Econometric Evaluation of the New Keynesian Phillips Curve*

We give an appraisal of the New Keynesian Phillips curve (NPCM) as an empirical model of European inflation. The favourable evidence for NPCMs on euro‐area data reported in earlier studies is shown to depend on specific choices made about estimation methodology. The NPCM can be re‐interpreted as a highly restricted equilibrium correction model. We also report the outcome of tests based on variable addition and encompassing of existing models. The results show that economists should not accept the NPCM too readily.     

Testing the New Keynesian Phillips Curve Through Vector Autoregressive Models: Results from the Euro Area*

This paper addresses the issue of testing the ‘hybrid’ New Keynesian Phillips curve (NKPC) through vector autoregressive (VAR) systems and likelihood methods, giving special emphasis to the case where the variables are non‐stationary. The idea is to use a VAR for both the inflation rate and the explanatory variable(s) to approximate the dynamics of the system and derive testable restrictions. Attention is focused on the ‘inexact’ formulation of the NKPC. Empirical results over the period 1971–98 show that the NKPC is far from providing a ‘good first approximation’ of inflation dynamics in the Euro area.     

The New Keynesian Model and the Euro Area Business Cycle*

This paper describes a New Keynesian model incorporating transactions‐facilitating money and a time‐to‐build constraint into endogenous capital accumulation. The calibrated New Keynesian model performs almost as well as the estimated vector autoregressive model in replicating Euro area cyclical correlations between key variables such as output and inflation, although it fares less well in predicting the procyclical dynamics of nominal interest rates. The presence of a time‐to‐build requirement in the model helps to improve its fit to Euro area data, whereas the role of transactions‐facilitating money is much less important. Impulse–response functions and a decomposition of variance complete the analysis.     

The New Keynesian Phillips curve with myopic agents

Empirical estimations of the New Keynesian Phillips curve support hybrid versions with a positive weight on lagged inflation and a weight less than one on expected inflation. We argue that myopic price setting of some agents explains the low weight on expected inflation. The lagged term can be explained by trend extrapolation if information about the future is costly. In a laboratory experiment we implement the Calvo (1983) microfoundations of the Phillips curve. Our hypotheses are supported by the experimental data. About half of the subjects set optimal Calvo prices while about a third is myopic.     

Forecasting the yield curve in a data-rich environment: A no-arbitrage factor-augmented VAR approach

This paper suggests a term structure model which parsimoniously exploits a broad macroeconomic information set. The model uses the short rate and the common components of a large number of macroeconomic variables as factors. Precisely, the dynamics of the short rate are modeled with a Factor-Augmented Vector Autoregression and the term structure is derived using parameter restrictions implied by no-arbitrage. The model has economic appeal and provides better out-of-sample yield forecasts at intermediate and long horizons than a number of previously suggested approaches. The forecast improvement is highly significant and particularly pronounced for short and medium-term maturities.     

Testing for short- and long-run causality: A frequency-domain approach

The framework of Geweke (1982. Journal of the American Statistical Association 77, 304–324.) and Hosoya (1991. Probability Theory and Related Fields 88, 429–444.) is adopted to construct a simple test for causality in the frequency domain. This test can also be applied to cointegrated systems. To study the large sample properties of the test, we analyze the power against a sequence of local alternatives. The finite sample properties are investigated by means of Monte Carlo simulations. Our methodology is applied to investigate the predictive content of the yield spread for future output growth. Using quarterly US data we observe reasonable leading indicator properties at frequencies around one year and typical business cycle frequencies.     

Monetary Policy in the Greenspan Era: A Time Series Analysis of Rules vs. Discretion*

Relationships between the Federal funds rate, unemployment, inflation and the long‐term bond rate are investigated with cointegration techniques. We find a stable long‐term relationship between the Federal funds rate, unemployment and the bond rate. This relationship is interpretable as a policy target because deviations are corrected via the Federal funds rate. Deviations of the actual Federal funds rate from the estimated target give simple indications of discretionary monetary policy, and the larger deviations relate to special episodes outside the current information set. A more traditional Taylor‐type target, where inflation appears instead of the bond rate, does not seem congruent with the data.     

Term structure models and the zero bound: An empirical investigation of Japanese yields

When Japanese short-term bond yields were near their zero bound, yields on long-term bonds showed substantial fluctuation, and there was a strong positive relationship between the level of interest rates and yield volatilities/risk premiums. We explore whether several families of dynamic term structure models that enforce a zero lower bound on short rates imply conditional distributions of Japanese bond yields consistent with these patterns. Multi-factor “shadow-rate” and quadratic-Gaussian models, evaluated at their maximum likelihood estimates, capture many features of the data. Furthermore, model-implied risk premiums track realized excess returns during extended periods of near-zero short rates. In contrast, the conditional distributions implied by non-negative affine models do not match their sample counterparts, and standard Gaussian affine models generate implausibly large negative risk premiums.     

