4 resultados para cancelled orders
em Scottish Institute for Research in Economics (SIRE) (SIRE), United Kingdom
Resumo:
We develop tests of the proportional hazards assumption, with respect to a continuous covariate, in the presence of unobserved heterogeneity with unknown distribution at the individual observation level. The proposed tests are specially powerful against ordered alternatives useful for modeling non-proportional hazards situations. By contrast to the case when the heterogeneity distribution is known up to …nite dimensional parameters, the null hypothesis for the current problem is similar to a test for absence of covariate dependence. However, the two testing problems di¤er in the nature of relevant alternative hypotheses. We develop tests for both the problems against ordered alternatives. Small sample performance and an application to real data highlight the usefulness of the framework and methodology.
Resumo:
This paper examines the effect that heterogeneous customer orders flows have on exchange rates by using a new, and the largest, proprietary dataset of weekly net order flow segmented by customer type across nine of the most liquid currency pairs. We make several contributions. Firstly, we investigate the extent to which customer order flow can help to explain exchange rate movements over and above the influence of macroeconomic variables. Secondly, we address the issue of whether order flows contain (private) information which explain exchange rates changes. Thirdly, we look at the usefulness of order flow in forecasting exchange rate movements at longer horizons than those generally considered in the microstructure literature. Finally we address the question of whether the out-of-sample exchange rate forecasts generated by order flows can be employed profitably in the foreign exchange markets
Resumo:
In this paper we analyse a simple two-person sequential-move contest game with heterogeneous players. Assuming that the heterogeneity could be the consequence of past discrimination, we study the effects of implementation of affirmative action policy, which tackles this heterogeneity by compensating discriminated players, and compare them with the situation in which the heterogeneity is ignored and the contestants are treated equally. In our analysis we consider different orders of moves. We show that the order of moves of contestants is a very important factor in determination of the effects of the implementation of the affirmative action policy. We also prove that in such cases a significant role is played by the level of the heterogeneity of individuals. In particular, in contrast to the present-in-the-literature predictions, we demonstrate that as a consequence of the interplay of these two factors, the response to the implementation of the affirmative action policy option may be the decrease in the total equilibrium effort level of the contestants in comparison to the unbiased contest game.
Resumo:
This paper discusses how to identify individual-specific causal effects of an ordered discrete endogenous variable. The counterfactual heterogeneous causal information is recovered by identifying the partial differences of a structural relation. The proposed refutable nonparametric local restrictions exploit the fact that the pattern of endogeneity may vary across the level of the unobserved variable. The restrictions adopted in this paper impose a sense of order to an unordered binary endogeneous variable. This allows for a uni.ed structural approach to studying various treatment effects when self-selection on unobservables is present. The usefulness of the identi.cation results is illustrated using the data on the Vietnam-era veterans. The empirical findings reveal that when other observable characteristics are identical, military service had positive impacts for individuals with low (unobservable) earnings potential, while it had negative impacts for those with high earnings potential. This heterogeneity would not be detected by average effects which would underestimate the actual effects because different signs would be cancelled out. This partial identification result can be used to test homogeneity in response. When homogeneity is rejected, many parameters based on averages may deliver misleading information.