The Stabilizing Effects of Publishing Strategic Central Bank Projections

Expectations are among the main driving forces for economic dynamics. Therefore, managing expectations has become a primary objective for monetary policy seeking to stabilize the business cycle. In this paper, we study whether central banks can manage private-sector expectations by means of publishing one-period ahead inflation projections in a New Keynesian learning-to-forecast experiment. Subjects in the experiment observe these projections along with the historic development of the economy and subsequently submit their own one-period ahead inflation forecasts. In this context, we find that the central bank can significantly manage private-sector expectations and that this management strongly supports monetary policy in stabilizing the economy. Moreover, published central bank inflation projections drastically reduce the probability of a deflationary spiral after strong negative shocks to the economy.

How influential are COVID–19 data points? A fresh look at an estimated small scale DSGE model for the Philippines

Shocks emanating from the global pandemic continue to reshape the macroeconomic landscape—dimming national growth prospects, prolonging widespread financial distress among households, firms, and governments and heightening uncertainty. Using a small-scale New Keynesian Dynamic Stochastic General Equilibrium (DSGE) model for the Philippines, we examine the model’s sensitivity to COVID-19 datapoints or extreme observations. Relative to estimates during the base period (2002Q1 to 2019Q4), the inclusion of extreme datapoints worsens the model’s log data density progressively, from the consideration of the first quarter of 2020 to the full sample – an indication that shock propagation mechanisms associated with COVID–19 and other natural disasters should be integrated into the model. Even with the inclusion of said extreme observations, however, the model’s parameters are identified, provided identification schemes are evaluated at posterior median estimates. Judging from the sets of parameter estimates relative to the base sample, the effects of extreme observations are found to be non–uniform, especially the size of the shocks. But there are other parameters, notably those that are embedded in the Taylor rule, which are relatively as stable as some household related parameters. These results imply that the size of standard errors for demand, supply, and monetary policy shocks adjust to partially capture the impact of extreme datapoints.

The effect of central bank credibility on forward guidance in an estimated New Keynesian model

This paper examines the effectiveness of forward guidance shocks in the US. We estimate a New Keynesian model with imperfect central bank credibility and heterogeneous expectations using Bayesian methods and survey data from the Survey of Professional Forecasters (SPF). The results provide important takeaways: (1) The estimated credibility of the Fed’s forward guidance announcements is relatively high, but anticipation effects are attenuated. Accordingly, output and inflation do not respond as favorably as in the fully credible counterfactual. (2) The so-called “forward guidance puzzle” arises partly from the unrealistically large responses of macroeconomic variables to forward guidance under perfect credibility and homogeneous fully informed rational expectations, assumptions which are found to be jointly inconsistent with the observed US data. (3) Imperfect credibility provides a plausible explanation for the empirical evidence of forecasting error predictability based on forecasting disagreement found in the SPF data. Thus, we show that accounting for imperfect credibility and forecasting disagreements is important to understand the formation of expectations and the transmission mechanism of forward guidance.

SECTORAL LABOR MOBILITY AND OPTIMAL MONETARY POLICY

How should central banks optimally aggregate sectoral inflation rates in the presence of imperfect labor mobility across sectors? We study this issue in a two-sector New-Keynesian model and show that a lower degree of sectoral labor mobility, ceteris paribus, increases the optimal weight on inflation in a sector that would otherwise receive a lower weight. We analytically and numerically find that, with limited labor mobility, adjustment to asymmetric shocks cannot fully occur through the reallocation of labor, thus putting more pressure on wages, causing inefficient movements in relative prices, and creating scope for central bank’ s intervention. These findings challenge standard central banks’ practice of computing sectoral inflation weights based solely on sector size and unveil a significant role for the degree of sectoral labor mobility to play in the optimal computation. In an extended estimated model of the US economy, featuring customary frictions and shocks, the estimated inflation weights imply a decrease in welfare up to 10% relative to the case of optimal weights.