Inequality in Pre‐Income Survey Times: A Methodological Proposal

• Author: Guillermo Lezama,Henry Willebald
• DOI: http://doi.org/10.1111/roiw.12425
• Published date: 01 December 2020
• Date: 01 December 2020

© 2019 Internation al Association for Re search in Inco me and Wealth

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INEQUALITY IN PRE-INCOME SURVEY TIMES: A

METHODOLO GICAL PROPOSAL

by Guillermo lezama*

Facultad de C iencias Social es,Universidad de l a República, Uru guay

AND

Henry Willebald

Facultad de C iencias Econó micas y de Admini stración,Universi dad de la Repúbli ca, Uruguay

We propose different alternatives of inequality estimation for economies with a big agricultural sector

where land is a decisive factor in income generation and where we do not have enough information

about personal earnings. To this end, we use the Uruguayan case to test our methodology. We propose

six analytical exercises where Gini indexes are calculated, and as reference we choose the estimation that

better adjusts to some theoretical and empirical conditions. Finally, we check the historical accuracy of

the series by looking at income distribution explicative variables and the shape of the Inequality possi-

bility frontier. Our results are consistent with the economic and social events of the period (1870–1912)

and with previous estimates which reveal worsening trends in income distribution. However, our annual

data allow capturing the dynamics of the process where breaks in the series are observed and improve-

ments and declines alternate in the evolution of income distribution.

JEL Codes: N36, O15, D31

Keywords: first globalization, Gini, historical statistics, income inequality, Uruguay

1. introduction

Inequality constitutes one of the most frequently discussed topics in social

sciences (e.g. Lindert and Williamson, 1982; Persson and Tabellini, 1994; Barro,

2000) and, particularly in economic history and economic development, the debate

on the measurement and interpretation of the long run evolution has attracted

considerable attention (Deininger and Squire, 1996; Milanovic, 2007).

Part of this debate is fueled by the different measurement concepts where

inequality has been defined as—population-weighted—“inter-country inequality”

of per capita incomes or as a combination of between- and within-country inequal-

ity. In comparative terms, it is possible to identify three concepts about inequality

Note: We have received valuable comments from the session participants in the V Congreso

Latinoamericano de Historia Económica, Sao Paulo, Brazil, and we are especially grateful to sugges-

tions of Javier Rodríguez Weber and Pablo Astorga. We also thank to Luis Bértola for sharing his da-

tabase of personal incomes and number of agricultural workers in 1909–1912 with us and to Leonel

Muinelo-Gallo and Carolina Román for their attentive reading. Finally, we thank an anonymous

referee and the editor for their suggestions and corrections. All remaining errors are our own.

*Correspondence to: Guillermo Lezama, Departamento de Economía, Facultad de Ciencias

Sociales, Universidad de la República, Constituyente 1502, Montevideo, 11200, Uruguay (guillermo.

lezama@cienciassociales.edu.uy).

Review of Inc ome and Wealth

Series 66 , Number 4, Decemb er 2020

DOI : 10.1111 /roi w.124 25

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Review of Income and Wealth, Series 66, Number 4, December 2020

932

© 2019 Internation al Association for Re search in Inco me and Wealth

(Milanovic, 2012). The first concept is focused on inequality between nations of

the world. It is an inequality statistic calculated across per capita GDPs or mean

incomes obtained from household surveys of all countries in the world as a proxy

of “international inequality”. In a second concept, we can correct this measure

considering population of each country to obtain a measure of weighted inter-

national inequality. Finally, global inequality, which is the most important con-

cept for those interested in the world as composed of individuals (not nations); i.e.

each person, regardless of their country, enters in the calculation with their actual

income. The most recent article where the changing shape of global inequality in

the long run (1820-2000) is studied belongs to Van Zanden et al. (2014). In this

work—in the tradition of Bourguignon and Morrisson (2002)—the authors apply

the main statistical tools for estimating inequality in economic history depending

on data availability and periods with the objective of obtaining a consistent dataset

of global inequality. This involves the following approaches:

1. Direct estimates of Gini coefficients of income inequality for the post-

World War II (WWII) period, when household budget surveys are

periodically available, together with efforts to harmonize data basically

following the procedure developed by François and Rojas-Romagosa

(2005).

2. A large number of estimates of Gini coefficients of income distribution

before 1945 are available and the authors converted other measures of in-

come inequality—in particular the numerous estimates of the share of the

highest 1 or 5 percent in total income that are available—into comparable

Gini coefficients, making use of the assumption that income has a log-

normal distribution (Soltow, 1998).

3. In addition, it is possible to apply the idea developed by Williamson (2000a,

2000b, 2002) and followers, and tested by Prados de La Escosura (2008):

changes in income inequality in developing countries may be approached

by the ratio between real wages and real per capita GDP.

4. Finally, it is possible to assume a relationship between the distribution of

heights (a measure of the “biological standard of living”) (Steckel, 1995)

and income distribution (Baten, 2000, and followers). Such a link can be

demonstrated for a set of countries and be used to obtain new data.

Our contribution corresponds to the second and th ird analytical fields but

it differs in t wo ways from them. Van Zanden et al. (2014) test Willia mson's ideas

for a set of (large) countries , and use this exercis e to find the relationship b etween

unskilled wages and per capita GDP in order to extrapolate or intrapolate Gin i

coefficients for a sample of countr ies for which the authors do not have di rect

estimates. By contrast, we consider only one case and a different Wil liamson

Index: land rent /uns killed wage (r/w).

Considering only one index in this field is not new. Prados de la Escosura

(2005, 2007) propose Gini coefficients projected backwards with inequality indices

constructed as the ratio between unskilled wage indices and GDP per worker. He

obtains Gini coefficients for 10-year periods and four Latin American countries:

Argentina, Brazil, Chile and Uruguay, from the second half of the 19th century

onwards.