
Markku Lanne and Jani Luoto, "A New Time-Varying Parameter Autoregressive Model for U.S. Inflation
Expectations", Journal of Money, Credit and Banking.


The data are in three separate text files, CPIQ.txt, PCE.txt and RTCPI.txt, which are zipped in the zip files TVPARrs.zip, TVPARs.zip, TVPNKPC.zip, and TVPARrsRealTime.zip, along with the algorithms. All these zip-files are, in turn, zipped in the file JMCB_NCAR.zip.

The file CPIQ.txt and PCE.txt contain the quarterly series from 1947:Q1 to 2015:Q1 on the seasonally adjusted Consumer Price Index for All Urban Consumers and Personal Consumption Expenditures (Chain-type Price Index), respectively, for the U.S. The series were downloaded from the Federal Reserve Economic Data (FRED) website, and they are freely available at http://research.stlouisfed.org/fred2/.

The file RTCPI.txt contains the quarterly (monthly averages) real-time CPI series from 1947:Q1 to 2015:Q1. In the columns are the vintages from 1994:Q3 to 2015:Q1. The series is downloaded from the Real-time Data Research Center of the Federal Reserve Bank of Philadelphia


The zip-files TVPARrs.zip and TVPARs.zip contain the Matlab codes for estimating the mixed and purely noncausal time-varying parameter AR models in the paper, respectively. The main scripts that carry out the computations are NCAR_ARMH.m and NCAR_ARMH_Purely.m, respectively. The zip-file TVPNKPC.zip contains the Matlab codes for estimating the parameters of the NKPC, and the main script is NKPC_ARMH.m. The zip-file TVPARrsRealTime.zip contains the Matlab codes for real-time-forecasting by the mixed noncausal time-varying parameter AR models, and the main script is NCAR_ARMH_forecasts.m.

The algorithms require the user to specify lags (r) and leads (s), the lower and upper bounds (a and b), forecast horizon (h), and the posterior sample size (N).

In some parts, the codes follow closely those in Chan, J.C.C., Koop, G. and Potter, S.M. (2013). "A New Model of Trend Inflation", Journal of Business and Economic Statistics, 31(1), 94-106, and Chan, J.C.C. (Forthcoming). "The Stochastic Volatility in Mean Model with Time-Varying Parameters: An Application to Inflation Modeling".Journal of Business and Economic Statistics. The m-file SV.m used to simulate the stochastic volatilities, is taken from Chan, J.C.C. (2013). "Moving Average Stochastic Volatility Models with Application to Inflation Forecast", Journal of Econometrics, 176(2), 162-172.