Mikkel Plagborg-Møller, an econometrician and assistant professor of economics in Princeton’s Department of Economics, has been named a 2023 recipient of the prestigious Sloan Research Fellowship for early career researchers. 

Sloan Research Fellows are selected annually by the Alfred P. Sloan Foundation to represent the next generation of scientific leaders in the United States and Canada. Plagborg-Møller is one of six Princeton faculty to receive the fellowship this year. According to the Adam Falk, president of the Alfred P. Sloan Foundation, the 125 early career scholars chosen as 2023 Fellows are “shining examples of innovative and impactful research.” 

As an econometrician, Plagborg-Møller refines the methodologies economists and other social scientists use to conduct their analyses.

“Mikkel is well on his way to becoming the most influential time series econometrician of his generation,” said Mark Watson, the Howard Harrison and Gabrielle Snyder Beck Professor of Economics and Public Affairs. “In his short career he has already produced fundamental research on statistical inference for dynamic causal effects in macroeconomic applications and has equally important research projects underway.”

The ultimate goal is to influence applied work

In one major strand of work–published as a series of three papers to-date, including two in the journal Econometrica–Plagborg-Møller has provided researchers with new tools for comparing two popular methods of analyzing the effects of policy changes over time: Local Projections (LPs) and Structural Vector Autoregressions (SVARs). The SVAR method was first pioneered by Chris Sims, the John J. F. Sherrerd ’52 University Professor of Economics at Princeton and 2011 recipient of the Nobel Prize in Economic Sciences.

Looking at these two different methods, Plagborg-Møller says his aim is to give researchers “a rationality for choosing between them.”

“Even though these are very popular methods that are used all the time at central banks, other policy institutions, and in academia, it turns out there wasn’t much of a framework for comparing them,” he said. 

One reason these methods aren’t often compared, Plagborg-Møller said, is because they were initially promoted as categorically different methods that served different purposes. 

“What I’ve been trying to show, formally, is that when you have a large dataset, these methods estimate the same thing. One of the main contributions of my research is establishing that these methods can and should be compared with one another.” 

In another major strand of work, Plagborg-Møller aims to help economists studying the macroeconomy make better use of the explosion of rich microeconomic data sets that are increasingly available to researchers working across a wide range of fields. Take, for example, the topic of income inequality. Over the last decade, researchers have been increasingly interested in studying how income inequality affects macroeconomic outcomes like economic growth, or how macroeconomic factors affect different groups of people in different ways. Despite having a wealth of data that might help answer these questions, researchers often lack guidance on the most appropriate way to use that data. 

“This is an important topic in macro research, but econometric methods have been lagging behind a bit,“ Plagborg-Møller said. “One reason is because we’re combining different kinds of datasets in order to learn as much as possible about these policy questions.”

Plagborg-Møller’s research has focused on how to best combine these datasets to ultimately improve the study of policy.

“Forecasting the path of the economy and the effects of policy actions on the economy has become both more difficult and more important in the last decade or two,” said Princeton Professor Chris Sims. “Mikkel’s work is at the leading edge of current developments in this area. The Sloan award recognizes both the high quality of his work and its centrality to current policy problems.”

“The ultimate goal for me, and many other econometricians, is to influence applied work that will actually have policy consequences,” Plagborg-Møller said.

Encouraging interest in time-series econometrics

Originally from Denmark, Plagborg-Møller came to the United States in 2008 as an exchange student at New York University (NYU). It was at NYU that he first developed an interest in economic research.

After completing his undergraduate studies at the University of Copenhagen, Plagborg-Møller began a Ph.D. in economics at Harvard University, where he was inspired to study econometrics after taking a class on time series econometrics taught by James Stock, the Harold Hitchings Burbank Professor of Political Economy, Faculty of Arts and Sciences. Stock–who along with Princeton’s Mark Watson is a co-author of a popular undergraduate econometrics textbook–eventually served at Plagborg-Møller ’s graduate advisor. 

“I always tell students you should sign up to be a research assistant for faculty, and that will teach you something about what you like and don’t like, and help you see the research process from the inside out,” Plagborg-Møller said. “That’s what I did with Jim, and I realized time-series econometrics was a perfect match for me.”

In addition to new applied work, for example a paper that argues recessions are “fundamentally unforecastable” and that policy institutions should therefore be skeptical about models that claim to provide timely warnings about downside risks to GDP growth, Plagborg-Møller is working on a paper that he hopes will serve as a clearer guide on how to choose between the two most popular methods for estimating dynamic causal effects, LPs and SVARs.

In forthcoming work, he is applying these different methods across thousands of different hypothetical data sets to show researchers what works well, on average. He is also committed, as a teacher, to inspiring econometricians to focus on time-series questions.

“It’s my goal to make sure that bright students will choose to be time series econometricians. Many of the most important questions in macroeconomics require the use of time series data. If we end up with a purely central bank focused field, if we completely cut out the use of our tools in academia, the field will become too insular and it won’t benefit anyone,” he said. 

“There’s recently been a resurgence of interest in time series methods for estimating dynamic cause and effect, and that’s something I’m very excited about. I hope it will generate interest among our graduate students, as well.” 

Candidates for the Sloan Fellowship are nominated by fellow scientists, and the winners are chosen by an independent panel. Including this year’s winners, 243 Princeton faculty members have received the fellowship since its inception in 1955. Recent winners from Princeton’s Economics Department include Professor of Economics and Public Affairs Owen Zidar, an expert in taxation and public finance who received the fellowship in 2020, and Professor of Economics Michal Kolesár, an econometrician who received the fellowship in 2019.