Abstract
SummaryStandard macroeconomic theory predicts rapid responses of asset prices to monetary policy shocks. Small‐scale vector autoregressions (VARs), however, often find sluggish and insignificant impact effects. Using the same high‐frequency instrument to identify monetary policy shocks, we show that a large‐scale dynamic factor model finds overall stronger and quicker asset price reactions compared to a benchmark VAR, both on euro area and US data. Our results suggest that incorporating a sufficiently large information set is crucial to estimate monetary policy effects.
Highlights
There are at least two reasons behind the economic profession’s renewed interest in the relationship between monetary policy and asset prices
In the Structural Factor Model (SFM), on the other hand, house prices drop on impact by about 1% and return to their previous level within 1-2 years
In the aftermath of the global financial crisis and the current low interest rate environment, it is of utmost importance to properly asses the relationship between monetary policy shocks and asset prices
Summary
There are at least two reasons behind the economic profession’s renewed interest in the relationship between monetary policy and asset prices. It becomes even more important to understand the relationship between monetary policy and asset prices, in order to assess the financial stability consequences of a monetary policy shock (Allen and Gale, 2004; Disyatat, 2010). The central bank monitors a very large set of indicators and sets the monetary policy stance based on this wide information set For both of these reasons, as we show, the empirical results will differ depending on whether the empirical model includes all of the relevant variables or not. This provides a theoretical motivation for the empirical investigations that follow.
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