Modelling the trend and seasonals within an AIDS model of the demand for alcoholic beverages in the United Kingdom

The argument that is put forward in this paper is that failure to represent stochastic trend and stochastic seasonality in an AIDS model leads to a misspecified and possibly structurally unstable model. This proposition is verified by estimating an AIDS model of the demand for alcoholic beverages in the United Kingdom. Three versions of the model are estimated, and it is demonstrated that the version allowing for stochastic trend and stochastic seasonality performs better than the other two versions of the model in terms of the diagnostics tests and goodness of fit measures. The best estimated model turns out to possess the properties of having common components and being homogenous. Further empirical testing reveals the presence of stochastic trends and cointegration between the budget shares of beer and wine. The results clearly indicate that there has been a shift away from the consumption of beer towards wine. Copyright © 2002 John Wiley & Sons, Ltd.     

In Defence of Model-Based Seasonal Adjustment: An Illustration Using Australian Data

It is argued that the X-11 seasonal adjustment procedure suffers from severe drawbacks, and so it should be abandoned in favour of model-based seasonal adjustment. Furthermore, it is argued that Harvey's structural time series model is superior to the conventional seasonal ARIMA models for the purpose of model-based seasonal adjustment. It is shown, with the help of a large number of Australian time series, that the nature of seasonality differs from one series to another, and this is why model selection is crucial for seasonal adjustment. It is further shown that model-based seasonal adjustment could produce results that are significantly different from those obtained by applying the X-11 procedure. Since the X-11 procedure is not based on an explicit model and in view of its other serious drawbacks, it is concluded that the procedure should be abandoned in favour of model-based seasonal adjustment.     

The wealth effect and diamond risk structure of financial regulation

The objective of this article was to evaluate the effect of announcements of financial regulation on risk and return in the Vietnamese equity market. The techniques used for the purpose of analysing risk and return include event study and non-parametric tests, as well as asset pricing models supplemented with interaction variables and a variety of ARCH-like specifications such as GARCH, TARCH, EGARCH and PARCH. We find evidence for the wealth effect, the presence of delayed response and a risk shifting behaviour in the form of diamond risk structure. Our results show that abnormal returns are present around the announcements of operating rules and other stock market regulations. Abnormal returns can also be obtained after considering legal documents such as circulars and decisions.     

Error correction modelling and dynamic specifications as a conduit to outperforming the random walk in exchange rate forecasting

The proposition that dynamic exchange rate models can outperform the random walk in out-of-sample forecasting, in the sense that they produce lower mean square errors, is examined and disputed. By using several dynamic versions of three macroeconomic exchange rate models, it is demonstrated that dynamic specifications outperform the corresponding static models but improvement in the forecasting power may not be sufficient for the dynamic models to perform better than the random walk. The results are explained by suggesting that any dynamic specification or transformation of the static model leads to the introduction of a lagged dependent variable, which in effect is a random walk component. The analysis leads to the conclusion that it is implausible to aim at beating the random walk by augmenting a static model with a random walk component.     

The dynamic relationship between the US GDP,imports and domestic production of crude oil

This article investigates the dynamic relationship between crude oil imports, gross domestic product (GDP) and domestic crude oil production of the United States using a Vector Error Correction model estimation, generalized impulse response functions, persistence profile and variance decompositions. This article results suggest that the GDP has a leading role in determining oil imports.     

The cyclical behaviour of prices in the U.K.: Some structural time series evidence

The cyclical behaviour of prices in the U.K. is investigated using a sample of annual observations covering the period 1886–1993. A structural time series model relating consumer prices to output is estimated over four sub-periods. The results indicate that prices were procyclical in the inter-war period, countercyclical in the post-1973 period and acyclical otherwise. The proposition that the cyclical behaviour of prices is determined by the dominance of supply or demand shocks alone is disputed on the basis of empirical evidence and theoretical reasoning. It is concluded that the cyclical behaviour of prices cannot be explained just by analysing time series on output and prices and that due attention should be paid to the institutional and policy changes occurring during the period under study. It is demonstrated that the empirical results are consistent with the events experienced by the U.K. economy in the most recent period. First version received: November 1998/final version accepted: October 1999     

The relationship between spot and futures prices: Evidence from the crude oil market

This article examines the relationship between the spot and futures prices of WTI crude oil using a sample of daily data. Linear causality testing reveals that futures prices lead spot prices, but nonlinear causality testing reveals a bidirectional effect. This result suggests that both spot and futures markets react simultaneously to new information. © 1999 John Wiley & Sons, Inc. Jrl Fut Mark 19: 175–193, 1999     

Does ownership concentration affect banks’ credit risk? Evidence from MENA emerging markets

The purpose of this study is to explore the impact of ownership concentration on banks’ credit risk. The study employs a dynamic panel approach using data from 98 banks listed in the 10 Middle East and North African (MENA) emerging stock markets between 2003 and 2016. To better understand the nature of the relationship between ownership concentration and bank credit risk and how this relationship is shaped by the recent financial crisis, we conducted a pre- and postcrisis analysis. Our findings document a positive relationship between ownership concentration and nonperforming loans in the precrisis period, which surprisingly reverses during the postcrisis period. We argue that the reversal of this relationship is driven by changes in controlling shareholders’ risk aversion, behavior, and attitude prompted by the financial crisis. Given that central banks are entrusted with forestalling banks’ failure, incorporating ownership concentration, as a fundamental determinant of banks’ credit risk, is crucial to anticipate future financial calamities. Our findings highlight the gravity of agency problems in emerging MENA markets. Reinforcing firm-level as well as country-level governance mechanisms is crucial to restore a sound banking system, enhance markets’ integrity, and increase investors’ confidence.