Don't blame Canada's productivity woes on the commodity boom -

Don’t blame Canada’s productivity woes on the commodity boom

An Econowatch special report on productivity (part four)


If you spend any time reading about the Canadian economy, you have inevitably come across the Great Canadian Productivity Puzzle. Canada’s productivity is much lower than that of other countries, and we don’t really know why. Neither do we seem to be able to fix the problem. Policymakers have used every trick in the book to try to boost productivity, but the results have disappointed. Productivity growth matters because it drives up our purchasing power: if it lags, so will our standard of living. And yet—here’s where things get interesting—Canadians are far better off than one would tell looking at our dismal productivity performance over the past 20 years. How did we do it? In this six-part special report, Maclean’s in-house economist Stephen Gordon investigates the mystery. (With a contribution from Econowatch editor Erica Alini.)

Click here to see what’s coming up next and visit past posts.

This chart from the second part of this series is probably the best illustration of the notion that Canada has an inordinately severe productivity problem:

Multifactor productivity (MFP), commonly interpreted as a measure of technical progress, is at the same level in 2011 as it was in 1971 (for an explanation of what MFP is, see part two). But if the numbers in that graph (series v41712881 in Statistics Canada’s Cansim database) are to be taken seriously, we’d be led to the conclusion that Canada’s business sector is using technologies that are about as sophisticated as the ones they were using 40 years ago. I don’t imagine anyone seriously believes this to be the case, so what’s going on with Statistics Canada’s MFP estimates? Answering that question is an ongoing research project, and I’ll get back to it in the next post.

For now, I think this chart suggests that declining MFP estimates don’t invariably lead to economic stagnation:

Both Canada and Australia pulled off the trick of producing significant gains in income even as MFP fell. I don’t think this is a coincidence. The next graph charts MFP growth for the Canadian business sector as a whole and two important sub-components, manufacturing and the mining and oil and gas industry.

Statistics Canada’s estimate for MFP in the mining, oil and gas extraction sector has been on a downward trend for decades. Interpreting MFP as a measure of technical progress would lead to the conclusion that technology used in 1961 was almost three times more advanced than the technology available now—which clearly cannot be.

I can think of at least two explanations why multifactor productivity estimates for the resource-extraction sector might underestimate the actual rate of technical progress:

1) “Low-hanging fruit” bias. In the standard model of multifactor productivity, an industry that displays no technical progress and sees no changes in the amounts of capital and labour would produce a constant level of output. But this is not generally true of resource-extraction industries. There is considerable variation in both the quality of and the ease with which a resource deposit can be extracted, so the most profitable strategy is to start with the high-quality, low-cost plays and, when these are exhausted, move on to deposits that are of lower quality and are more costly (think conventional oil fields vs. the oil sands).

This strategy of picking the “low-hanging fruit” first means that the baseline scenario of fixed technology and constant inputs will not produce a constant level of output. Output will decline as firms are forced to move on to increasingly marginal deposits. Applying the MFP formula to this sector would show negative MFP growth, even though technology hasn’t changed. More generally, the low-hanging fruit bias will produce MFP estimates that systematically understate technical progress in the resource sector.

2) “Time-to-build” bias. In most industries, new investment results in an increase in output right away, as many capital goods can be installed and put to use fairly quickly. But often that’s not the case in the mining, oil and gas extraction sector. It can take several years before, say, a new oil sands installation begins production. This means that for a period of time there will be investment expenditures with no corresponding increase in output. And if output is constant while input quantities are increasing, measured MFP growth will be negative.

Commodity prices have been surging since the 2002, which, in Canada as well as Australia, has resulted in a surge of investment in the resource industry. A shift of productive resources toward a sector where technical progress is consistently underestimated (and I don’t think there’s any question that MFP underestimates technical progress in the mining and oil and gas sector) would result in slower MFP growth rates in the economy as a whole. Higher resource prices aren’t a reprieve from slow productivity growth: They’re a reason why the measure of productivity growth is so slow.

In the next post, I’ll look at some recent research that revisits the question of how we should be interpreting MFP and measuring technical progress.



  • Part four: Don’t blame Canada’s productivity woes on the commodity boom

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Don’t blame Canada’s productivity woes on the commodity boom

    • Fixed now. Thank you for pointing out! -Erica

  1. OK, you’re on the right path, and with answering how to properly measure productivity being an ongoing research project, I’m going to throw out some point/issues to maybe consider.

