What (really) accounts for the fall in hours after a technology shock?

The paper asks how state of the art DSGE models that account for the conditional response of hours following a positive neutral technology shock compare in a marginal likelihood race. To that end we construct and estimate several competing small-scale DSGE models that extend the standard real business cycle model. In particular, we identify from the literature six different hypotheses that generate the empirically observed decline in hours worked after a positive technology shock. These models alternatively exhibit (i) sticky prices; (ii) firm entry and exit with time to build; (iii) habit in consumption and costly adjustment of investment; (iv) persistence in the permanent technology shocks; (v) labor market friction with procyclical hiring costs; and (vi) Leontief production function with labor-saving technology shocks. In terms of model posterior probabilities, impulse responses, and autocorrelations, the model favored is the one that exhibits habit formation in consumption and investment adjustment costs. A robustness test shows that the sticky price model becomes as competitive as the habit formation and costly adjustment of investment model when sticky wages are included.     

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.     

By force of demand: Explaining cyclical fluctuations of international trade and government spending

This paper explores the role of demand shocks, as an alternative to productivity shocks, in driving both domestic and international business cycles within the international real business cycle (IRBC) framework. In addition to those well-documented domestic business cycle fluctuations (e.g., the volatility and cyclicality of output, consumption, investment, labor hours, and labor productivity) and international business cycle properties (e.g., the countercyclical net export and the comovement puzzle), this paper focuses on two additional stylized facts in the industrialized countries: the procyclical trade openness (the GDP fraction of trade volume) and the countercyclical government size (the GDP fraction of government spending). Using a parsimonious dynamic stochastic general equilibrium model, we show that the model׳s predictions under productivity shocks are not consistent with these facts. Instead, a demand-shock-driven model replicates the above facts while matching other domestic and international business cycle properties. An estimated version of the model confirms the quantitatively important impacts of demand shocks.     

Interpreting shocks to the relative price of investment with a two-sector model

Consumption and investment comove over the business cycle in response to shocks that permanently move the price of investment. The interpretation of these shocks has relied on standard one-sector models or on models with two or more sectors that can be aggregated. We show that the same interpretation can also be motivated with a model that captures key features of the US Input–Output Tables and cannot be aggregated into a standard one-sector model. Our alternative model yields a closer match to the empirical evidence of positive comovement for consumption and investment subject shocks that permanently move the price of investment.     

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.     

Estimating contract indexation in a Financial Accelerator Model

This paper addresses the positive implications of indexing risky debt to observable aggregate conditions. These issues are pursued within the context of the celebrated financial accelerator model of Bernanke et al. (1999). The principal conclusions include: (1) the estimated level of indexation is significant, (2) the business cycle properties of the model are significantly affected by this degree of indexation, (3) the importance of investment shocks in the business cycle depends upon the estimated level of indexation, and (4) although the data prefers the financial model with indexation over the frictionless model, they have remarkably similar business cycle properties for non-financial exogenous shocks.     

Consumer misperceptions,uncertain fundamentals,and the business cycle

This paper estimates the importance of shocks to consumer misperceptions “noise shocks” for U.S. business cycle fluctuations. I embed imperfect information as in Lorenzoni (2009) into a Smets and Wouters (2007)-type DSGE model. Agents only observe aggregate productivity and a signal about the permanent component contaminated with noise. Based on this information agents form beliefs about the temporary and the permanent component of productivity. Shocks to the signal (noise shocks) trigger aggregate fluctuations unrelated to changes in productivity. Bayesian estimation shows that noise shocks explain up to 14 percent of output and up to 25 percent of consumption fluctuations. Nominal rigidities and the specification of the monetary policy rule are crucial for the importance of noise shocks. These features help to resolve conflicting results in the previous literature.     

CES technology and business cycle fluctuations

We contribute to an emerging literature that brings the constant elasticity of substitution (CES) specification of the production function into the analysis of business cycle fluctuations. Using US data, we estimate by Bayesian-Maximum-Likelihood methods a standard medium-sized DSGE model with a CES rather than Cobb–Douglas (CD) technology. We estimate a elasticity of substitution between capital and labour well below unity at 0.15–0.18. In a marginal likelihood race CES decisively beats the CD production and this is matched by its ability to fit the data better in terms of second moments. We show that this result is mainly driven by the implied fluctuations of factor shares under the CES specification. The CES model performance is further improved when the estimation is carried out under an imperfect information assumption. Hence the main message for DSGE models is that we should dismiss once and for all the use of CD for business cycle analysis.     

