Testing for Covariate Effect in the Cox Proportional Hazards Regression Model

This article presents methods for testing covariate effect in the Cox proportional hazards model based on Kullback–Leibler divergence and Renyi's information measure. Renyi's measure is referred to as the information divergence of order γ (γ ≠ 1) between two distributions. In the limiting case γ → 1, Renyi's measure becomes Kullback–Leibler divergence. In our case, the distributions correspond to the baseline and one possibly due to a covariate effect. Our proposed statistics are simple transformations of the parameter vector in the Cox proportional hazards model, and are compared with the Wald, likelihood ratio and score tests that are widely used in practice. Finally, the methods are illustrated using two real-life data sets.     

The Simplest Dynamic General-Equilibrium Model of an Open Economy

This paper presents the simplest possible general-equilibrium model of an open economy in which producer and consumer decisions are both intra- and intertemporally consistent. Consumers maximize the present value of the utility of consumption; producers maximize the present value of profits. The model solves for the set of intertemporally consistent prices. The parsimonious structure of the model is achieved by dividing the economy into two producing sectors—exports and domestic goods—and two consumed goods—imports and domestic goods. As a result, there is only one endogenous price per period to be solved for (the price of the domestic good), although “structural” questions, such as the evolution of the real exchange rate, can be posed with the model. Furthermore, with this structural breakdown, the model can be calibrated with national accounts data only. In the paper, we show how to calibrate such a model (including specification of an adjustment-cost function, to avoid “bang-bang” behavior) and use the model to examine various questions where intertemporal issues are important, including terms-of-trade shocks and tariff reform.