(New) Economic Thinking

In "Can New Economic Thinking Solve the Next Crisis?," Mark Thoma writes:

There has been quite a bit of criticism directed at the tools and techniques that macroeconomists use, e.g. criticism of dynamic stochastic general equilibrium (DSGE) models, but that criticism is misplaced. The tools and techniques that macroeconomists use are developed to answer specific questions. If we ask the right questions, then we will find the tools and techniques needed to answer them.  

The problem with macroeconomics is not that it has become overly mathematical – it is not the tools and techniques we use to answer questions. The problem is the sociology within the economics profession that prevents some questions from being asked. Why, for example, were the very questions we needed to ask prior to the Great Recession ridiculed by important voices within the profession?

Since I didn't start studying economics until the Great Recession was in full swing, I don't have a full perspective on "new economic thinking" compared to old, or on what it was like to be in the economics profession prior to the Recession. I only gain second-hand perspective through reading and through studying economic history (which at Berkeley, coincidentally, is largely supported by the Institute for New Economic Thinking).  Thoma's article was prompted by the Rethinking Economics conference, but for me, I'm still learning how to think economics, much less rethink it.

One course that was particularly helpful in shaping my economic thinking was an elective on Empirical Macrofinance taught by Atif Mian. He made a point on one of the first days of class that really stood out. He told us not to see what questions we could answer with the data we have, but rather, to start with the question, and then think about what data we needed to answer it. More often than not, we'd need microdata. Not a problem! We are not in a data-scarce environment!

Mian's work with Amir Sufi on the role of household debt in the Great Recession is a great example of both his point and Thoma's point: start with the question, then choose your tools, techniques, and data. I realize this is easier said than done (trust me, I really do, after spending the last few years trying to implement it in my dissertation), but to me, that's just economic thinking.

Speaking of my dissertation, I'm preparing to go on the job market this year, which is why the blogging has been a bit less frequent! While the preparation is a lot of work, I am fortunate to be very enthusiastic about my research, because I did start with questions I care about, so working on it is a joy, even if it takes away blogging time. Eventually I will blog about my research, just not quite yet.

Suzanne Scotchmer (1950-2013)

Suzanne Scotchmer, an economics and law professor at Berkeley, recently passed away. From Brad DeLong, here is the note sent out to the Berkeley Law community. An excerpt:

"Suzanne was particularly inspirational as one of very few women writing in the field of theoretical economics. Friends, colleagues and students across the campus and across her disciplines shared a deep appreciation for Suzanne's tirelessly creative mind, her enthusiasm for intellectual engagement at the highest level, and her preternatural ability to see to the heart of a complex problem immediately and describe it with clarity and insight."

The Toulouse School of Economics, where Scotchmer sat on the Scientific Council since 2007, also wrote a very nice tribute.

Joshua Gans leaves a summary of Scotchmer's work in innovation economics. Gans' article also includes some moving recollections of Scotchmer from her former student Neil Gandal. Another of Scotchmer's former students, Diane Coyle, was a graduate student at Harvard in the early 1980s when Scotchmer was there as an assistant professor. Coyle writes, "Then, as now, economics was very male-dominated and it was unspeakably encouraging to have a female role model who was highly supportive of students – and a normal human being too, warm, funny, with outside interests."

In addition to her work in innovation economics and patent law, Scotchmer made numerous contributions in mathematical economics, game theory, and public finance. In one interesting paper, "On the Evolution of Attitudes towards Risk in Winner-Take-All Games" (1999) with Eddie Dekel, she studies endogenous preference formation:

"Economists typically take preferences as given. This sets them apart from other social scientists, such as psychologists, who often try to explain preferences. In this paper we explore an evolutionary model where preferences, in particular attitudes toward risk, are endogenously determined."

In another paper, "The short-run and long-run benefits of environmental improvement," she suggests a technique for calculating the social value of nonmarginal improvements to social goods such as environmental improvement. Another interesting paper is "Risk taking and gender in hierarchies" (2008), which sheds some light on the controversy about gender differentials labor market outcomes. Suzanne Scotchmer left a tremendous intellectual and personal legacy and will be greatly missed.

Divided Fed, Broken Models

This week, it has become abundantly clear that the Fed is "deeply divided." In speeches and public communications, FOMC committee members and  Fed Chairman Ben Bernanke have revealed significant differences in their outlooks and intentions for the economy. Tim Duy writes that "The growing division makes it increasingly difficult to think of "the Fed" as a single entity with regards to policy intentions." This is an extremely important point, because most macroeconomic models do consider the Fed as a single entity, and would have different implications if they did not.

