Global income inequality measures and bibliography of household surveys, 1880-1960

Gazeley, Ian and Newell, Andrew and Reynolds, Kevin (2018). Global income inequality measures and bibliography of household surveys, 1880-1960. [Data Collection]. Colchester, Essex: UK Data Archive. 10.5255/UKDA-SN-853185

This project will calculate new estimates of world inequality in the period from the end of the nineteenth century until the 1960s, based on the results of household expenditure surveys.
Our investigations have located a vast cache of household expenditure surveys for the period. Thus far, we have identified around 800 household surveys from around the world, carried out between the 1880s and 1960s, of which around half are of sufficient scope as to be potentially useful for the investigation of inequality. We will extract the reported demographic and expenditure data by income group from these reports and use them to estimate parameters of the income distribution.
Using these estimates, we will investigate the changing nature of inequality within a number of key nation states, and also investigate the time path and geography of global inequality 1880-1960. In addition, we would use these data to estimate other indicators of living conditions, such as nutritional attainment, which may provide further insights into the impact of industrialisation on inequality.

Data description (abstract)

Dataset consisting of inequality measures for 46 nation states and a global bibliography of all known household expenditure surveys covering the period roughly 1880-1960. Each entry notes when and where the survey was carried out and salient characteristics of the survey such as number of households, whether income and/or expenditure data are collected etc. These bibliographies are organised by six world regions and then by 118 nation states. For a sub-set of the most useful surveys we have estimated various inequality measures from the published data for 46 nation states, organised by world region.

Data creators:

Creator Name	Affiliation	ORCID (as URL)
Gazeley Ian	Sussex University	https://orcid.org/0000-0002-4277-1001
Newell Andrew	Sussex University
Reynolds Kevin	Brighton University

Sponsors:

Economic and Social Research Council

Grant reference:

ES/L002523/1

Topic classification:

History
Economics

Keywords:

household budgets, social inequality

Project title:

Global Income Inequality, c1880-1960

Grant holders:

Ian Gazeley, Andrew Newell

Project dates:

From	To
13 January 2014	12 January 2018

Date published:

03 Jul 2018 12:10

Last modified:

03 Jul 2018 12:10

Coverage and Methodology

Temporal coverage:

From	To
1 January 1900	1 January 1960

Collection period:

Date from:	Date to:
15 January 2014	14 January 2018

Country:

World Wide

Data collection method:

This project utilised the published reports of household expenditure surveys. These published reports are held at copyright libraries or national statistical offices and were typically part of the output of government departments (for example, the UK Board of Trade). We compiled our bibliographies through library searches and requests to various national statistical offices. Many of these reports are published in English, but a substantial number are only published in the language of the relevant nation state.

The published household expenditure survey reports typically include summary tables of grouped data of income, expenditures, and household structure. All of these reports, and the data therein, are already in the public domain, and our bibliography provides details of when and where they were published. From these data we estimated a suite of inequality measures, using three different techniques. The inequality measures are: Gini coefficient, 90/10 percentile ratio, 90/50 percentile ratio, and the 50/10 percentile ratio. These inequality measures were estimated three ways: linear interpolation, the Beta-Lorenz method and a log normal density estimation.

Not all published household expenditure survey reports contain sufficient data to estimate inequality measures. Our selection was based simply on whether the reports published the appropriate data. All that we required to estimate inequality were total household income or expenditure grouped by class (and the group average incomes/expenditures) and the total number of households and average household size.

Observation unit:

Household, Geographic unit

Kind of data:

Numeric, Text

Type of data:

Historical data

Resource language:

English

Access and Administration