Sentiment and the U.S. business cycle

Psychological factors are commonly believed to play a role on cyclical economic fluctuations, but they are typically omitted from state-of-the-art macroeconomic models.This paper introduces “sentiment” in a medium-scale DSGE model of the U.S. economy and tests the empirical contribution of sentiment shocks to business cycle fluctuations.The assumption of rational expectations is relaxed. The paper exploits, instead, observed data on expectations in the estimation. The observed expectations are assumed to be formed from a near-rational learning model. Agents are endowed with a perceived law of motion that resembles the model solution under rational expectations, but they lack knowledge about the solution’s reduced-form coefficients. They attempt to learn those coefficients over time using available time series at each point in the sample and updating their beliefs through constant-gain learning. In each period, however, they may form expectations that fall above or below those implied by the learning model. These deviations capture excesses of optimism and pessimism, which can be quite persistent and which are defined as sentiment in the model. Different sentiment shocks are identified in the empirical analysis: waves of undue optimism and pessimism may refer to expected future consumption, future investment, or future inflationary pressures.The results show that exogenous variations in sentiment are responsible for a sizable (above forty percent) portion of historical U.S. business cycle fluctuations. Sentiment shocks related to investment decisions, which evoke Keynes’ animal spirits, play the largest role. When the model is estimated imposing the rational expectations hypothesis, instead, the role of structural investment-specific and neutral technology shocks significantly expands to capture the omitted contribution of sentiment.     

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.     

DSGE Models in the Frequency Domains

We use frequency domain techniques to estimate a medium‐scale dynamic stochastic general equilibrium (DSGE) model on different frequency bands. We show that goodness of fit, forecasting performance and parameter estimates vary substantially with the frequency bands over which the model is estimated. Estimates obtained using subsets of frequencies are characterized by significantly different parameters, an indication that the model cannot match all frequencies with one set of parameters. In particular, we find that: (i) the low‐frequency properties of the data strongly affect parameter estimates obtained in the time domain; (ii) the importance of economic frictions in the model changes when different subsets of frequencies are used in estimation. This is particularly true for the investment adjustment cost and habit persistence: when low frequencies are present in the estimation, the investment adjustment cost and habit persistence are estimated to be higher than when low frequencies are absent. Copyright © 2014 John Wiley & Sons, Ltd.     

Real rigidities, productivity improvements and investment dynamics

The theoretical literature on business cycles predicts a positive investment response to productivity improvements, a prediction we question from theoretical and empirical perspectives. We show that a short-term negative response of investment to a positive technology shock is consistent with a reasonably parameterized new Keynesian dynamic stochastic general equilibrium (DSGE) model in which firm-specific capital introduces an additional real rigidity, and monetary policy is not fully accommodative. Employing Bayesian techniques, we provide evidence that permanent productivity improvements have short-term, contractionary effects on investment. Although this result can be obtained from both firm-specific and rental capital models, only in the case of the former is the average price duration in line with the microeconometric evidence.     

In Search of the Transmission Mechanism of Fiscal Policy in the Euro Area

This paper applies the DSGE‐VAR methodology to assess the size of fiscal multipliers in the data and the relative contributions of two transmission mechanisms of government spending shocks, namely hand‐to‐mouth consumers and Edgeworth complementarity. Econometric experiments show that a DSGE model with Edgeworth complementarity is a better representation of the transmission mechanism of fiscal policy as it yields dynamic responses close to those obtained with the flexible DSGE‐VAR model (i.e. an impact output multiplier larger than one and a crowding‐in of private consumption). The estimated share of hand‐to‐mouth consumers is too small to replicate the positive response of private consumption. Copyright © 2016 John Wiley & Sons, Ltd.     

Optimal taxation in an RBC model: A linear-quadratic approach

We reconsider the optimal taxation of income from labor and capital in the stochastic growth model analyzed by Chari et al. [1994. Optimal fiscal policy in a business cycle model. Journal of Political Economy 102, 617–652; 1995. Policy analysis in business cycle models. In: Cooley, T.F. (Ed.), Frontiers of Business Cycle Research. Princeton University Press, Princeton], but using a linear-quadratic (LQ) approximation to derive a log-linear approximation to the optimal policy rules. The example illustrates how inaccurate ‘naive’ LQ approximation – in which the quadratic objective is obtained from a simple Taylor expansion of the utility function of the representative household – can be, but also shows how a correct LQ approximation can be obtained, which will provide a correct local approximation to the optimal policy rules in the case of small enough shocks. We also consider the numerical accuracy of the LQ approximation in the case of shocks of the size assumed in the calibration of Chari et al. We find that the correct LQ approximation yields results that are quite accurate, and similar in most respects to the results obtained by Chari et al. using a more computationally intensive numerical method.     

