Shaping the base of a renewable economy

The transition to a post-carbon energy economy will require extraction. As the sun set on the Bernie Sanders campaign, and with it the prominence of the Green New Deal in the contest for the presidency, the Trump administration issued an executive order encouraging private US exploitation of mineral resources in space. Whatever the shape of the coming transition away from fossil fuels, the need to understand the social and distributional costs of a changing energy infrastructure has never been greater. In a new report, I survey the state of mining, near-future ploys for extra-terrestrial extraction, and the persistent externalities of extraction.

Recent years have seen growing attention to the material requirements of information technologies, and especially to the social and environmental harms of sourcing rare earths and cobalt. Researchers highlight, for example, the dependence of electric vehicles and wind power infrastructure on rare earths, or batteries on lithium. But these discussions have tended to omit emphasis on necessity of extraction, relying instead on a more familiar idiom of consumer and corporate responsibility. Both the Trump administration's vision of celestial expansion and some visions of a post-carbon future depend, stated or not, upon a continuing regime of mineral extraction and outsourced harm.

The underlying problems in the US economy

Today’s Bureau of Labor Statistics (BLS) report hardly registers the cataclysm in the US job market. The sharp 0.9 percent uptick in unemployment—itself newsworthy—only grasps the very beginnings of the shutdown of the American economy. Since the BLS surveys were conducted in the week of March 12, 10 million people have filed for jobless benefits. Only when the April numbers are released at the beginning of next month will we begin to get a fuller statistical picture of the magnitude of the Covid-19 crash. Unemployment rates are expected to rise to 20 percent or more. Given the 10-year-long, bull run of the stock market, one might imagine that the US economy was in good shape before that crash began, and that the labor market will therefore bounce back from the novel coronavirus’s punch once the public health crisis ends. However, the opposite is true: the fundamentals of the US economy were already incredibly weak. They have been for some time. After a decade of slow economic expansion, the US labor market was barely beginning to recover from the last crisis in 2008. If the past is any guide to the future, it will likely take even longer to recover from this one. We are only starting to get a sense of the true extent of this disaster from the perspective of American workers.

The shape of the Covid-19 recession

It is hard to see how the United States can avoid a recession. Unemployment insurance claims have already surged, and this week's numbers look to be in the millions. All indications point to one of the fastest plunges of GDP in US history. Facing this, we may want to turn to previous American recessions to think about our immediate future. But the dynamics of this recession will be different in at least one major way from the recessions of recent memory: services. In most recessions, services are basically acyclical—they just don't move up and down with the booms and busts of the economy. The exception here is the Great Depression (see Figure 1 below), but there the decline in investment is much more severe, as is the upward swing in the recovery. Services, it seems, just don't fall that much—even in the Depression.

History, empirics, and industrial policy

Nathan Lane is an economist working on political economy, development, and economic history. Assistant Professor at Monash University, he is the co-founder of sodalabs.io, an interdisciplinary research hub for data-driven work in the social sciences.

Lane's research has focused on comparative development, in particular on state-led development patterns, including work on industrial policy in South Korea, the way historical states shape development and political action, and an indispensable look at the challenges of studying industrial policy and how new empirical strategies can overcome them.

Nathan blogs here, and tweets here. Below, his recommendations for Phenomenal Works.

On the neoclassical and stratification theories of race

Black America has had less wealth, less income, less education, and poorer health than white America for as long as records have been kept. To account for this disparity, economists have advanced three explanations: genetic, cultural, and structural. While the first of these had mostly fallen out of favor among social scientists by the mid-20th century (until a worrying revival in recent decades), the latter two have been adopted by somewhat distinct research communities that frequently collide. According to the cultural theory, racial disparities are the result of social capital deficits. This is the view that has been most widely adopted by the mainstream of the economics profession, and I refer to it as the neoclassical economics of race. By contrast, the structural theory argues that racial disparities in socioeconomic outcomes are created and maintained over time by American institutions, which privilege White Americans at the expense of Black Americans. This view is known as stratification economics, and, as I argue here, it offers a more accurate and empirically sound explanation for racial disparities in America than its counterpart. The neoclassical and stratification approaches disagree over the causes of and remedies for racial disparities in socioeconomic outcomes and differ substantially in their understanding of income, education, wealth, and health.

