Macroeconomic shocks and fluctuations in African economies

We estimate a monetary DSGE model to examine the role of macroeconomic shocks in generating fluctuations in ten African countries. The model is estimated with the Bayesian technique using twelve macroeconomic variables. The findings indicate that both the internal and external shocks significantly influence output fluctuations in African economies. Over a four quarter horizon, internal shocks are dominant and over eight to sixteen quarter horizons, external shocks are dominant. Among the external shocks, external debt, exchange rate, foreign interest rate and commodity price shocks account for a large part of output variations in African economies. Money supply and productivity shocks are the most important internal shocks contributing to output fluctuations in African countries.     

Rent-seeking in an emerging market: A DSGE approach

Due to the fact that rent-seeking is by definition an unobservable variable, measuring its size and evolution over the business cycle can be a daunting challenge. In this article, by embedding rent-seeking behavior in an otherwise standard open-economy DSGE model, we are able to derive a quarterly time series of this variable (expressed as a percentage deviation from the trend) for an emerging economy such as Brazil. The estimated series, spanning the period 2002Q1?2017Q4, shows a strong positive correlation with the “Commodity Super Cycle” of the 2000 decade and falls as a result of some political scandals and their ensuing investigations, among other driving forces. We also rely on the same model to assess how several shocks hitting the economy affect both rent-seeking and the relevant macroeconomic variables in our model. Barring monetary expansions, increased exports and higher income transfers to households, expansionary shocks are associated with lower rent-seeking activity. Factoring in these two sets of results, the upshot is that rent-seeking behavior shows a pattern of procyclicality in the Brazilian economy.     

RARE SHOCKS,GREAT RECESSIONS

We estimate a DSGE (dynamic stochastic general equilibrium) model where rare large shocks can occur, by replacing the commonly used Gaussian assumption with a Student's t‐distribution. Results from the Smets and Wouters (American Economic Review 2007; 97 : 586–606) model estimated on the usual set of macroeconomic time series over the 1964–2011 period indicate that (i) the Student's t specification is strongly favored by the data even when we allow for low‐frequency variation in the volatility of the shocks, and (ii)) the estimated degrees of freedom are quite low for several shocks that drive US business cycles, implying an important role for rare large shocks. This result holds even if we exclude the Great Recession period from the sample. We also show that inference about low‐frequency changes in volatility—and, in particular, inference about the magnitude of Great Moderation—is different once we allow for fat tails. Copyright © 2014 John Wiley & Sons, Ltd.     

The government wage bill and private activity

We estimate the macroeconomic effects of public wage expenditures in U.S. data by identifying shocks to public employment and public wages using sign restrictions. We find that public employment shocks are mildly expansionary at the federal level and strongly expansionary at the state and local level by crowding in private consumption and increasing labor force participation and private sector employment. Similarly, state and local government wage shocks lead to increases in consumption and output, while shocks to federal government wages induce significant contractionary effects. In a stylized DSGE model we show that the degree of complementarity between public and private goods in the consumption bundle is key for explaining the observed heterogeneity.     

What inventories tell us about aggregate fluctuations—A tractable approach to (S,s) policies

We estimate a DSGE model with (S,s) inventory policies. We find that (i) taking inventories into account can significantly improve the empirical fit of DSGE models in matching the standard business-cycle moments (in addition to explaining inventory fluctuations); (ii) (S,s) inventory policies can significantly amplify aggregate output fluctuations, in contrast to the findings of the recent general-equilibrium inventory literature; and (iii) aggregate demand shocks become more important than technology shocks in explaining the business cycle once inventories are incorporated into the model. An independent contribution of our paper is that we develop a solution method for analytically solving (S,s) inventory policies in general equilibrium models with heterogeneous firms and a large aggregate state space, and we illustrate how standard log-linearization methods can be used to solve various versions of our inventory model, generate impulse response functions, and estimate the model׳s deep structural parameters.     

两类DSGE模型的动态因子模型表示

为了识别动态因子模型（DFM）中不可观测动态因子、并解读其经济学意义,以及为DSGE模型提供一种新的估计途径,研究了新凯恩斯DSGE模型和具有Markov体制转换过程的DSGE（MS-DSGE）模型的DFM表示。结果表明,DSGE模型和MS-DSGE模型的动态行为均由共同因子和外生冲击的合并效应所决定;当外生冲击为相互独立的白噪声过程时,两类DSGE模型分别可以表示为标准的DFM和具有Markov体制转换过程的DFM。     

PRACTICAL TOOLS FOR POLICY ANALYSIS IN DSGE MODELS WITH MISSING SHOCKS

In this paper we analyze the propagation of shocks originating in sectors that are not present in a baseline dynamic stochastic general equilibrium (DSGE) model. Specifically, we proxy the missing sector through a small set of factors that feed into the structural shocks of the DSGE model to create correlated disturbances. We estimate the factor structure by either matching impulse responses of the augmented DSGE model to those generated by an auxiliary model or by using Bayesian techniques. We apply this methodology to track the effects of oil shocks and housing demand shocks in models without energy or housing sectors. Copyright © 2014 John Wiley & Sons, Ltd.     

