A new book by James Crotty reexamines the career of John Maynard Keynes

What drives economic growth and stagnation? What types of methodologies and tools do we need to accurately explain economic epochs in the past and present? What models and policy approaches can lead to prosperity for all? These questions occupied the mind of John Maynard Keynes from World War One until his death in 1946. Keynes, one of the most influential economists of all time, is often claimed to have “saved capitalism.” His legacy, as understood by most of the economics profession, was to cure laissez-faire capitalism with countercyclical fiscal policy—using expansionary government spending during recessions to increase output and employment.

In his new book, Keynes Against Capitalism, economist James Crotty argues that this interpretation of Keynes is profoundly mistaken. Keynes, Crotty argues, wanted to replace capitalism with his own program of “liberal socialism.” Through the book, he demonstrates that 1) Keynes fundamentally rejected the theoretical model that undergirds laissez-faire capitalism; and 2) the cornerstone of Keynes’ liberal socialism program was permanent, large-scale public and semi-public investment guided by the state, accompanied by low interest rates and capital controls.

The uses of algorithms discussed in the first part of this article vary widely: from hiring decisions to bail assignment, to political campaigns and military intelligence.

Across all these applications of machine learning methods, there is a common thread: Data on individuals is used to treat different individuals differently. In the past, broadly speaking, such commercial and government activities used to target everyone in a given population more or less similarly—the same advertisements, the same prices, the same political slogans. More and more now, everyone gets personalized advertisements, personalized prices, and personalized political messages. New inequalities are created and new fragmentations of discourse are introduced.

Is that a problem? Well, it depends. I will discuss two types of concerns. The first type, relevant in particular to news and political messaging, is that the differentiation of messages is by itself a source of problems.

Terminology like "machine learning," "artificial intelligence," "deep learning," and "neural nets" is pervasive: business, universities, intelligence agencies, and political parties are all anxious to maintain an edge over the use of these technologies. Statisticians might be forgiven for thinking that this hype simply reflects the success of the marketing speak of Silicon Valley entrepreneurs vying for venture capital. All these fancy new terms are just describing something statisticians have been doing for at least two centuries.

But recent years have indeed seen impressive new achievements for various prediction problems, which are finding applications in ever more consequential aspects of society: advertising, incarceration, insurance, and war are all increasingly defined by the capacity for statistical prediction. And there is crucial a thread that ties these widely disparate applications of machine learning together: the use of data on individuals to treat different individuals differently. In this two part post, Max Kasy surveys the politics of the machine learning landscape.

An interview with Adam Przeworski

Throughout the 20th century, radical social movements were plagued by their relationship to existing state institutions. Across Western Europe, labor movements found political expression in parties like the Swedish Social Democrats, the German SPD, and the French Socialist Party. In their pursuit of the democratization of wealth and political power, these organizations were criticized for moderating popular demands in favor of cross-party compromise. And while social democratic governments did make significant gains in the postwar period, today's landscape seems to testify against the durability of their reforms.

I met with Adam Przeworski—Professor of Politics at NYU, former member of the September Group of analytical Marxists, and a leading theorist of political economy—to discuss the role of elections in effecting social change, and the political transformations underway today. Over the course of a career spanning thirteen books and over 150 published articles, Przeworski's foremost contributions have been in the study of democratic transitions, distributional politics, and the determinants of economic growth.

It's by now common wisdom that American copyright law is burdensome, excessive, and failing to promote the ideals that protection ought to. Too many things, critics argue, are subject to copyright protections, and the result is an inefficient legal morass that serves few benefits to society and has failed to keep up with the radical transformations in technology and culture of the last several decades. To reform and streamline our copyright system, the thinking goes, we need to get rid of our free-for-all regime of copyrightability and institute reasonable barriers to protection.

But what if these commentators are missing the forest for the trees, and America's frequently derided copyright regime is actually particularly well-suited to the digital age? Could copyright protections—applied universally at the moment of authorship—provide a level of autonomy that matches the democratization of authorship augured by the digital age?

