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.     

Risk Premium Shocks and the Zero Bound on Nominal Interest Rates

Quantitative dynamic stochastic general equilibrium (DSGE) models often admit that the zero bound on nominal interest rates does not constrain (optimal) monetary policy. Recent economic events, however, have reinforced the relevance of the zero bound. This paper sheds some light on this disconnect by studying a broad range of shocks within a standard DSGE model. In contrast to earlier studies, we find that risk premium shocks are key to building quantitative models where the zero bound is relevant for monetary policy design. Other commonly included shocks, such as productivity, government spending, and money demand shocks, are unable to push nominal rates close to zero.     

Local identification in DSGE models

The issue of identification arises whenever structural models are estimated. Lack of identification means that the empirical implications of some model parameters are either undetectable or indistinguishable from the implications of other parameters. Therefore, identifiability must be verified prior to estimation. This paper provides a simple method for conducting local identification analysis in linearized DSGE models, estimated in both full and limited information settings. In addition to establishing which parameters are locally identified and which are not, researchers can determine whether the identification failures are due to data limitations, such as lack of observations for some variables, or whether they are intrinsic to the structure of the model. The methodology is illustrated using a medium-scale DSGE model.     

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.     

居民风险偏好与中国货币政策的宏观经济效应——基于DSGE模型的数量分析

当前,我国宏观经济形势复杂多变,货币政策实施效果的影响因素随之呈现多样化特征。在此背景下,本文试图以风险偏好为研究视角,对我国居民风险偏好水平变动与货币政策宏观经济效应之间的关系进行分析。本文以标准新凯恩斯模型为基础,构造符合我国宏观经济现实特征的DSGE(动态随机一般均衡)模型,并对转型时期的最优混合型货币政策规则进行研究;为进一步强调货币在中国宏观经济波动中所扮演的重要角色,模型中引入消费和实际货币余额不可分的跨期效用函数形式。研究结果表明:(1)包含名义货币增长的混合型泰勒规则拟合我国转型时期的货币政策规则效果最佳,因此货币供应量仍是重要的政策工具;(2)与可分性模型相比,不可分模型拟合我国宏观经济现实特征的效果更优。在不可分效用函数下,与货币供应量相关的实际货币余额将影响经济的产出缺口和通货膨胀,使得居民风险偏好成为决定货币政策效果的重要因素。具体而言,当居民风险偏好水平上升时,货币政策对我国宏观经济波动的影响随之增强。因此,在选择货币政策实施时点上,应充分考虑市场中的风险偏好情况,从而更好地发挥货币政策调控宏观经济的职能。     

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.     

居民风险偏好与中国货币政策的宏观经济效应——基于DSGE模型的数量分析

当前,我国宏观经济形势复杂多变,货币政策实施效果的影响因素随之呈现多样化特征。在此背景下,本文试图以风险偏好为研究视角,对我国居民风险偏好水平变动与货币政策宏观经济效应之间的关系进行分析。本文以标准新凯恩斯模型为基础,构造符合我国宏观经济现实特征的DSGE(动态随机一般均衡)模型,并对转型时期的最优混合型货币政策规则进行研究;为进一步强调货币在中国宏观经济波动中所扮演的重要角色,模型中引入消费和实际货币余额不可分的跨期效用函数形式。研究结果表明:(1)包含名义货币增长的混合型泰勒规则拟合我国转型时期的货币政策规则效果最佳,因此货币供应量仍是重要的政策工具;(2)与可分性模型相比,不可分模型拟合我国宏观经济现实特征的效果更优。在不可分效用函数下,与货币供应量相关的实际货币余额将影响经济的产出缺口和通货膨胀,使得居民风险偏好成为决定货币政策效果的重要因素。具体而言,当居民风险偏好水平上升时,货币政策对我国宏观经济波动的影响随之增强。因此,在选择货币政策实施时点上,应充分考虑市场中的风险偏好情况,从而更好地发挥货币政策调控宏观经济的职能。     

Exploring international differences in inflation dynamics

Standard closed-economy DSGE models have difficulty replicating the persistence of inflation. We use a multicountry dataset to establish some empirical regularities on persistence and volatility of aggregate consumer prices for 135 countries since 1993. We find both persistence and volatility to be low (high) in developed (developing) countries relative to the full sample average. This pattern is also observed in low (high) inflation countries. We then employ a two-country DSGE framework to investigate the extent to which structural open economy features, such as incomplete exchange rate pass-through, the existence of nontraded goods, and international financial market incompleteness, can help in replicating the persistence and volatility of consumer prices. Our simulation results indicate that the model can replicate the degree of inflation persistence seen in the data for both developed and developing countries, but cannot generate the low levels of volatility observed in developed economies.     

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.     

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.     

