We follow Belongia and Ireland (2021) and investigate the role that the Center for Financial Stability credit card-augmented Divisia monetary aggregates could play in monetary policy and business cycle analysis. We use Bayesian methods to estimate a structural VAR under priors that reflect Keynesian channels of monetary transmission, but produce posterior distributions for the structural parameters consistent with classical channels. We also find that valuable information is contained in the credit-augmented Divisia monetary aggregates and that they perform even better than the conventional Divisia aggregates, in terms of highlighting the role of the money supply in aggregate demand.

Can monetary policy stimulate consumption through inflation expectations? We study how US consumers revise inflation expectations and readiness to spend in response to monetary policy shocks using a structural vector-autoregressive model, where we identify exogenous policy shocks with interest rate surprises around FOMC announcements. Based on survey data, we construct measures of changes in consumers’ readiness to spend conditional on how consumers update their inflation expectations. Expansionary policy shocks tend to increase readiness to spend conditional on higher expected inflation outside the zero lower bound (ZLB), but the effect is small. At the ZLB, consumers increasingly reduce their readiness to spend if they expect higher inflation. Overall, we find only limited evidence suggesting that policy-induced variations in inflation expectations are associated with adjustments that are in line with the predictions of standard macroeconomic models.

This paper uses vector autoregression model analysis to identify monetary policy shocks on UK data using surprise changes in the policy rate as external instruments and imposing block exogeneity restrictions on domestic variables to estimate parameters from the viewpoint of the domestic economy. The results show large and persistent effects of monetary policy shocks on the domestic economy and point to the critical role of exchange rates and term premia. The analysis resolves important empirical puzzles of traditional recursive identification methods.

This study examines the driving forces behind the strong decline in German unemployment from 2005 onwards and the exceptionally small increase during the Great Recession. Structural vector autoregressions (VARs) with sign restrictions show that wage moderation in the aftermath of labor market reforms was the dominant factor of the unemployment decline, and that improved matching and shrinking labor supply also contributed to it. The adjustment to business cycle shocks (Great Recession), on the other hand, is to a large extent borne by the intensive margin, which can be explained by institutional aspects of the German labor market.

Exchange rate pass-through (ERPT) into prices and into income loss are shown to be enough to calculate ERPT into welfare loss using implications of a simple model. These ERPT measures are estimated at the good level using a unique micro-price data set from Turkey, and they are combined with income-group-specific expenditure shares at the good level to obtain aggregate-level ERPT measures for alternative income groups. An exchange rate shock resulting in a real depreciation of 1% is shown to decrease welfare by about 0.80% for the average-income consumer, while this estimate ranges between 0.73% and 0.83% for consumers in the lowest- and highest-income quintiles, respectively, suggesting evidence for redistributive effects of an exchange rate shock. Using micro prices has further resulted in showing that traded, nondurable, flexible-price, or income-elastic goods contribute more to ERPT into welfare loss for the average-income consumer, suggesting important policy implications for filtering out the noise in the measurement of aggregate-level prices.

We reassess the evidence for (or against) a key implication of the basic real business cycle model: that aggregate hours worked increase in response to a positive technology shock. Two novel aspects are the scope (14 OECD countries) and the inclusion of data on both labor supply margins to analyze the key margin of adjustment in aggregate hours. The short-run response of aggregate hours to a positive technology shock is remarkably similar across countries, with an impact fall in 13 out of 14 countries. In contrast, its decomposition into intensive and extensive labor supply margins reveals substantial heterogeneity in labor market dynamics across OECD countries. For instance, movements in the intensive margin are the dominant channel of adjustment in aggregate hours in 6 out of 14 countries of our sample, including France and Japan.

This paper introduces structural VAR analysis as a tool for investigating the anchoring of inflation expectations. We show that US consumers' inflation expectations are anchored in the long run because macro-news shocks are long-run neutral for long-term inflation expectations. The identification of structural shocks helps to explain why inflation expectations deviate from the central bank's target. Our results indicate that the recent decline in long-term inflation expectations does not result from deanchoring macro-news but can be attributed to downward adjustments in consumers' expectations about the central bank's inflation target.

We study the impact of oil price shocks on the U.S. stock market volatility. We jointly analyze three different structural oil market shocks (i.e., aggregate demand, oil supply, and oil-specific demand shocks) and stock market volatility using a structural vector autoregressive model. Identification is achieved by assuming that the price of crude oil reacts to stock market volatility only with delay. This implies that innovations to the price of crude oil are not strictly exogenous, but predetermined with respect to the stock market. We show that volatility responds significantly to oil price shocks caused by unexpected changes in aggregate and oil-specific demand, whereas the impact of supply-side shocks is negligible.

This paper investigates the international dimension of economic fluctuations and transmission of structural shocks by estimating a structural VAR model for the United States, the euro area, and Japan—the three largest economies—over the post-Bretton Woods period. The main findings are as follows: (1) Supply-side shocks (technology and supply-level shocks) explain most of the fluctuations in cross-country output deviations. (2) Real-demand shocks are the most important source of real-exchange-rate fluctuations. (3) Current account is usually influenced by all types of shocks, with technology shocks playing a stronger role. In particular, technology shocks play a prominent role in the existing global imbalance (the large external deficit of the United States). (4) Technology and supply-level shocks generate opposite-signed correlations between output differential and current account, whereas real and nominal-demand shocks generate opposite-signed correlations between real exchange rate and current account.

A recent finding of the SVAR literature is that the response of hours worked to a (positive) technology shock depends on the assumed order of integration of the hours. In this work we relax this assumption, allowing fractional integration in hours and productivity. We find that the sign and magnitude of the estimated responses depend crucially on the identification assumptions employed. Although the responses of hours recovered with short-run (SR) restrictions are positive in all data sets, long-run (LR) identification results in negative, although sometimes not significant responses. We check the validity of these assumptions with the Sims procedure, concluding that both LR and SR are appropriate to recover responses in a fractionally integrated VAR. However, the application of the LR scheme always results in an increase in sampling uncertainty. Results also show that even the negative responses found in the data could still be compatible with real business cycle models.

The performance of unit root tests on simulated series is compared, using the business-cycle model of Chang et al. [Journal of Money, Credit and Banking 39(6), 1357–1373 (2007)] as a data-generating process. Overall, Monte Carlo simulations show that the efficient unit root tests of Ng and Perron (NP) [Econometrica 69(6), 1519–1554 (2001)] are more powerful than the standard unit root tests. These efficient tests are frequently able (i) to reject the unit-root hypothesis on simulated series, using the best specification of the business-cycle model found by Chang et al., in which hours worked are stationary with adjustment costs, and (ii) to reduce the gap between the theoretical impulse response functions and those estimated with a Structural VAR model. The results of Monte Carlo simulations show that the hump-shaped behavior of data can explain the divergence between unit root tests.

We consider two kinds of answers to the title question: Do random shifts in monetary policy account for historical recessions, and would changes in the systematic component of monetary policy have allowed reductions in inflation or output variance without substantial costs. The answer to both questions is no. We use weak identifying assumptions and include extensive discussion of these assumptions, including a completely specified dynamic stochastic equilibrium model in which our identifying assumptions can be shown to be approximately satisfied.