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Economics - Research Publications
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ItemUsing the GB2 Income DistributionChotikapanich, D ; Griffiths, WE ; Hajargasht, G ; Karunarathne, W ; Rao, DSP (MDPI AG, 2018-06-01)To use the generalized beta distribution of the second kind (GB2) for the analysis of income and other positively skewed distributions, knowledge of estimation methods and the ability to compute quantities of interest from the estimated parameters are required. We review estimation methodology that has appeared in the literature, and summarize expressions for inequality, poverty, and pro-poor growth that can be used to compute these measures from GB2 parameter estimates. An application to data from China and Indonesia is provided.
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ItemEstimation and testing of stochastic frontier models using variational BayesHajargasht, G ; Griffiths, WE (Springer Verlag, 2018-10)We show how a wide range of stochastic frontier models can be estimated relatively easily using variational Bayes. We derive approximate posterior distributions and point estimates for parameters and inefficiency effects for (a) time invariant models with several alternative inefficiency distributions, (b) models with time varying effects, (c) models incorporating environmental effects, and (d) models with more flexible forms for the regression function and error terms. Despite the abundance of stochastic frontier models, there have been few attempts to test the various models against each other, probably due to the difficulty of performing such tests. One advantage of the variational Bayes approximation is that it facilitates the computation of marginal likelihoods that can be used to compare models. We apply this idea to test stochastic frontier models with different inefficiency distributions. Estimation and testing is illustrated using three examples.
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ItemSome models for stochastic frontiers with endogeneityGriffiths, WE ; Hajargasht, G (ELSEVIER SCIENCE SA, 2016-02)
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ItemOn GMM estimation of distributions from grouped dataGriffiths, W ; Hajargasht, G (Elsevier, 2015)For estimating distributions from grouped data, setting up moment conditions in terms of group shares and group means leads to an optimal weight matrix and a GMM objective function that are considerably simpler than those from a previous specification. Minimization is more efficient and convergence is more reliable.
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ItemSTOCHASTIC APPROACH TO INDEX NUMBERS FOR MULTILATERAL PRICE COMPARISONS AND THEIR STANDARD ERRORSHajargasht, G ; Rao, DSP (WILEY, 2010-06)The main objective of the paper is to demonstrate that a number of widely used multilateral index numbers for international comparisons of purchasing power parities (PPPs) and real incomes can be derived using the stochastic approach. The paper shows that price index numbers from commonly used methods like the Iklé, the Rao‐weighted, and an additive multilateral system are all estimators of the parameters of the country–product–dummy (CPD) model. The advantage of the stochastic approach is that we can derive standard errors for the estimates of the purchasing power parities (PPPs). The PPPs and the parameters of the stochastic model are estimated using a weighted maximum likelihood procedure under different stochastic specifications for the disturbance term. Estimates of PPPs and their standard errors for OECD countries using the proposed methods are presented. The paper also outlines a method of moments approach to the estimation of PPPs under the stochastic approach. The paper shows how the Geary–Khamis system of multilateral index numbers is a method of moments estimator of the parameters of the CPD model. The paper therefore provides a coherent stochastic framework for the Geary–Khamis system and derives standard errors of the Geary–Khamis PPPs.