How Sticky Is Sticky Enough? A Distributional and Impulse Response Analysis of New Keynesian DSGE Models

In this paper, we add to the literature on the assessment of how well data simulated from new-Keynesian dynamic stochastic general equilibrium (DSGE) models reproduce the dynamic features of historical data. In particular, we evaluate sticky price, sticky price with dynamic indexation, and sticky information models using impulse response and correlation measures and via implementation of a distribution based approach for comparing (possibly) misspecified DSGE models using simulated and historical inflation and output gap data. One of our main findings is that for a standard level of stickiness (i.e., annual price or information adjustment), the sticky price model with indexation dominates other models. We also find that when a lower level of information and price stickiness is used (i.e., bi-annual adjustment), there is much less to choose between the models (see Bils and Klenow 2004 , for evidence in favor of lower levels of stickiness). This finding is due to the fact that simulated and historical densities are "much" closer under bi-annual adjustment.     

Forming priors for DSGE models (and how it affects the assessment of nominal rigidities)

We discuss prior elicitation for the parameters of dynamic stochastic general equilibrium (DSGE) models, and provide a method for constructing prior distributions for a subset of these parameters from beliefs about steady-state relationships and second moments of the endogenous variables. The empirical application documents how the specification of the prior distribution affects our assessment of the relative importance of price and wage rigidities in a New Keynesian DSGE model.     

Non-stationary Hours in a DSGE Model

The time series fit of dynamic stochastic general equilibrium (DSGE) models often suffers from restrictions on the long-run dynamics that are at odds with the data. Using Bayesian methods we estimate a stochastic growth model in which hours worked are stationary and a modified version with permanent labor supply shocks. If firms can freely adjust labor inputs, the data support the latter specification. Once we introduce frictions in terms of labor adjustment costs, the overall time series fit improves and the model specification in which labor supply shocks and hours worked are stationary is preferred.     

Predicting Long‐Term Financial Returns: VAR versus DSGE Model—A Horse Race

This paper considers a U.S. institutional investor who is implementing a long‐term portfolio allocation using forecasts of financial returns. We compare the predictive performance of two competing macrofinance models—an unrestricted vector autoRegression (VAR) and a fully‐structural dynamic stochastic general equilibrium (DSGE) model—for horizons up to 15 years. Although the performances are similar for short horizons, the DSGE model outperforms the VAR at forecasting financial returns in the long term. This model also generates substantially higher Sharpe ratios. Although it contains fewer unknown parameters, it benefits from economically grounded restrictions that help anchor financial returns in the long term.     

House Prices and Government Spending Shocks

We show that dynamic stochastic general equilibrium (DSGE) models with housing and collateralized borrowing predict a fall in house prices following positive government spending shocks. By contrast, we show that house prices in the United States rise persistently after identified positive government spending shocks. We clarify that the incorrect house price response is due to a general property of DSGE models—approximately constant shadow value of housing—and that modifying preferences and production structure cannot help in obtaining the correct house price response. Properly accounting for the empirical evidence on government spending shocks and house prices using a DSGE model therefore remains a significant challenge.     

Putting the New Keynesian DSGE Model to the Real‐Time Forecasting Test

The paper compares the quality of real‐time forecasts from a standard medium‐scale New Keynesian dynamic stochastic general equilibrium (DSGE) model to those from the Survey of Professional Forecasters (SPF) and DSGE‐VARs. It is shown that the DSGE model is relatively successful in forecasting the U.S. economy. This is especially true for forecasts conditional on SPF nowcasts, in which case the forecasting power of the DSGE turns out to be similar or better than that of the SPF for all the variables and horizons. An important weakness of the benchmark DSGE model is the poor absolute performance of its point forecasts and rather badly calibrated forecast densities.     

Vector autoregressions and reduced form representations of DSGE models

The performance of dynamic stochastic general equilibrium models is often tested against estimated VARs. This requires that the data-generating process consistent with the DSGE theoretical model has a finite order VAR representation. This paper discusses the assumptions needed for a finite order VAR(p) representation of a DSGE model to exist. When a VAR(p) is only an approximation to the exact infinite order VAR, the truncated VAR(p) may return largely incorrect estimates of the impulse response function. The results do not hinge on small-sample bias or on incorrect identification assumptions. But the bias introduced by truncation can lead to bias in the identification of the structural shocks. Identification strategies that work in the exact VAR representation perform poorly in the truncated VAR.     

