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Interpreting Structural Shocks and Assessing Their Historical Importance
Abstract
We revisit three major US recessions through the lens of a standard medium-scale DSGE model (Smets, F., and R. Wouters. 2007. “Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach.” The American Economic Review 97: 586–606.) augmented with financial frictions. We first estimate the DSGE model using a Bayesian approach for three alternative periods, each containing a major US recession: the Great Depression, the Stagflation and the Great Recession. Then, we assess the stability of structural parameters, and analyze what frictions were particularly important and what shocks were the main drivers of aggregate fluctuations in each historical period. This exercise can be understood as a test of the standard New-Keynesian DSGE model with financial accelerator in closed economies. We find that the estimated DSGE model is able to provide a sound explanation of all three recessions by closely relating both estimated structural shocks and frictions with well known economic events.
Supplementary resource (1)
The purpose of this paper is to investigate the sources of business cycle fluctuations in a small open economy (SOE) using dynamic stochastic general equilibrium (DSGE) models and to assess the path of optimal policy decisions taken by the Central Bank of the Republic of Turkey (CBRT). To that purpose, the SOE-DSGE model is estimated using the Bayesian technique with Turkish data spanning the quarters 2003Q2–2020Q1. Based on the estimated model, the study finds that the explanatory power of the SOE-DSGE model for household, firm and central bank behavior decreases when consumer habit formation, price indexation and exchange rate sensitivity are included. Furthermore, technology, preferences, and risk premium shocks all have a significant impact on the Turkish economy. The CBRT, on the other hand, was principally concerned with price stabilization, interest rate smoothing, output and output growth stabilization, and nominal exchange rate stabilization, respectively. More importantly, the optimal monetary policy function implies that output growth should be better stabilized if exchange rate sensitivity target is ignored.
This paper provides a critique of the DSGE models that have come to dominate macroeconomics during the past quarter-century. It argues that at the heart of the failure were the wrong microfoundations, which failed to incorporate key aspects of economic behaviour, e.g. incorporating insights from information economics and behavioural economics. Inadequate modelling of the financial sector meant they were ill-suited for predicting or responding to a financial crisis; and a reliance on representative agent models meant they were ill-suited for analysing either the role of distribution in fluctuations and crises or the consequences of fluctuations on inequality. The paper proposes alternative benchmark models that may be more useful both in understanding deep downturns and responding to them.
Recent studies show that the estimated parameters of rational expectations dynamic stochastic general equilibrium models of the business cycle are largely time-varying. This paper shows that assuming adaptive learning (rather than rational expectations) strongly reduces the estimated parameter variability of standard models (by around 75%). Moreover, the reduction in parameter variability induced by adaptive learning is much stronger for the subsets of parameters that control nominal price and wage rigidity and the subset of policy rule parameters (at 98% and 83%, respectively). Furthermore, our estimation results suggest that adaptive learning helps to explain the recent swings in the comovements between real and nominal US macroeconomic variables, but the swing in the relative weight of supply and demand shocks seems to be the most important driving force.
We offer a tractable dynamic theory where excessive credit creation by the frictional banking sector may lead to over-investment and then endogenous boom-bust cycles. We formalize the idea in a general equilibrium framework with banks and financially constrained heterogeneous firms. In the static model, a moderate credit expansion has a nonmonotonic positive impact on aggregate output, but an excessive credit expansion can trigger an interbank market crisis and result in a discontinuous sharp fall in aggregate output. By extending to a dynamic setting, we show that this mechanism can generate endogenous boom-bust business cycles despite the absence of adverse shocks.
Presentation of our paper "Central Bank Losses and Monetary Policy Rules: A DSGE Investigation". Please cite this presentation as: Benchimol, J., and Fourçans, A., 2019. Central bank losses and monetary policy rules: a DSGE investigation. International Review of Economics & Finance, 61(1), 289-303.
