Women and the Plough, Agriculture and Gender

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On the Origins of Gender Roles:Women and the Plough

Alberto Alesina Paola Giuliano Nathan Nunn

April 2011

Abstract: This paper seeks to better understand the historic origins ofcurrent differences in norms and beliefs about the appropriate role ofwomen in society. We test the hypothesis that traditional agriculturalpractices influenced the historic gender division of labor and the evo-

lution and persistence of gender norms. We find that, consistent withexisting hypotheses, the descendants of pre-industrial societies thatpracticed plough agriculture, today have lower rates of female partici-pation in the work place, in politics, and in entrepreneurial activities,as well as attitudes reflecting gender inequality. We identify the causalimpact of traditional plough use on gender norms today by exploitingvariation in the historic geo-climatic suitability of the environmentfor growing crops that differentially benefited from the adoption ofthe plough. Our IV estimates, based on this variation, support thefindings from OLS. To isolate the importance of cultural transmissionas a mechanism, we examine female labor force participation of secondgeneration immigrants living within the US.

We thank Samuel Bowles, David Clingingsmith, Pauline Grosjean, Judith Hellerstein, Edward Miguel, as well asseminar participants at the Bank of Italy, Brown University, Harvard University, Hong Kong University of Scienceand Technology, MIT, New York University, Sciences Po, UCLA Kaler Meeting, University of Oklahoma, WashingtonUniversity St. Louis, World Bank, Stanfords SITE Conference, Coevolution of Behaviors and Institutions Conference,AEA Annual Meetings, Brooking Africa Growth Forum, and the IZA/Science Po Workshop on Trust, Civic Spiritand Economic Performance for valuable comments. We also thank Eva Ng for excellent research assistance. Giulianogratefully acknowledges support from the UCLA Senate.

Harvard University, IGIER Bocconi, NBER and CEPR. (email: [email protected])University of California Los Angeles, NBER, CEPR and IZA. (email: [email protected])Harvard University, NBER and BREAD. (email: [email protected])

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1. Introduction

The role of women in the family, in the work force, and in society varies across nations. In some

cultures the social norm is for women to work outside the house, while in others the norm is for

women to remain within the home, not actively participating in activities outside of the domestic

sphere. This study seeks to better understand the reasons underlying these differences.

We test the hypothesis, originally put forth by Boserup (1970), that cross-cultural differences

in gender role norms and attitudes arose from differences in agricultural technologies used

traditionally. In particular, she identifies important differences between shifting cultivation and

plough cultivation. Shifting cultivation, which uses hand-held tools like the hoe and the digging

stick, is labor intensive and women actively participate in farm work. Plough cultivation, by

contrast, is much more capital intensive, using the plough to prepare the soil. Unlike the hoe

or digging stick, the plough requires significant upper body strength, grip strength, and burst of

power, which are needed to either pull the plough or control the animal that pulls it.1 Because

of these requirements, when plough agriculture is practiced, men have an advantage in farming

relative to women (Murdock and Provost, 1973a). Also reinforcing this gender-bias in ability is

the fact that when the plough is used, there is less need for weeding, a task typically undertaken

by women and children (Foster and Rosenzweig, 1996). In addition, child care, a task almost

universally performed by women, is most compatible with activities that can be stopped and

resumed easily and do not put children in danger. These are characteristics that hold for hoe

agriculture, but not for plough agriculture, especially if animals are used to pull the plough.

The result is that societies that traditionally practiced plough agriculture rather than shifting

cultivation developed a specialization of production along gender lines. Men tended to work

outside of the home in the fields, while women specialized in activities within the home .2 This

1See Pitt, Rosenzweig and Hassan (2010) for evidence from Bangladesh and the USA on the distribution of strengthby gender.

