What does a technology shock do? A VAR analysis with model-based sign restrictions

This paper estimates the effects of technology shocks in VAR models of the U.S., identified by imposing restrictions on the sign of impulse responses. These restrictions are consistent with the implications of a popular class of DSGE models, with both real and nominal frictions, and with sufficiently wide ranges for their parameters. This identification strategy thus substitutes theoretically motivated restrictions for the atheoretical assumptions on the time-series properties of the data that are key to long-run restrictions. Stochastic technology improvements persistently increase real wages, consumption, investment and output in the data; hours worked are very likely to increase, displaying a hump-shaped pattern. Contrary to most of the related VAR evidence, results are not sensitive to a number of specification assumptions, including those on the stationarity properties of variables.     

The Effects of Monetary Policy on Unemployment Dynamics under Model Uncertainty: Evidence from the United States and the Euro Area

This paper explores the role that the imperfect knowledge of the structure of the economy plays in the uncertainty surrounding the effects of rule-based monetary policy on unemployment dynamics in the euro area and the United States. We employ a Bayesian model averaging procedure on a wide range of models which differ in several dimensions to account for the uncertainty that the policymaker faces when setting the monetary policy and evaluating its effect on real economy. We find evidence of a high degree of dispersion across models in both policy rule parameters and impulse response functions. Moreover, monetary policy shocks have very similar recessionary effects on the two economies with a different role played by the participation rate in the transmission mechanism. Finally, we show that a policymaker who does not take model uncertainty into account and selects the results on the basis of a single model may come to misleading conclusions not only about the transmission mechanism, but also about the differences between the euro area and the United States, which are on average essentially small.     

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.     

Comparing New Keynesian models of the business cycle: A Bayesian approach

The baseline New Keynesian model cannot replicate the observed persistence in inflation, output, and real wages for sensible parameter values. As a result, several extensions have been suggested to improve its fit to the data. We use a Bayesian approach to estimate and compare the baseline sticky price model of Calvo's [1983. Staggered prices in a utility maximizing framework. Journal of Monetary Economics 12, 383-398.] and three extensions. Our empirical results are as follows. First, we find that adding price indexation improves the fit of Calvo's [1983. Staggered prices in a utility maximizing framework. Journal of Monetary Economics 12, 383-398.] model. Second, models with both staggered price and wage setting dominate models with only price rigidities. Third, introducing wage indexation does not significantly improve the fit. Fourth, all model estimates suggest a high degree of price stickiness. Fifth, the estimates of labor supply elasticity are higher in models with both staggered price and wage contracts. Finally, the estimated inflation parameters of the Taylor rule are stable across models.     

Uncovering the Hit List for Small Inflation Targeters: A Bayesian Structural Analysis

We estimate underlying structural macroeconomic policy objectives of three of the earliest explicit inflation targeters within the context of a small open economy dynamic stochastic general equilibrium model. We assume central banks set policy optimally, such that we can reverse engineer policy objectives from observed time series data. Joint tests of the posterior distributions of these policy preference parameters suggest that the central banks are very similar in their overall objective. None of the central banks show a concern for stabilizing the real exchange rate. All three central banks share a concern for minimizing the volatility in the change in the nominal interest rate. We also show that the resulting optimal policy rule responds to exchange rate movements, even in the case where the central banks do not explicitly care about exchange rate stabilization. This result is also corroborated by results from an alternative simple-rule characterization and estimation of central bank behavior. These last two findings point to the pitfalls of making inferences, from the level of ad hoc simple rules, about what central banks may care about.     

Does Inflation Adjust Faster to Aggregate Technology Shocks than to Monetary Policy Shocks?

This paper studies U.S. inflation adjustment speed to aggregate technology shocks and to monetary policy shocks in a medium size Bayesian vector autoregression model. According to the model estimated on the 1959–2007 sample, inflation adjusts much faster to aggregate technology shocks than to monetary policy shocks. These results are robust to different identification assumptions and measures of aggregate prices. However, by separately estimating the model over the pre‐ and post‐1980 periods, this paper further shows that inflation adjusts much faster to technology shocks than to monetary policy shocks in the post‐1980 period, but not in the pre‐1980 period.     

