The Life and Death of the Canadian Contingent Gains and Losses Accounting Standards Project*

In April 1994, the Canadian Accounting Standards Board formally approved a new accounting standard for contingent gains and losses. The new standard would have increased the frequency of recording contingent losses, enabled the accrual of some contingent gains, and enhanced disclosures for all contingencies. The changes would primarily have been achieved by requiring management, and their legal advisers, to make predictions, estimates, and disclosures that the existing accounting standard enabled them to avoid. Over two years later, and following numerous changes to the implementation date, the board ultimately decided not to release the new standard, and in July 1999, formally abandoned the contingencies project. This study provides a telling of the standard's genesis, development, and ultimate demise, which should prove instructive to those parties with an interest and a stake in accounting standard setting.     

ON THE CONFLICT–POVERTY NEXUS

We develop a model to explore the inter-relationships between conflict and economic activity. We construct a simple two-period model where consumption and investment decisions are made in the presence of governments who consider initiating diversionary conflict to raise their chances of remaining in power. Economies with selfish leaders and lower gains from capital formation may fall prey to engaging in avoidable conflicts thereby lowering investment and hence future growth. Using panel data for over 152 countries from 1950 to 2000, we find evidence for conflict lowering economic growth and, after conditioning on the initial conditions of geography, private, public, and human capital investment, lower growth raising the likelihood of conflict. These results are broadly consistent with our model.     

TERRORISM AND THE RETURNS TO OIL

The effect of terrorism on global oil prices has been largely explained through demand-side effects. We estimate an empirical model to re-examine the effect of terrorism on the price of global oil stocks across oil market regimes that reflect different supply constraints. We believe that terrorism will have larger impacts when global capacity is tight (i.e. when global demand is close to global supply). This means that any shock to capacity (say by conflict) should have the largest impact on profits before the first OPEC shock in the early 1970s. Since then, conflict shocks would not allow firms to exploit production in the same way, thus reducing the available profits that could be garnered by such production manipulation. If capacity constraints are binding when a conflict occurs, then we predict that a positive stock price reaction can be expected for oil firms from such a shock. We exploit a new panel dataset to investigate the relationship between oil profitability and conflict, using conflict data from the top 20 oil producing and exporting countries in the world. We show that in the later part of our sample, 1974–2005, as cartel behavior of OPEC member countries has diminished and as conflict has become more regular and thus the information surrounding it noisier, oil stock prices do not increase in response to conflict. However, in earlier capacity constrained eras, we find that oil stocks can in fact increase in response to conflict. In some cases, the impact of conflict may cause the return of oil stocks to increase by as much as 10 percentage points.     

Simple Technical Trading Rules and the Stochastic Properties of Stock Returns

This paper tests two of the simplest and most popular trading rules—moving average and trading range break—by utilizing the Dow Jones Index from 1897 to 1986. Standard statistical analysis is extended through the use of bootstrap techniques. Overall, our results provide strong support for the technical strategies. The returns obtained from these strategies are not consistent with four popular null models: the random walk, the AR(1), the GARCH-M, and the Exponential GARCH. Buy signals consistently generate higher returns than sell signals, and further, the returns following buy signals are less volatile than returns following sell signals, and further, the returns following buy signals are less volatile than returns following sell signals. Moreover, returns following sell signals are negative, which is not easily explained by any of the currently existing equilibrium models.