Reexamining the Material Footprint of Nations

The material footprint of nations

Authors:

Wiedmann et al

Abstract:

Metrics on resource productivity currently used by governments suggest that some developed countries have increased the use of natural resources at a slower rate than economic growth (relative decoupling) or have even managed to use fewer resources over time (absolute decoupling). Using the material footprint (MF), a consumption-based indicator of resource use, we find the contrary: Achievements in decoupling in advanced economies are smaller than reported or even nonexistent. We present a time series analysis of the MF of 186 countries and identify material flows associated with global production and consumption networks in unprecedented specificity. By calculating raw material equivalents of international trade, we demonstrate that countries’ use of nondomestic resources is, on average, about threefold larger than the physical quantity of traded goods. As wealth grows, countries tend to reduce their domestic portion of materials extraction through international trade, whereas the overall mass of material consumption generally increases. With every 10% increase in gross domestic product, the average national MF increases by 6%. Our findings call into question the sole use of current resource productivity indicators in policy making and suggest the necessity of an additional focus on consumption-based accounting for natural resource use.

China's Productivity is Slowing Down

THE growth of China’s economy is staggering: it produced $9.5 trillion-worth of goods and services in 2013, nearly three times more than in 2007. But has that growth come simply from deploying more labour and capital? Or did total factor productivity (TFP)—the efficiency with which those two inputs are used—also increase? China’s future growth hinges on the answer.

A period of high growth does not necessarily involve a rise in productivity. The more people there are in employment, and the more factories and roads there are for them to use, the bigger an economy will be. But those workers and roads may not be put to good use. As long as the amount by which labour and capital grow outpaces any fall in productivity, GDP will still increase.

Growth of this sort, however, can last only so long. Neither labour nor capital are infinite. In the long run, improving the productivity with which they are used is the magic ingredient for any economy, the only path to sustainable growth. Hence the concerns about China. A series of estimates published this year have all suggested that productivity is flagging.

At the pessimistic end of the range is Harry Wu, an economist who has devoted much research to the shortcomings of China’s official economic data. He finds that since 2007 TFP has actually been a drag on the economy, denting growth by about 0.9 percentage points a year. At the more optimistic end, researchers at the World Bank think TFP added nearly three percentage points a year to growth from 2000 to 2010—but even they reckon that is 40% lower than in the 1990s. In between these two estimates are Jianhua Zhang, Chunxia Jiang and Peng Wang, two of whom are with the People’s Bank of China. They conclude that productivity increased just 1.5% a year between 1997 and 2012.

As these diverging estimates suggest, overall productivity growth, despite being central to economics, is frustratingly difficult to pin down. It cannot, after all, be seen. When comparing two workers with the same job in the same company, it is easy to determine which one produces more. For economies, such apple-to-apple comparisons are not possible. Instead, economists get at TFP by subtracting the change in capital and labour deployed from the change in overall output. The difference (known as the Solow residual, after Robert Solow, the economist who pioneered this method) reflects the contribution of productivity to growth. In this way, the unseen becomes visible.

But the process requires several accounting somersaults. Assumptions are needed about, among other things, the size of the capital stock, the rate of capital depreciation and the level of workers’ education. Mr Wu does not trust official GDP figures and so constructs his own. Because his estimate of average annual growth for 2008-12 (6.5%) is dramatically lower than the official figure (9.3%), his calculations yield a negative Solow residual. Productivity, in other words, appears to have gone into reverse.

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A Contrarian Reviews Race Against the Machine, Says Don't Blame the Bots

The “robots are coming” narrative dominating discussions of the economy was popularized by Erik Brynjolfsson and Andrew McAfee in their 2011 book, Race Against the Machine. They have built on that theme in the richer, deeper The Second Machine Age (W.W. Norton, 2014). The first half of the book provides a valuable window, at least for a non-technologist like me, into past developments and the future trajectory of digitization. Their claim is that digitization will do for mental power what the steam engine did for muscle power—that is, quite a bit, transforming our lives at work and play.

The remainder of the book dwells on the role of digitization in generating both bounty (more consumer choice and greater output, wealth, and income) and spread (greater inequalities of wages, income, and wealth). In treating these topics, they heavily rely on the work of others. As in their last book, they do not provide much direct evidence of the connection between technological change and wage inequality. I study these issues and believe they are wrong to tightly link digitization and robots to wage inequality and the slow job growth of the 2000s. Although the authors claim “technology is certainly not the only force causing this rise in spreads, but it is one of the main ones” my fear is that this book, like their last one, will fuel the mistaken narrative that technology is responsible for our job and wage problems and that we are powerless to obtain more equitable growth.

Let me start where we agree and where I very much appreciate their argumentation. Brynjolfsson and McAfee are very clear that we are experiencing a dramatic growth in wage, income, and wealth inequality; that living standards have faltered for a significant share of the population; and that these are challenges that must be addressed. They rightly fear that current inequities will generate greater future inequity: They argue that current wealth solidifies and expands inequality through the political process and worry that inequality impedes social mobility—the degree to which a child’s chances are linked to his or her parents’ current station. Inequality begets greater inequality. I appreciate their refutation of denialism and ‘so whatism’.

Their weakest case is that digitization is associated with the slow job growth of the last 15 years. The authors review all the reasons why economists find such a claim untrue, including 200 years of history disproving a link between technology and slow job growth. They propose a few reasons why things may be different now. However, their only evidence is that employment and productivity grew in tandem for many decades but became decoupled in the late 1990s and offer their “reading of technology” as an explanation. In fact, there’s a simple answer to the riddle of slow job growth: slow economic growth resulting from the collapse of two asset bubbles and inadequate policy responses. Job growth occurs when economic growth exceeds productivity. Simply put, if workers can produce 2 percent more this year than last year, the economy can grow 2 percent without adding any employment. Thus, the economy must grow faster than productivity to create jobs, something that has not happened in the unique circumstances of the 2000s.

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