On growth models, supply chains, and dollar hegemony

Mark Blyth is William R. Rhodes Professor of International Political Economy at Brown University and a Faculty Fellow at Brown’s Watson Institute for International Studies. His research examines how the interests of state level economic actors shape ideological consensus and institutional development at a global scale. His most recent book, Austerity: The History of a Dangerous Idea argues that throughout the 20th century, public spending cuts have been an irrational, ineffective, and inequitable response to debt crises born of a dysfunctional banking system. His 2002 book, Great Transformations, considers the role of economic ideas in paving the way for the embedded liberalism of the 1930s, and its disintegration in the 1970s. His co-authored and edited publications consider how powerful finance sectors shape policymaking, complicate existing narratives on EU economic policies, and ground the study of international political economy in a rigorous macroeconomic framework. Blyth's academic and popular writings are available on his website, and you can follow him here. Below, his selection for Phenomenal Works.

An interview with Kim Phillips-Fein

Kim Phillips-Fein is an associate professor of history at New York University and the author of the books Invisible Hands: the Businessmen’s Crusade Against the New Deal and Fear City: New York’s Fiscal Crisis and the Rise of Austerity Politics, as well as the editor and co-editor of several collections in political economy, business history, and labor history.

In a conjuncture defined by high ideological tension, in which elite consensus and power structures seem increasingly discredited and the scope of political possibility is wider than in recent memory, Phillips-Fein's work is particularly topical. She is an historian of social movements and of ideology—the political action that it both stems from and engenders, and the repercussions of elite politics for the lives of ordinary people. Her two books—which deal, respectively, with New York City's 1970s fiscal crisis and the rise of conservative business movement—also offer cautionary tales about the severe constraints under which political officials operate, and the ease with which powerful reactionary interests organize, relative to the public interest.

Exploring the limits of Expected Utility

I once wrote a post criticizing modern microeconomic models as both overly complex and unrealistic, leading their practitioners into theoretical dead ends without much corresponding increase in explanatory power. I suggested the entire enterprise of Expected Utility (EU) was a dead end based on a mistake and that I’d eventually write about superior ways of modelling individual decision making under uncertainty. It’s been a long time coming, but below I outline why taking time into account leads to better theories of decision making, and why human psychology does a fairly good job of guiding decisions in a dynamic world.

Fair algorithms from the seventeenth century to the present

As national and regional governments form expert commissions to regulate “automated decision-making,” a new corporate-sponsored field of research proposes to formalize the elusive ideal of “fairness” as a mathematical property of algorithms and especially of their outputs. Computer scientists, economists, lawyers, lobbyists, and policy reformers wish to hammer out, in advance or in place of regulation, algorithmic redefinitions of “fairness” and such legal categories as “discrimination,” “disparate impact,” and “equal opportunity.”

But general aspirations to fair algorithms have a long history. In these notes, I recount some past attempts to answer questions of fairness through the use of algorithms. My purpose is not to be exhaustive or completist, but instead to suggest some major transformations in those attempts, pointing along the way to scholarship that has informed my account.

An interview with Lorraine Daston

Lorraine Daston has published widely in the history of science, including on probability and statistics, scientific objectivity and observation, game theory, monsters, and much else. Director at the Max Planck Institute for the History of Science since 1995 (emeritus as of Spring 2019), she is the author and co-author of over a dozen books, each stunning in scope and detail, and each demonstrating of her ability to make the common uncommon—to illuminate what she calls the “history of the self-evident.”

Amidst the ever expanding reach of all varieties of quantification and algorithmic formalization, both the earliest of Daston's works (the 1988 book Classical Probability in the Enlightenment) and her most recent (an ongoing project on the history of rules) perform this task, uncovering the contingencies that swirled around the invention of mathematical probability, and the rise of algorithmic rule-making.

We spoke over the phone to discuss the labor of calculation, the various emergences of formal rationality, and the importance of interdisciplinarity in the social sciences. Our conversation was edited for length and clarity.