Variable Definitions 1 Ethnographic Atlas

Marital systems can be illustrated in several forms. First, the Ethnographic Atlas defines marital systems under variable 9: Marital Composition: Monogamy and Polygamy. Based on this codification, we distinguished three different types of marital unions: monogamous (codes 1 and 2), polygynous (codes 3 to 6) and polyandrous (code 7). As stated in chapter 2, we concentrate on polygynous and monogamous unions, leaving aside polyandry.

Additionally, residential arrangements and sororate were fully described for polygynous unions. In this way, we classified marital systems into three main groups: (i) Monogamy, (ii)

Polygyny 1, where co-wives live under the same dwelling, and (iii) Polygyny 2, where co-wives live in separate dwellings. Table 2.3 introduced this classification in chapter 2. For the main purpose of this chapter, we assume that Monogamy 1, henceforth perfect monogamy, and

Monogamy 2, henceforth monogamy with occasional polygyny, are just one marital system,

Monogamy, and deal with occasional polygyny as the exception, not the rule.

To compute female contribution to subsistence activities from the Ethnographic Atlas, we use the following methodology. First, values on economic dependence by activity were

127 _{These values were revised and updated with the latest revision from the Human Development Report. We}

managed to add three countries to the original data set of 116 countries or territories. These were Brunei Darussalam, Liberia and Libya.

taken from variables 1-5. There are five main subsistence activities described for each society: gathering, hunting, fishing, animal husbandry and agriculture. These values range from 0 to 9. Table A.3.4 in appendix 3 shows the codification. Variables 50-54 describe gender specific differences or sex differences in participation for each activity. To obtain a measure of female contribution, we first assign arbitrarily percentages to the codified values of variables 50-54. Table A.3.5 in appendix 3 illustrates the procedure128_{. For example, code}

1 implies that “Males only, or almost alone” participate in a particular activity, i.e. hunting. Therefore, female participation in hunting activities will be 0 percent. Once we have converted codes into percentages, we computed a weighted average with the values of economic dependence by activity. We computed female participation rates for 379 societies. The variable will be denoted as Female Contribution, and is a percentage.

Furthermore, settlement patterns, Settlement, are described under variable 30: Settlement Patterns. Table A.3.6 in appendix 3 illustrates the codification. We have grouped categories using a new code. In this way, there are three categories, (i) nomadic (code 1), (ii) semi- sedentary (codes 2-4) and (iii) sedentary (codes 5-8). Finally, we have also taken values regarding the size of the community for each society, Size of community, given under variable 33: Mean size of local communities. These values range from 1 to 8. Table A.3.7 in appendix 3 provides the Ethnographic Atlas codification.

128 _{All societies present values for economic dependence by activity, variables 1-5. Societies who did not}

present values for gender differences in participation for all activities were removed. Moreover, code 7: “Irrelevance of gender, especially industrialized production” and code 8: “Activity present: Sex participation unspecified” were also removed. We found zero societies under code 7 and only 7 under code 8. Finally code 9: Absent or unimportant activity, are associated with zero dependence.

3.4.2.2 Censuses and National Surveys

To measure the incidence of polygyny, we use a binary variable, polygyny, based on the country estimates derived in table A.2.4 in appendix 2. This variable takes the value of 1 if the country was described as polygynous (Po) and 0 otherwise. Therefore non-polygynous countries include monogamous (Mo) and occasional polygynous (OP). To control for cultural continuity, we also include the dummy variable Old World (as opposed to New World) which takes the value of 1 for those countries or geographical regions where more than 50 percent of the population have an indigenous language as mother tongue, and 0 otherwise129_.

Female participation in the labour market is measured with the ratio of women economically active per 100 men (WEA)130_{. The projected economic activity rate for male}

and female for the year 1980 covered ages of 15 years and over. Activity rate is the proportion of the population who are economically active, expressed as a percentage. The estimates take into account information on the economically active population obtained mainly from national censuses and labour force sample surveys131_{. These data have been}

129 _{To construct the dummy variable Old World, we used data from Alesina et al (2003) and Lewis (2009).}

First, we classified languages by family. Then, we verified which languages and families were indigenous. We define a language or a family as indigenous if it was widely spoken in the continent where the country belongs. Finally, the percentage of the population speaking an indigenous or non-indigenous language was computed. See table A.2.4 in appendix 2.

130 _{WEA captures gender differences in participation. Conventionally, male participation rates have been}

relatively high and constant across countries. On the other hand, female participation rates have shown striking differences. In this study, we use gender differences to better capture the role played by women in the labour market. Figure A.3.2 in appendix 3 illustrates a scattered graph and a linear prediction of our main variable of interest WEA against the percentage of women economically active (economic activity rate) both for 1980. [R2 _{= 0.9511].}

131 _{The International Labour Office defines persons as economically active, if they are working for pay or}

adjusted by the International Labour Office so as to arrive at a consistent set of data. WEA

can be understood as the number of economically active women for every 100 economically active men.

Economic development is captured with the Human Development Indices (HDI). The Human Development Indices are based on three dimensions of human and economic development: (i) Longevity (Life expectancy), (ii) Knowledge (Literacy and Enrolment ratios) and (iii) Standards of Living (GDP per capita)132_{. The HDI were first derived in}

1975. Subsequent revisions for some or all of the components of the HDI, changes in methodology, or variations in the country coverage suggest that HDI are not directly comparable over time. Nonetheless, HDI remain to be widely used as cross-country indicator of the level of human development. We prefer HDI over GDP per capita, because the latter only reflects average national income. GDP per capita does not capture how income is distributed, and our theory requires a reliable measure of human and economic development. Moreover, other control variables included in the cross section are URBAN

or the rate of urban population (percentage), Sex ratio 15--44 (number of women per 100 men aged 15-44 years old) and Muslim80 or the percentage of Muslim population within a country.

broadened in 1982 to include, if appropriate, persons available for work but not necessarily actively seeking work

132 _{Data on life expectancy come from World Population Prospects 1950-2050: The 2006 Revision,}

Department of Economic and Social Affairs, Population Division, New York, United Nations; Data on adult literacy rates from UNESCO (United Nations Educational, Scientific and Cultural Organization) Institute for Statistics. 2003. Data on combined gross enrolment ratios from UNESCO (United Nations Educational, Scientific and Cultural Organization) Institute for Statistics. 1999. Statistical yearbook. Data on GDP per capita (2000 PPP US$) and GDP per capita (PPP US$) come from World Bank, World Development Indicators 2007.