On the Predictive Content of Autoregression Residuals: A Semiparametric,Copula‐Based Approach to Time Series Prediction

This paper proposes an adjustment of linear autoregressive conditional mean forecasts that exploits the predictive content of uncorrelated model residuals. The adjustment is motivated by non‐Gaussian characteristics of model residuals, and implemented in a semiparametric fashion by means of conditional moments of simulated bivariate distributions. A pseudo ex ante forecasting comparison is conducted for a set of 494 macroeconomic time series recently collected by Dees et al. (Journal of Applied Econometrics 2007; 22: 1–38). In total, 10,374 time series realizations are contrasted against competing short‐, medium‐ and longer‐term purely autoregressive and adjusted predictors. With regard to all forecast horizons, the adjusted predictions consistently outperform conditionally Gaussian forecasts according to cross‐sectional mean group evaluation of absolute forecast errors and directional accuracy. Copyright © 2012 John Wiley & Sons, Ltd.     

Testing Interval Forecasts: A GMM‐Based Approach

This paper proposes a new evaluation framework for interval forecasts. Our model‐free test can be used to evaluate interval forecasts and high‐density regions, potentially discontinuous and/or asymmetric. Using a simple J‐statistic, based on the moments defined by the orthonormal polynomials associated with the binomial distribution, this new approach presents many advantages. First, its implementation is extremely easy. Second, it allows for a separate test for unconditional coverage, independence and conditional coverage hypotheses. Third, Monte Carlo simulations show that for realistic sample sizes our GMM test has good small‐sample properties. These results are corroborated by an empirical application on SP500 and Nikkei stock market indexes. It confirms that using this GMM test leads to major consequences for the ex post evaluation of interval forecasts produced by linear versus nonlinear models. Copyright © 2011 John Wiley & Sons, Ltd.     

Forecasting volatility of emerging stock markets: linear versus non‐linear GARCH models

ARCH and GARCH models are substantially used for modelling volatility of time series data. It is proven by many studies that if variables are significantly skewed, linear versions of these models are not sufficient for both explaining the past volatility and forecasting the future volatility. In this paper, we compare the linear(GARCH(1,1)) and non‐linear(EGARCH) versions of GARCH model by using the monthly stock market returns of seven emerging countries from February 1988 to December 1996. We find that for emerging stock markets GARCH(1,1) model performs better than EGARCH model, even if stock market return series display skewed distributions. Copyright © 2000 John Wiley & Sons, Ltd.     

Pre‐recession pattern of six economic indicators in the USA

This paper applies a tightly parameterized pattern recognition algorithm, previously applied to earthquake prediction, to the problem of predicting recessions. Monthly data from 1962 to 1996 on six leading and coincident economic indicators for the USA are used. In the full sample, the model performs better than benchmark linear and non‐linear models with the same number of parameters. Subsample and recursive analysis indicates that the algorithm is stable and produces reasonably accurate forecasts even when estimated using a small number of recessions. Copyright © 2000 John Wiley & Sons, Ltd.     

Modelling the development of supply‐restricted telecommunications markets

A large proportion of the world telecommunications market can be characterized as supply restricted. In ITU (1999) official waiting lists numbered about 50 million worldwide with an average waiting time of two years. More than 100 countries had not eliminated the waiting list for telephone connections and hence a supply restricted market prevailed in all of these countries. Only about 25 countries have succeeded in eradicating their waiting list for basic telephone service. In terms of the pattern of diffusion, the subscriber's flow from waiting applicants to adopters is controlled by supply restrictions adding an important dimension that needs to be addressed when modeling and forecasting demand. An empirical analysis of the diffusion of main telephones in 46 supply‐restricted countries is presented to demonstrate the usefulness of a three‐stage Bass model that has been proposed to capture the dynamics of supply restrictions. We also compare the forecasting ability of different approaches to estimation when panel data are available. Copyright © 2001 John Wiley & Sons, Ltd.     

Bananas and petrol: further evidence on the forecasting accuracy of the ABS ‘headline’ and ‘underlying’ rates of inflation

In the light of the still topical nature of ‘bananas and petrol’ being blamed for driving much of the inflationary pressures in Australia in recent times, the ‘headline’ and ‘underlying’ rates of inflation are scrutinised in terms of forecasting accuracy. A general structural time‐series modelling strategy is applied to estimate models for alternative types of Consumer Price Index (CPI) measures. From this, out‐of‐sample forecasts are generated from the various models. The underlying forecasts are subsequently adjusted to facilitate comparison. The Ashley, Granger and Schmalensee (1980) test is then performed to determine whether there is a statistically significant difference between the root mean square errors of the models. The results lend weight to the recent findings of Song (2005) that forecasting models using underlying rates are not systematically inferior to those based on the headline rate. In fact, strong evidence is found that underlying measures produce superior forecasts. Copyright © 2009 John Wiley & Sons, Ltd.     

On the historical origins of the contemporary notion of incommensurability: Paul Feyerabend’s assault on conceptual conservativism

This paper investigates the historical origins of the notion of incommensurability in contemporary philosophy of science. The aim is not to establish claims of priority, but to enhance our understanding of the notion by illuminating the various issues that contributed to its development. Kuhn developed his notion of incommensurability primarily under the influence of Fleck, Polanyi, and Köhler. Feyerabend, who had developed his notion more than a decade earlier, drew directly from Duhem, who had developed a notion of incommensurability in 1906. The idea is that in the course of scientific advance, when fundamental theories change, meanings change, which can result in a new conception of the nature of reality. Feyerabend repeatedly used this notion of incommensurability to attack various forms of conceptual conservativism. These include the logical positivists’ foundational use of protocol statements, Heisenberg’s methodological principle that established results must be presupposed by all further research, attempts to separate philosophical accounts of ontology from physics, Bohr’s principle of complementarity, and logical empiricist accounts of reduction and explanation. Focusing on the function of the notion of incommensurability common to Feyerabend’s various critiques explicates Feyerabend’s early philosophy as a series of challenges to forms of conceptual conservativism.