ESTIMATION OF INCOME DISTRIBUTION AND DETECTION OF SUBPOPULATIONS: AN EXPLANATORY MODEL

Inequality and polarization analyses are complementary but conceptually different. They are usually implemented independently in practic e, with different a priori assumptions and different tools. In this paper, we develop a unique method to study simultaneously these different and complementary concerns. Based on mixture models, the method we develop includes at the same time : an estimation of income distribution with no a priori assumptions - a decomposition in several homogeneous subpopulations - an explanatory model to study the structure of the income distribution.

Regime switching volatility calibration by the Baum-Welch method

Regime switching volatility models provide a tractable method of modelling stochastic volatility. Currently the most popular method of regime switching calibration is the Hamilton filter. We propose using the Baum-Welch algorithm, an established technique from Engineering, to calibrate regime switching models instead. We demonstrate the Baum-Welch algorithm and discuss the significant advantages that it provides compared to the Hamilton filter. We provide computational results of calibrating and comparing the performance of the Baum-Welch and the Hamilton filter to S&P 500 and Nikkei 225 data, examining their performance in and out of sample