Central banks' monetary policy rules being consistent with policy objectives are a fundamental of applied monetary economics. We seek to determine, first, which of the central bank's rules are most in line with the historical data for the US economy and, second, what policy rule would work best to assist the central bank in reaching its objectives via several loss function measures. We use Bayesian estimations to evaluate twelve monetary policy rules from 1955 to 2017 and over three different sub-periods. We find that when considering the central bank's loss functions, the estimates often indicate the superiority of NGDP level targeting rules, though Taylor-type rules lead to nearly identical implications. However, the results suggest that various central bank empirical rules, be they NGDP or Taylor type, are more appropriate to achieve the central bank's objectives for each type of period (stable, crisis, recovery).
The outcome of any important macroeconomic policy change is the net effect of forces operating on different parts of the economy. A central challenge facing policymakers is how to assess the relative strength of those forces. Economists have a range of tools that can be used to make such assessments. Dynamic stochastic general equilibrium (DSGE) models are the leading tool for making such assessments in an open and transparent manner. We review the state of mainstream DSGE models before the financial crisis and the Great Recession. We then describe how DSGE models are estimated and evaluated. We address the question of why DSGE modelers—like most other economists and policymakers—failed to predict the financial crisis and the Great Recession, and how DSGE modelers responded to the financial crisis and its aftermath. We discuss how current DSGE models are actually used by policymakers. We then provide a brief response to some criticisms of DSGE models, with special emphasis on criticism by Joseph Stiglitz, and offer some concluding remarks.
In recent business cycles, U.S. inflation has experienced a reduction of volatility and a severe weakening in the correlation to the nominal interest rate (Gibson paradox). We examine these facts in an estimated dynamic stochastic general equilibrium model with money. Our findings point at a flatter New Keynesian Phillips Curve (higher price stickiness) and a lower persistence of markup shocks as the main explanatory factors. In addition, a higher interest-rate elasticity of money demand, an increasing role of demand-side shocks, and a less systematic behavior of Fed's monetary policy also account for the recent patterns of U.S. inflation dynamics. (JEL E32, E47)
We present an estimated dynamic stochastic general equilibrium model of stock market bubbles and business cycles using Bayesian methods. Bubbles emerge through a positive feedback loop mechanism supported by self-fulfilling beliefs. We identify a sentiment shock that drives the movements of bubbles and is transmitted to the real economy through endogenous credit constraints. This shock explains most of the stock market fluctuations and sizable fractions of the variations in real quantities. It generates the comovement between stock prices and the real economy, and is the dominant force behind the internet bubbles and the Great Recession.
In this paper, I study how alternative assumptions about expectation formation can modify the implications of …nancial frictions for the real economy. I incorporate a …nancial accelerator mechanism into a version of the Smets and Wouters (2007) DSGE framework and explore the properties of the model assuming, on the one hand, complete rationality of expectations and, alternatively, several learning algorithms that di¤er in terms of the information set used by agents to produce the forecasts. I show that the implications of the …nancial accelerator for the business cycle may vary depending on the approach to modeling the expectations. The results suggest that the learning scheme based on small forecasting functions is able to amplify the e¤ects of …nancial frictions relative to the model with Rational Expectations. Speci…cally, I show that the dynamics of real variables under learning is driven to a signi…cant extent by the time variation of agents' beliefs about …-nancial sector variables. During periods when agents perceive asset prices as being relatively more persistent, …nancial shocks lead to more pronounced macroeconomic outcomes. The ampli…cation e¤ect rises as …nancial frictions become more severe. At the same time, a learning speci…cation in which agents use more information to generate predictions produces very di¤erent asset price and investment dynamics. In such a framework, learning cannot signi…cantly alter the real e¤ects of …nancial frictions implied by the Rational Expectations model.
This paper assesses the empirical relevance of financial frictions in the Euro Area (EA) and the United States (US). It provides a comprehensive set of comparisons between two models: (i) a Smets and Wouters (SW) [F. Smets and R. Wouters, Shocks and frictions in US business cycles: A Bayesian DSGE approach,
American Economic Review
97(3), 586–606 (2007)] model with financial frictions originating in nonfinancial firms and (ii) a SW model with frictions originating in financial intermediaries. The introduction of financial frictions in either way improves the models' fit compared to a standard SW model, and the empirical comparisons reveal that the latter model outperforms the former both in the euro area and in the United States. Two main factors explain this result: first, the magnitude of the financial accelerator effect, and second, the role of the investment-specific technology shock in affecting financial variables.
