For years, I have identified what I think of as ‘long walk’ problems - knotty issues that are best tackled if you can get away from it all. I often come back with an answer, or a few paragraphs, composed in my head.
He is wildly controversial, though. As one of the foremost scholars of game theory—or “rational choice,” as its political-science practitioners prefer to call it—Bueno de Mesquita is at the center of a raging hullabaloo that has taken over some of the most prestigious halls of learning in this country. Exclusive, highly complex mathematically, and messianic in its certainty of universal truths, rational-choice theory is not only changing the way political science is taught, but the way it’s defined.
To verify the accuracy of his model, the CIA set up a kind of forecasting face-off that pit predictions from his model against those of Langley’s more traditional in-house intelligence analysts and area specialists. “We tested Bueno de Mesquita’s model on scores of issues that were conducted in real time—that is, the forecasts were made before the events actually happened,” says Stanley Feder, a former high-level CIA analyst. “We found the model to be accurate 90 percent of the time,” he wrote. Another study evaluating Bueno de Mesquita’s real-time forecasts of 21 policy decisions in the European community concluded that “the probability that the predicted outcome was what indeed occurred was an astounding 97 percent.” What’s more, Bueno de Mesquita’s forecasts were much more detailed than those of the more traditional analysts. “The real issue is the specificity of the accuracy,” says Feder. “We found that DI (Directorate of National Intelligence) analyses, even when they were right, were vague compared to the model’s forecasts. To use an archery metaphor, if you hit the target, that’s great. But if you hit the bull’s eye—that’s amazing...
How does Bueno de Mesquita do this? With mathematics. “You start with a set of assumptions, as you do with anything, but you do it in a formal, mathematical way,” he says. “You break them down as equations and work from there to see what follows logically from those assumptions.” The assumptions he’s talking about concern each actor’s motives. You configure those motives into equations that are, essentially, statements of logic based on a predictive theory of how people with those motives will behave. From there, you start building your mathematical model. You determine whether the predictive theory holds true by plugging in data, which are numbers derived from scales of preferences that you ascribe to each actor based on the various choices they face.
The Prisoner’s Dilemma, a basic in game theory, explains it well: Two burglars are apprehended near the scene of a crime and are interrogated separately by the police. The police know these two goons did it, but they don’t know how, so they offer each one a deal. If they both confess and cooperate, they’ll both get a minor sentence of five years. If neither man confesses, they’ll both only get one year (for having been caught with some of the stolen loot on them). But, and here’s where it gets interesting, if one confesses and the other doesn’t, the one who confesses walks out scot-free while the other will do 10 years. What will they do? Will they trust each other and do what’s obviously in their best interest, which is not confess? Based on game theory’s assumptions about human nature, the math derived from this dilemma tells you squarely that the two goons will turn each other in...
There’s also the book he’s written with Condoleezza Rice and two other authors, The Strategy of Campaigning, which comes out in the fall. Given the Bush administration’s heavy ideological bent—which would seem to represent everything a rationalist like Bueno de Mesquita opposes—how does he justify putting his name on the same dust jacket as Rice’s Bueno de Mesquita repositions himself in his chair. “The central question in this book is a question that Condi raised before she came to Washington,” he says. (So is her name there just to sell books? “We are making a concerted effort not to play up the fact that the Secretary of State is a co-author,” he later adds.)
Meanwhile, he has just launched and is the director of NYU’s Alexander Hamilton Center. “The mission for the center is the application of logic and evidence to solving fundamental policy problems. Not to a bipartisan solution, but to a nonpartisan solution.” In his continuing work for the CIA and the Defense Department, one of his most recent assignments has been North Korea and its nuclear program. His analysis starts from the premise that what Kim Jong Il cares most about is his political survival. As Bueno de Mesquita sees it, the principal reason for his nuclear program is to deter the United States from taking him out, by raising the costs of doing so. “The solution, then, lies in a mechanism that guarantees us that he not use these weapons and guarantees him that we not interfere with his political survival,” he says.
Each book targets a different audience. Often there are advertisers lurking in the background. The primer I have enjoyed most, the one I would recommend to a friend who wanted to learn how economists think about the world right now, is one that passed almost completely unnoticed into the stream, perhaps because it is so slight. But then, that is the point of Economics: A Very Short Introduction, by Partha Dasgupta, the Frank Ramsey Professor of Economics at Cambridge University. He boils down everything that's ordinarily included in a thousand-page introductory text, and more, to 160 graceful but undersized pages. (The book is one of an interminable list of Very Short Introductions -- to everything from Anarchy, Anglicanism and Animal Rights to Schizophrenia, the World Trade Organization and, coming soon, Chaos -- from Oxford University Press.)
Dasgupta, 65, is one of those figures, well-known to insiders but virtually invisible to those outside the field, until they pop up some year as an October surprise. (Queen Elizabeth knighted him in 2002 "for services to economics.") He has done deep work on issues the length and breadth of economics -- he taught game theory to Joseph Stiglitz and learned the economic history of science from Paul David. But the contribution for which he is best known is a skein of work with Geoffrey Heal, then also of Cambridge University, on the economics of natural resources, begun in 1972, in the context of the then-best-selling The Limits to Growth, and finished with a prescient 1979 monograph, Economics Theory and Exhaustible Resources. That led Dasgupta to an engagement with the United Nations, and a long collaboration with Karl-Gšran Mþler, another environmental economics pioneer. Both are still at it; in 2001 Dasgupta published Human Well-Being and the Natural Environment, and expanded it in 2004. But also in 1972, he read John Rawls' A Theory of Justice, and that led to a second leg of work on social choice, on mechanism design and, ultimately, on the nature of wealth and destitution.
