TY  - THES
AU  - Hahn, Markus Hilmar
Y2  - 2021/09/14
Y1  - 2021
UR  - http://hdl.handle.net/11343/283384
AB  - Using tax data and combined tax-survey data, this thesis examines earnings inequality in Germany and income inequality in Australia. A particular focus is on combining tax record data and household survey data to obtain more accurate income data with the purpose of better understanding inequality in these two countries. 

Chapter 2, using tax data alone, creates historical series of top earnings shares. Using German wage tax statistics for 1926–2010, this chapter creates the first consistently measured long-term series of German top earnings shares. I find a U-shape pattern with top earnings shares falling from 1926 through the mid-1970s and almost continuously rising thereafter. I then compare my results to those from other studies examining top earnings shares in the US, UK, and France. Over the entire period it is reasonable to describe trends in the US, UK and Germany as U-shaped. All three decline from pre-WWII highs. The US shares begin to grow from the mid-1960s. The UK and German shares grow from the mid-1970s. In the mid-1990s, they begin to converge at a level substantially below the US. The French shares follow a different pattern that can be reasonably described as W-shaped.

Over the entire period (1957–2010) that it is possible to disaggregate the data by gender, women are underrepresented among top earners. Despite an increase in their labour force participation from 1957 to 1986, their share in the top 10% and top 1% of all workers remained unchanged. Only after German reunification in 1990 did women’s presence among top earners begin to increase.

Chapter 3, using a similar adjustment procedure as Burkhauser, Herault, et al. (2018) but applying it to earnings, combines data from tax records and from the German Socio-economic Panel (SOEP) to explore measures of annual earnings inequality that are broader than the top earnings shares of the previous chapter. I show that the unadjusted survey data, unlike the adjusted data, fail to replicate those shares. Using these enhanced data, I provide new evidence on German earnings inequality for the period 1992–2011. My results indicate higher levels of earnings inequality over this period than unadjusted survey data suggest. Inequality rose less quickly for measures that include all employees; it rose faster for measures of full-time, prime-aged employees.

Chapter 4 turns to Australia, demonstrating the importance of capturing high incomes well and consistently when calculating and examining inequality measures of equivalised household income. Using a similar adjustment approach as in Chapter 3, we examine the two major sources of household income data in Australia—the Survey of Income and Housing (SIH) and the Household, Income and Labour Dynamics in Australia (HILDA) Survey. We show that under-capture of top incomes by these surveys leads to underestimation of the extent of income inequality in Australia. The rise in income inequality in the 2000s exhibited by the unadjusted SIH data is considerably reduced when top incomes are adjusted to match tax record data; under-capture of top incomes by the SIH is greater in the early-2000s.
KW  - earnings inequality
KW  - wage inequality
KW  - income inequality
KW  - top earnings shares
KW  - top incomes
KW  - tax statistics
KW  - tax record data
KW  - household survey data
KW  - Germany
KW  - Australia
T1  - Earnings and Income Inequality in Germany and Australia: Evidence from Tax and Survey Data
L1  - /bitstream/handle/11343/283384/5518821c-1181-eb11-94d3-0050568d0279_Markus_H_Hahn_PhD_Thesis.pdf?sequence=1&isAllowed=y
ER  -