DYNAMICS OF UNEMPLOYMENT AND INFLATION IN WESTERN EUROPE: SOLUTION BY THE 1- D BOUNDARY ELEMENTS METHOD

Using an analog of the boundary elements method in engineering and science, we analyze and model unemployment rate in Austria, Italy, the Netherlands, Sweden, Switzerland, and the United States as a function of inflation and the change in labor force. Originally, the model linking unemployment to inflation and labor force was developed and successfully tested for Austria, Canada, France, Germany, Japan, and the United States. Autoregressive properties of neither of these variables are used to predict their evolution. In this sense, the model is a self-consistent and completely deterministic one without any stochastic component (external shocks) except that associated with measurement errors and changes in measurement units. Nevertheless, the model explains between ~65% and ~95% of the variability in unemployment and inflation. For Italy, the rate of unemployment is predicted at a time horizon of nine (!) years with pseudo out-of-sample root-mean-square forecasting error of 0.55% for the period between 1973 and 2006. One can expect that the unemployment will be growing since 2008 and will reach ~11.4% [±0.6 %] near 2012. After 2012, unemployment in Italy will start to descend.unemployment, inflation, labor force, boundary integral method, prediction, Western Europe

LONG-TERM LINEAR TRENDS IN CONSUMER PRICE INDICES

Headline CPI, core CPI and indices for various expenditure categories were analyzed. Long-term linear trends have been found in the difference between the core CPI and the headline CPI in the USA. Duration of these periods is different for positive (18 years) and negative (8 years) trends, and the trends change to opposite during some shorter time intervals of 2 to 4 years. The difference between the core CPI and the index for energy is similar to that between the core CPI and headline CPI. The index for energy will reach the core CPI in 2008, however. Then, one should not expect further increase in energy price beyond that dictated by the CPI. It is likely that oil price will be falling in absolute terms. The difference between the core CPI and the index for food also has two linear branches after 1980, but the slope of the current trend is weak and the difference will intercept zero line only in 2014. The difference between the core CPI and the housing index is characterized by an almost constant duration of negative and positive branches � approximately 11 years. The current period of negative slope in the difference will approach its turning point in 2008 or 2009 and is characterized by very high volatility. The next trend has to be positive, i.e. the housing index will be growing at a lower rate than the headlining CPI. The difference for the transportation index had a longer period of positive slope � between 1980 and 2004. During this period the difference reached the level of 30 units of index. Currently, a turning period is observed and a negative slope is developing. The difference related to price indices allows to accurately predicting the evolution of relevant stock market indices.CPI, core CPI, expenditure categories, price index, stock market index

The driving force of labor force participation in developed countries

The evolution of labor force participation rate is modeled using a lagged linear function of real economic growth, as expressed by GDP per capita. For the U.S., our model predicts at a two-year horizon with RMSFE of 0.28% for the period between 1965 and 2007. Larger part of the deviation between predicted and measured LFP is explained by artificial dislocations in measured time series induced by major revisions to the CPS methodology in 1979 and 1989. Similar models have been developed for Japan, the UK, France, Italy, Canada, and Sweden.labor force participation, real GDP per capita, prediction

MODELLING REAL GDP PER CAPITA IN THE USA:COINTEGRATION TESTS

A two-component model for the evolution of real GDP per capita in the United States is presented and tested. First component of the growth rate of GDP represents the growth trend and is inversely proportional to the attained level of real GDP per capita, with the nominator being constant through time. Second component is responsible for the fluctuations around the growth trend and is defined as a half of the growth rate of the number of 9-year-olds. This nonlinear relationship between the growth rate of real GDP per capita and the number of 9-year-olds in the US is tested for cointegration. For linearization of the problem, the population time series is predicted using the relationship. Both single year of age population time series, the measured and predicted one, are shown to be nonstationary and integrated of order 1 � the original series have unit roots and their first differences have no unit root. The Engel-Granger procedure is applied to the difference of the measured and predicted time series and to the residuals of a linear regression. Both tests show the existence of a cointegrating relation. The Johansen test results in the cointegrating rank 1. Since the cointegrating relation between the measured and predicted number of 9-year-olds does exist, the VAR, VECM, and linear regression are used in estimation of the goodness of fit and root mean-square errors, (RMSE). The highest R2=0.95 and the lowermost RMSE is obtained in the VAR representation. The VECM provides consistent, statistically reliable, and significant estimates of the slope in the cointegrating relation. Econometrically, the tests for cointegration show that the deviations of real economic growth in the US from the growth trend, as defined by constant annual increment of real per capita GDP, are driven by the change in the number of 9-year-olds.real GDP per capita, population estimates, cointegration, VAR, VECM, USA

COMPREHENSIVE MACRO � MODEL FOR THE US ECONOMY

We present a comprehensive macroeconomic model for the US There exist strict long�term relations between real GDP, price inflation, labor force participation, productivity, and unemployment. The evolution of real GDP depends only on exogenous demographic forces. Other macro�variables follow up the real GDP. The links between the variables have been valid during the last several decades. All relations were (successfully) tested for cointegration. Statistical estimates are also presented. The relationships allow a reliable prediction of the macroeconomic state at very large (more than 9 years) time horizons.US economy, GDP, inflation, unemployment, labor force, productivity, demography