IDEAS home Printed from https://ideas.repec.org/a/bla/ajarec/v57y2013i2p159-177.html
   My bibliography  Save this article

The distributional effects of the Hilmer reforms on the Australian gas industry

Author

Listed:
  • George Verikios
  • Xiao-guang Zhang

Abstract

We analyse changes in the Australian gas industry during 1990s that were motivated by the Hilmer Reforms. We estimate the effects on real household income of the changes by combining a computable general equilibrium model with a microsimulation model. Although the structural changes were significant in their effects on the gas industry, they are estimated to have had minor effects on real household income in all Australian regions owing to the small size of the gas industry and household gas consumption at that time, and low importance of gas as an input to other industries. The changes are estimated to have slightly increased income inequality owing to the redistribution of income from labour to other primary factors.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • George Verikios & Xiao-guang Zhang, 2013. "The distributional effects of the Hilmer reforms on the Australian gas industry," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 57(2), pages 159-177, April.
    • Handle: RePEc:bla:ajarec:v:57:y:2013:i:2:p:159-177
    DOI: 10.1111/ajar.2013.57.issue-2
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/10.1111/ajar.2013.57.issue-2
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1111/ajar.2013.57.issue-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. G. A. Meagher & Nisha Agrawal, 1986. "Taxation Reform and Income Distribution in Australia," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 19(3), pages 33-56, September.
    2. DeVuyst, Eric A. & Preckel, Paul V., 1997. "Sensitivity analysis revisited: A quadrature-based approach," Journal of Policy Modeling, Elsevier, vol. 19(2), pages 175-185, April.
    3. George Verikios & Xiao-guang Zhang, 2008. "Distributional Effects of Changes in Australian Infrastructure Industries during the 1990s," Staff Working Papers 0802, Productivity Commission, Government of Australia.
    4. Arntz, Melanie & Boeters, Stefan & Gürtzgen, Nicole & Schubert, Stefanie, 2008. "Analysing welfare reform in a microsimulation-AGE model: The value of disaggregation," Economic Modelling, Elsevier, vol. 25(3), pages 422-439, May.
    5. Naqvi, Farzana & Peter, Matthew W, 1996. "A Multiregional, Multisectoral Model of the Australian Economy with an Illustrative Application," Australian Economic Papers, Wiley Blackwell, vol. 35(66), pages 94-113, June.
    6. Unknown, 1999. "Impact of Competition Policy Reforms on Rural and Regional Australia," Inquiry Reports 31892, Productivity Commission.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Maheshwar Rao & Robert Tanton & Yogi Vidyattama, 2013. "‘A Systems Approach to Analyse the Impacts of Water Policy Reform in the Murray-Darling Basin: a conceptual and an analytical framework’," NATSEM Working Paper Series 13/22, University of Canberra, National Centre for Social and Economic Modelling.
    2. Marc Jim Mariano & George Verikios, 2022. "Understanding the Effects of Coronavirus on Australian Households: A Macro–Micro Analysis," Economic Papers, The Economic Society of Australia, vol. 41(3), pages 215-231, September.
    3. Ayala, Edgardo & Chapa, Joana & García, Lester & Hibert, Abel, 2018. "Welfare effects of the Telecommunication Reform in Mexico," Telecommunications Policy, Elsevier, vol. 42(1), pages 24-36.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. George Verikios & Xiao-guang Zhang, 2010. "Structural Change in the Australian Electricity Industry During the 1990s and the Effect on Household Income Distribution," Centre of Policy Studies/IMPACT Centre Working Papers g-207, Victoria University, Centre of Policy Studies/IMPACT Centre.
    2. Verikios, George & Zhang, Xiao-guang, 2013. "Structural change in the Australian electricity industry during the 1990s and the effect on household income distribution: A macro–micro approach," Economic Modelling, Elsevier, vol. 32(C), pages 564-575.
    3. George Verikios & Xiao-guang Zhang, 2012. "Microeconomic Reform and Income Distribution: The case of Australian Ports and Rail Freight Industries," Centre of Policy Studies/IMPACT Centre Working Papers g-230, Victoria University, Centre of Policy Studies/IMPACT Centre.
    4. Maheshwar Rao & Robert Tanton & Yogi Vidyattama, 2013. "‘A Systems Approach to Analyse the Impacts of Water Policy Reform in the Murray-Darling Basin: a conceptual and an analytical framework’," NATSEM Working Paper Series 13/22, University of Canberra, National Centre for Social and Economic Modelling.
