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The Australian Competition and Consumer Commission today accepted court enforceable undertakings from BHP Billiton Petroleum (Bass Strait) Pty Ltd (BHP) and Esso Australia Resources Pty Ltd (Esso) to separately market their share of gas produced under the Gippsland Basin Joint Venture (GBJV) from 1 January 2019. The separate marketing of GBJV gas means buyers will have access to competing offers from Esso and BHP in the future.

The ACCC was investigating the joint marketing arrangements between BHP and Esso as it was concerned that the arrangements were likely to have resulted in a substantial lessening of competition in the market for the supply of gas to buyers in the Southern states.

Frontier Economics provided a report to Esso and BHP on the likely effects of the joint marketing arrangement on competition, which was provided to the ACCC to assist in their inquiry.

Frontier Economics regularly advises clients in a range of competition matters.

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Frontier Economics director Jason Hall is presenting today at the Australasian Finance and Banking Conference in Sydney.  Jason will be explaining some recent work estimating the market value of imputation credits, outlined below.

Imputation tax credits are the credit an investor gets with a dividend for corporate tax already paid in Australia. The imputation system has been around for 30 years and there is still no consensus about how much the credits are worth. This is an issue because credits are not separately traded. You either get a credit with a dividend, or you don't, and only Australian resident investors get a cash flow benefit from the credits. For example, they are not useful for U.S. investors.

This creates a problem. As an Australian you get a large cash flow benefit from receiving a credit and if it was only Australians buying Australian-listed shares, you would pay more for a share that gives you a credit than a share which doesn't. But the international investors don't care about the credits. So when you have a market with Australian and international investors, it is an open question about how much higher the share price is if the company pays dividends that are accompanied by a tax credit.

It is considered important amongst regulators and regulated entities because the regulator makes an estimate about the value of the credits. The higher the assumed value of the credits by the regulator, the lower the revenue stream the regulated entity is allowed to earn. So the estimation of this single parameter affects the aggregate revenue stream of regulated entities by hundreds of millions of dollars.

The paper, co-authored by Stephen Gray, allows us to estimate the market value of imputation credits. We developed a novel technique that allows us to jointly estimate the value of cash dividends and credits (recall that it is hard to separately value them because credits are not traded). Our technique involves making an assumption about the distribution of error terms in regression analysis and then generating thousands of simulated samples in order to estimate confidence intervals.

Further, our research method has applications amongst any empirical analysis in which two of the explanatory variables are correlated. For example, suppose you were measuring the relationship between running times, testosterone and gender. There is correlation between testosterone and gender (if you code males = 1 and females = 0 there will be positive correlation between testosterone and gender); or suppose you were measuring the relationship between consumers' willingness to buy a train ticket as a function of (1) income and (2) distance to the CBD - people living close to the CBD have, on average, higher income so there will be negative correlation between income and distance. Our method has applications to those cases.

Click here to access the PowerPoint presentation (17 mins duration) and a transcript. (Please open the audio PowerPoint presentation as a slide show: the audio should automatically play).

The full research paper is available here.

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Econometrics is the application of statistical methods to the study of economic data and problems. In the area of competition and regulation, econometric analysis is often used to provide justification for regulatory proposals and decisions. Yet figures are not infallible and mistakes can happen for a number of reasons. This can have real ramifications for businesses that are being regulated. This new bulletin from Frontier Economics, Quantitative analysis - quality assured? uses recent actual examples to show the importance of using appropriate methods, and why it is critical to carefully review the analysis before drawing conclusions from the modelling results.

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Econometric modelling can go awry

Econometric analysis is often used to provide justification for regulatory proposals and decisions. Yet figures are not infallible and mistakes can happen for a number of reasons. This bulletin uses recent actual examples to show the importance of using appropriate methods, and why it is critical to carefully review the analysis before drawing conclusions from the modelling results.

The importance of being robust

Econometric analysis is a powerful tool. It can be used to test claims and draw conclusions. It can be used to study the growth of economies, underpin conclusions regarding market power in antitrust cases, and provide estimates of the efficient costs of regulated monopolies. But, like most tools, it must be used correctly to avoid inadvertently causing harm.

Just as you would want a qualified medical practitioner performing a routine check-up, econometric analysis should be performed by a knowledgeable practitioner and second opinions may also be valuable. Undertaking quality assurance is important.

Below, we discuss issues that may affect the validity of an econometric analysis, including some examples uncovered by Frontier Economics during recent reviews of work.

Computational errors

The potential for human error means it is possible to make mistakes when typing the commands for the statistical software used in econometric analysis. A missing hyphen led to the destruction of NASA’s Mariner 1 spacecraft; results of econometric analysis can similarly be impacted.

Mistakes like the above examples can be challenging to identify, even with rigorous quality assurance procedures. A culture of transparency can help mitigate risk. If suspicions arise about certain findings, stakeholders should verify the analysis undertaken by examining the code used to perform the analysis. Ultimately, all errors have some ramifications. While some may be purely academic, others may directly impact a business’s bottom line. In regulated industries, erroneous results might make a difference of millions of dollars. A number of regulators in Australia allow for stakeholders to review the code used in the analysis underpinning their findings. This improves accountability, and allows mistakes to be identified and corrected. This in turn improves the quality of decisions made by regulators.