Monetary policy is often modeled as a dynamic game in which the two players are the central banker and the public. Typically, the central banker can choose what private information to reveal to the public. Monetary policymakers' preferences and reputational concerns determine their optimal communication strategy in the equilibrium of this dynamic credibility game (see for example Faust and Svensson 2001). Depending on the exact "rules of the game," the optimal strategy turns out to be something less than full information revelation. This game-theoretic political economy paradigm for thinking about monetary policy became hugely influential after seminal papers by Kydland and Prescott in 1977 and Barro in 1986, and has shaped the way economists think about the merits of central bank independence, rules versus discretion, transparency, and explicit inflation targets, with. Insights from this huge literature have been thoroughly integrated into the policymaking sphere.


In reality, of course, in almost every country, monetary policy is not made by a single representative agent, but rather by a committee of very non-representative agents, each with their own, sometimes conflicting, preferences and reputational concerns. With multiple central bankers, monetary policy is a dynamic game between more than two players-- which makes computing optimal strategies dauntingly complex. Strategic behavior between members of the committee will influence each member's communication strategy with the public and with each other. And the public, aware of these strategic interactions, will have quite a complex task computing their best response.

I'm not quite sure where we go from here. One of the most brilliant and famous game theorists, John Nash, proved that non-cooperative games with an arbitrary finite number of players have a Nash equilibrium. But actually finding such an equilibrium is a huge challenge (plus, the non-cooperative assumption is kind of restrictive.) A pair of computer scientists at Berkeley and Stanford note that "even less is known about computing equilibria in multi-player games than in the (still mysterious) special case of two-player games." Even more telling is the title of another paper by Berkeley computer scientists: "Three-Player Games are Hard."

Services and the Slow Economic Recovery

The Berkeley Economic History Laboratory (BEHL) launched a series of working papers earlier this year. The BEHL website notes that "These papers are preliminary works, and their circulation is intended to stimulate discussion and comment." To further that goal, as I mentioned in an earlier post, I'll be spotlighting these working papers on the blog. Three new papers are out; the one I'd like to write about today is called "Goods, Services, and the Pace of Economic Recovery," by Martha Olney and Aaron Pacitti.

The authors cite Lazear and Spletzer's argument that “the problem [with the U.S. economy now] is not that the labor market is underperforming; it is that the recovery has been very slow” (2012 pg. 35). Olney and Pacitti offer an explanation for the slow recovery based on a hypothesis that recoveries from downturns should be slower when services are a larger share of the economy. This comes from the simple idea that goods, and not services, can be produced ahead of an anticipated increase in demand, because only goods can be inventoried. Here is the abstract:

Do service-based economies experience slower economic recoveries than goods-based economies? We argue they do. An economy recovers from a downturn when businesses increase production. Both goods and services can be produced in response to actual demand. But only goods—and not services—can be produced in response to anticipated increases in demand, allowing optimistic forward-looking producers to inventory goods until anticipated buyers appear. Services can’t be inventoried. The more services an economy produces relative to goods, the more production is dependent upon only actual increases in demand, and the slower the recovery. We exploit variation across time and states in the share of services in output. Controlling for the depth of the downturn, the higher is the share of services, the longer is the recovery. Extending our results to the current downturn, given the depth of the downturn, the rise in services alone will make the post-2009 recovery last about 1 year longer than it would have a half-century ago.

The authors use national data for the 10 recessions in the United States from 1948 to 2001, and a panel of state data for 50 states and 5 recessions from 1969 to 2001. They use the depth of each recession as a control variable. Getting the state-level data on service sector shares and business cycles was not an easy feat, and is an important contribution of this research. They are able to document interesting, and changing, variation in the share of services by state. My home state, Kentucky, had the second lowest share of services (39%) in the nation in 1967-1969; the share has risen to 50%. Now oil-rich states Wyoming, Alaska, and Louisiana have the lowest share of services. (Take a look at figure 6 and very cool figure 7 in the paper.)

I am left wondering about the other side of the business cycle. The story in this paper is that businesses can anticipate an increase in demand and build up an inventory. What happens when a decrease in demand is anticipated? Wouldn't goods-producing businesses decrease production and start using up their inventory? This would lengthen the downturn part of the cycle by making it start sooner. If this is the case, service-oriented economies would have longer recoveries and shorter downturns. I don't know if the effect would be asymmetrical. For the state-level data, the authors measure recovery as the length of time from one peak to the next peak of the business cycle. This actually captures the length of the downturn plus recovery. I think it would be preferable to use trough-to-peak length instead of peak-to-peak length if the data allowed it, since share of services could plausibly effect peak-to-trough length and trough-to-peak length in different ways.


