6 research outputs found
Does Banque de France control inflation and unemployment?
We re-estimate statistical properties and predictive power of a set of
Phillips curves, which are expressed as linear and lagged relationships between
the rates of inflation, unemployment, and change in labour force. For France,
several relationships were estimated eight years ago. The change rate of labour
force was used as a driving force of inflation and unemployment within the
Phillips curve framework. The set of nested models starts with a simplistic
version without autoregressive terms and one lagged term of explanatory
variable. The lag is determined empirically together with all coefficients. The
model is estimated using the Boundary Element Method (BEM) with the least
squares method applied to the integral solutions of the differential equations.
All models include one structural break might be associated with revisions to
definitions and measurement procedures in the 1980s and 1990s as well as with
the change in monetary policy in 1994-1995. For the GDP deflator, our original
model provided a root mean squared forecast error (RMSFE) of 1.0% per year at a
four-year horizon for the period between 1971 and 2004. The rate of CPI
inflation is predicted with RMSFE=1.5% per year. For the naive (no change)
forecast, RMSFE at the same time horizon is 2.95% and 3.3% per year,
respectively. Our model outperforms the naive one by a factor of 2 to 3. The
relationships for inflation were successfully tested for cointegration. We have
formally estimated several vector error correction (VEC) models for two
measures of inflation. At a four year horizon, the estimated VECMs provide
significant statistical improvements on the results obtained by the BEM:
RMSFE=0.8% per year for the GDP deflator and ~1.2% per year for CPI. For a two
year horizon, the VECMs improve RMSFEs by a factor of 2, with the smallest
RMSFE=0.5% per year for the GDP deflator.Comment: 25 pages, 12 figure