Fathom Geophysics Newsletter 24

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Industry conditions: Sector rides high

THE Australian mining industry has continued to enjoy a rebound after several years of very trying business conditions, reaching overall activity levels not seen since 2010 and 2011. The broader economy seems to be chugging along nicely too.

Fathom Geophysics' latest analysis of Australian Bureau of Statistics (ABS) data incorporates figures publicly available as at 28 September 2018. The study period we're discussing in this write-up extends from the June 2005 quarter through to the end of the June 2018 quarter.

In 2018 the Australian mining industry's activity was not far off from the levels reached during the heady 2006 peak of the so-called supercycle (see red line in Figure 1).

Since 2010, the mining industry's activity-level path has been an inversion of the stock market quip about how stock prices ride the escalator up but take the elevator down.

The broader Australian economy made a similar journey over that period, but apparently couldn't sustain the burgeoning activity it was showing in late 2016 (see gray line in Figure 1, which represents Australian income from GDP, a proxy we use to judge how the national economy seems to be traveling).

For a recap about the 37 ABS economic series that are factored into our analysis and about how we handle the data, see our first mining-industry conditions write-up, which appeared in Issue 17 of the Fathom Geophysics newsletter.*

If what our data analysis is showing is real and not spurious (always remembering that the endpoints of data series are inherently difficult to analyze), what might have explained last year's softening of the Australian economy? At the time, interviewees quoted in newsmedia stories and authors of consulting company economic reports mentioned factors such as [1] [2] [3] [4]:

  • prevailing inflation figures had been persistently below the target level established by the central bank (in other words, overall, the prices people were willing to pay for their goods and services were generally stable; said in another way, overall, people offering goods and services for sale were unable to make their attempted price increases stick), and so in turn
  • the demand for workers was quite easily met by the supply of workers, which in turn contributed to
  • stagnation in wages growth (despite rosy employment figures), still-sizeable levels of underemployment, and rising household over-indebtedness, which led to
  • dampened consumer spending.

And, as is the situation for other developed nations, consumer spending constitutes a very large part of the Australian economy.

Figure 1Figure 1: Activity level of the Australian minerals exploration and mining industry (red solid line) compared to Australian income from gross domestic product (grey solid line). Data were sourced from the Australian Bureau of Statistics and were the latest available as at 28 September 2018. Results are plotted on a financial quarterly basis (x-axis) and are shown in terms of the number of standard deviations above or below average (y-axis) for the time period analyzed (from the June 2005 quarter up to and including the June 2018 quarter). Dashed lines denote a relatively greater amount of uncertainty, which arises inherently near series end-points upon calculation of 7-term Henderson moving averages. To view a larger version, click on either the image or this text link.

Our analysis of currently available ABS data puts the Australian mining industry's current activity scenario situated in the times-are-in-the-pink upper right-hand quadrant when viewed as a trajectory plot (Figure 2).

It's relatively well-charted waters in that, looking at the whole study period, the industry has quite often operated at such above-average activity levels while the national economy simultaneously experiences similar above-average activity levels (as indicated by the ABS series called Income from GDP). However, judging by past pathways, this part of the trajectory plot tends not to be visited for very long. So the current situation, as it existed during the June 2018 quarter, may not be around for long. The industry's next plotpoints may involve progress into a boiling-over scenario (extreme upper-right postion) before taking a large arc toward the bottom of the plot. Or if there is some significant underlying weakness or unsustainability in current activity levels, the industry may stall out, as has also happened before.

Figure 2Figure 2: Trajectory plot of the Australian minerals exploration and mining industry's activity level (y-axis) relative to Australian income from gross domestic product (x-axis) for the time period analyzed (from the June 2005 quarter up to and including the June 2018 quarter). The scale on both axes are constructed in terms of the number of standard deviations above or below average. Dotted gray squares show the +/-0.5 standard deviation iso-line (inner square) and the +/-1.0 standard deviation iso-line (outer square). Note that a relatively greater amount of uncertainty arises inherently near series end-points upon calculation of 7-term Henderson moving averages. Note also that the trajectory line has been smoothed for ease of viewing. Data were sourced from the Australian Bureau of Statistics and were the latest available as at 28 September 2018. To view a larger version, click on either the image or this text link.

Industry's economic situation seems back to 'normality'

The various ABS economic time series we're including in our analysis have been displaying an average to low degree of collective unusualness in recent quarters (Figure 3). The degree of unusualness has retreated significantly from a significant peak reached in the first and second quarters of 2017, according to our analysis.

The measure of unusualness we use in our analysis is called the Mahalanobis distance.

