Inequality in Europe in the long run perspective (1300-1850): - PowerPoint PPT Presentation

Sixth CEPR Economic History Symposium Rome ( 22 - 24 June 2018) Inequality in Europe in the long run perspective (1300-1850): evidence from real wages  Giovanni Federico Department of Economics and Management, University of Pisa and CEPR  Alessandro Nuvolari Sant’Anna School of Advanced Studies, Pisa  Michelangelo Vasta Department of Economics and Statistics, University of Siena

Research question How did workers fare in relative terms in pre-industrial Europe?

Measuring inequality Standard measures of inequality: • Gini coefficients (Milanovic, Lindert and Williamson 2011) • Shares of top incomes (Atkinson et al 2011, Piketty and Saez 2014) • Wealth/GDP ratios (Piketty and Zucman 2014) • Factor shares - > distributional national accounts (Lindert-Williamson 2018, Piketty et al 2016 Bengtsson and Waldenstrom forthcoming)

Pre-industrial inequality • Conventional wisdom is that pre-industrial societies were highly unequal, within the constraints of low GDP per capita • Based on estimates of Gini coefficient inferred from – Social tables (Milanovic, Lindert and Williamson 2011, Allen forthcoming) – Tax records (Alfani and Ryckbosch 2016, Reis 2017)

Proxies for factor shares • Factor shares proxied by ratio of (indexes of) wage/GDP (Williamson 1997) or wage/rent (O’Rourke and Williamson 2005) • Ca 20% observations in data-base van Zanden et al (2014) • But comparable only in time, not across countries

Our contribution • Introducing a new framework for computing labour shares • comparable across countries and time • fully decomposable in the major drivers of inequality (wages, labour participation, working days, etc) • Estimating shares for unskilled labour (including women) and return to human capital from the Middle Ages to the Industrial Revolution for 5 major countries

Computing the labour share ( α ) 1/3 From identity W N *L= α *Y N With some manipulations (Angeles 2008), baseline definition α = w/y *L/N*(d/365) Where w daily real wages, y yearly GDP per capita, L number workers, N population, d number days worked

Computing the labour share ( α ), 2/3 Expanded version α = w M /y *[β+ γ - γ β]* μ/2*(δ M + δ F ) *(d/365) Where w M male real wage, β share males on workforce, γ ratio female/male wage, μ the share of working-age cohorts on total population, and δ is the activity rate

Computing the labour share ( α ), 3/3 If w M male wage of unskilled workers, share is return to pure labour Possible separate estimate of return to human capital as α HC = w M /y* μ/2*δ M * η * ξ * (d/365 ) Where η share of skilled workers and ξ skill premium, so that total labour share α TOT = α + α HC

The wages (w) • Real wages expressed in terms of Welfare Ratios (WR) –i.e. the number of bare-bone baskets which a male breadwinner can buy (Allen 2001) • Bare-bone basket must provide 1,940 calories (and other nutrients) at minimum cost • Household assumed to be two adults and two children= 3.15 baskets per day, including rent

Bare-bone baskets (kg.) England and Centre-North Item USA Holland France Wales Italy Oats 155 155 155 Maize 165 165 Rice Butter 3 3 3 3 3 Oil Meat 5 5 5 5 5 Beans 20 20 20 20 20

The wages, 2/2 To compute w/y, we convert the cost of a (bare-bones) basket in local prices (WR it ) into 2011 dollars (as Maddison GDP series) w it =DC $2011 *365*3* WR it Three alternatives for coefficient DC $2011 1. Market exchange rates (tradables) 2. ICP PPP (all goods) 3. Barebone PPPs (selected goods, with prices World Bank - ICP)

Converting welfare ratios: bare-bones PPPs The formula (Geary-Khamis dollars):

Daily costs of bare-bone baskets (2011 US$) 3,5 3 2,5 2 1,5 1 0,5 0 US exchange rate PPP barebone basket PPP OECD UK Netherlands France Italy Spain

Daily costs of PPP bare-bone baskets (2011 US$) 1,4 1,35 1,3 1,25 1,2 1,15 1,1 UK Netherlands France Italy Spain UK Netherlands France Italy Spain

Wages and GDP data Sample for five European countries in early modern period: GDP wages England and Wales Maddison (Broadberry Allen [London] (1301-1850) et al) Maddison (van Luewen Holland (1432-1807) Allen [Amsterdam] and van Zanden) France (1301-1850) Maddison (Ridolfi) Ridolfi [Paris] Centre-North Italy Maddison (Malanima) Allen [Milan/Florence] (1326-1850) Spain (1413-1787) Prados de la Escosura Allen [Valencia]

Four series of labour share • Baseline (labour) • Lower bound: women did not work • Upper bound: women paid as much as men • Total (including return to human capital)

0,4 0,6 0,8 0,2 1,4 1,2 0 1 1309 1319 1329 1339 Labour share 1301-1850 (baseline) 1349 1359 1369 1379 England and Wales 1389 1399 1409 1419 1429 1439 1449 1459 1469 1479 1489 1499 Holland 1509 1519 1529 1539 1549 1559 1569 France 1579 1589 1599 1609 1619 1629 1639 Centre-North Italy 1649 1659 1669 1679 1689 1699 1709 1719 1729 1739 1749 Spain 1759 1769 1779 1789 1799 1809 1819 1829 1839 1849 1859

