Approaches for the Joint Evaluation of Hypothesis Tests: Classical Testing, Bayes Testing, and Joint Confirmation

The occurrence of decision problems with changing roles of null and alternative hypotheses has increased interest in extending the classical hypothesis testing setup. Particularly, confirmation analysis has been in the focus of some recent contributions in econometrics. We emphasize that confirmation analysis is grounded in classical testing and should be contrasted with the Bayesian approach. Differences across the three approaches – traditional classical testing, Bayes testing, joint confirmation – are highlighted for a popular testing problem. A decision is searched for the existence of a unit root in a time-series process on the basis of two tests. One of them has the existence of a unit root as its null hypothesis and its non-existence as its alternative, while the roles of null and alternative are reversed for the other hypothesis test.Confirmation analysis, Decision contours, Unit roots

Testing for Stationarity in a Cointegrated System

In systems of variables with a specified or already identified cointegrating rank, stationarity of component variates can be tested by a simple restriction test. The implied decision is often in conflict with the outcome of unit root tests on the same variables. Using a framework of Bayes testing and decision contours, this paper searches for a solution to such conflict situations in sample sizes of empirical relevance. It evolves from the decision contour evaluations that the best test to be used jointly with a restriction test on self-cointegration is a modified version of the Dickey-Fuller test that accounts for the other system variables, whereas strictly univariate unit-root tests do not help much in the decision of interest.Bayes test, Unit roots, Cointegration, Decision contours

Unit Root in Unemployment - New Evidence from Nonparametric Tests

We apply range unit-root tests to OECD unemployment rates and compare the results to conventional tests. By simulations, we nd that unemployment is represented adequately by a new nonlinear transformation of a serially-correlated I(1) process.

The Effects of Dollar/Sterling Exchange Rate Volatility on Futures Markets for Coffee and Cocoa

The paper investigates the extent to which the dollar/sterling exchange rate fluctuations affect coffee and cocoa futures prices on the London LIFFE and the New York CSCE by means of multivariate GARCH models - under the assumption that traders in perfectly competitive markets have equal access to all available information on changes in weather and in global demand and supply conditions. In three out of the four investigated cases, exchange rate posed as a main source of risk for the commodity futures price. The significance and form of volatility spill-over effects of a bilateral exchange rate are shown to be specific for commodity and market. A forecasting comparison on the basis of the identified models suggests that possible gains in prediction accuracy may be small.Commodity markets, Multivariate GARCH models, Exchange rates, Volatility, Forecasting

Seasonal Cycles in European Agricultural Commodity Prices

This paper explores the seasonal cycles of European agricultural commodity prices. We focus on three food crops (barley, soft and durum wheat) and on beef. We investigate whether seasonality is deterministic or unit-root stochastic and whether seasonal cycle for specific agricultural commodities have converged over time. Finally, we develop time-series models that are capable of forecasting agricultural prices on a quarterly basis. Firstly, we find that seasonal cycles in agricultural commodity prices are mainly deterministic and that evidence on common cycles across countries varies over agricultural commodities. The prediction experiments, however, yield a ranking with respect to accuracy that does not always match the statistical in-sample evidence.Seasonal cycles, Seasonal unit roots, Forecasting, Agricultural commodities

Toward a Theory of Evaluating Predictive Accuracy

We suggest a theoretical basis for the comparative evaluation of forecasts. Instead of the general assumption that the data is generated from a stochastic model, we classify three stages of prediction experiments: pure non-stochastic prediction of given data, stochastic prediction of given data, and double stochastic simulation. The concept is demonstrated using an empirical example of UK investment data.Forecasting, Time series, Investment

Inflation in the West African Countries. The Impact of Cocoa Prices, Budget Deficits, and Migrant Remittances

We verify whether cocoa prices could be a source of inflation in five countries of the West African region within a framework that includes other variables such as migrant remittances to the region and a fiscal policy variable represented by the government budget deficit. Unlike earlier studies that explicitly use money supply variables, the inclusion of migrant remittances enables us to examine the effect of an international capital flow variable on inflation. The results reveal that the influence of cocoa prices on consumer price inflation is strong and statistically significant. The influence of the budget deficit and the flow of migrant remittance variables on inflation are, however, weak.Inflation, West Africa, Cocoa, Budget deficits, Remittances

Combining Forecasts Based on Multiple Encompassing Tests in a Macroeconomic Core System

We investigate whether and to what extent multiple encompassing tests may help determine weights for forecast averaging in a standard vector autoregressive setting. To this end we consider a new test-based procedure, which assigns non-zero weights to candidate models that add information not covered by other models. The potential benefits of this procedure are explored in extensive Monte Carlo simulations using realistic designs that are adapted to U.K. and to French macroeconomic data. The real economic growth rates of these two countries serve as the target series to be predicted. Generally, we find that the test-based averaging of forecasts yields a performance that is comparable to a simple uniform weighting of individual models. In one of our role-model economies, test-based averaging achieves some advantages in small samples. In larger samples, pure prediction models outperform forecast averages.Combining forecasts, encompassing tests, model selection, time series

On Mean Reversion in Real Interest Rates: An Application of Threshold Cointegtation

Using data from Germany, Japan, UK, and the U.S., we explore possible threshold cointegration in nominal short- and long-run interest rates with corresponding inflation rates. Traditional cointegration implies perfect mean reversion in real rates and hence confirms the Fisher hypothesis. Threshold cointegration accounts for the possibility that this mean reversion is active only conditional on certain threshold values in the observed variables. We investigate whether findings of such effects can be exploited for interest rate prediction.Nonlinear time series, Fisher equation, Yield spread, Forecasting

The Dynamic Interrelations between Unequal Neighbors: An Austro-German Case Study

This article investigates the effects and transmission channels of shocks between two asymmetric neighboring countries. In particular, we investigate Austria and Germany which are highly integrated due to their common language and common membership of the European Monetary Union. Generalized impulse response functions reveal that there are large and significant effects of shocks to the German economy on Austria. In contrast, the effects of shocks to the Austrian economy on Germany are barely significant and if they are, their magnitude is comparatively small. Furthermore we can show that multiplier effects are present in Germany but not in Austria and we identify hysteretic properties in Austrian unemployment.