Abstract

Estimates of total cattle based on historical data and modelling

Author(s)

Kees Klein Goldewijk, Utrecht University

Production date

2013-4-9

Variable(s)

Total cattle

Keywords

Cattle, livestock

Time period

1500 -2000

Geographical coverage

Worldwide

Methodologies used for data collection and processing

Historical livestock statistics from Mitchell are first adjusted to match the FAO statistics in 1961 (FAO presents statistics from 1961-present time). Then, the most historical data found in Mitchell is converted in a simple per-capita number, and this number is kept constant further back in time. Apparently for Europe this will result in an underestimate (evidence from Broadberry et al suggest that in Medieval times the per capita livestock number was higher), but for other regions this is probably not the case (Americas and Australia/New Zealand didn’t have livestock at all until the early 16th century resp. late 18th century)

Period of collection

Data collectors

HYDE database


1960 – 2000 period: good Ca 1800-1960 period: fair for Europe and N. America, poor for the rest of the world Pre-1800 period: rather poor, a few countries excepted

General references

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Caribbean

Anguilla[No Data]

Antigua and Barbuda1500 (5)-2013 (21)

Aruba[No Data]

Bahamas1500 (5)-2013 (23)

Barbados1500 (5)-2016 (28)

Bonaire, Sint Eustatius and Saba[No Data]

British Virgin Islands[No Data]

Cayman Islands[No Data]

Cuba1500 (8)-2016 (35)

Curaçao[No Data]

Dominica1500 (5)-2016 (21)

Dominican Republic1500 (6)-2018 (38)

Grenada1500 (5)-2013 (21)

Guadeloupe[No Data]

Haiti1500 (6)-2018 (36)

Jamaica1500 (6)-2018 (35)

Martinique[No Data]

Montserrat[No Data]

In 2010, the Netherlands Organisation for Scientific Research (NWO) awarded a subsidy to the Clio Infra project, of which Jan Luiten van Zanden was the main applicant and which is hosted by the International Institute of Social History (IISH). Clio Infra has set up a number of interconnected databases containing worldwide data on social, economic, and institutional indicators for the past five centuries, with special attention to the past 200 years. These indicators allow research into long-term development of worldwide economic growth and inequality.

Global inequality is one of the key problems of the contemporary world. Some countries have (recently) become wealthy, other countries have remained poor. New theoretical developments in economics - such as new institutional economics, new economic geography, and new growth theory - and the rise of global economic and social history require such processes to be studied on a worldwide scale. Clio Infra provides datasets for the most important indicators. Economic and social historians from around the world have been working together in thematic collaboratories, in order to collect and share their knowledge concerning the relevant indicators of economic performance and its causes. The collected data have been standardized, harmonized, and stored for future use. New indicators to study inequality have been developed. The datasets are accessible through the Clio Infra portal which also offers possibilities for visualization of the data. Clio Infra offers the opportunity to greatly enhance our understanding of the origins, causes and character of the process of global inequality.