Where is the GE? Consumption Dynamics in DSGEs

We offer a partial equilibrium perspective on the behavior of consumption in dynamic stochastic general equilibrium (DSGE) models. We consider a benchmark dynamic general equilibrium model and show that a standard calibration implies that the real interest rate is essentially fixed. One manifestation of this feature is that, with separable preferences, the reaction of consumption to total factor productivity (TFP) shocks is flat: the random‐walk permanent income hypothesis holds almost exactly, pretty much as in a partial equilibrium consumption‐savings problem. These results help explain the prominent role of aggregate demand, and how it is achieved, in modern DSGE analysis.     

Back to square one: Identification issues in DSGE models

We investigate identification issues in DSGE models and their consequences for parameter estimation and model evaluation when the objective function measures the distance between estimated and model-based impulse responses. Observational equivalence, partial and weak identification problems are widespread and typically produced by an ill-behaved mapping between the structural parameters and the coefficients of the solution. Different objective functions affect identification and small samples interact with parameters identification. Diagnostics to detect identification deficiencies are provided and applied to a widely used model.     

On Targeting Frameworks And Optimal Monetary Policy

We show that speed limit policy, a monetary policy strategy that focuses on stabilizing inflation and the change in the output gap, consistently outperforms flexible inflation targeting and flexible price level targeting in empirical medium‐scale DSGE models under discretionary policymaking. In contrast to small‐scale New Keynesian models, this welfare ranking of the targeting frameworks is not overturned when inflation dynamics are mostly backward‐looking. Importantly, the performance of the speed limit policy shows less sensitivity to its parameterization than other frameworks that target the inflation rate or the price level.     

Examining the bond premium puzzle with a DSGE model

The basic inability of standard theoretical models to generate a sufficiently large and variable nominal bond risk premium has been termed the “bond premium puzzle.” We show that the term premium on long-term bonds in the canonical dynamic stochastic general equilibrium (DSGE) model used in macroeconomics is far too small and stable relative to the data. We find that introducing long-memory habits in consumption as well as labor market frictions can help fit the term premium, but only by seriously distorting the DSGE model's ability to fit other macroeconomic variables, such as the real wage; therefore, the bond premium puzzle remains.     

The Phillips curve under state-dependent pricing

We derive a Phillips curve equation from the dynamic stochastic general equilibrium (DSGE) model with state-dependent pricing developed by Dotsey et al. [1999. State-dependent pricing and the general equilibrium dynamics of money and output. Quarterly Journal of Economics 114, 655-690]. This state-dependent Phillips curve encompasses the new Keynesian Phillips curve (NKPC) based on Calvo-type price setting as a special case. We analyze the effect of the state-dependent terms (that is, the variations in the distributions of price vintages) on inflation persistence, and we examine whether the hybrid NKPC (that is, the NKPC extended by a lagged inflation term) can adequately describe inflation dynamics generated in a calibrated state-dependent pricing economy.     

Equilibrium Indeterminacy and Asset Price Fluctuation in Japan: A Bayesian Investigation

This paper investigates sources of asset price fluctuation in Japan using an estimated financial accelerator model. For explicit treatment of expectational beliefs characterized by sunspots, the model is analyzed over the parameter space where the equilibrium can be indeterminate. We show that indeterminacy arises if the financial accelerator effect is sufficiently large. According to our Bayesian estimation results, Japan's economy was affected by sunspot shocks; however, the contribution of the sunspots to asset price volatility was low. Rather, net worth and cost shocks drove the asset price fluctuation. We find, however, that the sunspots substantially affected capital investment.     

