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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
Articles A* Publications - 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
- Griffiths W. and G. Hajargasht (2016) Some Models for Stochastic Frontiers with Endogenity, Journal of Econometrics, 190(2), 341-348
- 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
Income Distribution - Hajargasht G. and W. Griffiths (Forthcoming), Minimum Distance Estimation of Parametric Lorenz Curves, Econometric Reviews
- Chotikapanich, D., Griffiths, W. E., Hajargasht, G., Karunarathne, W., & Rao, D. S. (2018). Using the GB2 Income Distribution. Econometrics, 6(2), 21.
- 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. and W. Griffiths (2013), GMM Estimation of Mixtures from Grouped Data, Department of Economics - Working Papers Series 1148, The University of Melbourne.
- Chotikapanich D., W. Griffiths, G. Hajargasht and C. Xia, Inequality and Poverty in Africa: Regional Updates and Estimation of a Panel Of Income Distributions.
Purchasing Power Parities (PPP) - Hajargasht, G., & Rao, D. P. (2019). Multilateral index number systems for international price comparisons:properties, existence and uniqueness. Journal of Mathematical Economics, 83, 36-47.
- 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
- Hajargasht, G. and D.S. Prasada Rao and A. Valadkhani (2019), Reliability of Basic Heading PPPs, Economics Letters, 180, 102-107.
- 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. & 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
Productivity Measurement - Hajargasht G. and W. Griffiths (Forthcoming), “A
Semiparametric Stochastic Frontiers with Correlated Effects”, Advances in
Econometrics. Vol 40.
- Hajargasht G. and W. Griffiths (2018), "Estimation and Testing of Stochastic Frontier Models using Variational Bayes", Journal of Productivity Analysis, Code
- Griffiths W. and G. Hajargasht (2016) Some Models for Stochastic Frontiers with Endogenity, Journal of Econometrics, 190(2), 341-348
- Hajargasht G. (2015) Stochastic Frontiers with a Rayleigh Distribution, Journal of Productivity Analysis , 44,2, 199-208
- 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
- Valadkhani A., J Nguyen, R Hajargasht (2019), Incorporating daily market uncertainty data into a conventional short-run dynamic model: the case of the black-market exchange rate in Iran, Applied Economics.
- 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.
- 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.
Bayesian and Simulation Based Econometrics: Submitted Papers Hajargasht G. and W. Griffiths (2016) "Inference for Parametric Lorenz Curves" , Submitted. Code
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
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