In Memoriam: Christopher A. Sims
Lars Peter Hansen
April 6, 2026
This personal reflection was originally submitted to The Econometric Society:
Christopher A. Sims was the John J. F. Sherrerd ’52 University Professor of Economics at Princeton University (Emeritus starting in 2021). He was born on October 21, 1942, in Washington, D.C., and died on March 14, 2026, in Minneapolis, Minnesota. Sims earned his B.A. in mathematics in 1963 and his Ph.D. in economics in 1968, both from Harvard University, and went on to teach there initially. Later, he was on the faculty at the University of Minnesota and Yale University, prior to joining Princeton University. Sims was a member of the American Academy of Arts and Sciences, the National Academy of Sciences, and the American Philosophical Society. He served as President of the Econometric Society in 1995 and President of the American Economic Association in 2012. Together with Thomas Sargent, he won the Nobel Memorial Prize in Economic Sciences in 2011.
Time series analysis, applied to macroeconomics, provides the tools to examine some important questions that can’t be answered on purely statistical grounds without some form of economic modeling. How do we use macroeconomic time series data to identify and measure meaningful shocks or impulses to the economy, such as shifts in technology or monetary policy? How do we assess the accuracy of the resulting measurements? Sims provided a tractable vector autoregressive (VAR) method for addressing such questions requiring only a limited number of prior restrictions to identify economic shocks and their responses. His initial and most important contribution was his 1977 Fisher-Schultz Lecture to the Econometric Society entitled “Macroeconomics and Reality.” This contribution stands out as one of the most impactful Fisher-Schultz Lectures. The supporting paper both challenged current econometric practice and provided an alternative approach that has served as a guide for a remarkably large body of literature in empirical macroeconomics. It ushered in an approach to identification that featured the identification of economically interesting or so-called “structural” shocks and focused empirical measurement on how these shocks propagated over time.
In terms of his own empirical contributions, prior to VAR research, Sims investigated the time series relationship between money and aggregate output. Roughly speaking, his results were consistent with a view commonly held by monetarists of how the aggregate economy responds to exogenous movements in the money supply. Yet when he explored a substantially larger VAR system by incorporating additional economic time series such as interest rates, theinterpretation changed entirely. His findings and those of others using his approach upended previous analyses that focused on a single relationship with a monetary aggregate as the explanatory time series. Thus, Sims showed why it was essential to study a richer collection of time series simultaneously, allowing for flexible and convenient interrelated feedback. As Sims put it: “With a variety of identifying assumptions, a consistent picture has emerged: amonetary contraction produces a decline in output and a decline in inflation, with both responses smooth and delayed and the decline in output quicker.” These insights were extended to provide a more complete picture of changes in monetary regimes during the postwar period. Sims’s empirical analyses and those of others served in part as motivation for subsequent research on the interaction of fiscal and monetary policy as essential for understanding prices and inflation. Sims’s work provides examples of VAR methods applied to macro time series. This approach gave researchers the ability to measure the dynamic responses to a variety of economically interesting shocks. In addition to its academic interest, such research has played a prominent role in research produced within governmental agencies and has been used to help guide macroeconomic policy.
Especially early in his career, Sims wrestled with several approximation challenges pertinent to modeling economic time series and produced some very insightful and rigorous investigations. Much of this research was ahead of its time. There were a variety of dimensions to Sims’s contributions, including research that addressed questions such as: (a) what is the most relevant way to measure approximation errors and when might these errors matter the most, (b) what approximation issues emerge when investigating continuous-time stochastic models from discrete-time data, (c) how should a researcher confront seasonality in data when it is absent in the economic models of interest, and (d) what is the impact of Bayesian priors on infinite-dimensional spaces and what does this say about so-called “nonparametric analysis?” In this latter contribution, a Bayesian approach is used for its coherence; but the insights carry over more generally.
Sims initiated research in economics on “rational inattention.” To provide some context, much prior and, in fact, subsequent research starts with the study of signal extraction as a way to capture the limited information available to decision makers and the implied sequential learning. Typically, the signal structure is taken as a modeling input. Sims chose instead to use ideas from information theory to make the signal structure endogenous. A decision maker facing a potentially data-rich environment chooses where to “pay attention” in support of making prudent decisions. Sims’s research opened the door to a literature that has been subsequently pursued from a variety of angles by macroeconomists and applied theorists, with particular interest from decision theorists.
Remarkably, there has been and continues to be a substantial literature in macroeconomics that studies monetary policy while leaving fiscal policy in the background. Importantly, there have been some alternative approaches that assign a central place to the interaction between monetary and fiscal policy in the analysis of price determination and the resulting inflation. One important strand of literature that addresses the impact of this interaction is the fiscal theory of the price level. Sims was a prominent and early contributor to this literature. As one application, Sims used this theory to expose the potentially precarious foundations of the European Monetary Union. While the fiscal theory has yet to be fully embraced, it has very much become incorporated into important discussions of sources and consequences of inflation.
While Sims made fundamental contributions to a wide range of important research areas connected to macroeconomics and time series econometrics, his impact on research extends much beyond the papers he authored. He mentored and was a role model for a whole generation of scholars. Personally, I was fortunate to have a front-row seat to observe the development and emergence of some of Sims’s early path-breaking research. As a graduate student at the University of Minnesota in the mid-1970s, in addition to taking challenging but rewarding classes from Sims, I was his research assistant for his Fisher-Schultz Lecture paper. Sims became my dissertation adviserand since then, he has had a major influence on my research. Sims was seldom a “pat on the back” mentor. Instead, he challenged me to think harder and to probe questions more deeply and from different angles than I had considered. He was often one of my most severe critics. While I did not always fully embrace his feedback, I quickly learned not to ignore it either. On more than one occasion, I was provoked into rethinking important aspects of my research in ways that had long-term implications. While I mention my own experience, many other macroeconomists have had similar experiences and can attest to how much they benefited from their interaction with Sims.
Read Princeton University’s reflection on Christopher A. Sim’s passing here.