Papers

January 2021 | Article

Newly published paper in Proceedings of the National Academy of Sciences (PNAS) – “Rational Policymaking During a Pandemic”

Loïc Berger, Nicolas Berger, Valentina Bosetti, Itzhak Gilboa, Lars Peter Hansen, Christopher Jarvis, Massimo Marinacci, Richard D. Smith

Abstract:

Policymaking during a pandemic can be extremely challenging. As COVID-19 is a new disease and its global impacts are unprecedented, decisions need to be made in a highly uncertain, complex and rapidly changing environment. In such a context, in which human lives and the economy are at stake, we argue that using ideas and constructs from modern decision theory, even informally, will make policymaking more a responsible and transparent process.

 

Journal: PNAS|Tags: Uncertainty, Uncertainty and Valuation|Export BibTeX >
@article{berger2021rational,
  title={Rational policymaking during a pandemic},
  author={Berger, Lo{\"\i}c and Berger, Nicolas and Bosetti, Valentina and Gilboa, Itzhak and Hansen, Lars Peter and Jarvis, Christopher and Marinacci, Massimo and Smith, Richard D},
  journal={Proceedings of the National Academy of Sciences},
  volume={118},
  number={4},
  year={2021},
  publisher={National Acad Sciences}
}
December 2020 | Article

Recently published paper in Proceedings of the National Academy of Sciences (PNAS) – “Robust Identification of Investor Beliefs”

Xiaohong Chen, Lars Peter Hansen and Peter G. Hansen

This paper develops a new method informed by data and models to recover information about investor beliefs. Our approach uses information embedded in forward-looking asset prices in conjunction with asset pricing models. We step back from presuming rational expectations and entertain potential belief distortions bounded by a statistical measure of discrepancy. Additionally, our method allows for the direct use of sparse survey evidence to make these bounds more informative. Within our framework, market-implied beliefs may differ from those implied by rational expectations due to behavioral/psychological biases of investors, ambiguity aversion, or omitted permanent components to valuation. Formally, we represent evidence about investor beliefs using a novel nonlinear expectation function deduced using model-implied moment conditions and bounds on statistical divergence. We illustrate our method with a prototypical example from macro-finance using asset market data to infer belief restrictions for macroeconomic growth rates.

Paper

Associated Jupyter Code 

Journal: PNAS|Tags: Uncertainty|Export BibTeX >
@article{chen2020robust,
  title={Robust identification of investor beliefs},
  author={Chen, Xiaohong and Hansen, Lars Peter and Hansen, Peter G},
  journal={Proceedings of the National Academy of Sciences},
  volume={117},
  number={52},
  pages={33130--33140},
  year={2020},
  publisher={National Acad Sciences}
}
December 2020 | Article

Repercussions of Pandemics on Markets and Policy

Lars Peter Hansen

Abstract:

The COVID-19 pandemic that we are experiencing is both tragic and shocking. There is no question that, except in some Asian countries trained by prior infectious outbreaks, most policy makers around the world have been ill-prepared to respond to the crisis. The effects of the coronavirus on our mental and physical health has been indeed calamitous, and the economic and financial impacts for many have been truly unfortunate. Furthermore, the extreme nature of the event is challenging researchers to compile and interpret new evidence that is arriving at a rapid pace. The editors Hui Chen, Thierry Foucault, Jeffrey Pontiff, and Nikolai Roussanov and contributing authors are to be commended for assembling and collating a thought-provoking collection of papers. More time and study will be needed to fully sift through the evidence and to glean the lessons to be learned from this pandemic for policy makers and investors. But the evidence and insights in this volume are a very good start.

All papers of this volume are posted online on the Oxford University Press website.

Journal: The Review of Asset Pricing Studies|Publisher: Published Online by Oxford University Press|Tags: Uncertainty|Export BibTeX >
@article{peter2020repercussions,
  title={Repercussions of Pandemics on Markets and Policy},
  author={Peter Hansen, Lars},
  journal={The Review of Asset Pricing Studies},
  volume={10},
  number={4},
  pages={569--573},
  year={2020},
  publisher={Oxford University Press}
}
April 2020 | White Paper

Using Quantitative Models to Guide Policy Amid COVID-19 Uncertainty

Lars Peter Hansen

Abstract: 

Policymakers look to forecasts or projections about the future evolution of contagion and subsequent fatalities to guide their policy choices. These can be best guesses or warnings about how bad things could become. These considerations factor into their decision making in at least informal ways. Epidemiologists no doubt have important insights that we all look to digest. Economists and other social scientists are quick to consider ways by which they can draw upon their current stock of knowledge to incorporate endogenous responses of individuals and businesses to various policy alternatives. Quantitative predictions of disease transmission under alternative policies and the resulting social behaviors, however, bring special challenges. The reason is that models require specific assumptions and ingredients that govern the dynamic evolution and consequences of alternative forms of social and economic interactions. Subjective judgements are unavoidable. There are unknown parameters to calibrate in the face of limited data. These challenges are pervasive in quantitative modeling that aims to support policy. The unique challenges of the COVID-19 global situation are what draws our attention as we witness and participate in this harrowing episode.

