This study examines the relationship between healthcare expenditure and disposable income in the 50 US states over the period 1966-2009 using fractional integration and cointegration techniques. The degree of integration and nonlinearity of both series are found to vary considerably across...

This paper analyses the long-memory properties of US and European stock indices, as well as their linkages, using fractional integration and fractional cointegration techniques. These methods are more general and have higher power than the standard ones usually employed in the literature. The...

This paper discusses the type of trajectory a country's public debt path follows. In particular, a Markov switching ADF model is used to assess the sustainability of public debt by testing whether a government's present value borrowing constraint holds. Building on the work of Raybaudi et al....

This paper uses Markov switching models to study short-run movements of the Polish zloty and speculative phenomena in Poland, that is, to investigate whether the exchange rate is "contaminated" by a speculative bubble. The zloty movements are examined in terms of so-called long swings - periods...

A growing literature uses changes in residual volatility for identifying structural shocks in vector autoregressive (VAR) analysis. A number of different models for heteroskedasticity or conditional heteroskedasticity are proposed and used in applications in this context. This study reviews the...

We develop a structural vector autoregressive framework that combines external instruments and heteroskedasticity for identification of monetary policy shocks. We show that exploiting both types of information sharpens structural inference, allows testing the relevance and exogeneity condition...

The performance of information criteria and tests for residual heteroskedasticity for choosing between different models for time-varying volatility in the context of structural vector autoregressive analysis is investigated. Although it can be difficult to find the true volatility model with the...

We develop a vector autoregressive framework for combining the information in an external instrument with the information in the second moments of the data to identify latent monetary shocks in the United States. We show that the framework improves the identification of the structural model and...

We develop a vector autoregressive framework that combines an external instrument and heteroskedasticity for the identification of monetary policy shocks. We show that exploiting both types of information sharpens structural inference, allows testing both the relevance and exogeneity condition...