Information and Inequality in the Time of a Pandemic
We introduce two types of agent heterogeneity in a calibrated epidemiological search model. First, some agents cannot afford to stay home to minimize virus exposure. Our results show that poor agents bear most of the epidemic’s health costs. Furthermore, we show that when a larger share of agents fail to change their behavior during the epidemic, a deeper recession is possible. Second, agents develop symptoms heterogeneously. We show that for diseases with a higher share of asymptomatic cases, even when less lethal, health and economic outcomes are worse. Public policies such as testing, ...
We study the conditional distribution of GDP growth as a function of economic and financial conditions. Deteriorating financial conditions are associated with an increase in the conditional volatility and a decline in the conditional mean of GDP growth, leading the lower quantiles of GDP growth to vary with financial conditions and the upper quantiles to be stable over time: Upside risks to GDP growth are low in most periods while downside risks increase as financial conditions become tighter. We argue that amplification mechanisms in the financial sector generate the observed growth ...
Deflationary shocks and monetary rules: an open-economy scenario analysis
The paper considers the macroeconomic transmission of demand and supply shocks in an open economy under alternative assumptions about whether the zero interest rate floor (ZIF) is binding. It uses a two-country general-equilibrium simulation model calibrated to the Japanese economy relative to the rest of the world. Negative demand shocks have more prolonged and conspicuous effects on the economy when the ZIF is binding than when it is not binding. Positive supply shocks can actually extend the period of time over which the ZIF may be expected to bind. Economies that are more open hit the ZIF ...
Rational bias in macroeconomic forecasts
This paper develops a model of macroeconomic forecasting in which the wages firms pay their forecasters are a function of their accuracy as well as the publicity they generate for their employers by being correct. In the resulting Nash equilibrium, forecasters with identical models, information, and incentives nevertheless produce a variety of predictions in order to maximize their expected wages. In the case of heterogeneous incentives, the forecasters whose wages are most closely tied to publicity, as opposed to accuracy, produce the forecasts that deviate most from the consensus. We find ...
Forecasting Macroeconomic Risks
We construct risks around consensus forecasts of real GDP growth, unemployment, and inflation. We find that risks are time-varying, asymmetric, and partly predictable. Tight financial conditions forecast downside growth risk, upside unemployment risk, and increased uncertainty around the inflation forecast. Growth vulnerability arises as the conditional mean and conditional variance of GDP growth are negatively correlated: downside risks are driven by lower mean and higher variance when financial conditions tighten. Similarly, employment vulnerability arises as the conditional mean and ...
Forecasting Foreign Economic Growth Using Cross-Country Data
We construct a monthly measure of foreign economic growth based on a wide range of cross-county indicators. Unlike GDP data, which are normally released with a delay of one to two quarters in most countries, our monthly measure incorporates monthly information up to the current month. As new information arrives, this measure of foreign growth can be updated as frequently as daily. This monthly measure of foreign growth not only helps gauge the economic conditions in other countries but also provides a timely measure of foreign demand to help forecast U.S. export growth.
Assessing Macroeconomic Tail Risk
What drives macroeconomic tail risk? To answer this question, we borrow a definition of macroeconomic risk from Adrian et al. (2019) by studying (left-tail) percentiles of the forecast distribution of GDP growth. We use local projections (Jord, 2005) to assess how this measure of risk moves in response to economic shocks to the level of technology, monetary policy, and financial conditions. Furthermore, by studying various percentiles jointly, we study how the overall economic outlook-as characterized by the entire forecast distribution of GDP growth-shifts in response to shocks. We find that ...
Evaluating the Conditionality of Judgmental Forecasts
We propose a framework to evaluate the conditionality of forecasts. The crux of our framework is the observation that a forecast is conditional if revisions to the conditioning factor are faithfully incorporated into the remainder of the forecast. We consider whether the Greenbook, Blue Chip, and the Survey of Professional Forecasters exhibit systematic biases in the manner in which they incorporate interest rate projections into the forecasts of other macroeconomic variables. We do not find strong evidence of systematic biases in the three economic forecasts that we consider, as the interest ...
The Power of Narratives in Economic Forecasts
We apply textual analysis tools to the narratives that accompany Federal Reserve Board economic forecasts to measure the degree of optimism versus pessimism expressed in those narratives. Text sentiment is strongly correlated with the accompanying economic point forecasts, positively for GDP forecasts and negatively for unemployment and inflation forecasts. Moreover, our sentiment measure predicts errors in FRB and private forecasts for GDP growth and unemployment up to four quarters out. Furthermore, stronger sentiment predicts tighter than expected monetary policy and higher future stock ...
A Unified Framework for Dimension Reduction in Forecasting
Factor models are widely used in summarizing large datasets with few underlying latent factors and in building time series forecasting models for economic variables. In these models, the reduction of the predictors and the modeling and forecasting of the response y are carried out in two separate and independent phases. We introduce a potentially more attractive alternative, Sufficient Dimension Reduction (SDR), that summarizes x as it relates to y, so that all the information in the conditional distribution of y|x is preserved. We study the relationship between SDR and popular estimation ...