Dealing with financial instability under a DSGE modeling approach with banking intermediation: A predictability analysis versus TVP-VARs

In the dynamic stochastic general equilibrium (DSGE) literature there has been an increasing awareness on the role that the banking sector can play in macroeconomic activity. We present a DSGE model with financial intermediation as in Gertler and Karadi (2011). The estimation of shocks and of the structural parameters shows that time-variation should be crucial in any attempted empirical analysis. Since DSGE modelling usually fails to take into account inherent nonlinearities of the economy, we propose a novel time-varying parameter (TVP) state-space estimation method for VAR processes both for homoskedastic and heteroskedastic error structures. We conduct an exhaustive empirical exercise to compare the out-of-sample predictive performance of the estimated DSGE model with that of standard ARs, VARs, Bayesian VARs and TVP-VARs. We find that the TVP-VAR provides the best forecasting performance for the series of GDP and net worth of financial intermediaries for all steps-ahead, while the DSGE model outperforms the other specifications in forecasting inflation and the federal funds rate at shorter horizons.     

An econometric analysis of emission allowance prices

Knowledge of the statistical distribution of the prices of emission allowances, and their forecastability, are crucial in constructing, among other things, purchasing and risk management strategies in the emissions-constrained markets. This paper analyzes the two emission permits markets, CO₂ in Europe, and SO₂ in the US, and investigates a model for dealing with the unique stylized facts of this type of data. Its effectiveness in terms of model fit and out-of-sample value-at-risk-forecasting, as compared to models commonly used in risk-forecasting contexts, is demonstrated.     

Instability of sunspot equilibria in real business cycle models under adaptive learning

We provide conditions under which a general, reduced-form class of real business cycle (RBC) models has rational expectations equilibria that are both indeterminate and stable under adaptive learning. Indeterminacy of equilibrium allows for the possibility that non-fundamental “sunspot” variable realizations can be used to drive the model, and several researchers have offered calibrated structural models where sunspot shocks play such a role. However, we show that the structural restrictions researchers have adopted lead to reduced-form systems that are always unstable under adaptive learning dynamics, thus calling into question the plausibility of these sunspot-driven RBC models.     

What Drives the Owner‐Occupied and Rental Housing Markets? Evidence from an Estimated DSGE Model

Most dynamic stochastic general equilibrium (DSGE) models with a housing market do not explicitly include a rental market and assume a tight mapping between house prices and rents over the business cycle. However, rents are much smoother than house prices in the data. We match this feature of the data by adding both an owner‐occupied housing market and a rental market in a standard DSGE model. The intertemporal preference shock accounts for more than half of the variation in house prices and contributes to residential investment fluctuations through the liquidity constraint, and nominal rigidity in rental contracts captures the variation in the price‐rent ratio.     

货币超发是中国通货膨胀的根源吗?——基于DSGE模型不确定均衡解的分析

本文构建了一个充分反映中国宏观经济结构和体制特征的DSGE模型,并用贝叶斯估计方法对模型进行了估计和分析。我们发现,中国宏观经济存在非确定均衡解,自我实现的通胀预期对中国通货膨胀和产出波动有显著的影响,逆向供给冲击是近年来中国通货膨胀的主要原因。通过反事实模拟方法,我们发现近年来我国央行实施的实际货币政策基本符合最优货币政策,我们还估算中国货币增长长期目标的适度水平为18%左右,过高或过低的货币增长率都会加大消费和通货膨胀的波动,并降低社会的长期福利水平。     

Estimation of DSGE models when the data are persistent

Dynamic stochastic general equilibrium (DSGE) models are often solved and estimated under specific assumptions as to whether the exogenous variables are difference or trend stationary. However, even mild departures of the data generating process from these assumptions can severely bias the estimates of the model parameters. This paper proposes new estimators that do not require researchers to take a stand on whether shocks have permanent or transitory effects. These procedures have two key features. First, the same filter is applied to both the data and the model variables. Second, the filtered variables are stationary when evaluated at the true parameter vector. The estimators are approximately normally distributed not only when the shocks are mildly persistent, but also when they have near or exact unit roots. Simulations show that these robust estimators perform well especially when the shocks are highly persistent yet stationary. In such cases, linear detrending and first differencing are shown to yield biased or imprecise estimates.     

Determinacy, Learnability, and Monetary Policy Inertia

We show how monetary policy inertia can help alleviate problems of indeterminacy and non-existence of stationary equilibrium observed for some commonly studied monetary policy rules. We also find that inertia promotes learnability of equilibrium. The context is a simple, forward-looking model of the macroeconomy widely used in the rapidly expanding literature in this area. We conclude that this might be an important reason why central banks in the industrialized economies display considerable inertia when adjusting monetary policy in response to changing economic conditions.