14,153 research outputs found
The Phillips curve under state-dependent pricing
No full textThis paper is related to a large recent literature studying the Phillips curve in sticky-price equilibrium models. It differs in allowing for the degree of price stickiness to be determined endogenously. A closed-form solution for short-term inflation is derived from the dynamic stochastic general equilibrium (DSGE) model with state-dependent pricing originallydev eloped byDotsey , King and Wolman. This generalised Phillips curve encompasses the New Keynesian Phillips curve (NKPC) based on Calvo-type price-setting as a special case. It describes current inflation as a function of lagged inflation, expected future inflation, and current and expected future real marginal costs. The paper demonstrates that inflation dynamics generated bythe model for a broad class of time and state-dependent price-setting behaviours are well approximated bythe popular hybrid NKPC (with one lag of inflation) in a low-inflation environment. This provides an explanation of whythe hybrid NKPC performs well in describing inflation dynamics across industrial countries. It implies, however, that the reduced-form coefficients of the hybrid NKPC maynot have a structural interpretation.state-dependent pricing, inflation dynamics, Phillips curve
Does Modern Econometrics replicate the Phillips Curve?
No full textThis paper reexamines the existence of a long-run relationship between wages and unemployment in the U.K., with data over the period 1860-1913 used by A.W. Phillips to derive the well-known Phillips Curve. Using Johansen's maximum likelihood method of testing for cointegration, a long-run inverse relationship is indeed depicted between the rate of inflation and the unemployment rate. However, the main impact of deviations from this long-run equilibrium is on the unemployment rate rather than the rate of inflation.Phillips Curve; long-run equilibrium; cointegration
Identifying the New Keynesian Phillips Curve
No full textPhillips curves are central to discussions of inflation dynamics and monetary policy. New Keynesian Phillips curves describe how past inflation, expected future inflation, and a measure of real marginal cost or an output gap drive the current inflation rate. This paper studies the (potential) weak identification of these curves under GMM and traces this syndrome to a lack of persistence in either exogenous variables or shocks. We employ analytic methods to understand the identification problem in several statistical environments: under strict exogeneity, in a vector autoregression, and in the canonical three-equation, New Keynesian model. Given U.S., U.K., and Canadian data, we revisit the empirical evidence and construct tests and confidence intervals based on exact and pivotal Anderson-Rubin statistics that are robust to weak identification. These tests find little evidence of forward-looking inflation dynamics.Phillips curve, Keynesian, identification, inflation
The new Keynesian Phillips curve: empirical results for Luxembourg
No full textThe New Keynesian Phillips curve (NPC) differs from the conventional expectations-augmented Phillips curve in that it is forward-looking and links inflation to a measure of marginal cost instead of unemployment or the output gap. More fundamentally, the NPC is derived from New Keynesian models that combine nominal rigidities with individual optimising behaviour and model-consistent (rational) expectations. Because the NPC is grounded in micro-theory (unlike the conventional expectations-augmented Phillips curve), it is robust to some forms of the Lucas critique and may serve to analyse the impact structural changes such as increased price flexibility may have on inflation. New Keynesian Phillips curve estimates for Luxembourg using the Galí and Gertler (1999) hybrid form suggest that firms change prices often but tend to use backward-looking rules-of-thumb instead of resetting prices optimally using forward-looking expectations. In terms of policy implications, although the results suggest prices in Luxembourg are relatively flexible, the prevalence of backward-looking price setting implies greater inflation persistence and a higher sacrifice ratio attached to disinflationary monetary policy. From the perspective of individual firms, backward-looking price setting may be a rational response in a very small open economy because of its vulnerability to external shocks. Small size and openness plausibly imply higher costs of collecting information and lower benefits from optimal price setting.
Identifying the New Keynesian Phillips curve
No full textPhillips curves are central to discussions of inflation dynamics and monetary policy. New Keynesian Phillips curves describe how past inflation, expected future inflation, and a measure of real marginal cost or an output gap drive the current inflation rate. This paper studies the (potential) weak identification of these curves under generalized methods of moments (GMM) and traces this syndrome to a lack of persistence in either exogenous variables or shocks. The authors employ analytic methods to understand the identification problem in several statistical environments: under strict exogeneity, in a vector autoregression, and in the canonical three-equation, New Keynesian model. Given U.S., U.K., and Canadian data, they revisit the empirical evidence and construct tests and confidence intervals based on exact and pivotal Anderson-Rubin statistics that are robust to weak identification. These tests find little evidence of forward-looking inflation dynamics.
