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Jel Classification:E17 

Working Paper
Price dispersion and inflation: new facts and theoretical implications

From a macroeconomic perspective, price rigidity is often perceived to be an important source of price dispersion, with significant implications for the dynamic properties of aggregate variables, welfare calculations, and the design of optimal policy. For instance, in standard New Keynesian models, the key cost of business cycles stems from the price dispersion resulting from firms' inability to adjust prices instantaneously. However, different macroeconomic models make conflicting predictions about the level of price dispersion, as well as about its dynamic properties and sensitivity to ...
Working Papers , Paper 15-10

Working Paper
Theory and practice of GVAR modeling

The Global Vector Autoregressive (GVAR) approach has proven to be a very useful approach to analyze interactions in the global macroeconomy and other data networks where both the cross-section and the time dimensions are large. This paper surveys the latest developments in the GVAR modeling, examining both the theoretical foundations of the approach and its numerous empirical applications. We provide a synthesis of existing literature and highlight areas for future research.
Globalization Institute Working Papers , Paper 180

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 ...
Staff Reports , Paper 267

Journal Article
The role of expectations in the FRB/US macroeconomic model

In the past year, the staff of the Board of Governors of the Federal Reserve System began using a new macroeconomic model of the U.S. economy referred to as the FRB/US model. This system of mathematical equations, describing interactions among economic measures such as inflation, interest rates, and gross domestic product, is one of the tools used in economic forecasting and the analysis of macroeconomic policy issues at the Board. The FRB/US model replaces the MPS model, which, with periodic revisions, had been used at the Federal Reserve Board since the early 1970s. A key feature of the new ...
Federal Reserve Bulletin , Volume 83 , Issue Apr

How Tight is U.S. Monetary Policy

In this Chicago Fed Letter, we use a quantitative macroeconomic model to tackle the question of whether the response of the Federal Reserve (the Fed) to recent high inflation is consistent with its historical behavior. This is an important question because systematic deviations from past behavior could lead the private sector to revise its expectations about how the Fed will respond to inflation going forward, which, according to macroeconomic theory, could affect its ability to stabilize inflation in the future.
Chicago Fed Letter , Volume No 476

Working Paper
Addressing COVID-19 Outliers in BVARs with Stochastic Volatility

The COVID-19 pandemic has led to enormous movements in economic data that strongly affect parameters and forecasts obtained from standard VARs. One way to address these issues is to model extreme observations as random shifts in the stochastic volatility (SV) of VAR residuals. Specifically, we propose VAR models with outlier-augmented SV that combine transitory and persistent changes in volatility. The resulting density forecasts for the COVID-19 period are much less sensitive to outliers in the data than standard VARs. Evaluating forecast performance over the last few decades, we find that ...
Working Papers , Paper 21-02R

Working Paper
The Accuracy of Forecasts Prepared for the Federal Open Market Committee

We analyze forecasts of consumption, nonresidential investment, residential investment, government spending, exports, imports, inventories, gross domestic product, inflation, and unemployment prepared by the staff of the Board of Governors of the Federal Reserve System for meetings of the Federal Open Market Committee from 1997 to 2008, called the Greenbooks. We compare the root mean squared error, mean absolute error, and the proportion of directional errors of Greenbook forecasts of these macroeconomic indicators to the errors from three forecasting benchmarks: a random walk, a first-order ...
Finance and Economics Discussion Series , Paper 2015-62

Working Paper
Nowcasting Tail Risks to Economic Activity with Many Indicators

This paper focuses on nowcasts of tail risk to GDP growth, with a potentially wide array of monthly and weekly information. We consider different models (Bayesian mixed frequency regressions with stochastic volatility, classical and Bayesian quantile regressions, quantile MIDAS regressions) and also different methods for data reduction (either forecasts from models that incorporate data reduction or the combination of forecasts from smaller models). Our results show that, within some limits, more information helps the accuracy of nowcasts of tail risk to GDP growth. Accuracy typically ...
Working Papers , Paper 20-13R

Working Paper
Have Standard VARs Remained Stable since the Crisis?

Small or medium-scale VARs are commonly used in applied macroeconomics for forecasting and evaluating the shock transmission mechanism. This requires the VAR parameters to be stable over the evaluation and forecast sample, or to explicitly consider parameter time variation. The earlier literature focused on whether there were sizable parameter changes in the early 1980s, in either the conditional mean or variance parameters, and in the subsequent period till the beginning of the new century. In this paper we conduct a similar analysis but focus on the effects of the recent crisis. Using a ...
Working Papers (Old Series) , Paper 1411

Working Paper
Financial Conditions and Economic Activity: Insights from Machine Learning

Machine learning (ML) techniques are used to construct a financial conditions index (FCI). The components of the ML-FCI are selected based on their ability to predict the unemployment rate one-year ahead. Three lessons for macroeconomics and variable selection/dimension reduction with large datasets emerge. First, variable transformations can drive results, emphasizing the need for transparency in selection of transformations and robustness to a range of reasonable choices. Second, there is strong evidence of nonlinearity in the relationship between financial variables and economic ...
Finance and Economics Discussion Series , Paper 2020-095


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