Christopher A. Sims


Christopher A. Sims

My grandfathers were both immigrants to the US, one from Estonia, then part of the Russian empire, and the other from England. The Estonian, William Morris Leiserson, was Jewish. He fled Estonia in 1890 at the age of seven, through a forest in the dark of night, with his mother and two brothers. The family is not sure why they had to flee. It could have been because of a pogrom, or it could have been because of political activities of my great grandfather. Many Jews were fleeing Russia at the time. William’s father was meant to join them after they reached the US, but was not seen again. One of William’s older brothers, Louis, owned one of the shirtwaist companies in New York that were the site of the famous 1909 strike by the ILGWU, and William worked there as a youth. His formal education in public schools ended at the age of 14, but he read widely and attended public lectures in New York. At the age of 21 he went to Wisconsin, where he persuaded John R. Commons, the institutional economist, to take him on as a student despite his having no high school diploma. He later attended Columbia University in New York for his PhD work. He went on to teach at Antioch College and to become one of the first members of the US National Labor Relations Board, and then served on the National Mediation Service. He married Emily Bodman, whose family had many generations of roots in New England, and had seven children, one of them my mother, Ruth. Ruth, besides raising three children, headed the Connecticut League of Women Voters for a time and served two terms as First Selectman (similar to a mayor) of the town of Greenwich, Connecticut. She was the first woman, and the first Democrat in many decades, to be elected to that position.

My father Albert’s father James was an English immigrant who worked as an itinerant manager of textile factories in New England, brought in to turn around poorly performing factories (at a time when the industry was declining). He died at a relatively young age. His wife Minnie Love was also an immigrant, from Northern Ireland, and she, too, died at a young age, leaving seven children to manage their own household, which they did successfully. Albert went to Michigan State University and received a masters degree in public administration from Syracuse University. He worked in the US State Department, then as vice president of the College Board in New York.

Two of my uncles, Mark and Avery Leiserson, were professors. Mark was a labor economist, first at Yale, then at the World Bank. Avery spent most of his career at Vanderbilt University and served a term as president of the American Political Science Association. Both of them, and my grandfather “Billy” Leiserson, loved intellectual argument. I remember being greeted by grandpa, when I was about seven years old, with a twinkly eye and “Well, Chris, what do you think of the present situation of the country?” This was not an isolated incident. This was his standard greeting for grandchildren. Mark prodded me regularly, from about age 13 onward, to study economics. He gave me von Neumann and Morgenstern’s Theory of Games for Christmas when I was in high school. When I took my first course in economics, I remember arguing with him over whether it was possible for the inflation rate to explode upward if the money supply were held constant. I took the monetarist position. He questioned whether I had a sound argument to support it. For years I thought he was having the opposite of his intended effect, and I studied no economics until my junior year of college. But as I began to doubt that I wanted to be immersed for my whole career in the abstractions of pure mathematics, Mark’s efforts had left me with a pretty clear idea of an alternative.

While I was born in Washington DC (in 1942), from the ages of about five to seven I lived in Germany. My father had been part of the military government while in the Army, then switched to the State Department and brought the family over. We lived in Berlin and in Kronberg, near Frankfurt. At the time, I spoke some German, though I subsequently almost entirely forgot it. After returning to the US, we lived in Hollin Hills, Virginia for a few years, then moved to Greenwich, Connecticut when I was 11. I finished my schooling there and graduated from Greenwich High School in 1959. In high school I played football (third string linebacker, most of the time) and trombone in the band. I had a memorable math teacher in high school, Steven S. Willoughby, who later became president of the National Council of Teachers of Mathematics.

My undergraduate education was at Harvard, where I majored in mathematics, worked in a political group opposing nuclear testing and proliferation, played club rugby and weekend soccer, and played trombone in the band. My honors thesis generalized Khinchin’s version of the coding theorem of information theory to infinite-memory channels. Engineers who were roped into reading the thesis tried to convince me to enter graduate school in electrical engineering. In some of my recent research I have found a way to connect information theory to economics.

My first year of graduate study was at UC Berkeley, where I took Microeconomic Theory from Dan McFadden, econometrics from Dale Jorgenson, and Monetary Economics from Richard Lipsey, inspiring teachers. McFadden posed problems that were only nearly impossible, from which I learned a lot. He taught micro as largely a set of corollaries of convex analysis. He later told me that this was in the period before he learned how to teach, for which I think I am grateful. Lipsey taught economics as a set of open questions and gave students the sense that they might be finding answers. Jorgenson gave off an almost electric sense of energy and confidence in the power of the rapidly developing field of econometrics.

I moved back to Harvard in my second year of PhD study. My adviser there was Hendrik Houthakker, who largely gave me free rein. I decided to study, empirically, embodied technological change. As I thought I was nearing completion of the work on my model, Henk insisted that I should be able to formulate it in continuous time, then derive the discrete time version from the continuous time version. This was harder than I think Henk realized, and led me to learn a great deal of real analysis in a short time. John Chipman, then visiting Harvard, was the only person I found who not only understood the issues I was dealing with, but could point me to relevant mathematical literature. John urged me to consider the Minnesota department, but Harvard was about to hire Zvi Griliches and Dale Jorgenson, so I decided to stay at Harvard as an assistant professor for two years.