Data Quality/timeliness

Results of econometric analysis are only as reliable as the source data: garbage in, garbage out. The data may not be appropriate for the purpose it is used for, or perhaps there exists a better dataset, one that is likely to provide more reliable information. Stale data may cease to be useful in determining numerical relationships.

This is not to say that imperfect data is uninformative; data sources often fall short of perfection. But it is important to strive to have the most up-to-date and accurate information whenever practicable.

Improper cleaning techniques

Let’s assume the code has been programmed correctly, and the dataset is appropriate for the query at hand. What else is important? In a typical analysis, the data is obtained from a variety of sources. However, the data is often not in an immediately useable format and usually requires “cleaning”. There may be errors that could have a substantial impact on the results if not corrected. Data may have been inputted incorrectly, perhaps missing a digit. Units of measurement may also be inconsistent between observations - petrol prices may be reported in dollars for some observations and cents for others, distance travelled may be reported in kilometres, or thousands of kilometres. Frontier Economics has encountered and corrected for such errors on a number of occasions.

Ensuring that like is compared with like is important. Rigorous cleaning methods will reduce the chance that errors survive the cleaning process. But such mistakes may not be noticed, instead appearing as outliers or influential observations, impacting results.

Statistical misconceptions

Statistics, and by extension econometrics, is often at odds with intuition. People often have cognitive biases which may lead to incorrect conclusions. Patterns may be seen, when in fact there is no pattern. It is for this reason that it is preferable to employ an approach that satisfies statistical rigour—to separate genuine information from ‘noise’.

Careful attention needs to be paid in the prediction methodology to mitigate the impact of any selectivity biases.


Econometric analysis is not a trivial exercise and there are many potential issues that may undermine any conclusions reached. Hence, it is important not to take work performed by others at face value: a surprising finding may be the result of a tiny coding mistake, errors in the data or inappropriate statistical procedures and statistical reasoning. But when done right, econometric analysis can be a very powerful tool for quantifying economic analyses and underpinning economic and regulatory decision-making.

[1]            “(W)e were able to identify the selective exclusion of available data, coding errors and inappropriate methods for weighting summary statistics”, p.261 in Herndon, T., Ash, M., & Pollin, R. (2014). Does high public debt consistently stifle economic growth? A critique of Reinhart and Rogoff. Cambridge Journal of Economics, 38(2), 257-279.

[2]             “Following advice … that they were unable to replicate some of the findings … a review of the computer programs used to produce the table revealed some coding errors”, p.61 in Wilkins, R. (2015). The Household, Income and Labour Dynamics in Australia Survey: Selected Findings from Waves 1 to 12. Melbourne: Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.

[3]             Economics Regulation Authority (2017), Estimating the Utilisation of Franking Credits through the Dividend Drop-Off Method. available at Working Paper - Estimating the Utilisation of Franking Credits.PDF

[4]                 AER, Final Decision Ausnet Services Transmission Determination 2017-2022 - Attachment 3 - Rate of Return, April 2017, p. 403.

[5]                 Stochastic frontier analysis.

[6]                 The specific data requested may not have been recorded for the purposes of regulation in the early years of the sample.

[7]             See Kane and Staiger, The Promise and Pitfalls of Using Imprecise School Accountability Measures, 2002DOWNLOAD FULL PUBLICATION

Infrastructure Australia today released Reforming Urban Water: A national pathway for change outlining advice for governments and regulators around fundamental changes to the governance and regulation of Australia’s urban water markets.

Australia’s urban water sector provides water, wastewater, recycled water and stormwater services to a range of diverse customers across Australia. Each of these services is governed (to some extent) by state and territory based economic, environmental and health regulation, which aim to:

Importantly, these different types of regulation interact when determining the efficient and prudent costs – and ultimately, when determining the prices required to recover the costs of service provision.

However, urban water infrastructure is expensive to build and maintain, and faces a number of challenges over the coming years. In particular, a changing climate and substantial population growth is expected to place significant strain on ageing assets. Reform is required to ensure the sector can continue to provide safe, reliable and affordable services into the future. This will require re-shaping the urban water sector, including the range of institutions, regulatory frameworks and decision-making processes to be more efficient, resilient, transparent and accountable.

Infrastructure Australia engaged Frontier Economics (Asia-Pacific) and Arup to provide advice on the current state of economic, environmental and health regulation in the Australian urban water sector, and the opportunities for regulatory improvement. Our report set out minimum and best practice standards for economic, environmental and health regulation, assessed each Australian jurisdiction against these standards and outlined the pathway for regulatory improvement.

Our analysis and findings informed Infrastructure Australia’s advocacy and reform agenda in the Australian urban water sector and helped identify areas for reform. In particular, highlighting jurisdictions that have advanced with reforming their regulatory structures can help to identify what has worked, barriers to reform and the benefits that these reforms have delivered for operators and customers alike. These lessons can provide vital guidance for states and territories that may be further from best practice in each area of regulation, and establish links across jurisdictional borders to advance important reforms in line with nationally consistent standards.

Frontier Economics regularly advises clients in the water sector, including government, regulators and businesses.

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