1. NatStats 2010 Conference Bill Evans Chief Economist September 2010

2. Introduction Data provides a key indicator for economic policy; regulation and financial markets. Consider two examples of how the historical unreliability of data releases can affect policy. Bank regulation policy associated with “excessive credit growth”. Monetary Policy associated with the measurement of the Consumer Price Index.

3. Countercyclical Capital Buffer Basle guidelines for a countercyclical capital buffer. Required “top up” of capital for the banking system will be driven by the deviation from trend ( HP filter) of the credit (broadest measure) to nominal GDP ratio. Banks will only be required to “top up” continuously once the deviation is in the buffer zone. This top up will rely on stable reliable measures of credit and nominal GDP. The significance and volatility of Australia’s statistical discrepancy in measuring GDP adds unwelcome uncertainty to the banks’ capital planning. This study looks at the problems associated with the statistical discrepancy with other issues associated with revisions to GDP and credit aggregates additional challenges.

4. Aust Credit to GDP: deviation from trend

5. Countercyclical capital buffers for Aust

6. Australian GDP: three measures

9. Countercyclical Capital Buffer We estimate that once a banking system finds itself in the buffer zone economic data will have a profound impact on their capital planning. Under the example of 2009 when the growth rates of the various measures of GDP differed by 2 ppts the application of the countercyclical buffer could have varied the amount of extra capital that banks needed to acquire by up to $2.5 billion. Since 2008 this discrepancy could have varied the level of capital required to be held by the banking system by around $4 bn.

10. The Distortions from Measurement Error In 2009 various measures (GDP (E); GDP (I); and GDP (P)) registered growth in the Australian economy at variously 4.1%; 2.6% and 1.4% Which measure should be used for the countercyclical capital buffer measurement. We estimate that a 2 ppt shift in the GDP measure could result in banks having to increase their capital base by a further $2.5 bn. That would have serious implications for equity and capital markets. This does not take into account actual data revisions to GDP and credit aggregates..

11. Statistical discrepancy: mind the gap

12. Monetary Policy and the CPI The inflation report has been the most important driver of monetary policy decisions since the Bank formally adopted an inflation target. The concept “deposit and loan facilities” seeks to measure the cost of retail banking services by measuring the margins; fees and taxes for each financial product offered by deposit taking entities. It is done by sampling various accounts – sample size 7000 individual accounts which contain 3 million transactions annually. Issues such as nonlinearities of fees; waiving of fees; various types of accounts which differ across institutions; substitution between fees and margins; accuracy of account information all make this procedure complex and potentially unstable.

13. Monetary Policy and the CPI As an institution which needs to forecast the components of the CPI we find this component totally impossible to get any lead whatsoever. Not surprisingly we are unaware of any other country which includes this concept in its CPI. Such is the Reserve Bank’s scepticism about the component that the Bank often refers to inflation measures ex deposit and loan facilities. Policy decisions can “turn” on 0.1% of a quarterly CPI. In the lead up to the GFC the RBA always tightened when the core CPI printed 0.8% or more and only tightened on a 0.7% 50% of the time. In the last 3 years deposit and loan facilities contributed at least 0.1 ppt to the CPI on 75% of the reads. The measure is very important for the CPI. Of the 92 items in the CPI this measure with a 4% weighting is exceeded only by house purchase (8%); rents (5.9%); motor vehicles (4.1%)..

14. RBA responds to inflationary pressures forecasts GFC

15. Deposit & loan quarterly change

16. Deposit & loan contribution to headline CPI

17. Deposit & loan cont’n to ann headline CPI

18. Some Conclusions Data measurement can have serious implications for policy ; regulation and financial markets. Revisions; statistical discrepancies; measurement errors; have and will be critical to fine tune. Maintaining “elegant” approaches which cannot be measured in a stable fashion may be counterproductive Using inherently volatile data to dictate regulatory rules seems dangerous Measuring elegant concepts which are inherently random to drive the key policy variable is risky and unhelpful to markets Policy and regulation should rely on stable data series which are not prone to instability and volatility At the very least the “deposit and loans” component of the CPI should be dropped..

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