Andrew Foerster

Sixty-two countries around the world use some form of inflation targeting as their monetary policy framework, though none of these countries express explicit policy rules. In contrast, models of monetary policy typically assume policy is set through a rule such as a Taylor rule or optimal monetary policy formulation. Central banks often connect theory with their practice by publishing inflation forecasts that can, in principle, implicitly convey their reaction function. We return to this central idea to show how a central bank can achieve the gains of a rule-based policy without publicly stating a specific rule. The approach requires central banks to specify an inflation target, tolerance bands, and provide economic projections. Thus, when inflation moves outside the band, inflation forecasts provide a time frame over which inflation will return to within the band. We show how this approach replicates and provides the same information as a rule-based policy.

This paper studies the interaction between nominal rigidities, labor market frictions, and consumption risk in a model where firms face sticky prices and post wage contracts to attract risk averse workers in a frictional labor market. Comparing a calibrated version of the model with two alternative versions–one that separates search and pricing frictions between two types of firms, and one in which a representative household makes consumption and employment decisions at an aggregate level–highlights the importance of integrating labor market and price-setting frictions with individual consumption risk. Separating search and pricing frictions between wholesale and retail sectors increases movements in inflation while muting those in labor markets and other macroeconomic variables. Meanwhile, using a representative household model significantly diminishes the effects of shocks on output and inflation, but increases the effects on vacancies and unemployment.

We find disparate trend variation in TFP and labor growth across major U.S. production sectors over the post-WWII period. When aggregated, these sector-specific trends imply secular declines in the growth rate of aggregate labor and TFP. We embed this sectoral trend variation into a dynamic multi-sector framework in which materials and capital used in each sector are produced by other sectors. The presence of capital induces important network effects from production linkages that amplify the consequences of changing sectoral trends on GDP growth. Thus, in some sectors, changes in TFP and labor growth lead to changes in GDP growth that may be as large as three times these sectors’ share in the economy. We find that trend GDP growth has declined by more than 2 percentage points since 1950, and that this decline has been primarily shaped by sector-specific rather than aggregate factors. Sustained contractions in growth specific to Construction, Nondurable Goods, and Professional and Business and Services make up close to sixty percent of the estimated trend decrease in GDP growth. In addition, the slow process of capital accumulation means that structural changes have endogenously persistent effects. We estimate that trend GDP growth will continue to decline for the next 10 years absent persistent increases in TFP and labor growth.

An economy that switches between high and low growth regimes creates incentives for the monetary authority to change its rule. As lower growth tends to produce lower real interest rates, the monetary authority has an incentive to increase the inflation target and increase the degree of inertia in setting rates in an attempt to keep the nominal rate positive. An optimizing monetary authority therefore responds to permanently lower growth by slightly increasing both the inflation target and inertia; focusing solely on the inflation target ignores a key margin of adjustment. With repeated growth rate regime switches, an optimal monetary rule that switches at the same time internalizes both the direct effects of growth regime change and the indirect expectation effects generated by switching in policy. The switching rule improves economic outcomes relative to a constant rule and one that does not consider the impact of regime changes; this result is robust to the case when the monetary authority misidentifies the growth regime with relatively high frequency.

Large pending fiscal policy changes, such as in the United States in 2012 or in Japan with consumption taxes, often generate considerable uncertainty. “Fiscal cliff” episodes have several features: an announced possible future change, a skewed set of possible outcomes, the possibility that implementation may not actually occur, and a known resolution date. This paper develops a model capturing these features and studies their impact. Fiscal cliff uncertainty shocks have immediate impact, with a magnitude that depends on the probability of implementation, which generates economic volatility. The possibility of fiscal cliffs lowers economic activity even in periods of relative certainty.

Markov‐switching dynamic stochastic general equilibrium (MSDSGE) modeling has become a growing body of literature on economic and policy issues related to structural shifts. This paper develops a general perturbation methodology for constructing high‐order approximations to the solutions of MSDSGE models. Our new method—“the partition perturbation method”—partitions the Markov‐switching parameter space to keep a maximum number of time‐varying parameters from perturbation. For this method to work in practice, we show how to reduce the potentially intractable problem of solving MSDSGE models to the manageable problem of solving a system of quadratic polynomial equations. This approach allows us to first obtain all the solutions and then determine how many of them are stable. We illustrate the tractability of our methodology through two revealing examples.

This article considers the determinacy and distributional consequences of regime switching in monetary policy. Although switching in the inflation target does not affect determinacy, switches in the inflation response can cause indeterminacy. Satisfying the Taylor principle period by period is neither necessary nor sufficient for determinacy when inflation responses switch; indeterminacy can arise if monetary policy responds too aggressively to inflation in the active regime. Inflation target switches primarily impact the level of inflation, whereas inflation response switches primarily impact the volatility. Expecting an inflation target switch has minor effects on volatility, whereas expecting an inflation response switch raises volatility more substantially.

A central bank may purchase assets during a financial crisis and then exit from those purchases. Agents have rational expectations about financial crises as rare events, the probability the central bank purchases assets, and the exit strategy. Selling off assets quickly produces a double-dip recession while slowly unwinding generates a smooth recovery. Expectations about the exit strategy influence the initial effectiveness of purchases. Increasing the probability of purchases during crises distorts the pre-crisis economy and depends upon the exit strategy. The welfare benefits of unconventional policy may differ ex-ante versus ex-post, as can the preferred exit strategy.

Economic data are collected at various frequencies but econometric estimation typically uses the coarsest frequency. This article develops a Gibbs sampler for estimating vector autoregression (VAR) models with mixed and irregularly sampled data. The Gibbs sampler allows efficient likelihood inference and uses simple conjugate posteriors even in high-dimensional parameter spaces, avoiding a non-Gaussian likelihood surface even when the Kalman filter applies. Two examples studying the relationship between financial data and the real economy illustrate the methodology and demonstrates efficiency gains from the mixed frequency estimator.

Using factor methods, we decompose industrial production (IP) into components arising from aggregate and sector-specific shocks. An approximate factor model finds that nearly all of IP variability is associated with common factors. We then use a multisector growth model to adjust for the effects of input-output linkages in the factor analysis. Thus, a structural factor analysis indicates that the Great Moderation was characterized by a fall in the importance of aggregate shocks while the volatility of sectoral shocks was essentially unchanged. Consequently, the role of idiosyncratic shocks increased considerably after the mid-1980s, explaining half of the quarterly variation in IP.