10,249 research outputs found
Oil Painting of G. Willard Phillips
No full text65 cm. long by 58 cm. wide, oil painting in wooden and fabric frame of G. Willard Phillips. Gold plaque with name. Painting by Peter Nicastro. Inventory control number 831. Number has fallen off the back of the painting
Wage and Price Phillips Curves
No full textIn this paper we introduce a small Keynesian model of economic growth which is centered around two advanced types of Phillips curves, one for money wages and one for prices, both being augmented by perfect myopic foresight and supplemented by a measure of the medium-term inflationary climate updated in an adaptive fashion. The model contains two potentially destabilizing feedback chains, the so-called Mundell and Rose-effects. We estimate parsimonious and congruent Phillips curves for money wages and prices in the US over the past five decades. Using the parameters of the empirical Phillips curves, we show that the growth path of the private sector of the model economy is likely to be surrounded by centrifugal forces. Convergence to this growth path can be generated in two ways: a Blanchard-Katz-type error-correction mechanism in the money-wage Phillips curve or a modified Taylor rule that is augmented by a term, which transmits increases in the wage share (real unit labor costs) to increases in the nominal rate of interest. Thus the model is characterized by local instability of the wage-price spiral, which however can be tamed by appropriate wage or monetary policies. Our empirical analysis finds the error-correction mechanism being ineffective in both Phillips curves suggesting that the stability of the post-war US macroeconomy originates from the stabilizing role of monetary policy.Phillips curves, Mundell effect, Rose effect, monetary policy, Taylor rule, inflation, unemployment, instability
Econometric Analysis of Continuous Time Models: A Survey of Peter Phillips' Work and Some New Results
No full textEconometric analysis of continuous time models has drawn the attention of Peter Phillips for nearly 40 years, resulting in many important publications by him. In these publications he has dealt with a wide range of continuous time models and econometric problems, from univariate equations to systems of equations, from asymptotic theory to finite sample issues, from parametric models to nonparametric models, from identifocation problems to estimation and inference problems, from stationary models to nonstationary and nearly nonstationary models. This paper provides an overview of Peter Phillips' contributions in the continuous time econometrics literature. We review the problems that have been tackled by him, outline the main techniques suggested by him, and discuss the main results obtained by him. Based on his early work, we compare the performance of two asymptotic distributions in a simple setup. Results indicate that the in-fill asymptotics significantly outperforms the long-span asymptotics.
Wage and Price Phillips Curves An empirical analysis of destabilizing wage-price spirals
No full textIn this paper we introduce a small Keynesian model of economic growth which is centered around two advanced types of Phillips curves, one for money wages and one for prices, both being augmented by perfect myopic foresight and supplemented by a measure of the medium-term inflationary climate updated in an adaptive fashion. The model contains two potentially destabilizing feedback chains, the so-called Mundell and Rose-effects. We estimate parsimonious and congruent Phillips curves for money wages and prices in the US over the past five decades. Using the parameters of the empirical Phillips curves, we show that the growth path of the private sector of the model economy is likely to be surrounded by centrifugal forces. Convergence to this growth path can be generated in two ways: a Blanchard-Katz-type error-correction mechanism in the money-wage Phillips curve or a modified Taylor rule that is augmented by a term, which transmits increases in the wage share (real unit labor costs) to increases in the nominal rate of interest. Thus the model is characterized by local instability of the wage-price spiral, which however can be tamed by appropriate wage or monetary policies. Our empirical analysis finds the error-correction mechanism being ineffective in both Phillips curves suggesting that the stability of the post-war US macroeconomy originates from the stabilizing role of monetary policy.Phillips curves, Mundell effect, Rose effect, Monetary policy, Taylor Rule, Inflation, Unemployment, Instability
Mis-Specification in Phillips Curve Regressions: Quantifying Frequency Dependence in This Relationship While Allowing for Feedback.
No full textPhillips Curve, spectral regression, time series analysis.
Mis-Specification and Frequency Dependence in a New Keynesian Phillips Curve
No full textPhillips Curve, spectral regression, time series analysis
Technology, utilization and inflation: what drives the New Keynesian Phillips Curve?
No full textWe argue that the New-Keynesian Phillips Curve literature has failed to deliver a convincing measure of “fundamental inflation”. We start from a careful modeling of optimal price setting allowing for non-unitary factor substitution, non-neutral technical change and timevarying factor utilization rates. This ensures the resulting real marginal cost measures match volatility reductions and level changes witnessed in many US time series. The cost measure comprises conventional counter-cyclical cost elements plus pro-cyclical (and co-varying) utilization rates. Although pro-cyclical elements dominate, real marginal costs are becoming less cyclical over time. Incorporating this richer driving variable produces more plausible price-stickiness estimates than otherwise and suggests a more balanced weight of backward and forward-looking inflation expectations than commonly found. Our results challenge existing views of inflation determinants and have important implications for modeling inflation in New-Keynesian models. JEL Classification: E20, E30cyclicality, inflation, intensive labor, Labor Share, overtime premia, production function, real marginal costs, utilization
The New Keynesian Phillips curve : lessons from single-equation econometric estimation
No full textWe review single-equation methods for estimating the hybrid New Keynesian Phillips curve (NKPC) and then apply those methods to U.S. quarterly data for 1955?2007. Estimating the hybrid NKPC by the generalized method of moments yields stable coefficients with a large role for expected future inflation. Measures of marginal costs better explain U.S. inflation than does a range of measures of the output gap. But estimates of the slope of the NKPC are imprecise and confidence intervals that are robust to weak identification are wide. Further research on measuring marginal costs may reconcile these mixed findings. A reconciliation is important if the NKPC is to remain a fundamental component of models of the monetary transmission mechanism.Inflation (Finance) ; Phillips curve
Bayesian Routes and Unit Roots: de rebus prioribus semper est disputandum
No full textThis paper provides detailed responses to the following 8 discussants of my paper “To Criticize the Critics: An Objective Bayesian Analysis of Stochastic Trends”: Gary Koop and Mark Steel; Edward Leamer; In-Moo Kim and G. S. Maddala Dale J. Poirier; Peter C. Schotman and Herman K. van Dijk; James H. Stock; David Dejong and Charles H. Whiteman; and Christopher Sims. This reply puts new emphasis on the call made in the earlier paper for objective Bayesian analysis in time series; it underlines the need for a new approach, especially with regard to posterior odds testing; and it draws attention to a new methodology of Bayesian analysis developed in a recent paper by Phillips-Ploberger (1991). Some new simulations that shed light on certain comments of the discussants are proven; new empirical evidence is reported with the extended Nelson-Plosser data supplied by Schotman and van Dijk; and the new Phillips-Ploberger posterior odds test is given a brief empirical illustration
Indirect inference in spatial autoregression
No full textOrdinary least squares (OLS) is well-known to produce an inconsistent estimator of the spatial parameter in pure spatial autoregression (SAR). This paper explores the potential of indirect inference to correct the inconsistency of OLS. Under broad conditions, it is shown that indirect inference (II) based on OLS produces consistent and asymptotically normal estimates in pure SAR regression. The II estimator is robust to departures from normal disturbances and is computationally straightforward compared with pseudo Gaussian maximum likelihood (PML). Monte Carlo experiments based on various specifications of the weighting matrix confirm that the indirect inference estimator displays little bias even in very small samples and gives overall performance that is comparable to the Gaussian PML
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