The Zero Lower Bound and Parameter Bias in an Estimated DSGE Model

This paper examines how and to what extent parameter estimates can be biased in a dynamic stochastic general equilibrium (DSGE) model that omits the zero lower bound (ZLB) constraint on the nominal interest rate. Our Monte Carlo experiments using a standard sticky‐price DSGE model show that no significant bias is detected in parameter estimates and that the estimated impulse response functions are quite similar to the true ones. However, as the frequency of being at the ZLB or the duration of ZLB spells increases, the parameter bias becomes larger and therefore leads to substantial differences between the estimated and true impulse responses. It is also demonstrated that the model missing the ZLB causes biased estimates of structural shocks even with the virtually unbiased parameters. Copyright © 2015 John Wiley & Sons, Ltd.     

Professional forecasters and real-time forecasting with a DSGE model

This paper analyses the real-time forecasting performance of the New Keynesian DSGE model of Galí, Smets and Wouters (2012), estimated on euro area data. It investigates the extent to which the inclusion of forecasts of inflation, GDP growth and unemployment by professional forecasters improve the forecasting performance. We consider two approaches for conditioning on such information. Under the “noise” approach, the mean professional forecasts are assumed to be noisy indicators of the rational expectations forecasts implied by the DSGE model. Under the “news” approach, it is assumed that the forecasts reveal the presence of expected future structural shocks in line with those estimated in the past. The forecasts of the DSGE model are compared with those from a Bayesian VAR model, an AR(1) model, a sample mean and a random walk.     

Endogenous business cycle propagation and the persistence problem: The role of labor-market frictions

Contrasting sharply with a recent trend in DSGE modeling, we propose a business cycle model where frictions and shocks are chosen with parsimony. The model emphasizes a few labor-market frictions and shocks to monetary policy and technology. The model, estimated from U.S. quarterly postwar data, accounts well for important differences in the serial correlation of the growth rates of aggregate quantities, the size of aggregate fluctuations and key comovements, including the correlation between hours and labor productivity. Despite its simplicity, the model offers an answer to the persistence problem (Chari et al., 2000) that does not rely on multiple frictions and adjustment lags or ad hoc backward-looking components. We conclude modern DSGE models need not embed large batteries of frictions and shocks to account for the salient features of postwar business cycles.     

FACTOR ANALYSIS OF A LARGE DSGE MODEL

We study the workings of the factor analysis of high‐dimensional data using artificial series generated from a large, multi‐sector dynamic stochastic general equilibrium (DSGE) model. The objective is to use the DSGE model as a laboratory that allows us to shed some light on the practical benefits and limitations of using factor analysis techniques on economic data. We explain in what sense the artificial data can be thought of having a factor structure, study the theoretical properties of the principal components estimates of the factor space, investigate the substantive reason(s) for the good performance of diffusion index forecasts, and assess the quality of the factor analysis of highly disaggregated data. In all our exercises, we explain the precise relationship between the factors and the basic macroeconomic shocks postulated by the model. Copyright © 2012 John Wiley & Sons, Ltd.     

Coordination and non-coordination risks of monetary and macroprudential authorities: A robust welfare analysis

This study compares a central bank’s leaning against the wind approach with a mix of monetary and macroprudential policies under parameter uncertainty in an estimated DSGE model with two financial frictions. We show that uncertainty of the economic environment is an essential constituent in properly designing macroprudential policy. Although coordination between monetary and macroprudential policies minimizes the policymakers’ Bayesian risk, coordination and non-coordination risks threaten the goals of both authorities. The former describes the situation where the authorities partly resign from implementing the monetary policy objectives to stabilize macroprudential risk. The latter is when conducting a non-coordinated macroprudential policy induces higher total Bayesian risk than when only the central bank minimizes the expected total welfare loss. The robust Bayesian macroeconomic rules show that when financial shocks shrink the banks’ or entrepreneurial net worth, a contractionary macroprudential policy should be combined with an expansionary monetary policy. However, if capital adequacy ratio or risk shocks strike the economy, such a conflict in macroeconomics policy instruments disappears, thus synchronizing both policies.     

Endogenous risk in a DSGE model with capital-constrained financial intermediaries

This paper proposes a perturbation-based approach to implement the idea of endogenous financial risk in a standard DSGE macro-model. Recent papers, such as Mendoza (2010), Brunnermeier and Sannikov (2012) and He and Krishnamurthy (2012), that have stimulated the research field on endogenous risk in a macroeconomic context, are based on sophisticated solution methods that are not easily applicable in larger models. We propose an approximation method that allows us to capture some of the basic insights of this literature in a standard macro-model. We are able to identify an important risk-channel that derives from the risk aversion of constrained intermediaries and that contributes significantly to the overall financial and macroeconomic volatility.     

