Nonlinear Dynamics in the Finance-Inequality Nexus in China-CHNS Data

This paper empirically investigates the effects of financial development on incomes of Chinese residents particularly within various income groups using data from six provinces by applying the Quantile Regression model. The Greenwood and Jovanovich hypothesis that illustrates the inverted U shaped relationship between financial development and income inequality is tested. This empirical study demonstrates that financial development has a positive but non-linear effect on the annual income of individuals from various income groups at different quantiles. The effect is an inverted U or Kuznets effect indicating an increase at first and then a drop. As for the distribution of the impact on various income groups, the low-income group is under the most dominant influence followed by the high-income group with the middle-income groups receiving relatively smaller influence. Findings indicate that promoting balanced financial development would help to ease the income gap between Chinese residents

JUMP, NON-NORMAL ERROR DISTRIBUTION AND STOCK PRICE VOLATILITY — A NONPARAMETRIC SPECIFICATION TEST

This paper examines a wide variety of popular volatility models for stock index return, including Random Walk model, Autoregressive model, Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model, and extensive GARCH model, GARCH-jump model with Normal, and Student t-distribution assumption as well as nonparametric specification test of these models. We fit these models to Dhaka stock return index from 20 November 1999 to 9 October 2004. There has been empirical evidence of volatility clustering, alike to findings in previous studies. Each market contains different GARCH models, which fit well. From the estimation, we find that the volatility of the return and the jump probability were significantly higher after 27 November 2001. The model introducing GARCH jump effect with normal and Student t-distribution assumption can better fit the volatility characteristics. We find that RW-GARCH-t, RW-AGARCH-t RW-IGARCH-t and RW-GARCH-M-t can pass the nonparametric specification test at 5% significance level. It is suggested that these four models can capture the main characteristics of Dhaka stock return index.GARCH-jump, nonparametric specification test, t-distribution