This paper investigates the impacts of financial development, urbanization, and globalization on income inequality in China by applying a regression-based inequality decomposition approach to panel data on Chinese provinces. Provincial data on urbanization and globalization are combined with new data collected from a unique database of financial development in China compiled at the county level. Our findings suggest that financial development, urbanization, and globalization have a positive impact on income. However, our inequality decomposition suggests that financial development may be particularly important for promoting inclusive growth, since financial development not only stimulates economic growth but is also found to be a factor that reduces inequality.

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This paper empirically examines the impact of the economic policy uncertainty (EPU) index on market indicators of indemnificatory houses in China for the period from January 2012 to December 2018. We use three indicators of the indemnificatory housing market: (i) the price of commodity housing unit, (ii) the number of completion for indemnificatory housing unit and (iii) the amount of investment for indemnificatory housing unit. The findings from the Granger Causality in Distribution test show that the EPU causes the commodity housing price at the left-tail and the right-tail, but not at the centre of the distribution. Besides, the EPU causes the indemnificatory housing completion volume at the right tail, but not at the left and the centre of the distribution. Finally, we observe that the EPU causes the indemnificatory housing investment at the right tail but not at the left and the centre of the distribution. These findings indicate that the indemnificatory housing market in China is mainly affected by the extreme changes in the EPU.

In this study, we compare the adjustments of credit ratings by an investor-paid credit rating agency (CRA), represented by Egan-Jones Ratings Company, and an issuer-paid CRA, represented by Moody’s Investors Service, vis-à-vis conflict of interest and reputation. A novel distribution dynamics approach is employed to compute the probability distribution and, hence, the downgrade and upgrade probabilities of a credit rating assigned by these two CRAs of different compensation systems based on the dataset of 750 U.S. issuers between 2011 and 2018, that is, after the passage of the Dodd–Frank Act. It is found that investor-paid ratings are more likely to be downgraded than issuer-paid ratings only in the lower rating grades, which is consistent with the argument that investor-paid agencies have harsher attitudes toward potentially defaulting issuers to protect their reputation. We do not find evidence that issuer-paid CRAs provide overly favorable treatments to issuers with threshold ratings, implying that reputation concerns and the Dodd–Frank regulation mitigate the conflict of interests, while issuer-paid CRAs are more concerned about providing accurate ratings.

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