Statistics matter for carbon pricing and US banks
Dr Guohua Feng says the most challenging aspect of econometrics research is how to truly integrate statistics and economics. Guohua hopes to meet this challenge by using several research grants to investigate the economic impact of environmental regulation on Australia. This could improve efficiencies in affected industries and allow for a smoother transition to a carbon-priced economy.
The Gillard Government’s carbon tax has divided opinion due to its ramifications for industry, consumers and the economy. One question has been whether the government’s fixed-price model is a better option than a market-driven Carbon Pollution Reduction Scheme (CPRS).
In 2010, Guohua won a Dean’s Award for Excellence in Research by an Early Researcher for his work on carbon pricing.
“In my Dean's award application, I proposed to investigate the impacts of carbon pricing on Australian industries. That’s a very big issue in Australia. It’s a hot topic now,” Guohua says.
Guohua also received a grant for an ARC Discovery Project in 2010. He says this will allow him to research the impacts of environmental regulation on productivity growth at the industrial level.
“For the Dean’s award, I worked with a relatively small data set,” Guohua explains. “For the ARC Discovery Project, I significantly extended my research on the impacts of carbon pricing both in terms of theoretical depth and empirical evidence. With generous financial support from the ARC and the faculty, myself and my co-author completed a paper which has been resubmitted on request to a top A* journal in econometrics.”
Guohua was also accepted into the Monash Researcher Accelerator Program in August 2010. This gives him further scope to investigate the effect of environmental regulations on productivity growth.
Guohua says in terms of the breadth and magnitude of economic effects, the carbon price is arguably the most significant policy change in Australia’s history. He says it will be significant for both industry and consumers.
“I think it will have a big impact on resource-intensive industries, such as the mining and agricultural industries. It will also affect consumers because energy prices would rise,” Guohua says. “But if you look at it from a long-term perspective, they (consumers) are probably better off.
“Our standard of living depends ultimately on the international competitiveness of Australian companies. If they fail to keep up with other developed countries in moving to clean technologies, they will lose their competitiveness and may be forced out of the market.”
Guohua is also working on two papers that apply Stochastic Frontier Analysis to the US banking industry. Applying this complex method of economic modelling to such an important question could have a significant influence on the industry.
“The common theme of the papers is to investigate the productivity, technical change and returns to scale of the US banking industry. The paper I’m currently working on is investigating why large banks dominate the US banking industry,” Guohua says.
“In the last 20 years, the total assets of the US banking industry have increasingly concentrated among the largest banks with total assets in excess of $10 billion. The fact that these banks have become so big has raised serious concerns among policy makers and academics, for example the issue of ‘too big to fail’. I’m trying to explain from a productivity and efficiency perspective, using an econometric model I have developed, why this asset concentration has happened.”
Feng, G., Zhang, X., 2012, Productivity and efficiency at large and community banks in the US: A Bayesian true random effects stochastic distance frontier analysis, Journal of Banking and Finance [P], vol 36, issue 7, Elsevier BV, Amsterdam Netherlands, pp. 1883-1895.
Feng, G., Serletis, A., 2010, A primal Divisia technical change index based on the output distance function, Journal of Econometrics [P], vol 159, issue 2, Elsevier BV, North-Holland, Netherlands, pp. 320-330.
Feng, G., Serletis, A., 2010, Efficiency, technical change, and returns to scale in large US banks: Panel data evidence from an output distance function satisfying theoretical regularity, Journal of Banking and Finance [P], vol 34, issue 9, Elsevier BV, North-Holland, Netherlands, pp. 127-138.
Serletis, A., Feng, G., 2010, Semi-nonparametric estimates of currency substitution between the Canadian dollar and the U.S. dollar, Macroeconomic Dynamics [P], vol 14, issue 1, Cambridge University Press, UK, pp. 29-55.
Feng, G., Serletis, A., 2009, Efficiency and productivity of the US banking industry, 1998-2005: Evidence from the Fourier cost function satisfying global regularity conditions, Journal Of Applied Econometrics [P], vol 24, issue 1, John Wiley & Sons Ltd, UK, pp. 105-138.
Feng, G., Serletis, A., 2008, Productivity trends in U.S. manufacturing: Evidence from the NQ and AIM cost functions, Journal of Econometrics [P], vol 142, issue 1, Elsevier BV, North-Holland, Netherlands, pp. 281-311.
Serletis, A., Feng, G., 2006, Productivity trends in the United States, Journal of Economic Studies [P], vol 33, issue 5, Emerald Group Publishing Ltd, UK, pp. 320-335.
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