Shihan Xie 谢诗涵

Central Bank Communication with the Polarized Public, with Pei Kuang and Michael Weber

Featured in: Financial Times, VoxEU, BFI Research Briefs, Central Banking

Abstract: This paper examines the impact of political polarization on public trust in the Fed and its influence on macroeconomic expectations. Using a large-scale survey experiment which we fielded on President Trump's 2025 inauguration day, we study how households form beliefs about the Fed regarding its political leaning, independence, and trustworthiness. Political alignment significantly shapes perceptions: individuals who view the Fed as politically aligned report higher independence of and trust in the Fed, leading to lower inflation expectations and uncertainty. Strategic communication on institutional structure and policy objectives effectively mitigates perception biases, reinforcing the Fed's credibility and enhancing its policy effectiveness. 

Perceived Political Bias of the Federal Reserve, with Pei Kuang and Michael Weber

Featured in: Bloomberg, Brookings, Central Banking, CFO Dive, BFI Research Briefs

Abstract: We conduct a survey experiment with a large, politically representative sample of U.S. consumers to study how perceptions of the U.S. Federal Reserve’s (Fed) political stance shape macroeconomic expectations and trust in the Fed. The public is divided on the Fed's political leaning: most Republican-leaning consumers believe the Fed favors Democrats, whereas most Democrat-leaning consumers perceive the Fed as favoring Republicans. Consumers who perceive the Fed as aligned with their political affiliations tend to (1) have a more positive outlook on current and future economic conditions and express higher trust in the institution, (2) show greater willingness to pay for and are more likely to receive Fed communications, and (3) assign significantly more weight to Fed communications when updating their inflation expectations. Strong in-group favoritism generally amplifies these effects. Finally, if Trump were elected U.S. president, consumers would overwhelmingly view the Fed as favoring Republicans. 

Overconfidence in Private Information Explains Biases in Professional Forecasts, with Klaus Adam and Pei Kuang 

Abstract: We observe a rich set of public information signals available to participants in the Survey of Professional Forecasters (SPF) and decompose individual forecast revisions into those due to public information and a remainder due to residual information. We find that SPF forecasters overreact to residual information at almost all forecast horizons and for almost all forecast variables. In addition, forecasts are overly anchored to prior beliefs for all variables at all forecast horizons. We show analytically that overconfidence in private information qualitatively generates both of these features. It also implies that forecast errors correlate positively with past forecast revisions at the consensus level, but negatively at the individual level, as documented previously in the literature. Estimating Bayesian updating models on SPF data, we show that overconfidence in private information also replicates the observed patterns quantitatively. All estimated models display strong and statistically significant overconfidence in private information.

Extreme Weather and Low-Income Household Finance: Evidence from Payday Loans, with Victoria Wenxin Xie and Xu Zhang

Featured in: the Guardian, Politico Pro, ABC7

Abstract: This paper explores the impact of extreme weather exposures on the financial outcomes of low-income households. Using a novel dataset comprising individual-level payday loan applications and loan-level information,  we find that both extreme heat and cold days lead to surges in payday loan demand. Extra extreme heat days result in an increase in delinquency and default rates and a reduction of total credit issued, indicating a contraction in loan supply. The effects are especially noticeable for online payday loans. Our findings highlight the heightened financial vulnerability of low-income households to environmental shocks and underscore the need for targeted policies.

Stock-driven Household Attention, with Hie Joo Ahn

Abstract: We investigate the effects of stockholding on households' attention to the macroeconomy. Households' attentiveness is measured by their accuracy of inflation expectations and perceptions. Relative to non-stockholders, stockholders produce more accurate inflation forecasts and backcasts, disagree less about future inflation, and adjust their outlook more responsively to news, suggesting that stock-market participation raises households' attention. Frequent changes in stock prices incentivize stockholders to closely monitor financial markets for optimal trading, given the low cost of acquiring information. Consequently, paying attention to the macroeconomy helps hedge the risks associated with holding stocks. Therefore, attention heterogeneity driven by stockholdings can be a channel through which the distributional consequences of monetary policy are created.