2Boserup (1970) in her analysis clearly describes the relationship between traditional plough use and gender norms,even hypothesizing that the use of the veil may be associated with traditional plough use. She writes that ploughcultivation shows a predominantly male labor force. The land is prepared for sowing by men using draught animals,and this. . . leaves little need for weeding the crop, which is usually the womens task. . . Because village women workless in agriculture, a considerable fraction of them are completely freed from farm work. Sometimes such womenperform purely domestic duties, living in seclusion within their own homes only appearing in the street wearing aveil, a phenomenon associated with plough culture and seemingly unknown in regions of shifting cultivation wherewomen do most of the agricultural toil. (pp. 1314)

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division of labor then generated norms about the appropriate role of women in society.3 Societies

characterized by plough agriculture, and the resulting gender division of labor, developed the

belief that the natural place for women is within the home. These cultural beliefs tend to persist

even even if the economy moves out of agriculture, affecting the participation of women on

activities performed outside of the home, such as market employment, entrepreneurship, or

participation in politics.

To test Boserups hypothesis, we combine pre-industrial ethnographic data, reporting whether

societies traditionally used plough agriculture with contemporary measures of individuals views

about gender roles, as well as measures of female participation in activities outside of the home.

Our analysis examines variation across countries, ethnic groups, and individuals. Consistent

with Boserups hypothesis, we find a strong and robust negative relationship between historic

plough-use and attitudes of gender equality today. Traditional plough-use is positivly correlated

with attitudes reflecting gender inequality and negatively correlated with female labor force

participation, female firm ownership, and female participation in politics.

Although these findings support Boserups hypothesis, they are also consistent with other

interpretations. For example, we would observe the same relationships if societies with attitudes

favoring gender inequality were more likely to adopt the plough historically and if these attitudes

continue to persist today. To better understand whether past plough use did have a causal impact

on subsequent cultural norms, we instrument historic plough-use using specific geo-climatic

conditions of a societys historic location which affected the relative benefits of adopting the

plough. As Pryor (1985) shows, the benefit of the plough depends on the crop being cultivated.

The plough is more beneficial for crops that require large tracts of land to be prepared in a

short period of time (e.g., due to multiple-cropping), and can only be grown in soils that are

not shallow, sloped, or rocky.4 These crops, which Pryor refers to as plough-positive, include

teff, wheat, barley, rye and wet rice. These can be contrasted to plough-negative crops, such as

maize, sorghum, millet and various types of root and tree crops, which require less land to be

prepared over a longer period of time, and/or can be cultivated on thin, sloped or rocky soils,

3Prior to Boserup anthropologists and ethnographers had recognized a relationship between traditional genderroles and the use of the hoe (Baumann, 1928). However, Boserup was the first to argue for the impact of hoe andplough use on the subsequent evolution of norms and values, and their importance for the development process.

4For a recent study documenting the link between soil type and plough-use in modern India see Carranza (2010).In particular, she shows that plough technology is more likely to be adopted with deep loamy soils rather than shallowclay soils.

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where using the plough is difficult. Unlike plough-positive crops, plough-negative crops benefit

much less from the adoption of the plough.

Using data from the FAO, we identify the geo-climatic suitability of finely defined locations for

growing plough-positive cereals (wheat, barley and rye) and plough-negative cereals (sorghum

and millet). We then use the relative differences in ethnic groups geo-climatic conditions for

growing plough-positive and plough-negative cereals as instruments for historic plough use. We

find that the IV estimates provide results consistent with the OLS estimates. Traditional plough

use is associated with attitude of gender inequality, as well as less female labor force participation,

female firm-ownership, and female participation in politics.

Our analysis then considers potential underlying mechanisms. It is possible that the long-term

effect of the plough reflects persistent cultural beliefs. However, it is also possible that part of the

long-term impact arises because historic plough-use promoted the development of institutions,

policies and markets that are less conducive to the participation of women in activities outside

of the home.5 To distinguish these two channels we exploit the fact that cultural norms and

beliefs unlike institutions, policies and markets are internal to the individual. Therefore,

when individuals move, their beliefs and values move with them, but their external environment

remains behind. Exploiting this fact, we examine variation in cultural heritage among second

generation immigrants living in the US. All individuals born and raised in the US have been

exposed to the same institutions and markets. In effect, the analysis holds all external factors

constant, while examining variation in individuals internal beliefs and values. We find that

women from cultures that historically used the plough have lower rates of labor force participation

in the US. This provides evidence that part of the importance of the plough arises through its

impact on internal beliefs and values.