An interview with Almaz Zelleke

Feminist and women's movements in the mid-20th century developed demands for an unconditional basic income that emerged out of concrete experiences with the welfare state. What can the current discussion around UBI learn from examining this largely sidelined history?

In this conversation with basic income scholar Almaz Zelleke, we look at this history—and examine the reasons for its absence from the dominant intellectual histories of unconditional cash transfers. More broadly, our conversation explores political change and the processes that lead to policy creation. It touches on the movements that have brought basic income into the 2020 election cycle, considers how to focus political will surrounding basic income, and concludes with policy recommendations that will move America incrementally towards an unconditional UBI.

An interview with Rosella Cappella Zielinski

Academic study of war in the social sciences is as old as historiography itself, and political economists have considered the economic logic of war and peace for centuries. Yet social scientists have left several questions on the financing of conflict unaddressed. In her 2017 book How States Pay for Wars, Professor Rosella Cappella Zielinski maps out a theory of war finance.

As a sub-discipline, war finance has long existed on the periphery of academic debates in International Relations. Cappella Zielinski’s book is a novel contribution to a growing field, providing the first systematic review and analysis of how states are able to float the cost war. Her overarching theory of war finance is expansive, flexible, and useful for understanding the far-reaching implications of wars past and present. Cappella Zielinski’s research sheds light on the “tools of the trade” for raising money, the balancing act between domestic political concerns and politicians’ war finance decisions, and the unexpected consequences war finance has on income inequality.

Below we discuss what first sparked her interest in war finance, the history of the sub-discipline, and the puzzles that remain to be solved.

Randomized experiments have become part of the standard toolkit for policy evaluation, and are usually designed to give precise estimates of causal effects. But, in practice, their actual goal is to pick good policies. These two goals are not the same.

Is this the best way to go about things? Can we maybe make better policy choices, with smaller experimental budgets, by doing things a little differently? This is the question that Anja Sautmann and I address in our new work on “Adaptive experiments for policy choice.” If we wish to pick good policies, we should run experiments adaptively, shifting toward better policies over time. This gives us the highest chance to pick the best policy after the experiment has concluded.

Early on in The Wealth of Nations, Adam Smith asked who had the edge in negotiations between bosses and wage laborers. His answer: the bosses. In the case of a stalemate, landlords and manufacturers “could generally live a year or two” on their accumulated wealth, while among workers, “few could subsist a month, and scarce any a year, without employment.” Thus, concluded Smith in 1776, “masters must generally have the advantage.”

As economic thought progressed over subsequent centuries, however, Smith’s view of labor markets gave way to the reassuring image of perfect competition. In recent years, a model more in line with Smith’s intuitions has grown to challenge the neoclassical ideal. Under the banner of monopsony, economists have built up an impressive catalog of empirical work that offers a more plausible baseline model for labor markets.

When the media talks about ideological indoctrination in education, it is usually assumed to refer to liberal arts professors pushing their liberal agenda. Less discussed is the very different strain of ideology found in economics. The normative import is harder to spot here, as economics presents itself as a science: it provides an empirical study of the economy, just as mechanical engineering provides an empirical study of certain physical structures. When economists offer advice on matters of policy, it’s taken to be normatively neutral expert testimony, on a par with the advice of engineers on bridge construction. However, tools from the philosophy of explanation, in particular the work of Alan Garfinkel, show how explanations that appear purely empirical can in fact carry significant normative assumptions.1 With this, we will uncover the ideology embedded in economics.

More specifically, we’ll look at the ideology embedded in the foundations of traditional economics—as found in a typical introductory micro-economics class. Economics as a whole is diverse and sprawling, such that no single ideology could possibly be attributed to the entire discipline, and many specialized fields avoid many of the criticisms I make here. Despite this, if there are ideological assumptions in standard introductory course, this is of great significance.