Pricing Models: A Bayesian DSGE Approach for the U.S. Economy

This paper compares and estimates three pricing mechanisms in the context of a small DSGE model of the U.S. economy. We interpret our results as favoring the pricing mechanism presented in Wolman (1999 Wolman model) over the New Keynesian model with indexation ( Gali and Gertler 1999 , Smets and Wouters 2004a ) and the sticky information model of Mankiw and Reis (2002) . The key factor that explains the performance of the Wolman model is that the data reject the key assumption of the New Keynesian model that the firm's probability of price change is constant over time and independent of the contract's vintage. Our results also show that incorporating indexation in the New Keynesian model represents a poor expedient in matching the autocorrelation function of the inflation process over the last 20 years.     

Inflation and Welfare: A Search Approach

This paper uses a search model of monetary exchange to provide new insights for evaluating the welfare costs of inflation. We first show that the search model of money can rationalize the estimates of the welfare cost of inflation based on the "welfare triangle" methodology of Bailey (1956) and Lucas (2000) provided that buyers appropriate the social marginal benefit of their real balances. For other mechanisms, the measure given by the welfare triangle has to be scaled up by a factor that increases with sellers' market power. We introduce capital and endogenous participation decisions and study how the cost of inflation is affected. We provide calibrated examples in which a deviation from the Friedman rule is optimal.     

Information Content of Wages and Monetary Policy

We examine whether it is sufficient for central banks to observe and forecast nominal variables only. Analyzing the interplay of wage-setting unions and a central bank we show that although central banks may not gain more information by directly acquiring data about indicators of real shocks in the economy, such activities are nevertheless beneficial for central banks and yield lower social losses. Moreover, the extent of research activities by central banks should depend on the process of union formation.     

Measuring Inflation Expectations Uncertainty Using High‐Frequency Data

Inflation expectations play a key role in determining future economic outcomes. The associated uncertainty provides a direct gauge of how well‐anchored the inflation expectations are. We construct a model‐based measure of inflation expectations uncertainty by augmenting a standard unobserved components model of inflation with information from noisy and possibly biased measures of inflation expectations obtained from financial markets. This new model‐based measure of inflation expectations uncertainty is more accurately estimated and can provide valuable information for policymakers. Using U.S. data, we find significant changes in inflation expectations uncertainty during the Great Recession.     

99 Luftballons: Monetary policy and the house price boom across U.S. states

We use a dynamic factor model estimated on quarterly state-level data from 1986 to 2005 via Bayesian methods to disentangle the relative importance of the common component in OFHEO house price movements from local (state- or region-specific) shocks. We find that historically movements in house prices were mainly driven by the local component. The recent period (2001-2005) has been different: the increase in house prices is a national phenomenon. We use a VAR to investigate the extent to which expansionary monetary policy is responsible for this phenomenon. We find the impact of policy shocks on house prices to be small in comparison with the magnitude of recent fluctuations.     

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.     

Learning by Failing: A Simple VaR Buffer

We study in this article the problem of model risk in VaR computations and document a procedure for correcting the bias due to specification and estimation errors. This practical method consists of “learning from model mistakes”, since it dynamically relies on an adjustment of the VaR estimates – based on a back‐testing framework – such as the frequency of past VaR exceptions always matches the expected probability. We finally show that integrating the model risk into the VaR computations implies a substantial minimum correction to the order of 10–40% of VaR levels.     

Estimating the New Keynesian Phillips Curve: A Vertical Production Chain Approach

It has become customary to estimate the New Keynesian Phillips Curve (NKPC) with generalized method of moments using a large instrument set that includes lags of variables that are ad hoc to the firm's price-decision problem. Researchers have also conventionally used real unit labor cost (RULC) as the proxy for real marginal cost even though it is difficult to support its significance. This paper introduces a new proxy for the real marginal cost term as well as a new instrument set, both of which are based on the micro foundations of the vertical chain of production. I find that the new proxy, based on input prices as opposed to wages, provides a more robust and significant fit to the model. Instruments that are based on the vertical chain of production appear to be both more valid and relevant toward the model.     

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.     

Re-Examining the Consumption–Wealth Relationship: The Role of Model Uncertainty

This paper discusses the consumption–wealth relationship. We use data on consumption, assets, and labor income and a vector error correction framework. This framework defines a set of models that differ in the number of co-integrating vectors, the form of deterministic components and lag length. Further models can be defined through parametric restrictions and, in particular, interest centers on a weak exogeneity restriction that says that the co-integrating residuals do not affect consumption and income directly. Key results in previous work relate to the roles of permanent and transitory shocks in driving wealth and how consumption responds to these shocks. We investigate the robustness of these results to model uncertainty and argue for the use of Bayesian model averaging. We find that there is a large degree of model uncertainty. Whether this uncertainty has important empirical implications depends on the researcher's attitude toward the theory used to motivate a co-integrating relationship between consumption, assets and income. If we work with models consistent with this theory and impose the weak exogeneity restriction, we find precisely estimated results that show that permanent shocks have only a small role in driving assets and that the predominant transitory shocks have little effect on consumption. These findings are consistent with the previous literature. However, if we work with a broader set of models and let the data speak, we find that the exact magnitude of the role of permanent shocks is hard to estimate precisely. Thus, although some support exists for the view that their role is small, we cannot rule out the possibility that they have a substantive role to play.     