When the economic data's Mahalanobis distance is large (i.e., has a value that's very much above average on one of our graphs here), it means the situation is about as unusual as (say) having every student in a classroom ace a properly written, properly administered, nationally normed academic test. Equally, large measures of Mahalanobis distance would occur if (say) every student scored zero on one of these tests. Or if every student scored the exact same grade on the test. All these scenarios would be very strange occurrences. If, somehow, for an extended period of time every student were to ace every test, then under such 'new-normal' circumstances you'd get a large Mahalanobis distance if all of a sudden we obtained a nice bell-curve spread of results among students taking their next test. A small Mahalanobis distance (i.e., a value that's very much below average on one of our graphs here) occurs when the statistically-typical scenario is happening.

Figure 3Figure 3: Activity level of the Australian minerals exploration and mining industry (red solid line) compared to the degree of unusualness or turbulence of the industry's situation as defined by the data's Mahalanobis distance (gray dotted line). Data were sourced from the Australian Bureau of Statistics and were the latest available as at 28 September 2018. Results are plotted on a financial quarterly basis (x-axis) and are shown in terms of the number of standard deviations above or below average (y-axis) for the time period analyzed (from the June 2005 quarter up to and including the June 2018 quarter). Dashed lines denote a relatively greater amount of uncertainty, which arises inherently near series end-points upon calculation of 7-term Henderson moving averages. To view a larger version, click on either the image or this text link.

In trajectory view, our current analysis puts us in the upper left-hand quadrant (Figure 4), in which the Australian mining industry's activity level is above average and its situational unusualness is below average. It's a place that hasn't been frequented very often during the time period we're considering.

Still, none of the quadrants in this trajectory figure has a clear monopoly over its plotted points. This suggests that there's little correlation between the Australian mining industry's given activity level and the degree of unusualness displayed by the industry's economic data at that point in time. For instance, a gangbusters level of activity can occur at the same time there's a high, medium, or low degree of unusualness.

Figure 4Figure 4: Trajectory plot of the Australian minerals exploration and mining industry's activity level (y-axis) relative to the unusualness or turbulence of the industry's situation, as defined by the Mahalanobis distance (x-axis) for the time period analyzed (from the June 2005 quarter up to and including the June 2018 quarter). The scale on both axes are constructed in terms of the number of standard deviations above or below average. Dotted gray squares show the +/-0.5 standard deviation iso-line (inner square) and the +/-1.0 standard deviation iso-line (outer square). Note that a relatively greater amount of uncertainty arises inherently near series end-points upon calculation of 7-term Henderson moving averages. Note also that the trajectory line has been smoothed for ease of viewing. Data were sourced from the Australian Bureau of Statistics and were the latest available as at 28 September 2018. To view a larger version, click on either the image or this text link.

Industry is spending again, and inventories cupboard looks about average

The sales subindex for the Australian mining industry (see salmon line in Figure 5) has reached substantial levels. According to our analysis, the last time sales were in this region was in the post-Great Financial Crisis rebound took hold. It could be that producers have been booking in as much in sales as they can in anticipation (according to some news stories) of a possible softening in received prices ahead. [5] Alternatively, next quarter's full set of data from the ABS may see this subindex revised to lower levels.**

The production and income subindex is also right up there currently (see gold line in Figure 5) and has been going through contortions since the end of 2016.

The exports subindex has maintained consistently 'not bad' levels since the September 2016 quarter (see purple line in Figure 5).

At the same time, the industry's expenditure subindex has reverted to around the study-period average (see blue line in Figure 5). Expenditure was supressed for so long that it's now rebounding noticeably. Work on many long-delayed infrastructure-upkeep and wasting-asset-replacement projects may be responsible in part for this. [6] In addition, the industry has been showing indications, mentioned in a rash of recent newsmedia stories, that it's interested in hiring on staff and contractors again after several years of maintaining only skeleton crews. [7] [8] [9] [10] One recent opinion piece asserted that any mining industry cry of 'skills shortage' was an overblown fiction spread by the industry itself ahead of its plans to seek approvals to hire overseas workers, a form of wage-dampening labor arbitrage. [11]

The inventories subindex (see green line in Figure 5) seems to be hovering around the study period's average, which seems fairly favorable for supporting commodity export prices for the time being — assuming the inventories trend we're seeing is real and not an artifact of our data analysis moving-average calculations, and assuming the trend is occurring in the rest of the global commodities market. It also assumes that producers will collectively refrain from bringing subeconomic projects online again.