Macroprudential Policy and Housing Market Expectations, with Pei Kuang, Kaushik Mitra, and Li Tang

Abstract: Using a large-scale online survey experiment, we study the effects of changes in three borrower-based macroprudential policies: residential loan-to-value (LTV), debt-to-income, and buy-to-let LTV ratio, on British consumers' housing market expectations. Policy tightenings lead to lower house price expectations, more negative sentiments about housing transactions, and worsened affordability evaluations; policy loosenings cause opposite effects. The residential LTV ratio is the most effective tool. Changes in residential LTV ratio have larger impacts on house price expectations in "hot" markets. This finding is reconciled in a model featuring a feedback loop between house prices, credit, and price expectations.  

Navigating Fiscal Fog: Household Expectations in an Uncertain Fiscal Environment, with Junjie Guo, Li Tang, and Penghui Yin

Abstract: Using a novel survey of U.S. households, we study how fiscal policy uncertainty affects household macroeconomic expectations and consumption-saving decisions. We employ randomized information treatments to induce exogenous changes in perceived fiscal policy uncertainty. The results show that fiscal uncertainty dampens the crowding-out effect on household spending by lowering expectations of interest rates. Additionally, the findings support Ricardian equivalence, as households anticipating higher fiscal spending growth expect increased future taxes. Employing a quantitative model calibrated with survey data, we show that fiscal uncertainty significantly reduces the government spending multiplier, primarily by dampening investment responses. These insights highlight the importance of effective fiscal policy communication in uncertain environments. 

Effects of Monetary Policy on Household Expectations: The Role of Homeownership, with Hie Joo Ahn and Choongryul Yang. Journal of Monetary Economics, October 2024, Vol. 147, 103599. 

Featured in: Brookings, Interview with Faculti

Abstract: We study the role of homeownership in the effectiveness of monetary policy on households' expectations based on individual-level microdata in the U.S. We find that homeowners lower their near-term inflation expectations and optimism about the labor market outlook in response to a rise in mortgage rates, while renters are less likely to do so. We further show that forward guidance shocks lead to similar differences between homeowners and renters. Our results suggest that homeowners pay attention to news on interest rates and adjust their expectations accordingly in a manner consistent with the intended effect of monetary policy. We characterize this empirical finding with a rational inattention model where mortgage payments create an incentive for homeowners to acquire information on monetary policy, unlike renters. This housing-driven endogenous attentiveness is the key mechanism behind the compelling empirical link among homeownership, attention, and the transmission of monetary policy.

An Estimated Model of Household Inflation Expectations: Information Frictions and Implications. Review of Economics and Statistics, forthcoming

Abstract: This paper proposes and estimates a dynamic model of household inflation expectations with information frictions and time-varying parameters, where households use a Bayesian learning model to form and update inflation expectations. The model decomposes households' inflation expectation formation process into a learning component, a noisy signal component, and a measurement component. Model-implied household inflation expectations provide a robust fit for the expectation-augmented Phillips curve. As a result of time-varying inflation dynamics, households' attention to inflation is endogenous to its volatility. This insight offers explanations for the anchoring of inflation expectations during the Great Moderation.

Monetary Policy Shocks and Local Housing Prices. Accepted at International Journal of Central Banking

Abstract: This paper studies the channels by which monetary policy shocks affect local housing prices. It first documents there is a sluggish response of housing prices, suggesting that informational frictions may be potentially important. It then develops a structural model of housing prices with information frictions, and exploits variations in housing prices across metropolitan statistical areas to estimate it. The important finding is that although households are well-informed about local demand, they are ill-informed about how monetary policy affects the local housing market. A counterfactual experiment using the estimated model implies that deviations from the Taylor rule in the early 2000s contributed to about two-fifths of the subsequent housing boom.