0,4 0,6 0,8 0,2 Labour share 1301-1850 (baseline) 1,2 0 1 1300 1315 1330 1345 England and Wales 1360 1375 1390 1405 1420 1435 1450 1465 HP filtered 1480 Holland 1495 1510 1525 1540 1555 1570 France 1585 1600 1615 1630 1645 Centre-North Italy 1660 1675 1690 1705 1720 1735 1750 1765 1780 1795 Spain 1810 1825 1840

A new history of European inequality (1300-1850)? • 1300-1350: sizeable decline before the Black Death • 1350-1450: Black Death upswing • 1450-1550: Black Death backlash • 1550-1650: small divergence (a silent “golden age” for English and French workers?) • 1650-1750: small divergence continued (the Dutch poor join the club) • 1750-1850 the Age of Revolutions (generalized worsening, but post revolutionary France)

The proximate causes: levels (1413-1787) England Holland France Italy Spain Wages 0.19 0.30 0.06 -0.33 -0.22 GDP -0.14 0.46 -0.28 0.29 -0.32 Days -0.08 0.06 0.00 0.05 -0.03 Participation 0.04 0.20 0.01 0.01 -0.27 Gender wage gap -0.05 -0.01 -0.07 0.04 0.09

The proximate causes: change ( England) Working Gender wage W Y participation days gap 1305-1450 0.61 0.23 0.00 0.01 -0.04 1450-1550 -0.37 0.00 -0.02 0.30 -0.07 1550-1650 0.04 -0.02 0.07 0.18 0.01 1650-1750 0.31 0.53 0.09 0.01 0.02 1750-1850 0.02 0.48 -0.11 0.15 -0.09 Cell in bold indicates the main driver of change in the sub-period

The proximate causes: change ( Summary) England Holland France Italy Spain Initial year-1450 w w w w w 1450-1550 w w w w w 1550-1650 d y w w w 1650-1750 y w w w w 1750-Final year y w y w w

The differences • Wages and GDP determine both levels and trends of α , with one only exception - the increase in working days England 1550-1650 (an early Industrious Revolution?) • Caveat: the coefficients for participation, days (d) and gender wage gap ( γ) are sometimes assumed fixed for lack of data, and thus their contribution to changes might be underestimated

0,6 0,8 0,9 0,2 0,3 0,4 0,5 0,7 0,1 0 England and Wales 1/3, robustness checks 1 1301 1313 1325 1337 1349 1361 1373 1385 1397 1409 1421 1433 1445 1457 1469 1481 upper HP 1493 1505 1517 1529 1541 1553 baseline HP 1565 1577 1589 1601 1613 1625 1637 lower HP 1649 1661 1673 1685 1697 1709 1721 1733 1745 1757 1769 1781 1793 1805 1817 1829 1841

0,2 0,4 0,6 0,8 1,2 0 1 year 1311 1322 England and Wales 2/3, return to human capital 1333 1344 1355 1366 1377 1388 1399 1410 1421 1432 1443 1454 1465 baseline HP 1476 1487 1498 1509 1520 1531 1542 total HP 1553 1564 1575 1586 1597 1608 Return to human capital 1619 1630 1641 1652 1663 1674 1685 1696 1707 1718 1729 1740 1751 1762 1773 1784 1795 1806 1817 1828 1839

England and Wales 3/3, a comparison with Clark (2010) 0,4 0,6 0,8 0,9 0,5 0,7 1,1 1 1301 1314 1327 1340 1353 1366 1379 1392 1405 1418 1431 1444 1457 1470 1483 1496 1509 total HP 1522 1535 1548 1561 1574 1587 Clark (2010) 1600 1613 1626 1639 1652 1665 1678 1691 1704 1717 1730 1743 1756 1769 1782 1795 1808 1821 1834 1847

Conclusions, 1/2 • New method for computing shares of labour and human capital on GDP as a measure of inequality • Contrary to conventional wisdom of an uniformly inequal pre-industrial society, we find significant differences in time and across countries

Conclusions, 2/2 In particular – Inequality always higher in Mediterranean countries than Northern ones (and France) – Malthusian cycle around the Black Death (1300- 1550) – Further increase gap between Northern countries and Mediterranean ones (1550-1650) – Generalized rise of inequality (post 1750) but in France after the Revolution

Decomposition of yearly growth rates of the labour share (%): Holland Working Female W Y L/N days adjustement 1415-1450 1.16 0.41 0.00 0.00 0.00 1450-1550 -0.46 0.18 -0.01 0.00 0.00 1550-1650 0.05 0.35 0.13 0.18 -0.01 1650-1750 0.05 0.04 -0.03 0.00 0.00 1750-1802 -0.80 0.13 -0.02 0.00 -0.01 Cell in bold indicates the main driver of change in the sub-period