Figure 5Figure 5: Mineral commodity demand-side and supply-side subindices: Production and Income, Expenditure, Exports, Sales, Inventories. Also shown is the unusualness or turbulence of the industry's situation, as defined by the Mahalanobis distance. Data were sourced from the Australian Bureau of Statistics and were the latest available as at 28 September 2018. Results are plotted on a financial quarterly basis (x-axis) and are shown in terms of the number of standard deviations above or below average (y-axis) for the time period analyzed (from the June 2005 quarter up to and including the June 2018 quarter). Dashed lines denote a relatively greater amount of uncertainty, which arises inherently near series end-points upon calculation of 7-term Henderson moving averages. To view a larger version, click on either the image or this text link.

Profits return to earth as prices retreat to nearer study-period average

Measures of the Australian mining industry's profitability have backed off since their extreme export-price-supported peak of late 2016 (see red lines in Figure 6). The measures we follow are the ABS time series data for mining's corporate profits before income tax (labeled CPBIT-M on graphs), mining's company gross operating profits (labeled CGOP-M), and mining's ratio of business gross operating profits to sales (labeled RAT-BGOP/S-M).

The cancellation or delay of carrying out development projects and the jettisoning of non-core and subeconomic projects, royalties, and subsidiaries from balance sheets were ways that many mining industry entities improved flagging bottom lines during the latter stages of the recent prolonged industry downturn. [12] Another mechanism that miners and explorers resorted to was the use of explicit, contractualized policies of making exceedingly slow payments to suppliers. [13] [14] The institutionalized practice of paying suppliers months after the submission of an invoice (which may occur after a months-long stint of work) is still being practiced and if not abandoned soon may ultimately injure the industry's ability to quickly make large volumes of hay while the sun is shining. Suppliers are typically heavily cashflow-dependent and generally don't have deep enough pockets to advance the funds necessary to cover the inevitable fortnightly and monthly bills for wages, utilities, and plant and equipment that they cannot legally delay paying. If the mining industry squeezes too many of its suppliers into extinction, there'll be few left with any know-how during the current industry recovery. The first mining companies to break ranks and start paying suppliers in a reasonable timeframe will benefit from boosted supplier loyalty and the corollary of that: exemplary, timely work execution. Suppliers will give those companies' payment-laggard competitors less attention, raise prices for them due to the time value of money, and wherever possible will move their projects to the back of the work queue.

Like the selling of a farm, the trimming of an unruly asset collection and the temporary cash-hoarding associated with the instalment of a super-slow accounts payable system are stop-gap profit-boosting measures that pay dividends essentially just once during any given business cycle. In line with this (and with reduced export prices), profitability has been dropping lately, at the same time that the expenditure subindex has been climbing (see blue line in Figure 6).

Mining's wages and salaries (see black line in Figure 6), a variable that's incorporated into our expenditure subindex, rose back to the period's average faster than the broader subindex. However, wages and salaries don't seem to have been fueling expenditure increases lately, given that since the end of 2017 wages and salaries seem to have been trending counter to the expenditure subindex. (It's worth re-stating here that the most recent ABS data is subject to greater uncertainty and revision. So the apparent trends seen here now may or may not persist within future ABS data releases.)

Figure 6Figure 6: Profitability measures for the mining industry (red lines), namely corporate profits before income tax (solid red line labeled CPBIT-M), company gross operating profits (dashed red line labeled CGOP-M), and the ratio of business gross operating profits to sales (dotted red line labeled RAT-BGOP/S-M). Also shown for comparison purposes are the expenditure subindex (blue line), the inventories subindex (green line), and wages and salaries for mining (black line). Data were sourced from the Australian Bureau of Statistics and were the latest available as at 28 September 2018. Results are plotted on a financial quarterly basis (x-axis) and are shown in terms of the number of standard deviations above or below average (y-axis) for the time period analyzed (from the June 2005 quarter up to and including the June 2018 quarter). Note that a relatively greater amount of uncertainty arises inherently near series end-points upon calculation of 7-term Henderson moving averages. To view a larger version, click on either the image or this text link.

As we mentioned, the industry's 2016 profitability peak coincided with a peak in the average export price (see dotted green line in Figure 7). Prices then retreated back to around the study period's average, before returning to a more subdued high.

Interestingly, the downward export price signal received by the Australian industry in 2017 appeared to exert little influence on its appetite for mineral exploration activity in terms of exploration meters drilled (see dashed brown line in Figure 7) and exploration expenditures (see solid brown line in Figure 7). The last time exploration activity was this high was back in mid-2011.

