July 28th, 2018



On the history of economists in central banks 

A recent paper by FRANÇOIS CLAVEAU and JÉRÉMIE DION applies quantitative methods to the historical study of central banks, demonstrating the transition of central banking from an "esoteric art" to a science, the growth of economics research within central banking institutions, and the corresponding rise in the dominance of central banks in the field of monetary economics. From the paper: 

"We study one type of organization, central banks, and its changing relationship with economic science. Our results point unambiguously toward a growing dominance of central banks in the specialized field of monetary economics. Central banks have swelling research armies, they publish a growing share of the articles in specialized scholarly journals, and these articles tend to have more impact today than the articles produced outside central banks."

Link to the paper, popup: yes which contains a vivid 1929 dialogue between Keynes and Sir Ernest Musgrave Harvey of the Bank of England, who asserts, "It is a dangerous thing to start giving reasons." 

h/t to the always-excellent Beatrice Cherrier popup: yes who highlighted this work in a brief thread popup: yes and included some visualizations, including this one showing the publishing rate of central banking researchers: 

  • Via both Cherrier and the paper, a brief Economist article on the crucial significance of the central banking conference in Jackson Hole, hosted by the Federal Reserve Bank of Kansas City: "Davos for central bankers." Link popup: yes. (And link popup: yes to an official history of the conference.) 
  • Another paper co-authored by Claveau looks at the history of specialties in economics, using quantitative methods to map the importance of sets of ideas through time. "Among our results, especially noteworthy are (1) the clear-cut existence of ten families of specialties, (2) the disappearance in the late 1970s of a specialty focused on general economic theory, (3) the dispersal of the econometrics-centered specialty in the early 1990s and the ensuing importance of specific econometric methods for the identity of many specialties since the 1990s, and (4) the low level of specialization of individual economists throughout the period in contrast to physicists as early as the late 1960s." Link popup: yes
 Full Article

July 14th, 2018

Traveling Light


Considerations on data sharing and data markets 

CHARLES I. JONES and CHRISTOPHER TONETTI contribute to the “new but rapidly-growing field” known as the economics of data:

“We are particularly interested in how different property rights for data determine its use in the economy, and thus affect output, privacy, and consumer welfare. The starting point for our analysis is the observation that data is nonrival. That is, at a technological level, data is not depleted through use. Most goods in economics are rival: if a person consumes a kilogram of rice or an hour of an accountant’s time, some resource with a positive opportunity cost is used up. In contrast, existing data can be used by any number of firms or people simultaneously, without being diminished. Consider a collection of a million labeled images, the human genome, the U.S. Census, or the data generated by 10,000 cars driving 10,000 miles. Any number of firms, people, or machine learning algorithms can use this data simultaneously without reducing the amount of data available to anyone else. The key finding in our paper is that policies related to data have important economic consequences.”

After modeling a few different data-ownership possibilities, the authors conclude, “Our analysis suggests that giving the data property rights to consumers can lead to allocations that are close to optimal.” Link to the paper popup: yes.

  • Jones and Tonetti cite an influential 2015 paper by Alessandro Acquisti, Curtis R. Taylor, and Liad Wagman on “The Economics of Privacy”: “In digital economies, consumers' ability to make informed decisions about their privacy is severely hindered, because consumers are often in a position of imperfect or asymmetric information regarding when their data is collected, for what purposes, and with what consequences.” Link popup: yes.
  • For more on data populi, Ben Tarnoff has a general-interest overview in Logic Magazine, including mention of the data dividend and a comparison to the Alaska Permanent Fund. Tarnoff uses the oil industry as an analogy throughout: “In the oil industry, companies often sign ‘production sharing agreements’ (PSAs) with governments. The government hires the company as a contractor to explore, develop, and produce the oil, but retains ownership of the oil itself. The company bears the cost and risk of the venture, and in exchange receives a portion of the revenue. The rest goes to the government. Production sharing agreements are particularly useful for governments that don’t have the machinery or expertise to exploit a resource themselves.” Link popup: yes.
 Full Article

June 23rd, 2018

Yielding Stone


Including protected variables can make algorithmic decision-making more fair 

A recent paper co-authored by JON KLEINBERG, JENS LUDWIG, SENDHIL MULLAINATHAN, and ASHESH RAMBACHAN addresses algorithmic bias, countering the "large literature that tries to 'blind' the algorithm to race to avoid exacerbating existing unfairness in society":  

"This perspective about how to promote algorithmic fairness, while intuitive, is misleading and in fact may do more harm than good. We develop a simple conceptual framework that models how a social planner who cares about equity should form predictions from data that may have potential racial biases. Our primary result is exceedingly simple, yet often overlooked: a preference for fairness should not change the choice of estimator. Equity preferences can change how the estimated prediction function is used (such as setting a different threshold for different groups) but the estimated prediction function itself should not change. Absent legal constraints, one should include variables such as gender and race for fairness reasons.

Our argument collects together and builds on existing insights to contribute to how we should think about algorithmic fairness.… We empirically illustrate this point for the case of using predictions of college success to make admissions decisions. Using nationally representative data on college students, we underline how the inclusion of a protected variable—race in our application—not only improves predicted GPAs of admitted students (efficiency), but also can improve outcomes such as the fraction of admitted students who are black (equity).

Across a wide range of estimation approaches, objective functions, and definitions of fairness, the strategy of blinding the algorithm to race inadvertently detracts from fairness."

Read the full paper here popup: yes.

 Full Article

March 17th, 2018

Natatorium Undine



State universities' reliance on out-of-state enrollment

Research on enrollment patterns finds that shrinking state funds leads admissions departments to look for out-of-state tuition financing.

"Fixed effects panel models revealed a strong negative relationship between state appropriations and nonresident freshman enrollment. This negative relationship was stronger at research universities than master’s or baccalaureate institutions. These results provide empirical support for assertions by scholars that state disinvestment in public higher education compels public universities to behave like private universities by focusing on attracting paying customers.

We contribute to a growing body of evidence that showing that university revenue seeking behaviors are associated with a strong Matthew Effect. Cheslock and Gianneschi showed that only flagship research universities could generate substantial revenues from voluntary support. Therefore, increasing reliance on voluntary support increases the differences between ‘have’ and ‘have-not’ universities. Similarly, our results suggest that relying on nonresident enrollment growth to compensate for declines in state appropriations also increases the difference between the haves and the have-nots. Many public universities may desire tuition revenue from nonresident students. However, descriptive statistics suggest that only research universities are capable of generating substantial nonresident enrollment."

Link to the full paper, by OZAN JAQUETTE and BRADLEY CURS.

  • An NBER working paper, from 2016, produces similar findings in the case of international student enrollment: "Our analysis focuses on the interaction between the type of university experience demanded by students from abroad and the supply-side of the U.S. market. For the period between 1996 and 2012, we estimate that a 10% reduction in state appropriations is associated with an increase in foreign enrollment of 12% at public research universities and about 17% at the most resource-intensive public universities." Link to the paper, link to a summary.
 Full Article