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.     

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.     

Measuring the effects of geographical distance on stock market correlation

Recent studies suggest that the correlation of stock returns increases with decreasing geographical distance. However, there is some debate on the appropriate methodology for measuring the effects of distance on correlation. We modify a regression approach suggested in the literature and complement it with an approach from spatial statistics, the mark correlation function. For the stocks contained in the S&P 500 that we examine, both approaches lead to similar results. Contrary to previous studies we find that beyond 50 miles geographical proximity is irrelevant for stock return correlations. For distances below 50 miles, we can show that the magnitude of local correlations varies with investor sentiment.     

The Response of Hours to a Technology Shock: A Two-Step Structural VAR Approach

The response of hours to a technology shock is a controversial issue in macroeconomics. Part of the difficulty lies in that the estimated response is sensitive to the specification of hours in structural vector autoregressions (SVARs). This paper uses a simple two-step approach to consistently estimate the response of hours. The first step considers a SVAR model with a relevant stationary variable, but excluding hours. Given a consistent estimate of technology shocks in the first step, the response of hours to this shock is estimated in a second step. Simulation experiments from an estimated dynamic stochastic general equilibrium (DSGE) model show that this approach outperforms standard SVARs. When applied to U.S. data, the two-step approach predicts a short-run decrease followed by a hump-shaped positive response. This result is robust to other specifications and data.     

Do self-control preferences help explain the puzzling behavior of asset prices?

In the context of a simple asset-pricing environment, we study the ability of self-control preferences to account for the stock-price volatility, risk-free-rate and equity-premium puzzles. Using a full-information estimation procedure, we estimate the presence of a quantitatively small self-control effect in the data. Moreover, with results obtained using CRRA preferences serving as a benchmark, we find that the adoption of self-control preferences makes only a marginal contribution towards a resolution of these puzzles.     

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.     

Benefits from U.S. Monetary Policy Experimentation in the Days of Samuelson and Solow and Lucas

A policy maker knows two models. One implies an exploitable inflation-unemployment trade-off, the other does not. The policy maker's prior probability over the two models is part of his state vector. Bayes' law converts the prior probability into a posterior probability and gives the policy maker an incentive to experiment. For models calibrated to U.S. data through the early 1960s, we compare the outcomes from two Bellman equations. The first tells the policy maker to "experiment and learn." The second tells him to "learn but don't experiment." In this way, we isolate a component of government policy that is due to experimentation and estimate the benefits from intentional experimentation. We interpret the Bellman equation that learns but does not intentionally experiment as an "anticipated utility" model and study how well its outcomes approximate those from the "experiment and learn" Bellman equation. The approximation is good. For our calibrations, the benefits from purposeful experimentation are small because random shocks are big enough to provide ample unintentional experimentation.     

Monetary Policy and Asset Prices: A Mechanism Design Approach

We investigate the effects of monetary policy on asset prices in economies where assets are traded periodically in bilateral meetings. The trading mechanism is designed to maximize social welfare taking as given the frictions in the environment and monetary policy. We show that asset price “bubbles” emerge in a constrained‐efficient monetary equilibrium only if liquidity is abundant and the first‐best allocation is implementable. In contrast, if liquidity is scarce, assets are priced at their fundamental value in any constrained‐efficient monetary equilibrium, in which case an increase in inflation has no effect on asset prices, but it reduces output and welfare.     

The impact of foreign stock markets on macroeconomic dynamics in open economies: A structural estimation

With the increased international financial integration in recent years, bilateral financial linkages between countries may have a growing influence on their real economies. This paper employs a structural two-country New Keynesian model, which incorporates a cross-border wealth channel, to estimate the effect that foreign stock market fluctuations may have on macroeconomic variables in open economy countries.The model is estimated using Bayesian methods on a sample of open economies that can potentially be affected by changes in a larger foreign stock market: Australia, Canada, New Zealand, Ireland, Austria, and the Netherlands. The estimation allows for deviations from rational expectations and for learning by economic agents.The empirical results indicate important cross-country wealth effects for Ireland and Austria, from fluctuations in the U.S. and U.K. and in the U.S. and German stock markets, respectively; the wealth effect is largest in Ireland. The data favor, instead, specifications with no significant wealth effect for the remaining countries. Foreign stock price fluctuations, however, still play a role by affecting domestic expectations about future output gaps in all countries in the sample.     

Rethinking the liquidity puzzle: Application of a new measure of the economic money stock

Historically, attempts to solve the liquidity puzzle focus on narrowly defined monetary aggregates, such as non-borrowed reserves, the monetary base, or M1. Many of these efforts fail to find a short-term negative correlation between interest rates and monetary policy innovations. More recent research uses sophisticated macroeconomic and econometric modeling. However, little research has investigated the role measurement error plays in the liquidity puzzle, since in nearly every case, work investigating the liquidity puzzle has used one of the official monetary aggregates, which have been shown to exhibit significant measurement error. In this paper, we examine the role that measurement error plays in the liquidity puzzle by (i) providing a theoretical framework explaining how the official simple-sum methodology can lead to a liquidity puzzle, and (ii) testing for the liquidity effect by estimating an unrestricted VAR.