Consumption, the persistence of shocks, and asset price volatility

In a general equilibrium setting, a temporary component in consumption introduces a wedge between the volatility of equity returns and the volatility of consumption growth. This paper explores the asset pricing consequences of this property in a model in which consumption is the sum of a permanent and a transitory component. Permanent shocks are assumed to be rare events, while transitory shocks follow a diffusion process. When calibrated to US annual data, the model matches first and second moments of equity and bond returns for preference parameters within acceptable bounds. Permanent and transitory shocks together explain the equity premium, while transitory shocks alone explain the excess volatility of returns.     

Regime switching and monetary policy measurement

This paper applies regime-switching methods to the problem of measuring monetary policy. Policy preferences and structural factors are specified parametrically as independent Markov processes. Interaction between the structural and preference parameters in the policy rule serves to identify the two processes. The estimates uncover policy episodes that are initiated by switches to “dove regimes,” shown to Granger-cause both NBER recessions and the Romer dates. These episodes imply real effects of monetary policy that are smaller than those found in previous studies.     

Identifying VARS based on high frequency futures data

Using the prices of federal funds futures contracts, we measure the impact of the surprise component of Federal Reserve policy decisions on the expected future trajectory of interest rates. We show how this information can be used to identify the effects of a monetary policy shock in a standard VAR. This alternative approach to identification is quite different, and, we argue, more plausible, than the conventional identifying restrictions. We find that a usual recursive identification of the model is rejected, as is any identification that insists on a monetary policy shock having an exactly zero effect on prices contemporaneously. We nevertheless agree with the conclusion of much of the VAR literature that only a small fraction of the variance of output can be attributed to monetary policy shocks.     

A happy “half way-house”? Medium term inflation targeting in New Zealand

The 2002 Policy Targets Agreement (PTA) between the government and central bank of New Zealand asks the central bank to target inflation “over the medium term” rather than over an annual target. Delegating such a medium term objective to the central bank shifts inflation targeting towards a “halfway-house” between inflation targeting and price level targeting. We show empirically that this helps time consistent policy approximate the first-best commitment policy even when the government asks the central bank to weight output stabilisation differently to society. We estimate the New Zealand economy with a small open economy DSGE model and show that the happiest halfway house is located around a two year averaging horizon at most, which leads to mild improvements in monetary policy efficiency.     

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.     

Exchange rate bubbles: Fundamental value estimation and rational expectations test

We propose a model of periodically collapsing bubbles which extends the Van Norden (1996) model, and nests it, by considering a non-linear specification for the bubble size in the survival regime, and the endogenous determination of the level of the fundamental value of the stochastic process. They allow us to test for rationality in the formation of expectations, and remove the arbitrariness of exogenously setting the level of the fundamental value. This general model is applied to the exchange rate of the Brazilian real to the US dollar from March 1999 to February 2011. The futures market exchange rate is used as a proxy of its expected future value, and three different structural models are considered for the determination of the fundamental value. The first two imply that the exchange rate satisfies either purchasing power parity (PPP), or a modified version of it. The third structural model is a version of the monetary model of exchange rate determination, fitted to the period under consideration. We obtain the maximum likelihood estimate of the parameters of the models, explore the properties of the errors, test its restricted versions, and compare the three specifications for the fundamental. We find that the models we propose fit well the data, and are useful in the heuristic interpretation of the exchange rate movements of the period. Finally we select the structural models that display the best performance, according to several criteria.     

Why Has U.S. Inflation Become Harder to Forecast?

We examine whether the U.S. rate of price inflation has become harder to forecast and, to the extent that it has, what changes in the inflation process have made it so. The main finding is that the univariate inflation process is well described by an unobserved component trend-cycle model with stochastic volatility or, equivalently, an integrated moving average process with time-varying parameters. This model explains a variety of recent univariate inflation forecasting puzzles and begins to explain some multivariate inflation forecasting puzzles as well.     

Do Data Revisions Matter for DSGE Estimation?

This paper checks whether the coefficient estimates of a famous dynamic stochastic general equilibrium (DSGE) model are robust to macroeconomic data revisions. The effects of revisions are captured by rerunning the estimation on a real‐time data set compiled using the latest time series available each quarter from 1997 through 2015. Results show that estimates of the structural parameters are generally robust to changes in the data that have occurred over the past 20 years. By comparison, standard error estimates are more sensitive to revisions. The latter implies that judgments about the statistical significance of certain parameters depend on which data vintage is used for estimation.     