We argue that the vast bulk of movements in aggregate real economic activity during the Great Recession were due to financial frictions. We reach this conclusion by looking through the lens of an estimated New Keynesian model in which firms face moderate degrees of price rigidities, no nominal rigidities in wages, and a binding zero lower bound constraint on the nominal interest rate. Our model does a good job of accounting for the joint behavior of labor and goods markets, as well as inflation, during the Great Recession. According to the model the observed fall in total factor productivity and the rise in the cost of working capital played critical roles in accounting for the small drop in inflation that occurred during the Great Recession.
We provide a model of rational bubbles in a DNK framework. Entrepreneurs are heterogeneous in investment efficiency and face credit constraints. They can trade bubble assets to raise their net worth. The bubble assets command a liquidity premium and can have a positive value. Monetary policy affects the conditions for the existence of a bubble, its steady-state size, and its dynamics including the initial size. The leaning-against-the-wind interest rate policy reduces bubble volatility, but could raise inflation volatility. Whether monetary policy should respond to asset bubbles depends on the particular interest rate rule and exogenous shocks.
Many critiques of the state of macroeconomics are off target. Current macroeconomic research is not mindless DSGE modelling filled with ridiculous assumptions and oblivious of data. Rather, young macroeconomists are doing vibrant, varied, and exciting work, getting jobs, and being published. Macroeconomics informs economic policy only moderately, and not more than nor differently from other fields in economics. Monetary policy has benefitted significantly from this advice in keeping inflation under control and preventing a new Great Depression. Macroeconomic forecasts perform poorly in absolute terms and, given the size of the challenge, probably always will. But relative to the level of aggregation, the time horizon, and the amount of funding, macroeconomic forecasts are not so obviously worse than those in other fields. What is most wrong with macroeconomics today is perhaps that there is too little discussion of which models to teach and too little investment in graduate-level textbooks.
This paper examines the ability of a simple stylized general equilibrium model that incorporates nominal wage rigidity to explain the magnitude and persistence of the Great Depression in the United States. The impulses to our analysis are money supply shocks. The Taylor contracts model is surprisingly successful in accounting for the behavior of major macroaggregates and real wages during the downturn phase of the Depression, i.e., from 1929:3 through mid-1933. Our analysis provides support for the hypothesis that a monetary contraction operating through a sticky wage channel played a significant role in accounting for the downturn, and also provides an interesting refinement to this explanation. In particular, both the absolute severity of the Depression's downturn and its relative severity compared to the 1920-21 recession are likely attributable to the price decline having a much larger unanticipated component during the Depression, as well as less flexible wage-setting practices during this latter period. Another finding casts doubt on explanations for the 1933-36 recovery that rely heavily on the substantial remonetization that began in 1933.
We argue that the vast bulk of movements in aggregate real economic activity during the Great Recession were due to financial frictions interacting with the zero lower bound. We reach this conclusion looking through the lens of a New Keynesian model in which firms face moderate degrees of price rigidities and no nominal rigidities in the wage setting process. Our model does a good job of accounting for the joint behavior of labor and goods markets, as well as inflation, during the Great Recession. According to the model the observed fall in total factor productivity and the rise in the cost of working capital played critical roles in accounting for the small size of the drop in inflation that occurred during the Great Recession.
This paper proposes a straight model-based analysis of historical war episodes. We analyze the effects of world wars on the macroeconomic dynamics in the US, France, Germany, and the UK, by means of an estimated open-economy model where war episodes are modeled as an additional source of observed shocks. The model allows war episodes to affect the economy through lower capital depreciation, partial default on public debt, a military draft, changes in household preferences, and spillovers on other shocks (productivity, investment, trade, policy variables). In the US, the bulk of fluctuations during war episodes can be mainly explained by the rise in government spending, and the war shock plays a minor role. In other countries, the war shock is an essential driver of fluctuations. We also discuss the size and state-dependence of public spending multipliers, and produce a counterfactual exercise to quantify the welfare losses from war episodes.