Originally published by the Becker Friedman Institute in April 2020

Export BibTeX >
@article{hansen2020using,
  title={Using quantitative models to guide policy amid COVID-19 uncertainty},
  author={Hansen, Lars Peter},
  journal={White Paper, Becker Friedman Institute, Chicago},
  year={2020}
}
February 2020 | Article

New published paper and Python Code Posted – “Pricing Uncertainty Induced by Climate Change”

Michael Barnett, William Brock, and Lars Peter Hansen

Geophysicists examine and document the repercussions for the earth’s climate induced by alternative emission scenarios and model specifications. Using simplified approximations, they produce tractable characterizations of the associated uncertainty. Meanwhile, economists write simplified damage functions to assess uncertain feedbacks from climate change back to the economic opportunities for the macroeconomy. How can we assess both climate and emissions impacts, as well as uncertainty in the broadest sense, in social decision-making? We provide a framework for answering this question by embracing recent decision theory and tools from asset pricing, and we apply this structure with its interacting components in a revealing quantitative illustration.

Online Appendix 

Associated Results and Python Scripts – GitHub

Journal: The Review of Financial Studies |Volume: 33|Issue Number: 3|Pages: 1024-1066|Publisher: Oxford University Press|Tags: Climate, Risk, Robustness and Ambiguity, Uncertainty and Valuation|Export BibTeX >

@article{BarnettBrockHansen:2020,

Author = {Michael Barnett and William Brock and Lars Peter Hansen},

Date-Added = {2019-11-08 10:47:02 -0600},

Date-Modified = {2019-11-08 10:49:54 -0600},

Journal = {Review of Financial Studies},

Title = {Pricing Uncertainty Induced by Climate Change},

Year = {March 2020, The Review of Financial Studies}}

February 2020 | Article

Newly Published Paper: “Twisted Probabilities, Uncertainty and Prices”

Lars Peter Hansen, Thomas J. Sargent, Balint Szoke and Lloyd S. Han

A decision maker constructs a convex set of nonnegative martingales to use as likeli-hood ratios that represent alternatives that are statistically close to a decision maker’s baseline model. The set is twisted to include some specific models of interest. Max-min expected utility over that set gives rise to equilibrium prices of model uncertainty expressed as worst-case distortions to drifts in a representative investor’s baseline model. Three quantitative illustrations start with baseline models having exogenous long-run risks in technology shocks. These put endogenous long-run risks into con-sumption dynamics that differ in details that depend on how shocks affect returns to capital stocks. We describe sets of alternatives to a baseline model that generate countercyclical prices of uncertainty.

Keywords— Risk, uncertainty, relative entropy, robustness, asset prices, exponential quadratic stochastic discount factor

JEL Classification— C52, C58, D81, D84, G12

Paper

Associated Paper Results and Code

Journal: Journal of Econometrics|Volume: 216|Issue Number: 1|Publisher: Elsevier|Tags: Financial Market Linkages to the Macroeconomy, Risk, Robustness and Ambiguity, Uncertainty and Valuation|Export BibTeX >
@article{hansen2020twisted,
  title={Twisted probabilities, uncertainty, and prices},
  author={Hansen, Lars Peter and Sz{\H{o}}ke, B{\'a}lint and Han, Lloyd S and Sargent, Thomas J},
  journal={Journal of Econometrics},
  volume={216},
  number={1},
  pages={151--174},
  year={2020},
  publisher={Elsevier}
}
October 2018

Wrestling with Uncertainty in Climate Economic Models

Lars Peter Hansen and William Brock

As we all know, the human and economic impact on the climate has been a topic that has recently received substantial attention.

While there is considerable evidence documenting impacts of climate change, a full understanding of the magnitude and the timing of this impact remains uncertain.  Moreover, we still seek to comprehend  better the economic consequences of climate change. The construction of quantitative models that connect economics and climate impacts currently confront uncertainty in simplistic ways.  They serve as valuable illustrations, but there is much to be done in terms of developing models that are fully fledged quantitative tools for policy assessment.

Our aim is to take inventory on some of the challenges for building better models, models that can provide a more rigorous defense for say measurements of the social cost of carbon while recognizing that there are limits to our understanding of climate economic linkages.  We will not provide precise answers but instead suggest a productive quantitative modeling agenda going forward.

This paper uses insights from decision theory under uncertainty to explore research challenges in climate economics. We embrace a broad perspective of uncertainty with three components: risk (probabilities assigned by a given model), ambiguity (level of confidence in alternative models), and misspecification (potential shortfalls in existing models). We survey recent climate science research that exposes the uncertainty in climate dynamics that is pertinent in economic analyses and relevant for using models to provide policy guidance. The uncertainty components and their implications for decision theory help us frame this evidence and expose the modeling and evidential challenges.