Credit vs. demand constraints: The determinants of US firm-level investment over the business cycles from 1977 to 2011

The paper studies empirically how relative supply and demand conditions on the capital market affected US firm-level investment over the business cycles from 1977 to 2011. A dynamic econometric specification of capital accumulation including sales growth, Tobin's q, the cash flow-capital ratio and the cost of capital as covariates is fitted by a rolling window System GMM estimator using quarterly data on publicly traded US corporations in order to obtain time-varying coefficients. We find that the investment effects of the variables capturing the demand-side of the capital market, i.e. sales growth and Tobin's q, behave counter-cyclically, whereas this does not hold for the investment effects of supply-side variables such as cash flow or the cost of capital. Our results suggest that investment was typically driven by adverse demand rather than supply conditions on the capital market during the most severe recessions.     

Selecting structural innovations in DSGE models

Dynamic stochastic general equilibrium (DSGE) models are typically estimated assuming the existence of certain structural shocks that drive macroeconomic fluctuations. We analyze the consequences of estimating shocks that are “nonexistent” and propose a method to select the economic shocks driving macroeconomic uncertainty. Forcing these nonexisting shocks in estimation produces a downward bias in the estimated internal persistence of the model. We show how these distortions can be reduced by using priors for standard deviations whose support includes zero. The method allows us to accurately select shocks and estimate model parameters with high precision. We revisit the empirical evidence on an industry standard medium‐scale DSGE model and find that government and price markup shocks are innovations that do not generate statistically significant dynamics.     

The implications of financial frictions and imperfect knowledge in the estimated DSGE model of the U.S. economy

In this paper, I study how alternative assumptions about expectation formation can modify the implications of financial frictions for the real economy. I incorporate a financial 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 differ in terms of the information set used by agents to produce the forecasts. I show that the implications of the financial 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 effects of financial frictions relative to the model with Rational Expectations. Specifically, I show that the dynamics of real variables under learning is driven to a significant extent by the time variation of agents’ beliefs about financial sector variables. During periods when agents perceive asset prices as being relatively more persistent, financial shocks lead to more pronounced macroeconomic outcomes. The amplification effect rises as financial frictions become more severe. At the same time, a learning specification in which agents use more information to generate predictions produces very different asset price and investment dynamics. In such a framework, learning cannot significantly alter the real effects of financial frictions implied by the Rational Expectations model.     

Limited participation in international business cycle models: A formal evaluation

In this paper, we argue that limited asset market participation (LAMP) plays an important role in explaining international business cycles. We show that when LAMP is introduced into an otherwise standard model of international business cycles, the performance of the model improves significantly, especially in matching cross-country correlations. To perform formal evaluation of the models we develop a novel statistical procedure that adapts the statistical framework of Vuong (1989) to DSGE models. Using this methodology, we show that the improvements brought out by LAMP are statistically significant, leading a model with LAMP to outperform a representative agent model. Furthermore, when LAMP is introduced, a model with complete markets is found to do as well as a model with no trade in financial assets – a well-known favorite in the literature. Our results remain robust to the inclusion of investment specific technology shocks.     

利率期限结构、商业银行投资组合与宏观经济波动——基于DSGE的分析框架

将包含同业业务的商业银行投资组合、利润和利率期限结构的局部均衡模型嵌入以家庭、资本投资者、商业银行、中间厂商和最终厂商为经济主体的DSGE模型中,分析商业银行风险错配、货币政策工具和经济增长对利率期限结构的影响。结果表明:经济增长冲击和商业银行的风险错配冲击对我国利率期限结构的影响最大,其次是数量型货币政策和价格型货币政策冲击。     

A new approach to capital control for emerging market economies

The present paper proposes a new approach to capital control for emerging market economies, which restricts capital inflows to a fraction of the gap between foreign currency denominated loans and deposits in the economy. We show that the foreign-currency-gap capital control proposed here outperforms tax-based capital control in attenuating the negative effects of external shocks on business cycle fluctuations. This attenuation effect works via the interest rate channel and the capital control constraint itself. Compared to tax-based capital control, the foreign-currency-gap capital control is welfare enhancing, effectively mitigating financial instability with little cost in terms of macroeconomic stability. Countries with a high level of foreign currency denominated loans and deposits need to implement a stricter foreign-currency-gap capital control.