We quantify the macroeconomic effects of the European Central Bank's unconventional monetary policies using a dynamic stochastic general equilibrium model which includes a set of shadow interest rates. Extracted from the yield curve, these shadow rates provide unconstrained measures of the overall stance of monetary policy. Counterfactual analyses show that, without unconventional measures, the euro area would have suffered (i) a substantial loss of output since the Great Recession and (ii) a period of deflation from mid‐2015 to early 2017. Specifically, year‐on‐year inflation and GDP growth would have been on average about 0.61% and 1.09% below their actual levels over the period 2014Q1–17Q2, respectively.
This book was originally published by Macmillan in 1936. It was voted the top Academic Book that Shaped Modern Britain by Academic Book Week (UK) in 2017, and in 2011 was placed on Time Magazine's top 100 non-fiction books written in English since 1923. Reissued with a fresh Introduction by the Nobel-prize winner Paul Krugman and a new Afterword by Keynes’ biographer Robert Skidelsky, this important work is made available to a new generation.
The General Theory of Employment, Interest and Money transformed economics and changed the face of modern macroeconomics. Keynes’ argument is based on the idea that the level of employment is not determined by the price of labour, but by the spending of money. It gave way to an entirely new approach where employment, inflation and the market economy are concerned.
Highly provocative at its time of publication, this book and Keynes’ theories continue to remain the subject of much support and praise, criticism and debate. Economists at any stage in their career will enjoy revisiting this treatise and observing the relevance of Keynes’ work in today’s contemporary climate.
This paper assesses the empirical relevance of financial frictions in the Euro Area (EA) and the United States (US). It provides a comprehensive set of comparisons between two models: (i) a Smets and Wouters (2007) (SW) model with financial frictions originating in non-financial firms a la Bernanke et al. (1999) (SWBGG); and (ii) a SW model with frictions originating in financial intermediaries, a la Gertler and Karadi (2011) (SWGK). Proved that the introduction of financial frictions in either way improves the models' fit compared to a standard SW model, the empirical comparisons reveal that the SWGK model outperforms the SWBGG model both in the EA and the US. Two main factors explain this result: first, the magnitude of the financial accelerator effect; and second, the role of the investment-specific technology shock in affecting financial variables.
We estimate the Smets-Wouters model featuring the Gertler-Karadi banking sector on US data using real and financial observables. We investigate the gains from coordination between a flexible inflation targeting central bank and a macroprudential regulator charged with safeguarding financial stability. The potential gains from coordination depend on how much importance is given to the output gap in the macroprudential mandate. Coordination conflicts can be avoided by assigning similar importance to this common objective in the respective mandates of both policies. When we derive optimal mandates for monetary and macroprudential policy under no-coordination, we find that both policy makers should place a higher weight than society on the output gap.
We estimate a forward-looking monetary policy reaction function for the postwar United States economy, before and after Volcker's appointment as Fed Chairman in 1979. Our results point to substantial differences in the estimated rule across periods. In particular, interest rate policy in the Volcker-Greenspan period appears to have been much more sensitive to changes in expected inflation than in the pre-Volcker period. We then compare some of the implications of the estimated rules for the equilibrium properties of inflation and output, using a simple macroeconomic model, and show that the Volcker-Greenspan rule is stabilizing.
This paper employs an approximation that makes a nonlinear term structure
model extremely tractable for analysis of an economy operating near the zero
lower bound for interest rates. We show that such a model offers an excellent
description of the data compared to the benchmark model and can be used to
summarize the macroeconomic effects of unconventional monetary policy.
Our estimates imply that the efforts by the Federal Reserve to stimulate the
economy since July 2009 succeeded in making the unemployment rate in
December 2013 1% lower, which is 0.13% more compared to the historical
behavior of the Fed.