Monetary policy shocks and financial conditions: A Monte Carlo experiment

The effects of monetary policy shocks on financial conditions are often estimated by appealing to recursive Vector AutoRegressions (VARs). We assess the ability of this class of VARs to recover the true effects of a monetary policy shock via a Monte Carlo experiment in which the Data Generating Process is a Dynamic Stochastic General Equilibrium (DSGE) model featuring macro-finance interactions and estimated with U.S. quarterly data. Our DSGE model predicts a negative and significant reaction of financial conditions to an unexpected monetary policy tightening. We point out that such reaction is just overlooked by recursive VARs. Moreover, we show that Cholesky-VARs may substantially underestimate the welfare costs due to macroeconomic fluctuations.     

Tax Evasion,Investment Shocks,and the Consumption Puzzle: A DSGE Analysis with Financial Frictions

Recent studies identify Marginal Efficiency of Investment (MEI) shocks as important drivers of the business cycle. However, Dynamic Stochastic General Equilibrium (DSGE) models struggle to explain macroeconomic comovements between consumption and the key real variables after a MEI shock. Moreover, engaging in tax evasion practices is often an answer to financial constraints, which have been recognized as important determinants of cyclical fluctuations as well. We use a medium-scale New Keynesian DSGE model, that combines tax evasion with financial frictions, to simulate a MEI shock. We show that entrepreneurial tax evasion can solve the comovement problem to a fair extent.     

Measuring prior sensitivity and prior informativeness in large Bayesian models

In large Bayesian models, such as modern DSGE models, it is difficult to assess how much the prior affects the results. This paper derives measures of prior sensitivity and prior informativeness that account for the high dimensional interaction between prior and likelihood information. The basis for both measures is the derivative matrix of the posterior mean with respect to the prior mean, which is easily obtained from Markov Chain Monte Carlo output. We illustrate the approach by examining posterior results in the small model of Lubik and Schorfheide (2004) and the large model of Smets and Wouters (2007).     

我国DSGE模型的开发及在货币政策分析中的应用

DSGE模型是近年来宏观经济及货币政策分析方面关注的一个重要研究方向,也是中央银行在经济建模方面的一个新视角,该模型的显性建模框架、理论一致性、微观和宏观分析的完美结合、长短期分析的有机整合等独特性日益受到中央银行的青睐。本文结合我国的实际情况,建立了一个带有金融加速器的开放经济DSGE模型,基于我国的数据,采用Bayes技术估计了我国的DSGE模型,并利用该模型进行了政策分析。     

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.     

Econometric models of the Eleventh District Cost of Funds Index

The Eleventh District Cost of Funds Index (COFI) is a popular index for pricing adjustable-rate mortgages. COFI is calculated from the interest expenses incurred by thrifts when raising funds. It is a mixture of current and past interest rates on many different financial instruments. COFI can be modelled well with simple econometric models. Commonly used, simple COFI models are compared using a method developed by Hendry (1989). Some of these models, which appear to fit the data well, have nonrobust parameters, significant serial correlation, and heteroscedastic errors. These poorly specified models may lead to systematic mispricing of COFI mortgages. Once a robust econometric model is chose, the lagged adjustment of COFI to movements in interest rates can be incorporated into mortgage pricing models.     

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.     

Markov-switching in target stocks during takeover bids

This paper examines shifts in the market betas and the conditional volatility of stock prices of takeover targets. Using daily stock prices of five European and American targets, we find that adequately specified Markov-switching GARCH models are capable of detecting statistically significant regime-switches in all takeover deal-types (in cash bids, pure share-exchange bids, mixed bids). In particular, conditional volatility regime-switches are found to be most clear-cut for cash bids. Our econometric findings have implications for a broad range of financial applications such as the valuation of target stock options.     

The effects of the near-zero interest rate policy in a regime-switching dynamic stochastic general equilibrium model

Standard Dynamic Stochastic General Equilibrium (DSGE) models cannot explain the near-zero interest rate policy (near-ZIRP) by the Federal Reserve. I study two methods of modeling the near-ZIRP in DSGE models: the perfect foresight model and the Markov regime-switching model developed in this paper. The near-ZIRP has a significant expansionary effect, and the regime-switching model generates a more realistic predicted path of macro variables than the perfect foresight model. Furthermore, the government purchases multiplier in the near-ZIRP regime is smaller than what the literature finds at the zero lower bound (ZLB), and the contractionary effects of higher productivity found by the recent literature at the ZLB are not present in the regime-switching model.     

Assessing the Macroeconomic Effects of LTROs during the Great Recession

In response to the 2008–2009 crisis, faced with distressed financial intermediaries, the European Central Bank (ECB) embarked in longer term refinancing operations (LTROs) with full allotment. Using an estimated DSGE model with a frictional banking sector, we find that such liquidity injections have played a key role in averting a major credit crunch. A counterfactual analysis suggests that, absent these nonconventional measures, output, consumption, investment, and the GDP deflator would have been 2.5%, 0.5%, 9.7%, and 0.5% lower on average over 2009, respectively.