Brad DeLong: Worthy reads on equitable growth, January 25-31, 2020

Worthy reads from Equitable Growth:

1. Two more weeks to submit letters of inquiry! Equitable Growth’s “2020 Request for Proposals are due by Wednesday, February 12.
2. This is truly great from Equitable Growth new hire Claudia Sahm: “Why Americans need to know more about the Federal Reserve.”
3. Equitable Growth’s Heather Boushey at the Aspen Institute. Very much worth watching her “Measure What Matters: Realigning Measures of Economic Success with Societal Well-Being.”
4. Very smart from Jason Furman, “Data and Privacy in Online Platforms’ Market Power,” in which he writes: “The major digital platforms are highly concentrated and, absent policy changes, this concentration will likely persist with detrimental consequences for consumers. More robust competition policy can benefit consumers by helping to lower prices, improve quality, expand choices, and accelerate innovation. These improvements would likely include greater privacy protections given that these are valued by consumers. However, it is not clear that competition will be sufficient to adequately address privacy and several other digital issues. More robust merger enforcement should be part of the solution to expanding competition, including better technical capacity on the part of regulators, more forward-looking merger enforcement that is focused on potential competition and innovation, and legal changes to clarify these processes for the courts. A regulatory approach that is oriented toward increasing competition by establishing and enforcing a code of conduct, promoting systems with open standards and data mobility, and supporting data openness is essential. This is because more robust merger enforcement is too late to prevent the harms from previous mergers, and antitrust enforcement can take too long in a fast-moving market.”

Worthy reads not from Equitable Growth:

1. At a deep level, the argument over technology, employment, the workforce, and robots requires that we understand how our tools for thought—for augmenting human intellect—have worked, do work, and will work. And this requires that we have good answers to questions such as the ones asked by Michael Nielsen in his slide show “Engelbart: Augmenting Human Intellect,” in which he asks: “Augmenting intellect with paper and pencil: What is 427 x 784? Hard for an unaided human. Even harder: what is 721,269,127 x 422,599,421? Both problems become easy with paper and pencil. This is strange, a priori: wood pulp + wood + graphite = more intellectual capability! We’re used to this, but that doesn’t mean we understand it. What’s actually going on? For what class of problems does paper and pencil help? For what class of problems does it not help (or hinder)? How much can it help?”
2. Back from nine years ago now—how technology cannot be the successful key to development because it is a force multiplier for both honesty and dishonesty, both fair-dealing and corruption, for competence and incompetence. And the problems of economic development have always been primarily problems of corruption, dishonesty, and incompetence. Read Kentaro Toyama, “Technology Is Not the Answer,” in which he writes: “Information technology amplified the intent and capacity of human and institutional stakeholders, but it didn’t substitute for their deficiencies. If we collaborated with a self-confident community or a competent non-profit, things went well. But, if we worked with a corrupt organization or an indifferent group, no amount of well-designed technology was helpful … We also expect too much from other technologies, institutions, policies and systems.”
3. If you believe that the proper purpose of markets is to be effective societal decision-making mechanisms for choosing the path to equitable growth, then financial markets raise to special concerns. As John Maynard Keynes put it, the special object of financial markets is then “to defeat the dark forces of time and ignorance which envelop our future.” But here there are two problems: First, people have a very limited ability to form reasonable expectations and make correct judgments, and so the building blocks of which financial markets are constructed are far from adequate. Second, the bandwidth of the signals that are financial market prices is not wide enough to allow for the coordination of expectations and beliefs——even when supply balances demand in financial markets, many people’s expectations will be brutally disappointed even if there are no surprise events in the outside world, and that disappointment of expectations is a cause of major trouble. The Clower-Leijonhufvud UCLA macro school of the 1960s worried intensively about these issues. It was ignored. Now it has only one remaining eloquent standardbearer. Read David Glasner, “My Paper “Hayek, Hicks, Radner and Four Equilibrium Concepts” Is Now Available Online.”
4. And another very worthwhile piece from the very sharp David Glasner: one that I had missed. Read his “What’s Wrong with DSGE Models Is Not Representative Agency,” in which he writes: “The basic story always treats the whole economy as if it were like a person, trying consciously and rationally to do the best it can on behalf of the representative agent, given its circumstances. This cannot be an adequate description of a national economy, which is pretty conspicuously not pursuing a consistent goal. A thoughtful person, faced with the thought that economic policy was being pursued on this basis, might reasonably wonder what planet he or she is on. An obvious example is that the DSGE story has no real room for unemployment of the kind we see most of the time, and especially now: unemployment that is pure waste … While Solow’s criticism of the representative agent was correct, he left himself open to an effective rejoinder by defenders of DSGE models who could point out that the representative agent was adopted by DSGE modelers not because it was an essential feature of the DSGE model but because it enabled DSGE modelers to simplify the task of analytically solving for an equilibrium solution. With enough time and computing power, however, DSGE modelers were able to write down models with a few heterogeneous agents (themselves representative of particular kinds of agents in the model) and then crank out an equilibrium solution for those models … Chari also testified at the same hearing, and he responded directly to Solow, denying that DSGE models necessarily entail the assumption of a representative agent and identifying numerous examples even in 2010 of DSGE models with heterogeneous agents … But debunking the claim that DSGE models must be representative-agent models doesn’t mean that DSGE models have the basic property that some of us at least seek in a macro-model: the capacity to explain how and why an economy may deviate from a potential full-employment time path … The basic approach of DSGE is to treat the solution of the model as an optimal solution of a problem … The policy message … is that unemployment is attributable to frictions and other distortions that don’t permit a first-best optimum that would be achieved automatically in their absence from being reached. The possibility that the optimal plans of individuals might be incompatible resulting in a systemic breakdown—that there could be a failure to coordinate—does not even come up for discussion. One needn’t accept Keynes’s own theoretical explanation of unemployment to find the attribution of cyclical unemployment to frictions deeply problematic … A modeling approach … attributing … all cyclical unemployment to frictions or inefficient constraints on market pricing, cannot be regarded as anything but an exercise in question begging.”