Investment shocks and the comovement problem

Recent work based on sticky price-wage estimated dynamic stochastic general equilibrium (DSGE) models suggests investment shocks are the most important drivers of post-World War II US business cycles. Consumption, however, typically falls after an investment shock. This finding sits oddly with the observed business cycle comovement where consumption, along with hours-worked and investment, moves with economic activity. We show that this comovement problem is resolved in an estimated DSGE model when (i) the cost of capital utilization is specified in terms of increased depreciation of capital, as originally proposed by Greenwood et al. (1988) in a neoclassical setting, or (ii) there is no wealth effect on labor supply. The data, however, favors the first channel. Traditionally, the cost of utilization is specified in terms of forgone consumption following Christiano et al. (2005), who studied the effects of monetary policy shocks. The alternative specification we consider has two additional implications relative to the traditional one: (i) it has a substantially better fit with the data and (ii) the contribution of investment shocks to the variance of consumption is over three times larger. The contributions to output, investment, and hours, are also relatively higher, suggesting that these shocks may be quantitatively even more important than previous estimates based on the traditional specification.     

Marginalized Predictive Likelihood Comparisons of Linear Gaussian State‐Space Models with Applications to DSGE,DSGE‐VAR,and VAR Models

The predictive likelihood is useful for ranking models in forecast comparison exercises using Bayesian inference. We discuss how it can be estimated, by means of marzginalization, for any subset of the observables in linear Gaussian state‐space models. We compare macroeconomic density forecasts for the euro area of a DSGE model to those of a DSGE‐VAR, a BVAR and a multivariate random walk over 1999:Q1–2011:Q4. While the BVAR generally provides superior forecasts, its performance deteriorates substantially with the onset of the Great Recession. This is particularly notable for longer‐horizon real GDP forecasts, where the DSGE and DSGE‐VAR models perform better. Copyright © 2016 John Wiley & Sons, Ltd.     

Monetary policy shocks: We got news!

We assess the role of monetary policy news shocks in the context of a medium scale DSGE model estimated on US data. We estimate several versions of the model and find decisive evidence in favour of the inclusion of monetary policy news shocks over a two-quarter horizon. According to our results, monetary policy news shocks account for a non-negligible fraction of the variance of real variables, especially at shorter forecast horizons. Further, we document that the importance of monetary policy news shocks goes beyond what was observed in recent years. The historical importance of monetary policy news shocks dates back to the 1999–2006 period when the official FOMC statements provided information about both the current policy setting and the expected future policy path. We also show that adding monetary policy news shocks to the model does not lead to identification problems.     

Financial Intermediaries,Credit Shocks and Business Cycles

We document the cyclical properties of aggregate balance sheet variables of the US commercial banks: (i) Bank credits and deposits are less volatile than output, while net worth and leverage ratio are several times more volatile, (ii) bank credits and net worth are procyclical, while deposits, leverage ratio and loan spread are countercyclical. We then present a real business cycle model with a financial sector to investigate how the dynamics of macroeconomic aggregates and balance sheet variables of the US banks are influenced by empirically disciplined shocks to bank net worth. Both calibrated and estimated versions of the model show that these financial shocks are important not only for explaining the dynamics of financial flows but also for the dynamics of macroeconomic variables. We find that the recent deterioration in aggregate net worth of the US banking sector contributed significantly to the 2007–09 recession.     

Learning and time-varying macroeconomic volatility

This paper presents a DSGE model in which agents׳ learning about the economy can endogenously generate time-varying macroeconomic volatility. Economic agents use simple models to form expectations and need to learn the relevant parameters. Their gain coefficient is endogenous and is adjusted according to past forecast errors.The model is estimated using likelihood-based Bayesian methods. The endogenous gain is jointly estimated with the structural parameters of the system.The estimation results show that private agents appear to have often switched to constant-gain learning, with a high constant gain, during most of the 1970s and until the early 1980s, while reverting to a decreasing gain later on. As a result, the model can generate a pattern of volatility, which is increasing in the 1970s and falling in the second half of the sample, with a decline that can roughly match the magnitude of the so-called “Great Moderation” in the 1984–2007 period. The paper also documents how a failure to incorporate learning into the estimation may lead econometricians to spuriously find time-varying volatility in the exogenous shocks, even when these have constant variance by construction.     

NON‐LINEAR DSGE MODELS AND THE CENTRAL DIFFERENCE KALMAN FILTER

This paper introduces a quasi maximum likelihood approach based on the central difference Kalman filter to estimate non‐linear dynamic stochastic general equilibrium (DSGE) models with potentially non‐Gaussian shocks. We argue that this estimator can be expected to be consistent and asymptotically normal for DSGE models solved up to third order. These properties are verified in a Monte Carlo study for a DSGE model solved to second and third order with structural shocks that are Gaussian, Laplace distributed, or display stochastic volatility. Copyright © 2012 John Wiley & Sons, Ltd.