Abstract. This study proposes a novel approach to interpreting conventional tests of the Full Information Rational Expectations (FIRE) hypothesis, based on the distinctions between forecasts and expectations. First, I argue that these two objects coincide under highly restrictive conditions that are unrealistic in the context of professional forecasting. Evidence from reduced-form analysis suggests that forecasters pursue strategic incentives when responding to surveys, contaminating their responses and making their use as measures of expectations misleading. Second, I leverage this distinction to introduce a new parsimonious model of forecast formation that is related to rational inattention and sparsity-based models of bounded rationality, but that is exempt from their complications, including the dependence on Gaussian information. The proposed framework employs a global game structure featuring public and private information, as well as the strategic behavior of forecasters, and demonstrates that strategy can explain the anomalies in Coibion and Gorodnichenko (2015)-type regressions. Finally, I exploit the model's transparency to develop and apply a formal test that validates the strategic channel, advising caution in using surveys to elicit expectations.

[Draft coming soon] Abstract. This study examines the impact of interest rate disagreements between the Federal Reserve, markets, and professional forecasters on the transmission of monetary policy. Contrary to conventional wisdom, I demonstrate that market expectations reflected in tradeable asset prices generally outperform the Fed’s internal forecasts, with minor variation over different time horizons. Empirical analysis employing Lag-Augmented Local Projections and Proxy SVARs demonstrates that disagreement weakens monetary policy action, offering an economic rationale for apparent anomalies like the “activity puzzle.” A structural model incorporating endogenous disagreement provides a microfoundation for its empirical relevance, establishing the presence of a credibility channel shaping belief formation and market responses.

[Draft coming soon] – Abstract. This paper studies Donald Trump's presidential victory in 2016  to identify a large shock to the expectations about the future path of defense spending, which hits US regions differently. It then uses this heterogeneity to investigate the effects on a series of measures of real activity. We construct defense news shocks for defense contractors using a high-frequency identification approach. Specifically, we isolate exogenous variation in the excess returns of stock prices for defense contractors around the 9/11 incident and the election of Donald Trump. We find positive and significant responses of excess returns around both events (first stage). We use this variation to study the effect of defense news shocks on (i) employment and investment of defense contractors and (ii) employment and consumption in MSAs.

[Draft coming soon] – Abstract. We explore two major surveys of macroeconomic forecasts to highlight new patterns of heterogeneity in the cross-section of forecasting performance. We identify a range of new stylized features of forecast accuracy that, we show, are robust across horizons, variables, and surveys. We show that these properties cannot be accommodated by existing models of noisy or sticky information, and develop a parsimonious heterogeneous-agent hybrid model that nests both frameworks while offsetting the limitations inherent in each. When we take this novel, tractable model to the data, we demonstrate that it better fits the patterns of heterogeneity that emerged empirically. 

[Draft coming soon] – Abstract. What portion of the movements in real estate prices cannot be rationalized by the most commonly imputed economic factors? How much should we care about the "animal spirits'', intended as fluctuations in agents' beliefs, when studying the origination of financial crises? The goal of this paper is to assess the role of confidence in understanding the boom-bust dynamics of credit and house prices in the United States, with a focus on the Great Financial Crisis. We identify confidence shocks in a structural VAR as exogenous innovations to the University of Michigan Sentiment Index. A positive shock to confidence increases significantly and prolongedly house prices, and accounts for almost 30% of their variance after 12 months, remaining significant after five years. We embed confidence shocks in a DSGE model with households’ heterogeneity and financial frictions. Confidence shocks are modeled as exogenous shifts in beliefs that are unrelated to current and future economic fundamentals, and that can generate waves of optimism or pessimism about current economic activity. Results from a Bayesian estimation of the model show that innovations to confidence account for half of the volatility of observed house prices. Our estimated confidence series shows a strong positive correlation with the Sentiment Index, suggesting that belief fluctuations in the model resemble empirical measures of confidence.

[Draft coming soon] – Abstract. Economic models with input-output networks assume that firm or sector growth is driven by a combination of trade partners’ growth and idiosyncratic shocks. This assumption generates unrealistic restrictions on network weights. Allowing for correlated shocks exposes units to additional risk that captures their ability to substitute away from supply and demand shocks. We provide evidence that substitutability between trade partners is related to technological and product dispersion that is not captured by standard firm and industry definitions. We propose a production-based asset pricing model in which supply chain substitutability depends on product/technology dispersion and shock correlation driven by shared suppliers and customers. The model predicts that assets positively exposed to upstream and downstream shocks are useful hedges and earn lower average risk premia than less exposed peers. This is confirmed by estimated return spreads of -11.4% and -4.2% and a negative association with aggregate growth.  

Abstract. In regressions à la Coibion-Gorodnichenko, the distinction between the consensus and individual level of analysis is first-order: while at the consensus level the empirical results are straightforward to interpret due to the theoretical guidance offered by models of information rigidities, as sticky or noisy information, at the individual level we lack such mapping from the data moments to their structural counterparts. This paper advances a more general, unified framework to interpret individual coefficients without resorting to ad-hoc behavioral or non-rational explanations.

[Draft coming soon] 

Abstract. In this note, I identify and address an issue affecting part of the results in Bauer & Swanson (2023a), published in the NBER Macroeconomics Annuals. I illustrate that the results for the effects of the orthogonalized monetary policy surprises do not align with those reported in the study's figures. Upon investigating, I find this is due to an incorrect procedure in the manipulation of the data; specifically, the authors first aggregate the FOMC-level monetary policy surprises – after demonstrating their problematic predictability – and then orthogonalize the newly obtained monthly series with respect to the first observation of the six "news" variables at the origin of the predictability. This procedure implies a violation of the exogeneity restriction of instrumental variables similar to the one at the foundation of the study, as the performed orthogonalization (i) conflates distinct event-level shocks, and (ii) regresses them only on a subset of the available information. The correct procedure orthogonalizes the FOMC-level monetary policy surprises on the contemporaneous observations of the news variables first – ensuring an effective "purge" of the documented predictability – and then aggregates the resulting orthogonal series to monthly frequency, in the same fashion as the authors do for the non-orthogonalized series. However, implementing this procedure causes the results in the paper to fail to replicate due to a (theory-consistent) reduction in the instrumental power of the surprise series. The correctly purged monetary policy surprises show no recognizable effects on any of the macroeconomic variables under analysis, casting doubt either on the usefulness of the measure or, if taken seriously, on monetary non-neutrality.