In February 1967, a few months before completing my dissertation work, I married Catherine Sears. We postponed our honeymoon trip to the summer because of dissertation work, and then had to repostpone it because the work kept not finishing. We ended up with a rapid road trip to the Rocky Mountains in September. We arrived and pitched our tent in the dark, in the rain, and awoke to find our tent door flap frozen shut. Cathie, who had not camped before, has remained skeptical of camping trips ever since – even though the weather in the Rockies was better after that morning.

Our son Ben arrived two years later, shortly before we moved on to Minneapolis.

Tom Sargent and I knew each other slightly as graduate students at Harvard. We had both come across the issue of interpreting two-sided distributed lag regressions, and we talked about it on the phone once or twice. I had accepted a position for the next year at Minnesota, and my recollection is that I had heard that Neil Wallace and Jack Kareken at Minnesota were enthusiastic about hiring Tom, and that I was encouraging Tom to go to Minnesota during our telephone conversations. Tom, on the other hand, has said he is sure I proposed his name to Minnesota. In any case it was for me tremendous good fortune that he and I arrived at Minnesota at about the same time. He was and is a gifted teacher, whose students emerged both well trained and enthusiastic and confident about research. I was at Minnesota for 20 years, most of them with Tom as a colleague. Though Neil Wallace, Tom, Ed Prescott and I were seen by many outside Minnesota as a package of “fresh-water” innovators, from inside the Minnesota department we seemed to ourselves to represent sharply distinct viewpoints. We argued, and stimulated each other and our students. Actually much of the “arguing” was implicit, in the conflicting advice we sometimes gave our shared PhD students.

Our two younger children, Jody and Nancy, were born in Minneapolis and both live there now. We spent the entire 20 years in the same house in South Minneapolis, in a neighborhood where the single block-length of our street housed dozens of children. Summer evenings regularly involved “duck-duck grey-duck” and kickball games with street corners as bases.

My first econometrics and statistics courses (a statistics course from
Dempster and econometrics courses from Hendrik Houthakker and Lester Taylor, all while an undergraduate at Harvard) did not devote much attention to Bayesian approaches. I had looked at, but not read through Raiffa and Shlaifer’s book on decision theory and read some of Pratt’s articles that took a Bayesian perspective. As I started graduate school I think I had the impression that the difference between Bayesian and frequentist approaches was mainly semantics, with little implication for practical data analysis. Another student at some point showed me the standard “rare disease” example, in which a 99% confidence interval, while having 99% pre-sample coverage probability, fails to contain the truth in 99% of the cases where the test is positive for the disease. I still remember puzzling over the example. It changed my thinking. It was not until I started analyzing the discrepancy between Bayesian and frequentist approaches to possibly non-stationary time series models that I became convinced that the distinction between the two approaches was important enough in a wide enough class of applications that teaching should always start from the Bayesian perspective. Since then, my teaching at every level has started from a Bayesian perspective, teaching non-Bayesian approaches as side topics.

In macroeconomics, my thinking was of course influenced by my two colleagues Sargent and Wallace, who were part of the core group fomenting the “rational expectations revolution” in macroeconomics. My own research made little use of rational expectations theory at first, focusing instead on using simpler, minimal theory to find the effects of policy by analyzing time series data. This is not because I was opposed to rational expectations ideas – I thought they represented an advance. I just thought the “revolution” aspect of it, in particular the deprecation of the ideas and efforts of the Keynesian econometricians, was overdone. My own work involved criticizing the statistical underpinnings of the Keynesian econometric models, but I viewed them as flawed but important, not worthless. I found the story that those Keynesian models had led to the inflation of 1970s implausible, unsupported by evidence, and recent research seems to confirm that.

While at Minnesota I heard Michael Woodford give a talk, one part of which laid out how the government’s intertemporal budget constraint can be regarded as determining the price level. This set me to thinking and writing about the theory of price determination in models that treated both monetary and fiscal policy explicitly, a major part of my research from then on. In this theoretical work I made regular use of a rational expectations framework, which was by that time standard.

After Sargent left Minnesota, the department began to have internal disagreements about whether econometrics was an essential part of graduate training in economics. Many of the most interesting dissertations I helped supervised had been joint projects with Sargent, and his teaching had instilled an interest in careful quantitative research in Minnesota students. I decided it might be more interesting to work elsewhere, and settled on Yale. There I took a relatively bigger role in macro teaching and a relatively smaller one in econometrics teaching. Yale also had internal divisions, in this case over hiring macroeconomists who worked in the rational expectations framework. After nine years there, Princeton, which had a stellar collection of macro and monetary economists in Michael Woodford, Ben Bernanke, and Alan Blinder, and one of the best time series econometricians in Mark Watson, looked attractive, and I moved there. Soon Lars Svensson joined the Princeton faculty. For a few years, the research environment there, with constant interaction and discussion of theory and policy and shared responsibility for advising students, was as good or better than the early days at Minnesota.

Ten years ago, my wife Cathie, who had ridden horses extensively when she was younger, decided to take up riding again, and eventually bought a horse. I thought I should learn to ride to keep up with her. Riding turned out to be a great pleasure for me, and eventually I, too, bought a horse.

Cathie and I now have four grandchildren, aged two to ten, two living in Minneapolis, two in Los Alamos, New Mexico. We visit them regularly, and were happy that all four, with their parents, joined us in Stockholm for the Nobel ceremony.

Copyright © The Nobel Foundation 2011

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