The Incremental Predictive Information Associated with Using Theoretical New Keynesian DSGE Models vs. Simple Linear Econometric Models*

In this paper we construct output gap and inflation predictions using a variety of dynamic stochastic general equilibrium (DSGE) sticky price models. Predictive density accuracy tests related to the test discussed in Corradi and Swanson [Journal of Econometrics (2005a), forthcoming] as well as predictive accuracy tests due to Diebold and Mariano [Journal of Business and Economic Statistics (1995) , Vol. 13, pp. 253–263]; and West [Econometrica (1996) , Vol. 64, pp. 1067–1084] are used to compare the alternative models. A number of simple time‐series prediction models (such as autoregressive and vector autoregressive (VAR) models) are additionally used as strawman models. Given that DSGE model restrictions are routinely nested within VAR models, the addition of our strawman models allows us to indirectly assess the usefulness of imposing theoretical restrictions implied by DSGE models on unrestricted econometric models. With respect to predictive density evaluation, our results suggest that the standard sticky price model discussed in Calvo [Journal of Monetary Economics (1983), Vol. XII, pp. 383–398] is not outperformed by the same model augmented either with information or indexation, when used to predict the output gap. On the other hand, there are clear gains to using the more recent models when predicting inflation. Results based on mean square forecast error analysis are less clear‐cut, although the standard sticky price model fares best at our longest forecast horizon of 3 years, it performs relatively poorly at shorter horizons. When the strawman time‐series models are added to the picture, we find that the DSGE models still fare very well, often outperforming our forecast competitions, suggesting that theoretical macroeconomic restrictions yield useful additional information for forming macroeconomic forecasts.     

How better monetary statistics could have signaled the financial crisis

This paper explores the disconnect of Federal Reserve data from index number theory. A consequence could have been the decreased-systemic-risk misperceptions that contributed to excess risk-taking prior to the housing bust. We find that most recessions in the past 50 years were preceded by more contractionary monetary policy than indicated by simple-sum monetary data. Divisia monetary aggregate growth rates were generally lower than simple-sum aggregate growth rates in the period preceding the Great Moderation, and higher since the mid 1980s. Monetary policy was more contractionary than likely intended before the 2001 recession and more expansionary than likely intended during the subsequent recovery.     

How does Monetary Policy Respond to Exchange Rate Movements? New International Evidence*

This article analyzes how monetary policy has responded to exchange rate movements in six open economies, paying particular attention to the two‐way interaction between monetary policy and the exchange rate. We address this issue using a structural VAR model that is identified using a combination of sign and short‐term (zero) restrictions. Doing so we find that, while there is a instantaneous reaction in the exchange rate following a monetary policy shock in all countries, monetary policy responds significantly on impact to an exchange rate shock in only four of the six countries.     

A Coincident Index,Common Factors,and Monthly Real GDP*

The Stock–Watson coincident index and its subsequent extensions assume a static linear one‐factor model for the component indicators. This restrictive assumption is unnecessary if one defines a coincident index as an estimate of monthly real gross domestic products (GDP). This paper estimates Gaussian vector autoregression (VAR) and factor models for latent monthly real GDP and other coincident indicators using the observable mixed‐frequency series. For maximum likelihood estimation of a VAR model, the expectation‐maximization (EM) algorithm helps in finding a good starting value for a quasi‐Newton method. The smoothed estimate of latent monthly real GDP is a natural extension of the Stock–Watson coincident index.     

A No‐Arbitrage Structural Vector Autoregressive Model of the UK Yield Curve*

This article combines a Structural Vector Autoregression with a no‐arbitrage approach to build a multifactor Affine Term Structure Model (ATSM). The resulting No‐Arbitrage Structural Vector Autoregressive (NASVAR) model implies that expected excess returns are driven by structural macroeconomic shocks. This is in contrast with a standard ATSM, in which agents are concerned with non‐structural risks. As a simple application, we study the effects of supply, demand and monetary policy shocks on the UK yield curve. We show that all structural shocks affect the slope of the yield curve, with demand and supply shocks accounting for a large part of the time variation in bond yields.     

New Keynesian monopolistic competition and objective demand

The New Keynesian model of monopolistic competition by Blanchard [Blanchard, O., Kiyotaki, N., 1987. Monopolistic competition and the effects of aggregate demand. American Economic Review 77 (4), 647–666] is reformulated according to an objective demand approach making the behavior of all agents fully rational. The revised model is compared with the original model in terms of prices, quantities and welfare. Working with the revised model enhances the validity of the menu-cost argument and, different from the original model, implies that price rigidity is increasing in market concentration.     

