A Review of the `BMS' Package for R

This paper describes the relative merits and attractiveness of the newest Bayesian model averaging package, BMS, available in the statistical software R to implement a Bayesian model averaging exercise. This package provides the user with a wide range of customizable priors for conducting a BMA analysis, provides ample graphs to visualize the results and offers several alternative model search mechanisms.Model Averaging, Zellner's g Prior, BMS

Income Polarization, Convergence Tools and Mixture Analysis

Modeling the cross-country distribution of per capita using mixture analysis provides a natural platform for the recovery or detection of clubs of countries. Unfortunately, these mixture methods, when based on a strictly univariate approach are limiting towards one's ability to learn about the underlying process of the emergence of the clubs. This paper takes a fresh look at the sources contributing to the emergence of clubs in the distribution of cross-country output using bivariate and multivariate mixture analysis.Convergence, Orientation, Mixture Densities

Bayesian Model Averaging in R

Bayesian model averaging has increasingly witnessed applications across an array of empirical contexts. However, the dearth of available statistical software which allows one to engage in a model averaging exercise is limited. It is common for consumers of these methods to develop their own code, which has obvious appeal. However, canned statistical software can ameliorate one's own analysis if they are not intimately familiar with the nuances of computer coding. Moreover, many researchers would prefer user ready software to mitigate the inevitable time costs that arise when hard coding an econometric estimator. To that end, this paper describes the relative merits and attractiveness of several competing packages in the statistical environment R to implement a Bayesian model averaging exercise.Model Averaging, Zellner's g Prior, BMS

HAS THE WORLD TRADE ORGANIZATION PROMOTED SUCCESSFUL REGIONAL TRADE AGREEMENTS?

This study uses econometric gravity equations to test whether the WTO has promoted successful regional trade agreements (RTA). Two important findings emerge. First, we find that two countries that are members of the GATT/WTO and enter into a regional trade agreement stimulate trade. However, the effect on trade is not nearly as large as that between two RTA members that belong to the GATT/WTO. Contrary to the findings in Rose (2004), this result tends to support the fact that the GATT/WTO has liberalized multilateral trade, outside of RTAs. In other words, the effect of an RTA on countries’ trade who are not party to the GATT/WTO should generate a large RTA trade response due to relatively large pre-existing trade distortions. Second, we show that the GATT/WTO has not promoted successful RTAs using explicit RTA variables that controls for the notification status (to the GATT/WTO) of an RTA. Interestingly, non-notified RTAs trade significantly more than their notified counterparts.International Relations/Trade,

Normal Reference Bandwidths for the General Order, Multivariate Kernel Density Derivative Estimator

This note derives the general form of the approximate mean integrated squared error for the q-variate, th-order kernel density r th derivative estimator. This formula allows for normal reference rule-of-thumb bandwidths to be derived. We give tables for some of the most common cases in the literature.Derivative Estimation, Smoothing, AMISE

Imposing Economic Constraints in Nonparametric Regression: Survey, Implementation and Extension

Economic conditions such as convexity, homogeneity, homotheticity, and monotonicity are all important assumptions or consequences of assumptions of economic functionals to be estimated. Recent research has seen a renewed interest in imposing constraints in nonparametric regression. We survey the available methods in the literature, discuss the challenges that present themselves when empirically implementing these methods and extend an existing method to handle general nonlinear constraints. A heuristic discussion on the empirical implementation for methods that use sequential quadratic programming is provided for the reader and simulated and empirical evidence on the distinction between constrained and unconstrained nonparametric regression surfaces is covered.identification, concavity, Hessian, constraint weighted bootstrapping, earnings function

Canonical Higher-Order Kernels for Density Derivative Estimation

In this note we present r th order kernel density derivative estimators using canonical higher-order kernels. These canonical rescalings uncouple the choice of kernel and scale factor. This approach is useful for selection of the order of the kernel in a data-driven procedure as well as for visual comparison of kernel estimates.Derivative Estimation, AMISE

Paperless Food Assistance: The Impact of Electronic Benefits on Program Participation

Food Stamp Program, Electronic Benefits, Program Participation, Food Security and Poverty, Health Economics and Policy, I38, C23, C25,

Decomposing The Conditional Variance of Cross-Country Output

A well established fact in the growth empirics literature is the increasing variation in output per capita across countries. This phenomena however does not adequately describe changes in the distribution of output since it does not account for changes in the covariates which undoubtedly in influence per capita output levels. We propose a robust, nonparametric decomposition of the conditional variation of per capita output and find that OECD countries have experienced diminishing conditional variation while other regions have experienced increasing conditional variation. Our decomposition suggests that most of these changes in the conditional variance of output is due to unobserved factors not accounted for by the traditional growth determinants. In addition to this we show as these factors played very different roles over time and across regions.Generalized Kernel, Nonparametric, Conditional Variation

Does urbanization mean bigger governments?

This paper proposes urbanization as a determinant of government size. As people move to cities, their demand for a more de ned set of regulations, but also for basic health, education, and income standards rises. Our theoretical framework determines how the regional distribution of the population a ects government size. We test this theory on panel data of 175 countries from 1960 to 2010 and two state-level samples from Colombia and Germany. Results demonstrate a strong positive e ect from urbanization on government spending, with a 1 percent increase in the amount of urban citizens leading to a 0.2 percent rise in public expenditure. Our ndings indicate that public sectors may become more important as worldwide urbanization is progressing. This result underlines why government e ectiveness and the quality of public goods provision will be even more important in the future