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.
Published Articles (Refereed Journals and Volumes)
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.
Perturbation Methods for Markov-Switching Dynamic Stochastic General Equilibrium Models
Quantitative Economics 7(2), July 2016, 637-669 | With Rubio-Ramirez, Waggoner, and Zha
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.
Monetary Policy Regime Switches and Macroeconomic Dynamics
International Economic Review 57(1), February 2016, 211-230
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.
Financial Crises, Unconventional Monetary Policy Exit Strategies, and Agents’ Expectations
Journal of Monetary Economics 76, November 2015, 191-207
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.
Bayesian Mixed Frequency VARs
Journal of Financial Econometrics 13(3), Summer 2015, 698-721 | With Eraker, Chiu, Kim, and Seoane
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.
Sectoral versus Aggregate Shocks: A Structural Factor Analyses of Industrial Production
Journal of Political Economy 119(1), February 2011, 1-38 | With Sarte and Watson
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.
We study the growth properties of an economy where different sectors are linked by way of intermediates and potentially grow at different rates. We characterize the economy’s equilibrium balanced growth path, and derive an analytical expression that summarizes how TFP growth in a given sector affects value added growth in every other sector and, therefore, aggregate GDP growth. We show in a special case that a version of Hulten’s (1978) theorem, whereby the effects of changes in sector-specific productivity on GDP are entirely captured by that sector’s share in GDP, also holds in growth rates along a balanced growth path. In that case, changes in TFP growth specific to that sector do not directly affect value added in other sectors regardless of its linkages in the economy. In the more general case, changes in sectors that are more capital intensive, and central as intermediate goods suppliers, have larger effects on value added growth in other sectors and aggregate GDP. In a calibrated version of our benchmark case, we find substantive quantitative differences in the effects of sectoral TFP growth changes on GDP relative to the case where these effects are given by sectoral value added shares only.
Investment growth slowed from 2014 to 2016, a period when the overall economy was expanding. Using a statistical model, I find clear evidence that investment growth fluctuates between high and low growth regimes that usually correspond to expansions and recessions. However, during 2014–16, the investment sector experienced an isolated recession within an overall expansion, which is unusual by historical standards.
The U.S. economy is a collection of varied industries linked by the goods and services they exchange with one another during production. In this way, industries form a network of input-output relationships with potentially important implications for economic activity. For example, supply disruptions to one industry might spill over to industries that receive inputs from the affected industry. The magnitude of these spillover effects depends crucially on both the affected industry’s links to other industries as well as its importance within the network.
Andrew Foerster and Jason Choi document the input-output network structure of the U.S. economy and examine how the connectivity and centrality of industries have changed over time. They find that the number of connections between industries has varied, with a decrease in industry interconnection more recently. In addition, they find that certain services-based industries have become more important in the network over time.
The financial crisis and recession of 2007–09 hit household balance sheets hard. Even as the economy began to recover, diminished income, a stagnant labor market, and tight credit conditions made it difficult for households to increase their consumption as rapidly as they had a few years earlier. Indeed, consumption has grown more slowly after the Great Recession than in recoveries from previous recessions, suggesting a fundamental shift in the economy. Andrew Foerster and Jason Choi compare consumption growth’s historical behavior with its behavior during the most recent recovery. The authors find that the recent period of slow consumption growth was due not to new or transitory factors but rather the persistent influence of factors unusual to see outside recessions. They find that durables and nondurables consumption behaved much as they did during precious recoveries; total and services consumption, however, grew more slowly than usual throughout the expansion.
When uncertainty about the future increases, economic activity tends to decrease as firms delay hiring and consumers defer purchases. When a bout of uncertainty subsides, however, firms may only cautiously increase the pace of hiring and investment. As a result, short-lived spikes in uncertainty, such as those experienced during the current recovery, may have persistent effects on employment growth, thus lowering the total level of employment.
Recovery from the recent financial crisis has been sluggish by historical standards, and employment growth has been similarly disappointing. Three periods of heightened economic uncertainty—the European sovereign debt crisis, the U.S. debt ceiling crisis, and, to a lesser extent, 2013’s brief “taper tantrum”—may have contributed to this lackluster response. Foerster introduces a statistical model to analyze spikes in stock market volatility during these periods and thus quantify uncertainty’s influence. He finds that uncertainty has asymmetric effects, with large increases in uncertainty affecting growth more than large decreases. The results suggest that temporary spikes in uncertainty following the financial crisis may have had persistent economic effects, leading to an anemic recovery and substantial cumulative employment losses across industries.
During and after the recent financial crisis, the Federal Reserve turned to a number of unconventional tools to bolster the economy. The effectiveness of one such tool, large-scale asset purchases (LSAPs)—often referred to as quantitative easing—has been hard to measure. ; Efforts to estimate LSAP impact have often relied on an “event study” approach, focusing on short time intervals around the announcements of new LSAP programs. But these studies typically ignore the fact that financial market participants sometimes expect a given LSAP announcement in advance—and such expectations can affect interest rates prior to the time interval considered. ; Authors Foerster and Cao present evidence that LSAP announcements were often at least partially expected in advance, and they argue that event studies, by ignoring the effects of prior expectations, likely misestimate the impact of LSAPs.
In modern corporations, ownership is typically separate from control. Given that employees are motivated by self interest, incentive problems arise. Employees are disciplined, in part, by their career concerns. Employees’ compensation depends on their reputations—the labor market’s beliefs about their future productivity. The labor market learns about the employees’ future productivity by observing their performance. Therefore, when the employees decide their actions, they care about their performance (and the performance of the firms they work for) because their performance influences their reputation. However, career concerns do not necessarily eliminate the inefficiencies created by the separation of ownership and control.