    5. George Verikios & Xiao-guang Zhang, 2016. "Structural change and income distribution: the case of Australian telecommunications," Journal of the Asia Pacific Economy, Taylor & Francis Journals, vol. 21(4), pages 549-570, October.
    6. Verikios, George & Zhang, Xiao-guang, 2015. "Reform of Australian urban transport: A CGE-microsimulation analysis of the effects on income distribution," Economic Modelling, Elsevier, vol. 44(C), pages 7-17.
    7. Giesecke, James A. & Madden, John R., 2013. "Regional Computable General Equilibrium Modeling," Handbook of Computable General Equilibrium Modeling, in: Peter B. Dixon & Dale Jorgenson (ed.), Handbook of Computable General Equilibrium Modeling, edition 1, volume 1, chapter 0, pages 379-475, Elsevier.
    8. E.A. Haddad & J. Bonet & G.J.D. Hewings & F.S. Perobelli, 2009. "Spatial aspects of trade liberalization in Colombia: A general equilibrium approach," Papers in Regional Science, Wiley Blackwell, vol. 88(4), pages 699-732, November.
    9. Lips, Markus & Rieder, Peter, 2002. "Endogenous adjusted Output Quotas - The Abolishment of the Raw Milk Quota in the European Union," Conference papers 330980, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    10. Tetsuji Tanaka & Jin Guo & Naruto Hiyama & Baris Karapinar, 2022. "Optimality Between Time of Estimation and Reliability of Model Results in the Monte Carlo Method: A Case for a CGE Model," Computational Economics, Springer;Society for Computational Economics, vol. 59(1), pages 151-176, January.
    11. Horridge, Mark & Madden, John & Wittwer, Glyn, 2005. "The impact of the 2002-2003 drought on Australia," Journal of Policy Modeling, Elsevier, vol. 27(3), pages 285-308, April.
    12. Lindner, Robert K., 2004. "Privatised provision of essential plant breeding infrastructure," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 48(2), pages 1-21.
    13. Kym Anderson & Ernesto Valenzuela & Lee Ann Jackson, 2008. "Recent and Prospective Adoption of Genetically Modified Cotton: A Global Computable General Equilibrium Analysis of Economic Impacts," Economic Development and Cultural Change, University of Chicago Press, vol. 56(2), pages 265-296, January.
    14. Peter B. Dixon & Maureen T. Rimmer, 2004. "Measuring Contributions To The Australian Economy: The Benefits Of A Fast-Growing Motor Vehicle And Parts Industry," Economic Papers, The Economic Society of Australia, vol. 23(1), pages 73-87, March.
    15. Hertel, Thomas W. & Tyner, Wallace E. & Birur, Dileep K., 2008. "Biofuels for all? Understanding the Global Impacts of Multinational Mandates," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6526, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    16. T. Chatzivasileiadis & F. Estrada & M. W. Hofkes & R. S. J. Tol, 2019. "Systematic Sensitivity Analysis of the Full Economic Impacts of Sea Level Rise," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 1183-1217, March.
    17. Hermeling, Claudia & Löschel, Andreas & Mennel, Tim, 2013. "A new robustness analysis for climate policy evaluations: A CGE application for the EU 2020 targets," Energy Policy, Elsevier, vol. 55(C), pages 27-35.
    18. repec:unu:wpaper:wp2012-60 is not listed on IDEAS
    19. Hertel, Thomas & Hummels, David & Ivanic, Maros & Keeney, Roman, 2007. "How confident can we be of CGE-based assessments of Free Trade Agreements?," Economic Modelling, Elsevier, vol. 24(4), pages 611-635, July.
    20. B. Henderson & A. Golub & D. Pambudi & T. Hertel & C. Godde & M. Herrero & O. Cacho & P. Gerber, 2018. "The power and pain of market-based carbon policies: a global application to greenhouse gases from ruminant livestock production," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 23(3), pages 349-369, March.
    21. Altamirano-Cabrera, J.C. & Bicchetti, D. & Drouet, L. & Thalmann, P. & Vielle, M., 2008. "A global carbon tax to compensate damage and adaptation costs or climate change compensation through a global carbon tax," Conference papers 331782, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.

    More about this item

    JEL classification:

    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • C69 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Other
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:ajarec:v:57:y:2013:i:2:p:159-177. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/aaresea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.