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

    Articles        

Hajargasht, R., Hill, R. J., Rao, D. P., & Shankar, S. (2018). Spatial Chaining in International Comparisons of Prices and Real Incomes (No. 2018-03). University of Graz, Department of Economics.

Griffiths W. and G. Hajargasht (2016) Some Models for Stochastic Frontiers with Endogenity, Journal 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 Distribution, Journal 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 Data, Economic Modelling, 33, 593-604

Hajargasht G., Griffiths, W. , Brice, J., Rao, D.S. and Chotikapanich, D. (2012) Inference for Income Distributions using  Grouped Data, Journal 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 Letters, Elsevier, vol. 100(2), pages 185-188

Hajargasht G., and D.S. Prasada Rao (2015),"Multilateral Index Number Systems For International Price Comparisons: Properties, Existence and Uniqueness", Revise-Resubmit

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

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

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

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 Data, Department 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 Bayes, Department of Economics - Working Papers Series, The University of Melbourne

Coelli T., G. Hajargasht and C.A. Lovell, Econometric 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