The relationship between traditional plough use and gender roles has been well-studied in the

fields of history, anthropology and sociology. Since Boserups initial hypothesis, various scholars

have, through qualitative analysis, examined the relationship between the plough and attitudes

toward gender roles (Goody, 1976, Whyte, 1978 and Braudel, 1998). A particularly interesting

case is Braudels (1998) description of how gender relations, culture, and society were impacted

by the adoption of the plough in Mesopotamia between 4,000 and 6,000 BC. He writes: Until

5See the recent studies by Alesina, Algan, Cahuc and Giuliano (2010), Guiso, Sapienza and Zingales (2008b) andTabellini (2008) that investigate feedback effects between culture and institutions.

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now, women had been in charge of the fields and gardens where cereals were grown: everything

had depended on their tilling the soil and tending the crop. Men had been first hunters, then

herdsmen. But now men took over the plough, which they alone were allowed to use. At a

stroke, it might seem that the society would move from being matriarchal to patriarchal: that

there would be a shift away from the reign of the all-powerful mother goddesses. . . and towards

the male gods and priests who were predominant in Sumer and Babylon. . . and was accompanied

with a move towards male domination of society and its beliefs (p. 71).

Our focus on a historical determinant of gender roles is not meant to imply that other factors,

particularly factors that can change significantly over time, are unimportant. A number of

existing studies have examined other important determinants, including economic development,

medical progress, and the production structure of the economy (e.g., Iversen and Rosenbluth,

2010, Goldin, 2006, Ross, 2008, and Albanesi and Olivetti, 2007, 2009).6 As we show in section

4, even accounting for these important factors, there remains a strong persistent impact of the

plough on gender norms today.

A logical implication of our finding of a deep historical determinant of gender norms is that

there must be some persistence in gender norms and female activity outside of the home over

time. We provide evidence for this in section 4 where we show a very strong positive relationship

between pre-industrial female participation in agriculture and female labor force participation

today.

Our findings add to a recent line of research that has emphasized the importance of cultural

norms and beliefs as important factors underlying the persistent differences in gender roles across

societies (Alesina and Giuliano, 2010, Fernandez, 2007, Fernandez and Fogli, 2009, and Fortin,

2005, 2009). Although the link between gender norms and female labor force participation is well-

established, little is known about the origin of these cultural differences. Our findings suggest

that an important determinant of these differences is the nature of traditional farming practices.

Our findings also provide an example of how historic factors shape the evolution and persistent

of norms and beliefs. Thus, they contribute a number of recent studies that also seek to explain the

historic determinants of various cultural characteristics today. For instance, Guiso, Sapienza and

6One of the more novel hypotheses is provided by Ross who argues that countries that specialize in oil productioncrowd out the production of low-end export-oriented manufacturing activities, like textiles and footwear, which areparticularly well-suited for female employment. Therefore, specialization in oil results in less female labor forceparticipation and attitudes of gender inequality. We test explicitly for Ross hypothesis in our analysis.

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Zingales (2008a) test Robert Putnams hypothesis of the historic origins of regional differences of

social capital and trust within Italy.7 Nunn and Wantchekon (2011) examine the historic roots of

mistrust within sub-Saharan Africa. Grosjean (2010b) examines the historical origins of a culture

of honor in the US South, and Grosjean (2010a) and Becker, Boeckh, Hainz and Woessman (2010)

examine the lasting impact that historic empires had on cultural outcomes.