Title of book: forthcoming in Climate Change Economics: The Role of Uncertainty and Risk|Editor(s): V.V. Chari and Robert Litterman|Tags: Climate, Uncertainty|Export BibTeX >

@article{brockhansen:2017wrestling,
title={Wrestling with Uncertainty in Climate Economic Models},
author={Brock, W.A. and Hansen, L. P.},
journal={SSRN Working Paper},
year={2018}
}

August 2018 | Article

Aversion to Ambiguity and Model Misspecification in Dynamic Stochastic Environments

Lars Peter Hansen and Jianjun Miao

In many dynamic economic settings, a decision maker finds it challenging to quantify the uncertainty or to assess the potential for mistakes in models. We explore alternative ways of acknowledging these challenges by drawing on insights from decision theory as conceptualized and implemented in statistics, engineering, and economics. Building on prior research, we suggest tractable and revealing ways to incorporate behavioral responses to uncertainty, broadly conceived. Our analysis adopts recursive intertemporal preferences for decision makers that allow them to be ambiguity averse and concerned about the potential misspecification of subjective uncertainty. By design, these representations have revealing implications for continuous-time environments with Brownian information structures.   Problems where uncertainty’s structure is obscure such as macroeconomics, finance and climate change are promising areas for application of these tools.

 

Supplemental Index

Journal: Proceedings of the National Academy of Sciences of the United States of America |Publisher: PNAS|Tags: Risk, Robustness and Ambiguity|Export BibTeX >

@article{hansen:2018aversion,
title={Aversion to Ambiguity and Model Misspecification in Dynamic Stochastic Environments},
author={Hansen, L. P. and Miao, J.},
journal={Proceedings of the National Academy of Sciences},
volume={115},
number={37},
pages={9163–9168},
year={2018},
publisher={National Academy of Sciences}
}

December 2017

Time Series Econometrics in Macroeconomics and Finance

Lars Peter Hansen

Ninety years ago, Slutsky (1927) and Yule (1927) opened the door to the use of probability models in the analysis of economic time series. Their vision was to view economic time series as linear responses to current and past independent and identically distributed impulses or shocks. In distinct contributions, they showed how to generate approximate cycles with such models. Each had a unique background and perspective. Yule was an eminent statistician who, in the words of Stigler (1986), among his many contributions, managed effectively to invent modern time series analysis.” Yule constructed and estimated what we call a second-order model and applied it to study the time series behavior of sunspots. Slutsky wrote his paper in Russia in the 1920s motivated by the study of business cycles. Much later, his paper was published in Econometrica, but it was already on the radar screen of economists, such as Frisch. Indeed Frisch was keenly aware of both Slutsky (1927) and Yule (1927) and acknowledged both in his seminal paper Frisch (1933) on the impulse and propagation problem. Building on insights from Slutsky and Yule, Frisch pioneered the use of impulse response functions in economic dynamics. His ambition was to provide explicit economic interpretations for how current period shocks alter economic time series in current and future time periods. The Journal of Political Economy (JPE) provided an important platform for research that confronts Frisch’s ambition in substantively interesting ways. Read full paper here.

Journal: “The Past, Present, and Future of Economics: A Celebration of the 125 Year Anniversary of the JPE and of Chicago Economics,” Journal of Political Economy 125|Publisher: University of Chicago Press |Tags: Econometrics|Export BibTeX >

@article{hansen:2017time,
title={Time-Series Econometrics in Macroeconomics and Finance},
author={Hansen, L. P.},
journal={Journal of Political Economy},
volume={125},
number={6},
pages={1774–1782},
year={2017},
publisher={University of Chicago Press Chicago, IL}
}

June 2017

Uncertainty in Economic Analysis and the Economic Analysis of Uncertainty

Lars Peter Hansen

This essay was written for the inaugural issue of a journal Called KNOW, published in conjunction with the Stevanovich Institute for the Formation of Knowledge. I explore why addressing uncertainty in our knowledge is especially important in economic analyses when we seek a better understanding of markets, economic outcomes, and the impact of alternative policies. I also provide some historical context to the formalization of the alternative components to uncertainty and their impact in economic analyses. It has been important in economic scholarship to take inventory, not only of what we know, but also of the gaps in this knowledge. Thus, part of economic research assesses what we know about what we do not know and how we confront what we do not know. Not only does uncertainty matter for how economic researchers interpret and use evidence, but also for how consumers and enterprises we incorporate in models confront the future.

Journal: KNOW |Volume: 1|Issue Number: 1|Publisher: University of Chicago Press |Tags: Uncertainty and Valuation|Export BibTeX >

@article{hansen:2017uncertainty,
title={Uncertainty in Economic Analysis and the Economic Analysis of Uncertainty},
author={Hansen, L. P.},
journal={KNOW: A Journal on the Formation of Knowledge},
volume={1},
number={1},
pages={171–197},
year={2017},
publisher={University of Chicago Press}
}