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Keywords:vector autoregressions 

Working Paper
Interpreting Shocks to the Relative Price of Investment with a Two-Sector Model

Consumption and investment comove over the business cycle in response to shocks that permanently move the price of investment. The interpretation of these shocks has relied on standard one-sector models or on models with two or more sectors that can be aggregated. However, the same interpretation continues to go through in models that cannot be aggregated into a standard one-sector model. Furthermore, such a two-sector model with distinct factor input shares across production sectors and commingling of sectoral outputs in the assembly of final consumption and investment goods, in line with ...
Finance and Economics Discussion Series , Paper 2016-7

Working Paper
Local Projections for Applied Economics

The dynamic causal effect of an intervention on an outcome is of paramount interest to applied macro- and micro-economics research. However, this question has been generally approached differently by the two literatures. In making the transition from traditional time series methods to applied microeconometrics, local projections can serve as a natural bridge. Local projections can translate the familiar language of vector autoregressions (VARs) and impulse responses into the language of potential outcomes and treatment effects. There are gains to be made by both literatures from greater ...
Working Paper Series , Paper 2023-16

Briefing
Monetary Policy across Space and Time

Many major macroeconomic events have occurred across multiple countries. This Economic Brief looks at similarities and differences among the euro area, the United Kingdom, and the United States and finds that macroeconomic variables tend to become more interconnected during periods of financial distress. Movements in monetary policy are highly correlated across all three regions. In addition, inflation and unemployment become less responsive to monetary policy shocks over time.
Richmond Fed Economic Brief , Issue August

Working Paper
Financial Nowcasts and Their Usefulness in Macroeconomic Forecasting

Financial data often contain information that is helpful for macroeconomic forecasting, while multistep forecast accuracy also benefits by incorporating good nowcasts of macroeconomic variables. This paper considers the role of nowcasts of financial variables in making conditional forecasts of real and nominal macroeconomic variables using standard quarterly Bayesian vector autoregressions (BVARs). For nowcasting the quarterly value of a variety of financial variables, we document that the average of the available daily data and a daily random walk forecast to fill in the missing days in the ...
Working Papers (Old Series) , Paper 1702

Working Paper
The Response of Stock Market Volatility to Futures-Based Measures of Monetary Policy Shocks

In this paper, we investigate the dynamic response of stock market volatility to changes in monetary policy. Using a vector autoregressive model, our findings reveal a significant and asymmetric response of stock returns and volatility to monetary policy shocks. Although the increase in the volatility risk premium, futures-trading volume, and leverage appear to contribute to a short-term increase in volatility, the longer-term dynamics of volatility are dominated by monetary policy's effect on fundamentals. The estimation results from a bivariate VAR-GARCH model suggest that the Fed does not ...
FRB Atlanta Working Paper , Paper 2014-14

Working Paper
Refining Set-Identification in VARs through Independence

Identification in VARs has traditionally mainly relied on second moments. Some researchers have considered using higher moments as well, but there are concerns about the strength of the identification obtained in this way. In this paper, we propose refining existing identification schemes by augmenting sign restrictions with a requirement that rules out shocks whose higher moments significantly depart from independence. This approach does not assume that higher moments help with identification; it is robust to weak identification. In simulations we show that it controls coverage well, in ...
Working Papers , Paper 21-31

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