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Prepared by Emilia Jurzyk, Rui C. Mano, and Ananya Shukla.
See Box 2 in People’s Republic of China—Hong Kong SAR 2016 Article IV Staff Report on discussion of difficulties in comparing Gini coefficients across countries and data sources.
Levels of market and net Gini coefficients used in this paper for Hong Kong SAR differ, as some of the coefficients have been taken from the Hong Kong SAR Census and Statistics Department and from the Standardized World Income Inequality Database on per capita basis, while others are reported on a household level basis (also from the Hong Kong SAR Census and Statistics Department). The narrative, however, remains unchanged.
A thorough discussion of each of these variables and the literature on their connection to inequality can be found in JC et al.
We found significant differences between SWIID based inequality data and official sourced data for HKSAR. We decided to take the latter for this study, while maintaining the dataset in JC et al for all other countries which was based on SWIID data.
Underlying these assumptions is the idea that education, urbanization and sectoral compositions are close to their long-run steady-state levels while ageing is not.
This is done by estimating the historical relationship between the IMF team’s estimates of the house price gap (which is an average over 5 different approaches) and property tax revenues between FY95/96 and FY17/18. Such an analysis finds that the tax revenues in FY17/18 of 4.7 percent of GDP were almost 2 percentage points higher than the level consistent with a zero house price gap (or the full period average since full-sample estimates of house price gaps are around zero).
These include Belgium, Ireland, Luxembourg, Netherlands, Singapore, and Switzerland.
The assumed level of property tax revenue to GDP in 2050 (3.5 percent) is still lower than its current level (4.7 percent), but higher than the current average of financial centers or its “natural” level if the house price gap closes (2.3 and 2.8, respectively).
Refers to growth rate regression with fertility variable omitted (Table 4 in Barro, 1999).
Another older strand of the literature asserts that higher inequality may prompt voters to demand higher taxation and regulation, higher public expenditure programs and transfer payments, which in turn could lower investment and reduce economic efficiency (Bertola, 1993; Alesina and Rodrik, 1994; Persson and Tabellini, 1994; Benabou, 1996; Perotti, 1996) but empirical evidence is weakas recent studies have shown (Ostry, 2014, Cingano, 2014).