The availability of new internationally-harmonized innovation survey data collected from OECD countries has created some interesting opportunities for studying the following two key areas: (1) the determinants of innovation behavior at firm level, and (2) innovation as an important factor...

This paper is an empirical analysis of knowledge capital and performance heterogeneity at the firm level. We apply new econometric methods to extensive data on innovation and innovative activities in Swedish manufacturing. Knowledge capital, defined as the ratio of innovation sales to total...

The availability of new internationally-harmonized innovation survey data collected from OECD countries has created some interesting opportunities for studying the following two key areas: (1) the determinants of innovation behavior at firm level, and (2) innovation as an important factor...

This paper considers nine long Swedish macroeconomic time series whose business cycle properties were discussed by Englund, Persson, and Svensson (1992) using frequency domain techniques. It is found by testing that all but two of the logarithmed and difference series are non-linear. The...

The paper discusses a simple univariate nonlinear parametric time-series model for unemployment rates, focusing on the asymmetry observed in many OECD unemployment rate series. The model is based on a standard logistic smooth transition autoregressive (LSTAR) model for the first difference of...

When testing the null hypothesis of linearity of a univariate time series against smooth transition autoregression (STAR), standard asymptotic distribution results do not apply since nuisance parameters in the model are unidentified under the null hypothesis. The prevailing test of Luukkonen,...

A smooth transition autoregressive model is estimated for the Southern Oscillation Index, an index commonly used as a measure of El Niño events. Using standard measures there is no indication of nonstationarity in the index. A logistic smooth transition autoregressive model describes the most...