We begin our analysis by first documenting that in societies that traditionally used plough

agriculture women did in fact participate less in farm-work and other activities outside of the

domestic sphere. In section 3, we then explain the procedure used to link the historical use

of the plough, which is measured at the ethnicity level, to current data on gender norms or

female labor force participation, measured either at the country or individual level. Section 4

and 5 report OLS and IV estimates of the relationship between traditional plough use and gender

outcomes today, examining variation across individuals and countries. In section 6, we then

turn to mechanisms, using second generation US immigrants to test for persistent impacts of the

plough arising through cultural transmission. Section 7 offers concluding thoughts.

2. The historic impacts of traditional plough use

We begin our analysis by first confirming that societies that traditionally used plough agriculture

had lower female participation in agricultural activities. We also check whether plough use was

associated with differences in other activities within and outside of the domestic sphere.

Our analysis relies on information on traditional plough use taken from the Ethnographic

Atlas, a world wide ethnicity-level database constructed by George Peter Murdock that contains

ethnographic information for 1,267 ethnic groups around the world. Information for societies

in the sample have been coded for the earliest period for which satisfactory ethnographic data

are available or can be reconstructed. The earliest observation dates are for groups in the Old

World where early written evidence is available. For the parts of the world without a written

history the information is from the earliest observers of these cultures. For some cultures the first

recorded information is from the early 20th century. However, even for these observations, the

data should capture, to the maximum extent possible, the characteristics of the ethnic group prior

to European contact. For all groups in the dataset, the variables are taken from the societies prior

to industrialization.

7See also Guiso, Sapienza and Zingales (2004) on social capital and financial development.

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The database contains a measure of the historic use of plough agriculture. Groups are classified

into one of three mutually exclusive categories: (i) the plough was absent, (ii) the plough existed

at the time the group was observed but it was not aboriginal, and (iii) the plough was aboriginal

and found in the society prior to contact. There are data on plough use for 1,158 of the 1,267

societies in the database. There is hardly any evidence of groups repeatedly switching from one

form of agriculture to another. In other words, the use (or non-use) of the plough remains stable

over time.

The database does record adoption if it occurred after European contact. However, we do not

have the exact date of adoption for the other cases of adoption. It is possible that the plough has

a bigger effect on gender norms amongst groups that adopted early, and therefore have used the

technology for a longer period of time. However, because of data limitation, we are unable to test

for this. Therefore our estimates should be interpreted as the average effect of having adopted the

plough among all ethnic groups that did so prior to industrialization. There may be heterogeneity

within the group of adopters, but we are only able to estimate an average effect.

The number of societies that did not use the plough is greater than the number that did.

Descriptive statistics for all the data used in the paper are reported in Appendix Table A1. In the

sample, 86% of the ethnicities did not use the plough, 12.18% of the societies used the plough,

and in 1.5% of the societies the plough was not initially used, but it was adopted after European

contact. However, this actually provides an inaccurate description of the extent of plough use

historically. First of all, the database under-samples European ethnic groups. Second, ethnic

groups that adopted the plough were larger historically, and are larger today. For example, many

of the ethnic groups that did not adopt the plough are indigenous groups located in the Americas,

with small populations historically and even smaller populations today. More generally, the ethnic

groups are not of equal size or importance today as compared to the historical period to which

the Ethnographic Atlas refers to. For our analysis (as we describe below) we first link the historical

data to information about the current population distributions of ethnic groups, as a second step

we link the information about the population weighted distribution on the use of the plough to

contemporary datasets on female labor force participation and gender role attitudes. Our analysis

is therefore not biased by the fact that the Ethnographic Atlas over-samples small groups or groups

that are less populous today. In addition, in past centuries there have been significant migrations

of groups, particularly Europeans and Africans across the Atlantic. Our analysis also takes this

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into account, since we match the ethnographic data to current outcome data based on ethnic

groups and not geographic locations and we are therefore able to follow ethnic groups that have

moved.

