Economic Development Indicators as Determinants of Medal Winning at the Sydney Olympics: An Extreme Bounds Analysis

This paper examines the variables that determine the performance of countries at the Olympic Games as measured by a weighted sum of the medals won at the Sydney 2000 Games. While previous studies have identified the importance of a country's economic size and the resources available to sport, this paper examines nine more variables including the number of athletes representing each nation and some development indicators. Based on 2310 regressions, both traditional and restricted extreme bounds analysis show that only two variables are robust: the number of athletes and national expenditure on health. Thus, the final model recognises four explanatory variables that include these two as well as GDP and population.     

Price Discovery and Risk Transfer in the Crude Oil Futures Market: Some Structural Time Series Evidence

This paper re-examines the Garbade and Silber (1983) model with the objective of finding out if the crude oil futures market performs the functions of price discovery and risk transfer. The model is estimated, using daily data, as a system of two seemingly unrelated time series equations allowing the coefficients to be time-varying. The empirical results reveal that the futures market performs about 60 per cent of the price discovery function, and that the elasticity of supply of arbitrage services is adequately high for the market to perform the risk transfer function.
(J.E.L: G13, C22).     

GDP nowcasting: application and constraints in a small open developing economy

Despite data limitations, an attempt is made to find out if a GDP nowcasting model can provide reliable forecasts for a small open economy. Two competing Bayesian vector autoregressive models are tested rigorously to obtain the optimal model by minimizing in-sample forecasting errors. The main finding of this study is that GDP nowcasting can produce reliable results for a small open economy despite the unavailability of sufficient data sets and the lack of high frequency indicators.     

Cointegration as an explanation for the Meese–Rogoff puzzle

Some economists suggest that the failure of exchange-rate models to outperform the random walk in exchange rate forecasting out of sample can be attributed to failure to take into account cointegration when it is present. We attempt to find out if cointegration matters for forecasting accuracy by examining the relation between the stationarity and size of the forecasting error. Results based on three macroeconomic models of exchange rates do not provide strong support for the proposition that cointegration matters for forecasting accuracy. The simulation results show that while stationary errors tend to be smaller than non-stationary errors, this is not a universal rule. Irrespective of the presence or absence of cointegration, none of the three models can outperform the random walk in out-of-sample forecasting, which means that cointegration cannot solve the Meese–Rogoff puzzle.     

The profitability of interest arbitrage when the base currency is pegged to a basket

When the interest rate on a currency that is pegged to a basket differs from the interest rate on the basket (as a weighted average), it is possible to make profit from interest arbitrage by going short on the basket and long on the pegged currency, or vice versa. This proposition is illustrated by using data on the Kuwaiti dinar and its basket currencies over the period 1998–2002 when the currency was pegged to a basket. Monte Carlo simulations show that the probability of making arbitrage profit from any single operation is about 95%.     

Modelling Seasonality in the Australian Consumption Function

This paper puts forward the proposition that failure to take account of stochastic seasonality results in dynamic misspecification. This point is illustrated by estimating various versions of a simple Australian consumpt ion function using seasonally unadjusted data covering the period 1959(3)–1993(3). It is demonstrated that only the equation modelling stochastic seasonality as an unobserved component shows no dynamic misspecification unlike other equations. This equation is also shown to have the highest explanatory power and, unlike other equations, to be structurally stable     

SOME EVIDENCE ON MEAN REVERSION IN EX ANTE REAL INTEREST RATES

Ex ante real interest rates and their differentials are tested for mean reversion using quarterly data on three-month treasury bill rates and consumer prices for 12 major industrial countries over the period 1972:l-1993:3. The results are strongly supportive of mean reversion, particularly when less conventional tests are employed. The conclusion that can be derived from the empirical evidence is that goods, capital and foreign exchange markets have become highly integrated in the countries under consideration.     

Demystifying the Meese–Rogoff puzzle: structural breaks or measures of forecasting accuracy?

Structural breaks have been suggested by several economists as a possible explanation for the Meese–Rogoff puzzle, in the sense that an exchange rate model can outperform the random walk in terms of the out-of-sample forecasting error if the period under investigation is free of structural breaks. The results indicate that structural breaks cannot explain the inability of the flexible price monetary model to outperform the random walk. The only plausible explanation for the Meese–Rogoff puzzle is that forecasting accuracy is traditionally assessed by magnitude-only measures. When forecasting accuracy is assessed by alternative measures that do not rely exclusively on the magnitude of error, the monetary model can outperform the random walk regardless of the presence or otherwise of structural breaks.