US inflation dynamics on long-range data

References

• Ashley, R. and Patterson, D. M. (2000) A Nonlinear Time Series Workshop: A Toolkit for Detecting and Identifying Nonlinear Serial Dependence, Kluwer Academic Publishers, Norwell.
   Google Scholar
• Baillie, R. T., Chung, C.-F. and Tieslau, M. A. (1996) Analysing inflation by the fractionally integrated ARFIMA-GARCH model, Journal of Applied Econometrics, 11, 23–40. doi:10.1002/(SICI)1099-1255(199601)11:1<23::AID-JAE374>3.0.CO;2-M
   Web of Science ®Google Scholar
• Benati, L. (2008) Investigating inflation persistence across monetary regimes, Quarterly Journal of Economics, 123, 1005–60. doi:10.1162/qjec.2008.123.3.1005
   Web of Science ®Google Scholar
• BenSaida, A. and Litimi, H. (2013) High level chaos in the exchange and index markets, Chaos, Solitons and Fractals, 54, 90–5. doi:10.1016/j.chaos.2013.06.004
   Web of Science ®Google Scholar
• Brock, W. A., Dechert, W. and Scheinkman, J. (1996) A test for independence based on the correlation dimension, Econometric Reviews, 15, 197–235. doi:10.1080/07474939608800353
   Google Scholar
• Calvo, G. A. (1983) Staggered prices in a utility maximizing framework, Journal of Monetary Economics, 12, 383–98. doi:10.1016/0304-3932(83)90060-0
   Web of Science ®Google Scholar
• Chung, H., Kiley, T. M. and Laforte, J.-P. (2010) Documentation of the estimated, dynamic, optimization-based (EDO) model of the U.S. economy, Finance and Economics Discussion Series 2010-29, Board of Governors of the Federal Reserve System.
   Google Scholar
• Cogley, T., Primiceri, G. E. and Sargent, T. J. (2010) Inflation-gap Persistence in the US, American Economic Journal: Macroeconomics, 2, 43–69.
   Web of Science ®Google Scholar
• Cogley, T. and Sargent, T. J. (2005) Drifts and volatilities: monetary policies and outcomes in the post WWII US, Review of Economic Dynamics, 8, 262–302. doi:10.1016/j.red.2004.10.009
   Web of Science ®Google Scholar
• Culver, S. E. and Papell, D. H. (1997) Is there a unit root in the inflation rate? Evidence from sequential break and panel data models, Journal of Applied Econometrics, 12, 435–44. doi:10.1002/(SICI)1099-1255(199707)12:4<435::AID-JAE430>3.0.CO;2-1
   Web of Science ®Google Scholar
• Delignieres, D., Ramdani, S. and Lemoine, L. (2006) Fractal analyses for ‘short’ time series: a re-assessment of classical methods, Journal of Mathematical Psychology, 50, 525–44. doi:10.1016/j.jmp.2006.07.004
   Web of Science ®Google Scholar
• Dickey, D. and Fuller, W. (1981) Likelihood ratio statistics for autoregressive time series with a unit root, Econometrica, 49, 1057–72. doi:10.2307/1912517
   Web of Science ®Google Scholar
• Dittmar, R. D., Gavin, W. and Kydland, F. (2005) Inflation persistence and flexible prices, International Economic Review, 46, 245–61. doi:10.1111/j.0020-6598.2005.00317.x
   Web of Science ®Google Scholar
• Eke, A., Herman, P. and Kocsis, L. (2002) Fractal characterization of complexity in temporal physiological signals, Physiological Measurement, 23, 1–38. doi:10.1088/0967-3334/23/1/201
   PubMed Web of Science ®Google Scholar
• Engle, R. (1982) Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation, Econometrica, 50, 987–1007. doi:10.2307/1912773
   Web of Science ®Google Scholar
• Engle, R. and Granger, C. (1987) Cointegration and error correction: representation, estimation and testing, Econometrica, 55, 251–94. doi:10.2307/1913236
   Web of Science ®Google Scholar
• Evans, M. and Wachtel, P. (1993) Inflation regimes and the sources of inflation uncertainty, Journal of Money, Credit and Banking, 25, 475–511. doi:10.2307/2077719
   Web of Science ®Google Scholar
• Hassler, U. and Wolters, J. (1995) Long memory in inflation rates: international evidence, Journal of Business and Economic Statistics, 13, 37–45.
   Web of Science ®Google Scholar
• Hinich, M. and Patterson, D. M. (1985) Evidence of nonlinearity in daily stock returns, Journal of Business and Economic Statistics, 3, 69–77.
   Web of Science ®Google Scholar
• Hsieh, D. A. (1991) Chaos and nonlinear dynamics: application to financial markets, The Journal of Finance, 46, 1839–77. doi:10.1111/j.1540-6261.1991.tb04646.x
   Web of Science ®Google Scholar
• Hurst, H. E. (1951) Long-term storage capacity of reservoirs, Transactions of the American Society of Civil Engineers, 116, 770–99.
