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.

Lessons from the 1970s experiments in guaranteed income

One of the questions at the heart of contemporary debates over the merits of UBI is ‘what would it fund?’ In other words, what type of activities would it encourage? There are of course the widely debunked quibbles about guaranteed income encouraging anti-social behaviors, but there’s also a feminist critique of basic income proposals.

The feminist case against a UBI centers around the fear that, in contrast to more robust funding for social programs such as subsidized child care or parental leave, UBI would disproportionately encourage women to leave the labor force to provide care work in the home— reinscribing the gendered division of labor against which women have long struggled. In this view, UBI is undesirable—expected to fund the isolation of women in the domestic sphere, and preventing them from wielding influence over the real machinations of society.

A new working paper models the effects of a basic income in New York City

Skeptics of guaranteed income tend to worry about the policy’s inflationary effects; absent rent regulation, for instance, one might expect housing costs to rise in proportion to the increase in disposable income generated by the policy. A new JFI-supported working paper presents the first attempt to model a UBI’s general equilibrium effects at the city level. In “Universal Basic Income and the City (2019),” Khalil Esmkhani, Jack Favilukis and Stijn Van Nieuwerburgh explore the effects of a guaranteed income policy implemented at the city-level in New York City. They find that, when financed through a progressive income tax, a UBI increases general welfare and, perhaps most surprisingly, does not lead to housing market inflation. Their research sheds new light on the possible inflationary effects of basic income policies. It also suggests that the method used to finance a UBI has significant implications for the policy’s outcomes and characteristics. Though the results are tentative and the authors plan to expand their analysis to examine different scenarios and to perform sensitivity checks, their efforts already represent a major advance in the study cash transfer policy. In what follows, I present an overview of the macroeconomic literature on basic income before turning back to the model, its findings, and the plan for future work.

On incorporating distributional concerns into macroeconomic models

Recent years have seen the revival of academic conversation around rising wealth inequality and its distributional consequences. But while applied, microeconomics-oriented fields like public and labor economics have long engaged with questions around inequality, macroeconomics has historically paid less attention to these questions, particularly as they relate to business cycles. Instead, it has focused more on the relationships between aggregate macroeconomic outcomes—such as unemployment, income, and consumption—and how they fluctuate during booms and recessions. As a result, research on rising income and wealth inequality in the United States tends to overlook the macroeconomic consequences of these developments, as well as the long-term macroeconomic trends which have contributed to their rise.

In order to assess what rising inequality means for our society, and what policies we should enact to mitigate its effects, we must understand its relationship to the economy as a whole. What macroeconomic forces have contributed to rising inequality, and how might elevated levels of inequality be shaping our economy? We need macroeconomic research to fully understand how income and wealth inequality have evolved in the United States. Particularly, we need a range of macroeconomic models, each of which can capture meaningful differences in household income or wealth but emphasizes different, potentially relevant features of the economy.