After the recent banking crisis in 2008, financial market conditions have turned out to be a relevant factor for economic fluctuations. This paper provides a quantitative assessment of the impact of financial frictions on the U.S. business cycle. The analysis compares the original Smets and Wouters model (2003, 2007) with an alternative version augmented with the financial accelerator mechanism á la Bernanke, Gertler and Gilchrist (1996, 1999). Both versions are estimated using Bayesian techniques over a sample extended to 2012. The analysis supports the role of financial channels, namely the financial accelerator mechanism, in transmitting dysfunctions from financial markets to the real economy.
The Smets and Wouters model, augmented with the financial accelerator mechanism, is suitable to capture much of the historical developments in U.S. financial markets that led to the financial crisis. The model can account for the output contraction in 2008, as well as the widening in corporate spreads, and supports the argument that financial conditions have amplified the U.S. business cycle and the intensity of the recession.
After the recent banking crisis in 2008, financial market conditions have turned out to be a relevant factor for economic fluctuations. This paper provides a quantitative assessment of the impact of financial frictions on the U.S. business cycle. The analysis compares the original Smets and Wouters model (2003, 2007) with an alternative version augmented with the financial accelerator mechanism à la Bernanke, Gertler and Gilchrist (1996,1999). Both versions are estimated using Bayesian techniques over a sample extended to 2012. The analysis supports the role of financial channels, namely the financial accelerator mechanism, in transmitting dysfunctions from financial markets to the real economy. The Smets and Wouters model, augmented with the financial accelerator mechanism, is suitable to capture much of the historical developments in U.S. financial markets that led to the financial crisis. The model can account for the output contraction in 2008, as well as the widening in corporate spreads and supports the argument that financial conditions have amplified the U.S. business cycle and the intensity of the recession.
A restricted-perceptions equilibrium exists in which risk-averse agents believe stock prices follow a random walk with a conditional variance that is self-fulfilling. When agents estimate risk, bubbles and crashes arise. These effects are stronger when agents allow for ARCH in excess returns.
We augment a standard monetary DSGE model to include a Bernanke-Gertler-Gilchrist financial accelerator mechanism. We fit the model to US data, allowing the volatility of cross-sectional idiosyncratic uncertainty to fluctuate over time. We refer to this measure of volatility as 'risk'. We find that fluctuations in risk are the most important shock driving the business cycle.Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.
We estimate a two-sector DSGE model with financial intermediaries—a-la Gertler and Karadi 2011) and Gertler and Kiyotaki (2010)—and quantify the importance of financial shocks in accounting for aggregate and sectoral fluctuations. Our results indicate a significant role of financial market news as a predictive force behind fluctuations. Specifically, news about the valuation of assets held by financial intermediaries, reflected one to two years in advance in corporate bond markets, affect the supply of credit and are estimated to be a significant source of aggregate fluctuations, accounting for approximately 25% of output, 20% of investment and 25% of hours variation in both cyclical and lower frequencies. Financial intermediation is essential for the importance and propagation of these valuation shocks. Importantly, valuation news shocks generate both aggregate and sectoral co-movement as in the data.
This paper analyzes the contribution of anticipated capital and labor tax shocks to business cycle volatility in an estimated New Keynesian DSGE model. While fiscal policy accounts for 12 to 20 percent of output variance at business cycle frequencies, the anticipated component hardly matters for explaining fluctuations of real variables. Anticipated capital tax shocks do explain a sizable part of inflation and interest rate fluctuations, accounting for between 5 and 15 percent of total variance. In line with earlier studies, news shocks in total account for 20 percent of output variance. Further decomposing this news effect, we find that it is mostly driven by stationary TFP and non-stationary investment-specific technology.
We investigate the relationship between monetary policy and inflation dynamics in the US using a medium scale structural model. The specification is estimated with Bayesian techniques and fits the data reasonably well. Policy shocks account for a part of the decline in inflation volatility; they have been less effective in triggering inflation responses over time and qualitatively account for the rise and fall in the level of inflation. A number of structural parameter variations contribute to these patterns.
