It's All Relative! A Method to Counter Human Bias in Crowdsourced Stance Detection of News Articles (2022; with Ehsan-Ul Haq and Pan Hui)

(Proceedings of the ACM on Human-Computer Interaction, Vol 6, Issue CSCW2)


Using human intelligence to identify news articles' political stances is common in research and practical applications. But human judgement can be biased and prone to errors stemming from the comprehension of tasks and political alignment. This paper proposes a relative rating method based on news articles' stances relative to raters' own stances to avoid comprehension inconsistency and to control for human bias in crowdsourced stance detection of news articles. We also show how to use the relative ratings to construct a measure for raters' stances on a political topic and to identify raters whose ratings are of higher quality than others. We implement our proposed methods in an online experiment that recruits Amazon Mechanical Turk users as raters for news articles on Gun Control. Using the data from the experiment, we find evidence that raters' own stances on Gun Control significantly impact ratings of related news articles, both at the individual levels and at the aggregate levels. We also present evidence that our relative-rating-based stance measure captures more information about raters' actual stances than their self-reported stance does.


Credibility and Explicit Inflation Targeting (2022; with Robert G. King)

This article belongs to a collection of essays honoring Marvin Goodfriend.


In his 2004 inflation targeting manifesto, Marvin Goodfriend described US monetary policy as implicit inflation targeting and advocated explicit targeting. Summarizing the 1965-2000 US inflation experience, he highlighted the importance of evolving Fed credibility, which accords with our recent work using a quantitative New Keynesian model. We define credibility as policy consistency with a publicly announced framework and develop two lessons theoretically. First, under explicit targeting, no conflict arises between flexible inflation targeting and maintaining/accumulating credibility. Second, implicit targeting reduces the effectiveness of expectations management and stabilization policy, as well as opening the door to costly inflation scare episodes.


Creating Confusion (2021; with Chris Edmond) Online appendix

(Journal of Economic Theory, Vol 191, 105145)


We develop a model in which a politician seeks to prevent a group of citizens from making informed decisions. The politician can manipulate information at a cost. The citizens are rational and internalize the politician's incentives. In the unique equilibrium of the game, the citizens' beliefs are unbiased but endogenously noisy. We interpret the social media revolution as a shock that simultaneously (i) improves the underlying, intrinsic precision of the citizens' information, but also (ii) reduces the politician's costs of manipulation. We show that there is a critical threshold such that if the costs of manipulation fall enough, the social media revolution makes the citizens worse off despite the underlying improvement in their information.


Decentralization and Political Career Concerns (2017; with Jiahua Che and Kim-Sau Chung)

(Journal of Public Economics, Vol 145, 201-210)



Politicians¡¯ career paths often start at some subnational governments and end at the national one. Allocation of authorities among national and subnational governments affects (i) how tempting the prospects of taking national offices are, and hence how strong bureaucrats¡¯ political career concerns are, and (ii) whether the incentives generated by these political career concerns can be put into productive use at subnational governments. We illustrate this tradeoff in determining the optimal degree of decentralization using China as a case study. We also compare the equilibrium degree of decentralization in autocracy and in democracy.


Optimal Reputation Building in the New Keynesian Model (2016; First Author, with Robert G. King and Ernesto S. Pasten)

(Journal of Monetary Economics, Vol 84, 233-249)



We study the optimal committed monetary policy when the private sector has imperfect information and has to infer the central banker's ability to commit. The optimal policy is designed to influence learning and improve the central banker's reputation of being committed. The reputation building implies that when a committed central banker first takes office, he should resist the temptation to stimulate output with initially high but declining inflation; he should reverse a missed inflation target rather than accommodate it; and he should adopt a less accommodative inflation response to a cost-push shock than a full commitment solution suggests.


The Power of Whispers: A Theory of Rumor, Communication and Revolution (2016; with Heng Chen and Wing Suen)

(International Economic Review, Vol 57, Issue 1, 89-116)



We study how rumors mobilize individuals who take collective action. Rumors may or may not be informative, but they create public topics on which people can exchange their views. Individuals with diverse private information rationally evaluate the informativeness of rumors about regime strength. A rumor against the regime can coordinate a larger mass of attackers if individuals can discuss its veracity than if they cannot. Communication can be so effective that a rumor can have an even greater impact on mobilization than when the same story is fully believed by everybody. However, an extreme rumor can backfire and discourage mobilization.