    1) How does MFP account for capital costs? You highlighted the multi-year lag between when capital costs are incurred, and a large (say oilsands) plant goes onstream. The accounting convention is to amortize costs over the life of the project (say 40 years productive life= 1/40th costs depreciated each year using straight line method.) And do they account for accelerated CCA – typical of oil sands developments? (btw, the treatment of costs – should balance out over time as the capital stock /number of projects increases – but can affect the curves in the early stages).

    2) You have raised this point yourself, elsewhere. What falls under the “manufacturing” catch-all classification? A lot of capital costs associated with oil sands investments are what I would refer to as “fabrication”. Storage tanks, pressure vessels, piping, valves etc. And what you can’t shop assemble into modules, shipped to site, you need to field fabricate often out in the middle of nowhere where costs escalate. Do these show up as “manufacturing” or “mining” in the MFP graph above?

    3)Legacy costs – such as cleaning up tailings ponds etc. and more stringent environmental standards – additional costs perhaps not accounted for yet, but, once incurred, no offsetting increase in existing production.

    • 1) Capital costs are taken into account (sort of) in the calculation of an expected rate of return. Getting good estimates for the rates of return is actually a very big sticking point.

      2) Manufacturing is NAICS code 31-33. Some of the output of the manufacturing sector is indeed purchased as capital equipment for the oil and gas sector.

      3) This is a point that has been raised before. It definitely works as an additional factor that would lead you to underestimate productivity growth, but I don’t know if anyone’s been able to put numbers on it.

      • 1) I presume you are referring to the invest/don’t invest decision by a company (using also forecasts of production rates as well as prices for production streams).

        But does MFP also use this? Perhaps you can direct me to the relevant section. My initial thinking is that StatsCan would just lump all capital costs into the years they are incurred (not expensed).

        • This recent survey is probably as good a place as any to start.

          • Thx. Looks like they made some changes in 2002:

            When Statistics Canada first published MFP estimates, a simple summation of assets was used to measure capital stock, and in turn, capital input, and an aggregation of total hours worked was used to measure labour input. In 2002, the MFP measures were re-engineered. The constant quality index of capital and labour input, as proposed by Jorgenson and Griliches (1967), was introduced. The assets used to estimate capital were expanded to include land and inventories in addition to fixed reproducible assets (machinery and equipment and structures). New estimates of depreciation were introduced, which incorporated the rate of decline in asset prices after purchase; previous estimates had been based on expected lengths of lives and arbitrary assumptions about decay functions. These changes brought the Canadian practice in line with U.S. Bureau of Labor Statistics (BLS) estimates, which, in turn, were based on the work of Hulten and Wykoff (1981).

    • What about the cost of increased safety? I know in shaft sinking (mine shafts), the expectation used to be one death per 1000′ of shaft. Today, the actual number for an entire project must be much lower than one, the expectation is zero.

      A lot of money gets spent on mining projects, sometimes wasted, trying to improve safety. A lot of the innovation we see is aimed at improving safety, not productivity. Is the decreased loss of life and limb properly accounted for in MFP? Is there any measurement of the effectiveness of this spending?

  2. There is no “low hanging fruit bias” in productivity. If it costs more to produce less, productivity decreases, no matter which way you slice it. With oil production, any gains in technical progress are offset by the difficulty in extracting the oil. Surface mining bitumen is less productive than extracting conventional oil. In-situ extraction is less productive than surface mining. So expect further decreases in productivity from the resource sector.

    The real gains to be made in productivity come from value-added goods and services, especially those that are based on information technologies.

    According to the Conference Board of Canada:

    “The debate over [Multi-Factor Productivity] methodology and measurement obscures the fact that no matter what method is used, our productivity growth is still dismal. In fact, a careful reading of the new research indicates that Canada’s productivity performance could actually be worse than thought!

    “Canada’s weak productivity growth has caused us to slip further and further behind the United States and other major industrial economies in terms of real income per capita—something that hits every Canadian in the wallet. The need for concerted action on productivity growth and innovation must remain a national priority if we hope to maintain our high living standards.”

    Conference Board of Canada: Canada’s Productivity Problem Can’t Be Measured Away

    • Do you think that the technology used in the oil and gas sector in 1961 was three times more advanced than the technology available today?

      • I have to admit, I’m a bit confused here. MFP is an economic ratio ie pct GDP cost per capita, rather than pct GDP cost per unit production (barrels in the case of oil), no?

        In other words, if the cost of the inputs goes up faster than the value of the outputs, margins are squeezed, MFP declines. True?

        btw, my read of how depreciation is treated in MFP calculation is that capital investment is added to the asset base and starts depreciating when it goes into production – so no lag effect as per point #2 Time to Build