Dynamic stochastic general equilibrium (DSGE) models use modern macroeconomic theory to explain and predict comovements of aggregate time series over the business cycle and to perform policy analysis. We explain how to use DSGE models for all three purposes — forecasting, story telling, and policy experiments — and review their forecasting record. We also provide our own real-time assessment of the forecasting performance of the Smets and Wouters (2007) model data up to 2011, compare it with Blue Chip and Greenbook forecasts, and show how it changes as we augment the standard set of observables with external information from surveys (nowcasts, interest rate forecasts, and expectations for long-run inflation and output growth). We explore methods of generating forecasts in the presence of a zero-lower-bound constraint on nominal interest rates and conditional on counterfactual interest rate paths. Finally, we perform a postmortem of DSGE model forecasts of the Great Recession and show that forecasts from a version of the Smets-Wouters model augmented by financial frictions, and using spreads as an observable, compare well with Blue Chip forecasts.
Macroeconomic shocks such as wil price increases induce a systematic (endogenous) response of monetary policy. We develop a VAR-based technique for decomposing the total economic effects of a given exogenous shock into the portion attributable directly to the shock and the part arising from the policy response to the shock.
This chapter develops a dynamic general equilibrium model that is intended to help clarify the role of credit market frictions in business fluctuations, from both a qualitative and a quantitative standpoint. The model is a synthesis of the leading approaches in the literature. In particular, the framework exhibits a “financial accelerator”, in that endogenous developments in credit markets work to amplify and propagate shocks to the macroeconomy. In addition, we add several features to the model that are designed to enhance the empirical relevance. First, we incorporate money and price stickiness, which allows us to study how credit market frictions may influence the transmission of monetary policy. In addition, we allow for lags in investment which enables the model to generate both hump-shaped output dynamics and a lead-lag relation between asset prices and investment, as is consistent with the data. Finally, we allow for heterogeneity among firms to capture the fact that borrowers have differential access to capital markets. Under reasonable parametrizations of the model, the financial accelerator has a significant influence on business cycle dynamics.
The current …nancial crisis has made it abundantly clear that business cycle model-ing no longer can abstract from …nancial factors. It is also becoming increasingly clear that the stylized modeling of labor markets without explicit unemployment that is the current standard approach has its limitations. Some questions which the dominating extant business cycle models are mute on, but that we would like to answer are: How important are …nancial and labor market frictions for the business cycle dynamics of a small open economy? In particular, what are the quantitative e¤ects of …nancial factors on output and ination, and how do they interact with monetary policy? What drives the variation in the intensive and extensive margin of labor supply respectively? What is the estimated Frisch elasticity in a model that allows for both an intensive and an extensive margin of labor supply? In order to address these questions we extend what is becoming the standard new Keynesian model in three important dimensions. First, we incorporate …nancial frictions in the accumulation and management of capital. Second, we model the labor market using a search and matching framework. Third, we extend the model into a small open economy setting. We make a theoretical contribution by incorporating endogenous job separation in this rich framework. Finally, we estimate the full model using Bayesian techniques and illustrate the importance of the various frictions. seminar participants at various presentations. The views expressed in this paper are solely the responsibility of the authors and should not be interpreted as reecting the views of the Executive Board of Sveriges Riksbank or of the European Central Bank.
A DSGE model is identifiable when perturbing the parameters characterizing the forward looking optimizing model induces a distinguishable solution to the model. This paper studies identification of the parameters of a DSGE model using all the second moment properties of the data. We show that the solution of the model does not have the usual properties of a reduced form even when the shocks are uncorrelated and the system is stochastically non-singular. Hence, classical identification results do not apply. We use the restrictions that two linear dynamic models with identical spectrum must satisfy to obtain the rank and order conditions for identification. Both conditions depend on the solution parameters alone, and can be checked before any observations are considered. We also provide results for conditional identification under a priori restrictions, and partial identification of a subset of the parameter of interest. The results are established in a general set up that allows for fewer shocks than endogenous variables. Two examples are considered to illustrate the results.