The South African Phillips Curve: How Applicable is the Gordon Model?
No full textIs there a Phillips curve relationship present in South Africa and if so, what form does it take? Traditionally the way to estimate the Phillips curve is merely to regress the change in the price level on a measure of the output gap (or the deviation of actual unemployment from the NAIRU). However, Gordon (1990:481-5) has argued that estimating the Phillips curve in this manner biases the estimated results. Instead, Gordon (1997; 1989) puts forward his so-called triangular model that controls for inertia effects, output level effects and rates-of-change (in output) effects. He applies the model to several European countries, the US and Japan and finds meaningful results. The question this paper poses is whether or not the triangular model also applies to South Africa. In estimating the Phillips curve for South Africa the paper also experiments with four versions of the output gap, based on four different methods to estimate long run output, including the standard Hodrick-Prescott (HP) filter and the production function approach. There are several variants of the Phillips curve. The first, as estimated by Phillips (1958) himself, measures the relationship between wage inflation and unemployment. However, other versions consider the relationship between price inflation and unemployment or price inflation and output. This paper focuses on the latter, given the absence of quarterly unemployment data in South Africa, as well as the lack of a reliable and sufficiently long unemployment time series. The paper first presents an overview of literature on the Phillips curve and its estimation for South Africa and other countries. This is followed by the second section that considers the model to be estimated, the data as well as the discussion of the alternative measures of the output gap. The third section presents the estimated results followed by section four that contains the conclusion and a discussion of the policy implications.
ML vs GMM Estimates of Hybrid Macroeconomic Models (With an Application to the "New Phillips Curve")
No full textMany macroeconomic models (including the NKPC - "New Keynesian" Phillips Curve) involve hybrid equations, in which some variables depend on both their lags and leads. Hybrid models have produced conflicting empirical results: GMM (respectively ML) estimation find the forward- looking component to be large (small). A rationalization for this conflict is provided, allowing for two kinds of misspecifications (omitted dynamics and measurement error): we show analytically in a simple DGP that the GMM (ML) estimator overstates (understates) the size of the forward- looking component. Monte-Carlo experiments indicate this result has some generality. We use these findings to rationalize discrepancies observed in NKPC estimates.Rational-expectation model, GMM estimator, ML estimator, Inflation, New Phillips curve.
Metadata Representations for Queryable ML Model Zoos
No full textMachine learning (ML) practitioners and organizations are building model zoos of pre-trained models, containing metadata describing properties of the ML models and datasets that are useful for reporting, auditing, reproducibility, and interpretability purposes. The metatada is currently not standardised; its expressivity is limited; and there is no interoperable way to store and query it. Consequently, model search, reuse, comparison, and composition are hindered. In this paper, we advocate for standardized ML model metadata representation and management, proposing a toolkit supported to help practitioners manage and query that metadata.Web Information SystemsHuman-Centred Artificial Intelligenc
A Manifesto of Nodalism
No full textThis paper proposes the notion of Nodalism as a means describing contemporary culture and of understanding my own creative practice in electronic music composition. It draws on theories and ideas from Kirby, Bauman, Bourriaud, Deleuze, Guatarri, and Gochenour, to demonstrate how networks of ideas or connectionist neural models of cognitive behaviour can be used to contextualize, understand and become a creative tool for the creation of contemporary electronic music
A Bias in ML Estimates of Branch Lengths in the Presence of Multiple Signals
No full textSequence data often have competing signals that are detected by network programs or Lento plots. Such data can be formed by generating sequences on more than one tree, and combining the results, a mixture model. We report that with such mixture models, the estimates of edge (branch) lengths from maximum likelihood (ML) methods that assume a single tree are biased. Based on the observed number of competing signals in real data, such a bias of ML is expected to occur frequently. Because network methods can recover competing signals more accurately, there is a need for ML methods allowing a network. A fundamental problem is that mixture models can have more parameters than can be recovered from the data, so that some mixtures are not, in principle, identifiable. We recommend that network programs be incorporated into best practice analysis, along with ML and Bayesian trees
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