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    Current Research Interests

Microeconometrics: Inference for Income Distribution, Inequality and Poverty      

Measures; Nonparametric Inference; Bayesian IV

Index Numbers: in particular Purchasing Power Parities

Productivity: Efficiency and Productivity Measurement

Bayesian and Simulation Based Econometrics: MCMC, Variational Bayes,  

Bayesian Large Macroeconometric Models, Maximum Simulated Likelihood


Griffiths W. and G. Hajargasht (2016) Some Models for Stochastic Frontiers with EndogenityJournal of Econometrics, 190(2), 341-348

Rao D.S. Prasada and G. Hajargasht (2016), Stochastic Approach to Computation of Purchasing Power Parities in the International Comparison Program (ICP), Journal of Econometrics, 191(2), 414–425          

Hajargasht G. (2015) Stochastic Frontiers with a Rayleigh DistributionJournal of Productivity Analysis , 44,2, 199-208

Griffiths, W. and G. Hajargasht (2015) On GMM Estimation of Distributions from Grouped Data, Economics Letters, 126, 122-126.

Hajargasht G. and Griffiths, W. (2013) Pareto–Lognormal Distributions: Inequality, Poverty, and Estimation  from Grouped Income DataEconomic Modelling, 33, 593-604

Hajargasht G., Griffiths, W. , Brice, J., Rao, D.S. and Chotikapanich, D. (2012) Inference for Income Distributions using  Grouped DataJournal of Business and Economic Statistics, 30, 563-75

Hajargasht, G. & D.S. Prasada Rao. (2010) “Stochastic Approach to Index Numbers for Multilateral Price Comparisons and their Standard Errors", Review of Income and Wealth, 56, S32-S58

Hajargasht, G., Coelli, T and Rao, D.S. Prasada, (2008). "A Dual Measure of Economies of Scope", Economics LettersElsevier, vol. 100(2), pages 185-188

     Submitted Papers
           Hajargasht G. and W. Griffiths (2016) "Inference for Parametric Lorenz Curves" , Submitted. Code

Hajargasht G. and W. Griffiths (2016), "Estimation and Testing of Stochastic Frontier Models using Variational Bayes", Submitted.   Code

     Working Papers

Chotikapanich D., W. Griffiths, G. Hajargasht and C. XiaInequality and Poverty in Africa: Regional Updates and Estimation of a Panel Of Income Distributions.

Hajargasht, G. (2014), The Folded Normal Stochastic Frontier ModelCode

Hajargasht, G. and D.S. Prasada Rao, Nonparametric  Panel  Data  Models:  A  Penalized  Spline Approach.  

Hajargasht G. and W. Griffiths (2013), GMM Estimation of Mixtures from Grouped DataDepartment of Economics - Working Papers Series 1148, The University of Melbourne.

Hajargasht G. and W. Griffiths (2013), Estimation and Testing of Stochastic Frontier Models using Variational BayesDepartment of Economics - Working Papers Series, The University of Melbourne

Coelli T., G. Hajargasht and C.A. LovellEconometric Estimation of an Input Distance Function in a System of Equations," CEPA Working Papers Series WP012008, School of Economics, University of Queensland, Australia.

     Works in Progress:

 Flexible Estimation of Stochastic Frontiers (1):  A Bayesian Penalized Spline Approach.

 Flexible Estimation of Stochastic Frontiers (2): Panel Data Models.

 Flexible Estimation of Stochastic Frontiers (3): Time-Varying Panel Data Models.

 Variational Bayes Methods for Large Bayesian VARs

 Accurate Computation of Marginal Data Density using Variational Bayes

 A Minimum Distance and the Generalized EKS Approaches to Multilateral Comparisons of    Prices  and Real Incomes

 Panel Data Models with Endogeniety and Sample Selection

 Stochastic Frontiers Using Maximum Simulated Likelihood