Optimal Policy with Credibility Concerns (2013)

(Journal of Economic Theory, Vol 148, Issue 5, 2007-2032)


This paper considers a reputation model of optimal taxation in which the public is unsure about the government type. A long-lived government can be trustworthy (meaning that it commits to its announced tax rate) or opportunistic (meaning that it retains the ability to change its tax rate after announcing it). Unlike in most prior studies, the committed strategy in this model is optimally chosen by the trustworthy type. We show that this change has significant consequences for the equilibrium dynamics. The optimal committed strategy is found to vary with the time preferences of the two government types, the initial reputation of the government, and the elasticity of household production. This formulation explains differences in policy responses across governments in the face of similar credibility problems.


Modeling and Forecasting Stock Return Volatility Using a Random Level Shift Model (2009; with Pierre Perron)

(Journal of Empirical Finance, Vol. 17, Issue 1, 138-156)


We consider the estimation of a random level shift model for which the series of interest is the sum of a short memory process and a jump or level shift component. For the latter component, we specify the commonly used simple mixture model such that the component is the cumulative sum of a process which is 0 with some probability (1-¦Á) and is some random variable with probability ¦Á. Our estimation method transforms such a model into a linear state space form with mixture of normal innovations, so that an extension of Kalman filter algorithm can be applied. We estimate this random level shifts models for volatility series, proxied by the logarithm of the absolute returns. We do this for the S&P 500, AMEX, Dow Jones and the NASDAQ stock market return indices. Our point estimates imply few level shifts for all series. But once these are taken into account, there is little evidence of serial correlation in the remaining noise and, hence, no evidence of long memory. Once the estimated shifts are introduced to a standard GARCH model, any evidence of GARCH effects disappears. We also produce rolling out-of-sample forecasts. In most cases, our simple random level shift model clearly outperforms a standard GARCH(1,1) model and, in many cases, it also provides better forecasts than a fractionally integrated GARCH model.


Managing Expectations (working paper version, May, 2008; with Robert G. King and Ernesto S. Pasten)

(Journal of Money, Credit and Banking, Vol 40, Issue 8, 1625-1666)


The idea that monetary policy is principally about "managing expectations" has taken hold in central banks around the world.  Discussions of expectations management by central bankers, academics and by financial market participants frequently also include the idea that central bank credibility is imperfect. We adapt a familiar macroeconomic model so as to discuss key concepts in the area of expectations management. Our work also exemplifies a model construction approach to analyzing the dynamics of announcements, actions and credibility which we think makes feasible a wide range of future investigations concerning the management of expectations.


Working Papers

Evolving Reputation for Commitment: The Rise, Fall and Stabilization of US Inflation (Nov 2023, with Robert G. King)


We develop a computable recursive equilibrium for a dynamic game involving two types of purposeful policymakers -- one with commitment capacity and the other without -- and private agents who form expectations about future policies. Private agents are uncertain about policymaker type and their learning yields a time-varying reputation state. When applied to a New Keynesian setup with forward-looking inflation dynamics and a standard policy objective, our theory highlights the interplay between the reputation state and the differences in optimal policies of the two policymaker types. We provide a quantitative implementation of our theory via a nonlinear filter to show that active management of evolving reputation by committed policy is central to US inflation history.



The Signaling Effects of Sovereign Borrowing (Feb 2023, with Bowen Qu)


We provide novel empirical evidence suggestive of signaling effects of sovereign borrowing on a country's default risk. Using the S&P sovereign rating as a proxy for default risk, we find significant state-contingent effects of sovereign debt growth on a country's rating, with the state being the country's recent fiscal performance measured by its government operating balance. Conditional on a good fiscal state, higher sovereign debt growth significantly improves the sovereign rating, indicating a positive signaling effect of sovereign borrowing that more than compensates for its direct effect of increasing a country's debt burden. Conditional on a poor fiscal state, higher debt growth significantly reduces the sovereign rating, even after the lagged rating, current government operating balance, sovereign bond yield, and other common determinants of sovereign rating are controlled for, which suggests a negative signaling effect of sovereign borrowing. We also provide a two-period model to rationalize these findings.



Learning, Rare Disasters, and Asset Prices (Jan 2016; with Michael Siemer)


We incorporate joint learning about state and parameter into a consumption-based asset pricing model with rare disasters. Agents are uncertain whether a negative shock signals the onset of a disaster or how much long-term damage a disaster will cause and they update their beliefs over time. The interaction of state and parameter uncertainty increases the total amount of uncertainty and slows learning. Once the two types of uncertainty are both priced in asset prices, their joint effect enables our model to account for the level and volatility of U.S. equity returns without relying on exogenous variation in disaster risk or any realization of disaster shock in the data sample.



Coordinating Expectations and the Informational Role of Policy (under revision; with Ernesto S. Pasten)


Policy has leverage on the dynamics of self-fulfilling prophecies by distorting the informational content of aggregate history.



Discussion of ¡°Scarcity of Safe Assets, Inflation, and the Policy Trap¡± by Andolfatto and Williamson


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