Figure 7Figure 7: Average export price (green dotted line), which is the average of (1) the export price index by balance of payments classification of exports for metal ores and minerals, and (2) the export price index by balance of payments classification of exports for metals excluding non-monetary gold. Also shown is non-petroleum mineral exploration activity in terms of exploration meters drilled (dashed brown line, obtained by averaging the meters drilled at new deposits and the meters drilled at existing deposits), and exploration expenditures (solid brown line, obtained by averaging expenditures at new deposits and expenditures at existing deposits). The activity level of the Australian minerals exploration and mining industry (gray solid line) is included for comparison purposes. Data were sourced from the Australian Bureau of Statistics and were the latest available as at 28 September 2018. Results are plotted on a financial quarterly basis (x-axis) and are shown in terms of the number of standard deviations above or below average (y-axis) for the time period analyzed (from the June 2005 quarter up to and including the June 2018 quarter). Note that a relatively greater amount of uncertainty arises inherently near series end-points upon calculation of 7-term Henderson moving averages. To view a larger version, click on either the image or this text link.

* We came up with our data analysis because we wanted a formalized, agnostic and at least semi-realistic snapshot of the state of the industry, instead of relying on statistics like Diggers and Dealers attendance figures, idle drill-rig counts, Gina Rinehart's current net worth, or the price of coffee in Perth, Australia. It's our hope that our industry activity index, our industry turbulence index, and our group of demand-side and supply-side subindices spark useful debate and discussion. Please note that the results of our analysis and our discussion of them should not be regarded in any way as advice (e.g., investment advice, financial planning advice, career advice, and so on). If you choose to act upon the information contained in the above material, then be it upon your own head.

** Keep in mind that the various ABS time series we rely on are subject to upward or downward revisions with each new data release (which is inherent in doing economic surveys). Revisions tend to be only quite minor, and tend to affect only the most recent quarters. But if enough small revisions occur, and if they tend to occur together in one direction (e.g., mostly upward, or mostly downward), then that can significantly reset industry trends seen in the final analysis. It means, for instance, that once all of the next quarter's datasets are made completely available, we may end up seeing a re-jigging of the trends we're currently examining and pondering about in this write-up.

References

[1] See, for example: M. Janda (as updated 5 December 2017) "GDP: Australia's economic growth improves but weak consumers disappoint the optimists", ABC News.

[2] See, for example: I. Verrender (as updated 20 November 2017) "You won't see a bump in your pay packet any time soon", ABC News.

[3] See, for example: KPMG Economics (December 2017) "Quarterly economic outlook: Global and Australian forecasts", 24 pages.

[4] See, for example: P. Ryan (as updated 9 November 2017) "RBA edges down growth outlook, sees gradual inflation rise", ABC News.

[5] See, for example: S. Chalmers (8 Jan 2018) "Commodity boom forecast to peak then plateau as prices slide", ABC News.

[6] See, for example: J. Carmody (15 June 2018) "BHP approves $4.7b South Flank project in WA to replace Yandi mine", ABC News.

[7] K. Diss (11 July 2018) "Bidding war begins as WA once again searches for workers to fuel a mining boom", ABC News.

[8] E. Kennedy (8 July 2018) "A new skills shortage looms in Western Australia as fears of automation turns workers away", ABC News.

[9] S. Mangan (13 June 2018) "Mining industry and infrastructure projects in 'war for talent', report finds", ABC News.

[10] J. Lucas (9 June 2018) "Skills shortage: Australia facing critical decline of new mining engineers", ABC News.

[11] S. Smith (31 August 2018) "Mining skills shortage is a fiction the industry must address", The West Australian, Opinion.

[12] See for example: The Economist (18 February 2016) "Core ores".

[13] T. de Landgrafft (7 February 2017) "Payment terms crippling mining and associated small and medium enterprises in Australia according to latest survey", ABC News.

[14] S. Masige (2 May 2016) "Tackling longer payment terms", Australian Mining.

About Fathom Geophysics

In early 2008, Amanda Buckingham and Daniel Core teamed up to start Fathom Geophysics. With their complementary skills and experience, Buckingham and Core bring with them fresh ideas, a solid background in geophysics theory and programming, and a thorough understanding of the limitations of data and the practicalities of mineral exploration.

Fathom Geophysics provides geophysical and geoscience data processing and targeting services to the minerals and petroleum exploration industries, from the regional scale through to the near-mine deposit scale. Among the data types we work on are: potential field data (gravity and magnetics), electrical data (induced polarization and electromagnetics), topographic data, seismic data, geochemical data, precipitation and lake-level time-lapse environmental data, and remotely-sensed (satellite) data such as Landsat and ASTER.

We offer automated data processing, automated exploration targeting, and the ability to tailor-make data processing applications. Our automated processing is augmented by expert geoscience knowledge drawn from in-house staff and from details relayed to us by the project client. We also offer standard geophysical data filtering, manual geological interpretations, and a range of other exploration campaign-related services, such as arranging surveys and looking after survey-data quality control.