Overall, I think this working paper documents an intriguing empirical fact. Has anyone out there read (or written) a macro model with two firms with heterogeneous inventory costs? Please comment or send it my way if you have.Setting the inventory costs of one of the firms to infinity could represent the service sector. I think it would be useful to have a model to go along with this paper-- both to help think about my point in the last paragraph and because I am having trouble thinking about GE implications for relative prices and wages in the goods and services sectors and what role that could play. Any other comments or suggestions on the paper are of course welcome, and I will pass them along to the authors.

When Economists Have an Auction

I just got back from the Berkeley Economics annual skit party. The skit party is combined with an auction to raise money for the Graduate Economics Association. Professor Yuriy Gorodnichenko contributed a very interesting auction item: a promise to pay $500 if Christina Romer or Janet Yellen becomes Fed chair at any time in the future.

The bidding started at $50, and quickly jumped up to $200. I was bidding against Gabriel Chodorow-Reich, a fellow macro student. I chickened out and went silent after he bid $220, so he won. Immediately after, I was kicking myself for not sticking in a little longer. I think Gabe got a heck of a deal-- plus I would just love to be able to say that I had bought this unique asset.

Professor Gorodnichenko (who also swept the awards ceremony tonight, winning the Best Professor and Best Adviser awards) donated another auction item-- a check with the amount drawn from a beta distribution with parameters alpha=3 and beta=2, multiplied by $100. The beta distribution is only nonzero on the unit interval, so the check will have value between $0 and $100. The mean of the beta distribution is alpha/(alpha+beta), so the expected value should be $100 (3/5)=$60. The item went for $50 -- so everyone in the audience must have been risk averse, loss averse, financially illiterate, or liquidity constrained (or some combination, like me.) A bottle of wine from Professor David Card's vineyard was the highest-priced item, going for $240.

The most creative item was donated by grad student Kaushik Krishnan. He collected and printed all of Brad DeLong's "Liveblogging World War II" blog posts and put them into a binder, which he promises to get signed by DeLong next time he's in Berkeley. If I remember right, that went for around $40.

New Berkeley Working Papers

The Berkeley Economic History Lab (BEHL) has just announced the launch of a new working paper series. BEHL was established in 2011 with funding from the Institute for New Economic Thinking (INET). I have certainly benefited from BEHL, mostly from the weekly seminar series, post-seminar coffee hours, faculty mentoring, and biweekly student seminar lunches. The working papers are contributed by visitors and other affiliates of the BEHL. Since "their circulation is intended to stimulate discussion and comment," I plan to use the blog as a venue to assist with that. I will put up a link and write a paragraph or so about each working paper as they appear, and invite you to read the papers that interest you and leave your comments and questions. I'll send the relevant authors a link to the comment thread. Two working papers are already up.

The first is "State Capacity and Long Run Performance" by Mark Dincecco and Gabriel Katz. State capacity refers to the combined extractive and productive capabilities of the state-- its ability to tax and to provide public goods and services. The concept has come to prominence in the development literature, where it is recognized that lack of state capacity is a limit to development. This is the theme of a 2011 paper by Timothy Besley and Torsten Persson who study current-day "fragile states" that are ineffective at taxing and providing basic services to citizens. Dincecco and Katz' paper studies state capacity from an economic history perspective, using four centuries of European data (1650-1913). They study the impacts of political transformations--particularly fiscal centralization and parliaments-- on extractive and productive capabilities, and in turn on economic growth.

The second is "Financing a Planned Economy: Institutions and Credit Allocation in the French Golden Age of Growth (1954-1974) " by Eric Monnet. The years 1945-1974 are called the "Golden Age of European Growth," yet they witnessed startlingly high levels of financial repression. Monet investigates this seeming discrepancy between high growth and financial distortion. He looks in detail at the planned ("dirigiste") economy of postwar France, where the "nationalization of credit" was a priority. The Planning office, the Bank of France, and semi-public credit institutions played decisive roles in allocating credit in accordance with national economic and social priorities. The state actively supported the development of bank credit. This paper also provides an original database and analyzes it to account for the role of finance in the French Golden Age.

Take a look at these new working papers and stay tuned for more in the BEHL series!