Microsoft Word 1060-frontespizio doc

Figures 

 

Figure 1. Profession and sector distribution in Florence 1427

 

Professions (a) 

 

Sectors (b) 

 

Authors’ elaborations on data drawn from 1427 Census of Florence. 

 

 

 

Figure 2. Italian city-states in the 15

th

 century 

 

 

 

 

artisan

44%

entrepreneur

18%

government 

servant

7%

lettered 

profession

9%

merchant

9%

unskilled

13%

agriculture

2%

manufacture: 

textile

37%

manufacture: 

other

12%

construction

5%

trade

13%

food and 

wine

8%

other 

services

7%

public 

services

16%

32 

 

---

 

Figure 3. Population and GDP per capita over the long run

 

Population (a) 

(thousands of inhabitants)

 

 

GDP per capita (b) 

(1427=1)

 

 

Figures for population refer to the city of Florence (authors’ elaborations on data drawn from 

http://www.paolomalanima.it/

 and Census data from 1861 on); figures for GDP per capita refer to Florence or the Italian 

Centre-North, depending on data availability, and are drawn from 

http://www.paolomalanima.it/

). 

 

 

 

Figure 4. Earnings mobility with randomly assigned surnames

 

 

Distribution of estimated earnings elasticity randomly matching ancestors’ and descendants’ earnings; 

dashed lines represent 95° and 99° percentile, red line represents the earnings  elasticity properly 

matching ancestors and descendants through surnames. 

 

 

0

100

200

300

400

500

1400

1500

1600

1700

1800

1900

2000

0

2

4

6

8

10

12

14

1400

1500

1600

1700

1800

1900

2000

0

10

20

30

-.1

-.05

0

.05

.1

earnings elasticity

33 

 

---

Figure 5. Wealth mobility with randomly assigned surnames

 

 

Distribution of estimated wealth elasticity randomly matching ancestors’ and descendants’ wealth; 

dashed lines represent 95° and 99° percentile, red line represents the wealth elasticity properly 

matching ancestors and descendants through surnames. 

 

 

 

Figure 6. Earnings and real wealth distribution by survival rate

 

Earnings (a) 

 

Real wealth (b) 

 

Authors’ elaborations on data drawn from 1427 Census of Florence. 

 

 

 

 

0

10

20

30

40

50

-.04

-.02

0

.02

.04

wealth elasticity

0

.5

1

1.

5

2

3

4

5

6

7

log of earnings in 1427

surviving families

missing families

0

.1

.2

.3

0

2

4

6

8

10

log of wealth in 1427

surviving families

missing families

34 

 

---

Figure 7. Income persistence in Florence: 1427 vs. 2005

 

 

Histograms represent the intergenerational income elasticity obtained as projections of the 

pseudo-ICS measure by Güell et al. (2015b); figures for Florence in the 1427 are based on authors’ 

elaborations on data drawn from 1427 Census of Florence; figures for Florence in the mid-2000s 

are drawn from Güell et al. (2015a). 

 

 

 

Figure 8. Earnings by professions: 1427 vs. 2000s

 

1427 

 

2000s 

 

 

Figures for 1427 are drawn from 1427 Census of Florence; figures for 2005 are drawn from sectoral studies (Studi di settore) by the 

Ministry of Economics and Finance for lawyers, doctors, pharmacists and goldsmiths and from Ciapanna et al. (2015) for bankers. 

Corresponding average values in the population are reported with diamonds. 

 

0,0

0,2

0,4

0,6

0,8

1,0

1427

2005

0

150

300

450

banker

lawyer

doctor or

pharmacist

goldsmith

0

60

120

180

banker

lawyer

doctor or

pharmacist

goldsmith

35 

 

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