C13 - Estimation: General
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Assessing Indexation-Based Calvo Inflation Models
Using identification-robust methods, the authors estimate and evaluate for Canada and the United States various classes of inflation equations based on generalized structural Calvo-type models. The models allow for different forms of frictions and vary in their assumptions regarding the type of price indexation adopted by firms. -
Inflation Dynamics and the New Keynesian Phillips Curve: An Identification-Robust Econometric Analysis
The authors use identification-robust methods to assess the empirical adequacy of a New Keynesian Phillips curve (NKPC) equation. -
The U.S. New Keynesian Phillips Curve: An Empirical Assessment
The authors examine the evidence presented by Galí and Gertler (1999) and Galí, Gertler, and Lopez-Salido (2001, 2003) that the inflation dynamics in the United States can be well-described by the New Keynesian Phillips curve (NKPC). -
Estimating New Keynesian Phillips Curves Using Exact Methods
The authors use simple new finite-sample methods to test the empirical relevance of the New Keynesian Phillips curve (NKPC) equation. -
Fractional Cointegration and the Demand for M1
Using wavelets, the author estimates the fractional order of integration of a common long-run money-demand relationship whose parameters are obtained from a full-information maximum-likelihood procedure. -
Estimating the Fractional Order of Integration of Interest Rates Using a Wavelet OLS Estimator
The debate on the order of integration of interest rates has long focused on the I(1) versus I(0) distinction. In this paper, we use instead the wavelet OLS estimator of Jensen (1999) to estimate the fractional integration parameters of several interest rates for the United States and Canada from 1948 to 1999. -
A Comparison of Alternative Methodologies for Estimating Potential Output and the Output Gap
In this paper, the authors survey some of the recent techniques proposed in the literature to measure the trend component of output or potential output. Given the reported shortcomings of mechanical filters and univariate approaches to estimate potential output, the paper focusses on three simple multivariate methodologies: the multivariate Beveridge-Nelson methodology (MBN), Cochrane's methodology (CO), and the structural VAR methodology with long-run restrictions applied to output (LRRO).
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