New evidence on the monetary approach of exchange rate determination in Mexico 1994–2007: A cointegrated SVAR model

We provide empirical evidence supporting the validity of both short and long run versions of the Monetary Approach of Exchange Rate determination for the Mexican peso–U.S. dollar exchange rate from 1994 to 2007 using a cointegrated SVAR model. We estimate not only the long-run relationship, between the variables of the monetary model for the exchange rate, but also the very short run effects which have been often ignored in previous empirical work. We show that there are robust short and long-run relationships between the Mexican monetary aggregates and the exchange rate, which ultimately responds to what Bilson's variant of MAER predicts.     

Stochastic Volatility in a Macro-Finance Model of the U.S. Term Structure of Interest Rates 1961–2004

This paper generalizes the standard homoscedastic macro-finance model by allowing for stochastic volatility, using the "square root" specification of the mainstream finance literature. Empirically, this specification dominates the standard model because it is consistent with the square root volatility found in macroeconomic time series. Thus it establishes an important connection between the stochastic volatility of the mainstream finance model and macro-economic volatility of the Okun–Friedman type. This research opens the way to a richer specification of both macro-economic and term structure models, incorporating the best features of both macro-finance and mainstream finance models.     

How arbitrage-free is the Nelson-Siegel model?

We test whether the Nelson and Siegel (1987) yield curve model is arbitrage-free. Theoretically, the Nelson-Siegel model does not ensure the absence of arbitrage opportunities, as shown by Bjork and Christensen (1999) and Filipovic (1999). Still, central banks and wealth managers rely heavily on it. Using zero-coupon yield curve data from the US market, we find that the no-arbitrage parameters are not statistically different from those obtained from the Nelson-Siegel model. We therefore conclude that the Nelson-Siegel yield curve model is compatible with the no-arbitrage constraints on the US market. To corroborate this result, we also show that the Nelson-Siegel model performs as well as its no-arbitrage counterpart in an out-of-sample forecasting experiment.     

A Long-Run Non-Linear Approach to the Fisher Effect

We argue that the empirical failure of the Fisher effect found in the literature may be due to the existence of non-linearities in the long-run relationship between interest rates and inflation. We present evidence that, for the U.S. during the 1960–2004 period, the Fisher relation presents important non-linearities. We model the long-run non-linear relationship and find that an ESTR model for the pre-Volcker era and an LSTR model for the post-Volcker era are able to control for non-linearities and constitute long-run co-integration vectors. Monte Carlo evidence produces support for the hypothesis that non-linearities may also be responsible for the less than proportional coefficients of inflation usually found in the linear specifications.     

What do technology shocks tell us about the New Keynesian paradigm?

Researchers have used unanticipated changes to monetary policy to identify preference and technology parameters of macroeconomic models. This paper uses changes in technology to identify the same set of parameters. Estimates based on technology shocks differ substantially from those based on monetary policy shocks. In the post-World War II United States, a positive technology shock reduces inflation and increases hours worked, significantly and rapidly in both cases. Relative to policy shock identification, technology shock identification implies: (i) long duration durability in preferences instead of short duration habit, (ii) built-in inflation inertia disappears and price flexibility increases. In response to technological improvement, consumption durability increases hours worked because households temporarily increase labor supply to accumulate durables towards a new, higher steady state level. Limited nominal rigidities allow inflation to fall because firms are able to immediately cut prices when households’ labor supply increases. Finally, we consider alternative data constructions and econometric specifications; we find that (i) and/or (ii) hold in nearly every case.     

Expectations, learning and macroeconomic persistence

Monetary DGSE models under rational expectations typically require large degrees of features as habit formation in consumption and inflation indexation to match the inertia of macroeconomic variables.This paper presents an estimated model that departs from rational expectations and nests learning by economic agents, habits, and indexation. Bayesian methods facilitate the joint estimation of the learning gain coefficient together with the ‘deep’ parameters of the economy.The empirical results show that when learning replaces rational expectations, the estimated degrees of habits and indexation drop closer to zero, suggesting that persistence arises in the model economy mainly from expectations and learning.