   Google Scholar
• Kim, C.-J. (1993) Unobserved component time series models with Markov-switching heteroscedasticity: changes in regime and the link between inflation rates and inflation uncertainty, Journal of Business and Economic Statistics, 11, 341–9.
   Web of Science ®Google Scholar
• Korenok, O., Radchenko, S. and Swanson, N. R. (2010) International evidence on the efficacy of new-Keynesian models of inflation persistence, Journal of Applied Econometrics, 25, 31–54. doi:10.1002/jae.1128
   Web of Science ®Google Scholar
• Kumar, M. S. and Okimoto, T. (2007) Dynamics of persistence in international inflation rates, Journal of Money, Credit and Banking, 39, 1457–79. doi:10.1111/j.1538-4616.2007.00074.x
   Web of Science ®Google Scholar
• Kwiatkowski, D., Phillips, P. C. B., Schmidt, P. et al. (1992) Testing the null hypothesis of stationarity against the alternative of a unit root, Journal of Econometrics, 54, 159–78. doi:10.1016/0304-4076(92)90104-Y
   Web of Science ®Google Scholar
• Le Bihan, H. and Matheron, J. (2012) Price stickiness and sectoral inflation persistence: additional evidence, Journal of Money, Credit and Banking, 44, 1427–42. doi:10.1111/j.1538-4616.2012.00538.x
   Web of Science ®Google Scholar
• Lucas Jr, R. E. (1976) Econometric policy evaluation: a critique, Journal of Monetary Economics. doi:10.1016/S0167-2231(76)80003-6
   Google Scholar
• Mandelbrot, B. B. and Wallis, J. R. (1969) Robustness of the rescaled range R/S in the measurement of noncyclic long-run statistical dependence, Water Resources Research, 5, 967–88. doi:10.1029/WR005i005p00967
   Web of Science ®Google Scholar
• McLeod, A. I. and Li, W. K. (1983) Diagnostic checking ARMA time series models using squared-residual autocorrelations, Journal of Time Series Analysis, 4, 269–73. doi:10.1111/j.1467-9892.1983.tb00373.x
   Google Scholar
• Mulligan, R. F. and Koppl, R. (2011) Monetary policy regimes in macroeconomic data: an application of fractal analysis, The Quarterly Review of Economics and Finance, 51, 201–11. doi:10.1016/j.qref.2011.01.001
   Google Scholar
• Noriega, A. E. and Ramos-Francia, M. (2009) The dynamics of persistence in U.S. inflation, Economics Letters, 105, 168–72. doi:10.1016/j.econlet.2009.07.016
   Web of Science ®Google Scholar
• Peng, C. K., Buldyrev, S. V. and Havlin, S. et al. (1994) Mosaic organization of DNA nucleotides, Physical Review E, 49, 1685–9. doi:10.1103/PhysRevE.49.1685
   PubMed Web of Science ®Google Scholar
• Phillips, P. C. B. and Perron, P. (1988) Testing for a unit root in time series regression, Biometrika, 75, 335–46. doi:10.1093/biomet/75.2.335
   Web of Science ®Google Scholar
• Pivetta, F. and Reis, R. (2007) The persistence of inflation in the United States, Journal of Economic Dynamics and Control, 31, 1326–58. doi:10.1016/j.jedc.2006.05.001
   Web of Science ®Google Scholar
• Rudd, J. and Whelan, K. (2007) Modeling inflation dynamics: a critical review of recent research, Journal of Money, Credit and Banking, 39, 155–70. doi:10.1111/j.1538-4616.2007.00019.x
   Web of Science ®Google Scholar
• Serletis, A. and Gogas, P. (1997) Chaos in East European black market exchange rates, Research in Economics, 51, 359–85. doi:10.1006/reec.1997.0050
   Google Scholar
• Solow, R. (1976) Down the Phillips curve with gun and camera, in Inflation, Trade and Taxes: essays in Honor of Alice Bourneuf, Belsey, D. (Eds), Ohio State University Press, Columbus, pp. 3–22.
   Google Scholar
• Stock, J. (2001) Comment on evolving post world war II U.S. inflation dynamics, NBER Macroeconomics Annual, 16, 379–87. doi:10.1162/088933601320225044
   Web of Science ®Google Scholar
• Stock, J. H. and Watson, M. W. (2007) Why has US inflation become harder to forecast?, Journal of Money, Credit and Banking, 39, 3–33. doi:10.1111/j.1538-4616.2007.00014.x
   Web of Science ®Google Scholar
• Taylor, J. B. (2000) Low inflation, pass-through, and the pricing power of firms, European Economic Review, 44, 1389–408. doi:10.1016/S0014-2921(00)00037-4
   Web of Science ®Google Scholar
• Tsay, R. S. (1986) Nonlinearity tests for time series, Biometrika, 73, 461–6. doi:10.1093/biomet/73.2.461
   Web of Science ®Google Scholar
• Weron, R. (2011) DFA: MATLAB Function to Compute the Hurst Exponent Using Detrended Fluctuation Analysis (DFA), HSC Software M11002, Hugo Steinhaus Center, Wrocław University of Technology, Wrocław.
   Google Scholar