Spurious Relationship of AR(P) Stable Sequences in Presence of Trends Breaks

This paper analyzes spurious regression phenomenon involving AR(p) stable processes with trend breaks. It shows that when those time series are used in ordinary least squares regression, the convenient t-ratios procedures wrongly indicate that the spurious relationship is present as the pair of independent stable series contains trend changes. The spurious relationship becomes stronger as the sample size approaches to infinite. As a result, spurious effects might occur more often than we previously believed as they can arise even between AR(p) stable series in present of trend breaks

True Versus Spurious Long Memory: Some Theoretical Results and a Monte Carlo Comparison

A common feature of financial time series is their strong persistence. Yet, long memory may just be the spurious effect of either structural breaks or slow switching regimes. We explore the effects of spurious long memory on the elasticity of the stock market price with respect to volatility and show how cross-sectional aggregation may generate spurious persistence in the data. We undertake an extensive Monte Carlo study to compare the performance of five tests, constructed under the null of true long memory versus the alternative of spurious long memory due to level shifts or breaks

Cliometrics and Time Series Econometrics: Some Theory and Applications

The paper discusses a range of modern time series methods that have become popular in the past 20 years and considers their usefulness for cliometrics research both in theory and via a range of applications. Issues such as, spurious regression, unit roots, cointegration, persistence, causality, structural time series methods, including time varying parameter models, are introduced as are the estimation and testing implications that they involve. Applications include a discussion of the timing and potential causes of the British Industrial Revolution, income „convergence? and the long run behaviour of English Real Wages 1264 – 1913. Finally some new and potentially useful developments are discussed including the mildly explosive processes; graphical modelling and long memory.Time series; cointegration; unit roots; persistence; causality; cliometrics; convergence; long memory; graphical modelling; British Industrial Revolution

Fractional Output Convergence, with an Application to Nine Developed Countries

We argue that cross-country convergence of output per capita should be examined in a fractional-integration time-series context and we propose a new empirical strategy to test it, which is the first one that discriminates between fractional long-run convergence and fractional catching-up. The starting point of the paper is: since there are reasons to believe that aggregate output is fractionally integrated, the usual testing strategy based on unit-root or traditional I(1)-I(0) cointegration techniques is too restrictive and may lead to spurious results. We then propose a new classification of output convergence processes which is valid when outputs are fractionally integrated and which nests the usual definitions built for an I(1)-versus-I(0) world. The new testing strategy, which can identify the precise type of convergence, is based on the combined use of new inferential techniques developed in the fractional integration literature. The advantage of these new techniques is that of being robust both to the presence of a trend and to a memory parameter d above 0.5. We explain in detail the importance of this advantage for testing convergence. This strategy applied on a group of developed countries (G-7, Australia and New Zealand) shows that these countries converged in the last century; it also determines the type of convergence for each one. The main result is that per-capita-output differentials are typically mean-reverting fractionally I(d), with d significantly above 0 but below 1. This contrasts with the results of divergence obtained with six unit-root tests and by other authors with I(1)-I(0) (co)integration techniques. The paper therefore contributes to solve the puzzling negative or inconclusive results about convergence usually obtained with I(1)-I(0) tests; our results also prove that the proposed widening of the statistical definition of output convergence is necessary and that convergence does take place but is slower than traditionally expectedreal convergence, fractional integration, unit roots, non stationarity

Long range dependence in South African Platinum prices under heavy tailed error distributions

South Africa is rich in platinum group metals (PGMs) and these metals are important in providing jobs as well as investments some of which have been seen in the Johannesburg Securities Exchange (JSE). In this country this sector has experienced some setbacks in recent times. The most notable ones are the 2008/2009 global nancial crisis and the 2012 major nationwide labour unrest. Worrisomely, these setbacks keep simmering. These events usually introduce jumps and breaks in data which changes the structure of the underlying information thereby inducing spurious long memory (long range dependence). Thus it is recommended that these two phenomena must be addressed together. Further, it is well-known that nancial returns are dominated by stylized facts. In this thesis we carried out an investigation on distributional properties of platinum returns, structural changes, long memory and stylized facts in platinum returns and volatility series. To understand the distributional properties of the returns, we used two classes of heavy tailed distributions namely the alpha-Stable distributions and generalized hyperbolic distributions. We then investigated structural changes in the platinum return series and changes in long range dependence and volatility. Using Akaike information criterion, the ARFIMA-FIAPARCH under the Student distribution was selected as the best model for platinum although the ARCH e ects were slightly signi cant, while using the Schwarz information criteria the ARFIMA-FIAPARCH under the Normal distribution. Further, ARFIMA-FIEGARCH under the skewed Student distribution and ARFIMA-HYGARCH under the Normal distribution models were able to capture the ARCH effects. The best models with respect to prediction excluded the ARFIMA-FIGARCH model and were dominated by ARFIMA-FIAPARCH model with non-Normal error distributions which indicates the importance of asymmetry and heavy tailed error distributions.StatisticsM. Sc. (Statistics

Real interest rate persistence: evidence and implications

The real interest rate plays a central role in many important financial and macroeconomic models, including the consumption-based asset pricing model, neoclassical growth model, and models of the monetary transmission mechanism. We selectively survey the empirical literature that examines the time-series properties of real interest rates. A key stylized fact is that postwar real interest rates exhibit substantial persistence, shown by extended periods of time where the real interest rate is substantially above or below the sample mean. The finding of persistence in real interest rates is pervasive, appearing in a variety of guises in the literature. We discuss the implications of persistence for theoretical models, illustrate existing findings with updated data, and highlight areas for future research.Interest rates

Real interest rate persistence: evidence and implications

The real interest rate plays a central role in many important financial and macroeconomic models, including the consumption-based asset pricing model, neoclassical growth model, and models of the monetary transmission mechanism. The authors selectively survey the empirical literature that examines the time-series properties of real interest rates. A key stylized fact is that postwar real interest rates exhibit substantial persistence, shown by extended periods when the real interest rate is substantially above or below the sample mean. The finding of persistence in real interest rates is pervasive, appearing in a variety of guises in the literature. The authors discuss the implications of persistence for theoretical models, illustrate existing findings with updated data, and highlight areas for future research.Interest rates