This paper develops a wavelet (spectral) approach to estimate the parameters of a linear regression model where the regressand and the regressors are persistent processes and contain a measurement error. We propose a wavelet filtering approach which does not require instruments and yields...

Long-run income convergence is investigated in the US context. We employ a novel pair-wise econometric procedure based on a probabilistic definition of convergence. The time-series properties of all the possible regional income pairs are examined by means of unit root and non-cointegration tests...

Using a long historical dataset, we estimate a Threshold Vector Autoregression (T-VAR) model for the UK based on a financial stress measure, the debt-to-GDP ratio, borrowing costs and real GDP growth. Our model allows for the impact of debt/GDP to vary between periods of high and low economic...

We extend previous literature on fiscal policy sustainability by introducing non-linear fiscal reaction functions with endogenously estimated state-varying thresholds to capture the behaviour of fiscal policy authorities during “good” and “bad” times. These thresholds vary with the level...

This study examines the determinants of bond yield spreads for 22 emerging markets in the period 1998-2009. In addition to the usual EMBI index data from credit default swaps (CDS) are also used. Three sets of determinants are considered: domestic, external, and institutional factors. In...

In this paper we examine long-run house price convergence across US states using a novel econometric approach advocated by Pesaran (2007) and Pesaran et al. (2009). Our empirical modelling strategy employs a probabilistic test statistic for convergence based on the percentage of unit root...

The proposed tests are derived from maximizing the differential entropy subject to moment constraints. By exploiting the equivalence between the Maximum Entropy and Maximum Likelihood estimates of the general exponential family, we can use the conventional Likelihood Ratio, Wald and Lagrange...

Conventional time series analysis, focusing exclusively on a time series at a given scale, lacks the ability to explain the nature of the data generating process. A process equation that successfully explains daily price changes, for example, is unable to characterize the nature of hourly price...