In addition to quantitative assessment of economic growth using econometric models, business cycle analyses have been proved to be helpful to practitioners in order to assess current economic conditions or to anticipate upcoming fluctuations.
We use TVP models and real-time data to describe the evolution of the leading properties of the yield spread for output growth in five European economies and in the US over the last decades and until the third quarter of 2010.
The Paper presents a model in which the exogenous money supply causes changes in the inflation rate and the output growth rate. While inflation and growth rate changes occur simultaneously, the inflation acts as a tax on the return to human capital and in this sense induces the growth rate decrease.
National accounts statistics undergo a process of revisions over time because of the accumulation of information and, less frequently, of deeper changes, as new definitions, new methodologies etc. are implemented.
We document the empirical properties of revisions to major macroeconomic variables in the United States. Our findings suggest that they do not satisfy simple desirable statistical properties. In particular, we find that these revisions do not have a zero mean, which indicates that the initial announcements by statistical agencies are biased.
This paper explores the usefulness of bagging methods in forecasting economic time series from linear multiple regression models. We focus on the widely studied question of whether the inclusion of indicators of real economic activity lowers the prediction mean-squared error of forecast models of US consumer price inflation.