Standards as Barriers Versus Standards as Catalysts: Assessing the Impact of HACCP Implementation on U.S. Seafood Imports

The United States mandated a Hazard Analysis Critical Control Points (HACCP) food safety standard for seafood in 1997. Panel model results for 1990 to 2004 suggest that HACCP introduction had a negative and significant impact on overall imports from the top thirty-three suppliers. While the effect for developed countries was positive, the negative effect for developing countries supports the view of “standards as barriers” versus “standards as catalysts.” A different perspective emerges from individual country-level analysis. Regardless of development status, leading seafood exporters generally experienced a positive HACCP effect, while most other smaller trading partners faced a negative effect

A Multi-objective Exploratory Procedure for Regression Model Selection

Variable selection is recognized as one of the most critical steps in statistical modeling. The problems encountered in engineering and social sciences are commonly characterized by over-abundance of explanatory variables, non-linearities and unknown interdependencies between the regressors. An added difficulty is that the analysts may have little or no prior knowledge on the relative importance of the variables. To provide a robust method for model selection, this paper introduces the Multi-objective Genetic Algorithm for Variable Selection (MOGA-VS) that provides the user with an optimal set of regression models for a given data-set. The algorithm considers the regression problem as a two objective task, and explores the Pareto-optimal (best subset) models by preferring those models over the other which have less number of regression coefficients and better goodness of fit. The model exploration can be performed based on in-sample or generalization error minimization. The model selection is proposed to be performed in two steps. First, we generate the frontier of Pareto-optimal regression models by eliminating the dominated models without any user intervention. Second, a decision making process is executed which allows the user to choose the most preferred model using visualisations and simple metrics. The method has been evaluated on a recently published real dataset on Communities and Crime within United States.Comment: in Journal of Computational and Graphical Statistics, Vol. 24, Iss. 1, 201

Cross-border electronic commerce: distance effects and express delivery in European Union markets

This empirical study examines distance effects on cross-border electronic commerce and in particular the importance of express delivery in reducing the time dimension of distance. E-commerce provides suppliers with a range of opportunities to reduce distance as perceived by online buyers. They can reduce psychological barriers to cross-border demand by designing websites that simplify the search for and comparison of products and suppliers across countries. They can reduce cost barriers by applying pricing strategies that redistribute transportation costs, and they can overcome time barriers offering express delivery services. This study of 721 regions in five countries of the European Union shows that distance is not “dead” in e-commerce, that express delivery reduces distance for cross-border demand, and that e-demand delivered by express services is more time sensitive and less price sensitive than e-demand satisfied by standard delivery. The willingness of e-customers to pay for express services is shown to be affected by income and by the relative lead-time benefits and express charges. Furthermore, the adoption of express delivery is positively associated with e-loyalty in terms of repurchase rates. The results confirm the importance for e-suppliers of cleverly designed delivery services to reduce distance in order to attract online customers across borders

Handbook of Econometrics

The greatest problem for empirical analysis is how best to allow the context to affect the inferences. Econometric theory presupposes contextual "restrictions" that can be taken as given or assigned a probability distribution. These contextual inputs are rarely available. I illustrate this point with a review of the empirical work in international economics which has focused not on properties of estimators but instead how best to link the theory with the data. I argue that the two errors we should worry about are not rejecting a true null or accepting a false null but rather taking the theory too seriously and not taking the theory seriously enough.

Handbook of Econometrics

Often researchers find parametric models restrictive and sensitive to deviations from the parametric specifications; semi-nonparametric models are more flexible and robust, but lead to other complications such as introducing infinite-dimensional parameter spaces that may not be compact and the optimization problem may no longer be well-posed. The method of sieves provides one way to tackle such difficulties by optimizing an empirical criterion over a sequence of approximating parameter spaces (i.e., sieves); the sieves are less complex but are dense in the original space and the resulting optimization problem becomes well-posed. With different choices of criteria and sieves, the method of sieves is very flexible in estimating complicated semi-nonparametric models with (or without) endogeneity and latent heterogeneity. It can easily incorporate prior information and constraints, often derived from economic theory, such as monotonicity, convexity, additivity, multiplicity, exclusion and nonnegativity. It can simultaneously estimate the parametric and nonparametric parts in semi-nonparametric models, typically with optimal convergence rates for both parts. This chapter describes estimation of semi-nonparametric econometric models via the method of sieves. We present some general results on the large sample properties of the sieve estimates, including consistency of the sieve extremum estimates, convergence rates of the sieve M-estimates, pointwise normality of series estimates of regression functions, root-n asymptotic normality and efficiency of sieve estimates of smooth functionals of infinite-dimensional parameters. Examples are used to illustrate the general results.

Handbook of Econometrics

This chapter presents a unified set of estimation methods for fitting a rich array of models describing dynamic relationships within a longitudinal data setting. The discussion surveys approaches for characterizing the micro dynamics of continuous dependent variables both over time and across individuals, focusing on two flexible sets of empirical specifications: dynamic simultaneous equations models incorporating error-components structures, and autoregressive quantile models. The chapter is motivated by the principle that, whenever possible, estimation methods should rely on routines available in familiar software packages to make them accessible to a wide range of practitioners. Conventional method-of-moments procedures offer a general apparatus for estimating parameters of panel-data specifications, though one must introduce a series of modifications to overcome challenges arising from: (1) use of unbalanced data structures, (2) weighting to account for stratified sampling inherent in survey longitudinal data, (3) incorporation of predetermined variables in estimation, and (4) computational complexities confronted when estimating large systems of equations with intricate intertemporal restrictions. To allow researchers to separate the estimation of longitudinal time-series specifications into manageable pieces, the discussion describes multi-step approaches that estimate subsets of parameters appearing in a single model component (such as the autoregressive or moving-average structure of the error process) without having to estimate all parameters of the entire model jointly. Such procedures offer a powerful set of diagnostic tools for narrowing model choices and for selecting among specifications that fit the underlying data. To illustrate all of the econometric methods outlined in this chapter, the analysis presents a set of empirical applications summarizing the dynamic properties of hourly wages for adult men using data from the Panel Study of Income Dynamics.