Testing for Parameter Stability in Dynamic Models across Frequencies*

This paper contributes to the econometric literature on structural breaks by proposing a test for parameter stability in vector autoregressive (VAR) models at a particular frequency ω, where ω ∈ [0, π]. When a dynamic model is affected by a structural break, the new tests allow for detecting which frequencies of the data are responsible for parameter instability. If the model is locally stable at the frequencies of interest, the whole sample size can then be exploited despite the presence of a break. The methodology is applied to analyse the productivity slowdown in the US, and the outcome is that local stability concerns only the higher frequencies of data on consumption, investment and output.     

Time Horizons and Smoothing in the Bank of England's Reaction Function: The Contrast Between the Standard GMM and Ex Ante Forecast Approaches*

The monetary policy reaction function of the Bank of England is estimated by the standard GMM approach and the ex ante forecast method developed by Goodhart (2005) , with particular attention to the horizons for inflation and output at which each approach gives the best fit. The horizons for the ex ante approach are much closer to what is implied by the Bank's view of the transmission mechanism, while the GMM approach produces an implausibly slow adjustment of the interest rate, and suffers from a weak instruments problem. These findings suggest a strong preference for the ex ante approach.     

Money‐output Causality Revisited – A Bayesian Logistic Smooth Transition VECM Perspective*

This article proposes a Bayesian approach to examining money‐output causality within the context of a logistic smooth transition vector error correction model. Our empirical results provide substantial evidence that the postwar US money‐output relationship is nonlinear, with regime changes mainly governed by the output growth and price levels. Furthermore, we obtain strong support for nonlinear Granger causality from money to output, although there is also some evidence for models indicating that money is not Granger causal or long‐run causal to output.     

Testing Uncovered Interest Rate Parity and Term Structure Using a Three‐regime Threshold Unit Root VECM: An Application to the Swiss ‘Isle’ of Interest Rates*

In this article, a three‐regime multivariate threshold vector error correction model with a ‘band of inaction’ is formulated to examine uncovered interest rate parity (UIRP) and expectation hypothesis of the term structure (EHTS) of interest rates for Switzerland. Combining both UIRP and EHTS in a model that allows for nonlinearities, we investigate whether the Swiss advantage is disappearing with respect to Europe. Our results favour threshold cointegration and show that both hypotheses hold, at least in one of the three regimes of the process for Switzerland/Germany. The same is not true between Switzerland and the United States.     

Analysing I(2) Systems by Transformed Vector Autoregressions*

We characterize the restrictions imposed by the minimal I(2)‐to‐I(1) transformation that underlies much applied work, e.g. on money demand relationships or open‐economy pricing relationships. The relationship between the parameters of the original I(2) vector autoregression, including the coefficients of polynomially cointegrating relationships, and the transformed I(1) model is characterized. We discuss estimation of the transformed model subject to restrictions as well as the more commonly used approach of unrestricted reduced rank regression. Only a minor loss of efficiency is incurred by ignoring the restrictions in the empirical example and a simulation study. A properly transformed vector autoregression thus provides a practical and effective means for inference on the parameters of the I(2) model.     

The Beveridge–Nelson decomposition in retrospect and prospect

Beveridge and Nelson [Beveridge, Stephen, Nelson, Charles R., 1981. A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the ‘business cycle’. Journal of Monetary Economics 7, 151–174] proposed that the long-run forecast is a measure of trend for time series such as GDP that do not follow a deterministic path in the long run. They showed that if the series is stationary in first differences, then the estimated trend is a random walk with drift that accounts for growth, and the cycle is stationary. In contrast to linear de-trending, the smoother of Hodrick and Prescott (1981) and Hodrick and Prescott [Hodrick, Robert, Prescott, Edward C., 1997. Post-war US business cycles: An empirical investigation. Journal of Money Credit and Banking 29 (1), 1–16] and the unobserved components model of Harvey, [Harvey, A.C., 1985. Trends and cycles in macroeconomic time series. Journal of Business and Economic Statistics 3, 216–227]. Watson [Watson, Mark W., 1986. Univariate detrending methods with stochastic trends Journal of Monetary Economics 18, 49–75] and Clark [Clark, Peter K., 1987. The cyclical component of US economic activity. The Quarterly Journal of Economics 102 (4), 797–814], the BN decomposition attributes most variation in GDP to trend shocks while the cycles are short and brief. Since each is an estimate of the transitory part of GDP that will die out, it seems natural to compare cycle measures by their ability to forecast future growth. The results presented here suggest that cycle measures contain little if any information beyond the short-term momentum captured by BN.