n?u=RePEc:auu:hpaper:052&r=his

repec.nep.his

n?u=RePEc:auu:hpaper:052&r=his

= 0.1*313 = 31.3 implying 280 actual days worked per year for more skilled workers

also on daily rates. Excel: Pre-1830s w & p.xlsx, 1830s w & p data.xlsx.

A4. Sources and methods for the inequality proxies.

Skill premiums: see above for working class wages and earnings data, while the white

collar earnings data are taken from NSW and TAS Blue Books. Excel: 1830s to 1870s

summary.xlsx

Labor scarcity and land abundance: see above for working class wages and earnings

data, while the land values are from Soos (2016) at

Philip_Soos_Australian_Land_Values_Datasets_v2.xlsx. Excel: Wages vs land values

1830s-1870s.xlsx

Changing gaps between middle and bottom: Real GDP from M. Butlin et al. (2015),

Table A1, pp. 555-8. Labor force 1841-1881 from M. Butlin et al. (2015), Table A2;

1828-1841 for NSW from Withers & Perry (1985), linked to Butlin et al. (2015) at

1841; see above for earnings, while CPI is built from the prices in Coghlan (1918,

vols. 1 and 2). Excel: 1830s to 1870s summary.xlsx

Regional Inequality: Based on real earnings, weighted by occupation employment

figures. See above for wages and prices for the 1830s, the 1850s are from Coghlan

(1918: vol. 2), and the 1870s from Coghlan (1918: vol. 3). The CPI uses the 1861

NSW budget weights in McLean and Woodward (1992, Table 2, p. 20). Coghlan's

1850s prices are linked to McLean and Woodward (1992) to cover the years 1850s-

1870s. The occupational employment data are from the colonial censuses. Excel:

1830s to 1870s summary.xlsx

A5. Employment by Occupation

The employment data by occupation are taken from the NSW census (1841, 1871),

the VIC census (1841, 1871) and the TAS census (1842, 1871). We distributed the

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