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In this paper we build upon the robust procedures proposed in Vogelsang (1998) for testing hypotheses concerning the deterministic trend function of a univariate time series. Vogelsang proposes statistics formed from taking the product of a (normalised) Wald statistic for the trend function hypothesis under test with a specific function of a separate variable addition Wald statistic. The function of the second statistic is explicitly chosen such that the resultant product statistic has pivotal limiting null distributions, coincident at a chosen level, under I(0) or I(1) errors. The variable addition statistic in question has also been suggested as a unit root statistic, and we propose corresponding tests based on other well-known unit root statistics. We find that, in the case of the linear trend model, a test formed using the familiar augmented Dickey-Fuller [ADF] statistic provides a useful complement to Vogelsang's original tests, demonstrating generally superior power when the errors display strong serial correlation with this pattern tending to reverse as the degree of serial correlation in the errors lessens. Importantly for practical considerations, the ADF-based tests also display significantly less finite sample over-size in the presence of weakly dependent errors than the original tests.

This paper sets up a simple AK-type growth model with heterogeneous consumption goods. It is shown that the (overall) intertemporal elasticity of substitution, the saving rate, and the growth rate of income unambiguously increase in the course of economic development. Moreover, the model offers an intuitive explanation of sectoral change. It is demonstrated that there are a number of implications which are in line with the empirical evidence on economic growth and sectoral change.

Two versions of a fractionally cointegrating vector error correction model (FVECM) are presented. In the case of regular cointegration, linear combinations of fractionally integrated variables are integrated to lower order. Generalized cointegration is defined as the case where the cointegrating variables may be fractional differences of the observed series. The concepts are applied to a model of poll data on approval of the performance of prime ministers and governments in the UK.

Using UK data over the 1973q1-2004q1 period, we find that the dynamics of the real exchange rate, real wages and unemployment vary both with large versus small real exchange rate disequilibria and rising versus falling unemployment regimes. The short-run real exchange rate adjusts only when large disequilibrium deviations occur. We report fast real exchange rate adjustment in periods of falling unemployment. This implies that prices and wages are more flexible when real output is high. When the real exchange rate is highly undervalued, workers respond to an improvement in domestic competitiveness by demanding and getting higher wages. Unemployment is reduced following gains in competitiveness when the real exchange rate is further away from equilibrium.

Inferences about the presence or absence of threshold type nonlinearities in TAR models are conducted within models whose lag length has been estimated in a preliminary stage. Typically the null hypothesis of linearity is then tested against a threshold alternative on which the estimated lag length is imposed on each regime. In this paper we evaluate the properties of test statistics for detecting the presence of threshold effects in autoregressive models when this model uncertainty is taken into account. We show that this approach may lead to important distortions when the underlying model has truly threshold effects by establishing the limiting properties of the estimated lag length in the mispecified linear autoregressive fit and assessing the impact of this model uncertainty on the power of the tests. We subsequently propose a full model selection based approach designed to jointly detect the presence of threshold effects and optimally specify its dynamics and compare its performance with the traditional test based approach.

This paper modifies an ad hoc index originated by Eichengreen et al (1995,1996), which is often used to document financial crises in emerging markets. By assuming nonlinear dynamics in a system of financial data, we successfully develop an alternative approach that not only captures the essence of the conventional index but also offers an indicator that leads the crises in-sample. This is very important for policy markers of transitional economies like Macedonia, for which the historical macroeconomic data are often inadequate for existing "early warning sign" systems of potential crises.