Thus Dasgupta is supremely well qualified to write an overview of economics for the layman. Originally, he says, he had it in mind to lay out what he understood to be the research frontier. "But even though the analytical and empirical core of economics had growth from strength to strength over the decades," he writes, "I haven't been at ease with the selection of topics that textbooks offer for discussion (rural life in poor regions -- that is the economic life of some 2.5 billion people -- doesn't get mentioned at all, nor with the subjects that are emphasized in leading economic journals (Nature rarely appears there as an active player)." The result is a serious textbook treatment shaped around the lives of two ten-year-old "literary grandchildren," Becky in a small Midwestern suburb where her father works for a firm specializing in property law, Desta in a village in southwestern Ethiopia, where her father farms half a hectare of land.
Sample sizes in cross-country growth regressions vary greatly, depending on data availability. But if the selected samples are not representative of the underlying population of nations in the world, ordinary least squares coefficients (OLS) may be biased. This paper re-examines the determinants of economic growth in cross-sectional samples of countries utilizing econometric techniques that take into account the selective nature of the samples. The regression results of three major contributions to the empirical growth literature by Mankiw-Romer-Weil (1992), Barro (1991) and Mauro (1995), are considered and re-estimated using a bivariate selectivity model. Our analysis suggests that sample selection bias could significantly change the results of empirical growth analysis, depending on the specific sample utilized. In the case of the Mankiw- Romer-Weil paper, the value and statistical significance of some of the estimated coefficients change drastically when adjusted for sample selectivity. But the results obtained by Barro and Mauro are robust to sample selection bias...
In the Mankiw-Romer-Weil (1997) paper, we found that using their 75-country sample leads to the exclusion of a number of low-income and middle-income countries that results in a substantial sample selection bias. The value and statistical significance of the estimated growth equation coefficients reported by Mankiw-Romer-Weil for this sample of countries change drastically when adjusted for sample selectivity. But in re-examining these results using Mankiw-Romer-Weil’s 98-country sample, we found much smaller differences in estimated coefficients. The impact of sample selection bias on the Mankiw-Romer-Weil results is thus dependent on the choice of sample.
I have long been skeptical about how much one can learn from cross-country growth regressions. In the early 1990s, I wrote one paper in that literature, coauthored with David Romer and David Weil, and to my surprise, it turned out to be my most cited paper by a very large margin. In a subsequent paper, The Growth of Nations, I tried to spell out the reasons for my skepticism. I emphasized three problems, which I called the simultaneity problem (it is hard to disentangle cause and effect), the multicollinearity problem (most of the potential determinants of growth are correlated with each other and imperfectly measured, making it hard to figure out which is the true determinant), and the degrees-of-freedom problem (there are more plausible hypotheses than data points). To some extent, the subsequent literature addresses some of my concerns. For example, there is more attention now to trying to find exogenous differences across countries, but the task is inherently difficult, so one should not expect to find definitive answers about the causes of growth from this literature.
In my mind, the next big challenge is to integrate the work on macro (mostly growth, trade, and finance) with the work on micro (mostly health, education, and evaluation). A few people are working in that intersection, but not nearly enough in my view. The micro economists face the challenge of demonstrating that their work can say something about economy-wide growth patterns and differentials--the strongest determinant of poverty patterns in the world. Meanwhile, macro types have to develop evidence that passes the microeconomists' more demanding requirements.
1 The ‘peak shift principle’ makes exaggerated elements attractive
2 Isolating a single cue helps to focus attention
3 Perceptual grouping makes objects stand out from background
4 Contrast is reinforcing
5 Perceptual ‘problem solving’ is also reinforcing
6 Unique vantage points are suspect
7 Visual ‘puns’ or metaphors enhance art
8 Symmetry is attractive
Difference in Difference (DD) is a commonly used empirical estimation technique in economics. Let us take a hypothetical example where a state (Wisconsin) passes a bill which makes employer-provided health insurance tax deductible. Let us also assume that in the year after the bill passed (year 2) the percentage of firms offering health insurance increased by 50% compared to the year before the bill was passed (year 1). In order to estimate the impact of the of the bill on the percentage of firms offering health insurance, we could simply do a ‘before and after’ analysis and conclude that the bill increased insurance offerings by 50%. The problem is that there could be a trend over time for more employers to offer insurance. It is impossible to identify if the tax deductibility or the time trend caused this increase in firm offering...
Joe, you may not remember this, but in the late 1980s, I once enjoyed the privilege of being in the office next to yours for a semester. We young economists all looked up to you in awe. One of my favorite stories from that era is a lunch with you and our former colleague, Carl Shapiro, at which the two of you started discussing whether Paul Volcker merited your vote for a tenured appointment at Princeton. At one point, you turned to me and said, "Ken, you used to work for Volcker at the Fed. Tell me, is he really smart?" I responded something to the effect of "Well, he was arguably the greatest Federal Reserve Chairman of the twentieth century" To which you replied, "But is he smart like us?" I wasn't sure how to take it, since you were looking across at Carl, not me, when you said it.
Real economic growth in the USA
Inflation in the USA
Economic inequality in the USA
