Rao, B. Bhaskara and Paradiso, Antonio (2011): Estimates of the US Phillips curve with the general to specific method.
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Abstract
This paper distinguishes between the long run and short run Phillips curve (PC) and uses the micro theory based specification, with forward looking expectations, for the long run PC. The long run and the implied short run dynamic equations are estimated in one step with the general to specific method (GETS). Our approach has two distinct advantages. Firstly, classical estimation methods can be used, irrespective of the stationarity properties of the variables. Secondly, instead of arbitrarily adding the lagged inflation rate to the theory based long run PC to capture persistence in inflation, our approach shows that persistence effects can also be captured through the dynamic adjustment equations. This has an added advantage because it offers a more flexible lag structure to estimate dynamic adjustments compared to the partial adjustment process in the hybrid NKPC.
Item Type: | MPRA Paper |
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Original Title: | Estimates of the US Phillips curve with the general to specific method |
Language: | English |
Keywords: | US New Keynesian Phillips Curve, Forward looking expectations, Alternative measures of the Driving Forces, GETS |
Subjects: | E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E31 - Price Level ; Inflation ; Deflation B - History of Economic Thought, Methodology, and Heterodox Approaches > B2 - History of Economic Thought since 1925 > B22 - Macroeconomics C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes |
Item ID: | 28411 |
Depositing User: | B. Bhaskara Rao |
Date Deposited: | 27 Jan 2011 16:57 |
Last Modified: | 28 Sep 2019 01:45 |
References: | References Baghestani, H. and Noori, E. (1988), “On the rationality of the Michigan monthly survey of inflationary expectations”, Economics Letters, 27, 333-315. Boug, P., Cappelen, A. and Swensen, A. R. (2010), “The new Keynesian Phillips curve revisited”, Journal of Economic Dynamics and Control, 34, 858-874. Gali, J. and Gertler, M. (1999), “Inflation dynamics: A structural econometric analysis”, Journal of Monetary Economics, 44, 195-222. Guerron-Quintana, P. A. (2011), “The implications of inflation in an estimated new Keynesian model”, Journal of Economic Dynamics and Control, doi:10.1016/j.jedc. 2011.01.008. Pearce, D. K. (1978), “Comparing survey and rational measures of expected inflation: Forecast performance and interest rate effects”, Journal of Money, Credit and Banking, 11, 446-456. Pesaran, H. M., and Shin, Y. (1999), “Autoregressive distributed lag modelling approach to cointegration analysis, Chapter 11, in: Storm, S. (ed.), Econometrics and Economic Theory in the 20th Century: The Ragnar Frisch Centennial Symposium, Cambridge University Press. Rao, B. B. (2007), “Estimating short and long run relationships: A guide for the applied economist”, Applied Economics, 39, 1613-1625. Rao, B. B., Singh, R. and Kumar, S. (2010), “Do we need time series econometrics?”, Applied Economics Letters, 17, 695-697. Rao, B. B. and Paradiso, A. (2011), “Time series estimates of the US NKPC”, mimeographed. Rudd, J. and Whelan, K. (2006), “Can Rational Expectations Sticky-Price Models Explain Inflation Dynamics?”, American Economic Review, 96 (March), 303–320. Rudd, J. and Whelan, K. (2007), “Modelling inflation dynamics: A critical review of recent research”, Journal of Money, Credit and Banking, 39, 155–170. Shimer, R. (2005), “Reassessing the Ins and Outs of unemployment”, NBER Working Paper No. 13421. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/28411 |