focused individuals were exposed to low (high) arousal-inducing stimuli. Changes in self-rated arousal and affect valence levels (arousal and valence levels were measured after the service failure and then after exposure to the incidental arousal-inducing stimuli) mediated the effect on these consumer behaviors. These insights extend theory by considering the combined effect of regulatory focus and affect. They also have practical relevance.     

China and India： A Tale of Two Economies

I. Two Populous GiantsIt has been conventional wisdom to make comparison between the two geographicallylarge and populous countries, which share a long common border, have entrepreneurialtrading heritage, enormous internal diversity, large agricultural sectors, ancient culturesand almost five thousand years of histories. Both were noted for their economic prowess inthe past, albeit their more recent history of the last two centuries has been replete withdistressful colonization of one and eco…     

Hub-and-Spokes Free Trade Agreements in the Presence of Technology Spillovers: An Application to the Western Hemisphere

Using a comparative-static general equilibrium model in the context of the Western Hemisphere, this paper compares the economic effects of a “hub-and-spokes” type of bilateral trade configuration (with Chile being the hub) with those of a more comprehensive regional FTA (namely, the FTAA). The model is augmented to account for the possibility of technology spillovers and its effective assimilation among participating economies. In particular, absorptive capacity, governance factor, proximity and socio-institutional congruence conjointly determine an economy’s capacity to capture the technology that is transmitted from the developed spoke United States to other regions. JEL no. D58, F13, O33     

Fiscal consolidation with high growth: A policy simulation model for India

In this paper a fiscal consolidation program for India has been presented based on a policy simulation model that enables us to examine the macroeconomic implications of alternative fiscal strategies, given certain assumptions about other macro policy choices and relevant exogenous factors. The model is then used to estimate the outcomes resulting from a possible strategy of fiscal consolidation in the base case. The exercise shows that it is possible to have fiscal consolidation while at the same time maintaining high GDP growth of around 8% or so. The strategy is to gradually bring down the revenue deficit to zero by 2014–15, while allowing a combined fiscal deficit for centre plus states of about 6% of GDP. This provides the space for substantial government capital expenditure, which translates to a significant public investment program. This in turn leads to high overall investment directly and indirectly, via the crowding in effect on private investment, which drives the high GDP growth. The exercise has also tested the robustness of this strategy under two alternative scenarios of higher and lower advanced country growth compared to the base case.     

On someE-optimal block designs

Summary TheE-optimality of block designs is the concern of this paper. Bounds for the smallest positive eigenvalue of theC-matrix of block designs are obtained in some general classes of connected designs with equal or unequal block sizes. Use of these bounds is made to obtainE-optimal block designs in various classes.     

Interpartner Legitimacy in the Alliance Development Process*

abstract We propose a framework to understand interpartner legitimacy in strategic alliances. Interpartner legitimacy is the mutual acknowledgment by the alliance partners that their actions are proper in the developmental processes of the alliance. We argue that interpartner legitimacy is needed for cooperation to achieve alliance objectives. We propose three types of interpartner legitimacy – pragmatic, moral, and cognitive legitimacy – and discuss the dynamics of these three types in the formation, operation, and outcome stages of alliance development. Further, we discuss the salience of interpartner legitimacy in different alliance types. Finally, we derive propositions for further research, and discuss strategies that alliance managers can adopt to develop interpartner legitimacy.     

Analysis of marginally specified semi-nonparametric models for clustered binary data

Generalized linear mixed models are widely used for analyzing clustered data. If the primary interest is in regression parameters, one can proceed alternatively, through the marginal mean model approach. In the present study, a joint model consisting of a marginal mean model and a cluster-specific conditional mean model is considered. This model is useful when both time-independent and time-dependent covariates are available. Furthermore our model is semi-parametric, as we assume a flexible, smooth semi-nonparametric density of the cluster-specific effects. This semi-nonparametric density-based approach outperforms the approach based on normality assumption with respect to some important features of 'between-cluster variation'. We employ a full likelihood-based approach and apply the Monte Carlo EM algorithm to analyze the model. A simulation study is carried out to demonstrate the consistency of the approach. Finally, we apply this to a study of long-term illness data.