We construct a plough indicator variable that takes on the value of one if the plough was

present (whether aboriginal or not) among the ethnic groups and zero otherwise. Nineteen

percent of societies in the sample used the plough. Female labor force participation is a categorical

variable which is increasing in the degree of participation of women in agriculture. In particular,

the variable indicates whether agriculture is a male or female dominated activity and can take the

following values: (1) males only, (2) males appreciably more, (3) equal participation, (4) female

appreciably more, and (5) females only.8 Thirty two percent of ethnic groups historically had

either mostly men or only men working in agriculture, 32 percent had equal participation and 36

percent had either mostly female or only female participation.9

We estimate an OLS regression of female participation in agriculture on the presence of the

plough. In all specifications, we control for the presence of domesticated bovine or equine

animals since low participation of women in agriculture could be due to the female monopoly

over the care of domesticated animals. This variable equals one if the ethnic group has bovine

or equine animals as predominant type of animal husbandry. We also include measures of

economic and political complexity of the ethnic groups. Economic complexity is measured by

a variable (increasing in the level of economic complexity) indicating the settlement pattern of

the ethnic group. This variable can take the following values: (1) nomadic or fully migratory, (2)

semi-nomadic, (3) semi-sedentary, (4) compact but not permanent settlements, neighborhoods of

dispersed family homesteads, (5) separate hamlets, (6) forming a single community, (7) compact

and relatively permanent settlements and (8) complex settlements. We proxy for political com-

plexity with a variable that measures the number of levels of jurisdictional hierarchy beyond the

local community. The two variables have been shown to be correlated with economic development

and societal complexity (Murdock and Provost, 1973b).

OLS results are reported in Table 1. Column 1 shows a negative relationship between historic

plough use and historic participation of women in agriculture. A one standard deviation increase

8The original categorization from the Ethnographic Atlas distinguished between differentiated but equal participa-tion and equal participation. Since this distinction is not relevant for our purposes, we combine the two categoriesinto one.

9Information on female participation in agriculture is missing for 547 observations in the sample. For 232 ethnicgroups agriculture was not practiced and for 315 groups the data are missing.

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in the use of the plough, implies a reduction in female participation in agriculture of0.30 (10% of

the sample average of the left hand side variable). The Ethnographic Atlas unfortunately does not

provide any detail on the type of tasks women do when they work in agriculture. We therefore

complement our analysis by using Murdock and Whites (1969) Standard Cross-Cultural Sample

(SCCS), a dataset containing ethnographic information on 186 societies, intentionally chosen to

be representative and historically and culturally independent from one another. The authors

group the 1267 societies from the Ethnographic Atlas into 186 clusters of closely related cultures.

They then chose, for each, a particularly well-documented and representative culture to be an

observation in the SCCS.

Using the SCCS data, we first replicate the regressions using the Ethnographic Atlas. As shown

in column 2, we find similar results.10 In columns 314, we then look specifically at gender

role specialization in the following specific tasks: land clearance, soil preparation, planting, crop

tending, harvesting, care of small and large animals, milking, cooking, fuel gathering, water

fetching and burden carrying. Each specialization variable is coded on a 1 to 5 integer scale,

increasing in the participation of women: (1) male exclusively, (2) males predominantly, (3) equal

division, (4) females predominantly, and (5) females exclusively.

We find that if the plough was used, women tended to participate significantly less in the

primary agricultural activities, including land clearance soil preparation, planting, crop tending

and harvesting (although for land clearance the coefficient is smaller in magnitude and statis-

tically insignificant). This is consistent with Boserups assertion that traditional plough use

was associated with less female participation in agriculture outside of the home. We also find

evidence that women in plough societies tended to participate less in other activities performed

outside the house, including fuel gathering, water fetching, and burden carrying (although the

coefficient for water fetching is smaller and not statistically different from zero). We dont find

statistically significant evidence that women in plough societies increased their participation

in other activities, including caring for large or small animals, milking or cooking. For these

activities the estimated coefficients are positive but always statistically insignificant.

Overall, the ethnographic evidence confirms that women participated less in farm activities

in societies that historically practiced plough agriculture. This is consistent with the analysis of

10The magnitude of the coefficient is slightly higher. An increase in one standard deviation in the use of the ploughimplies a decline in female labor force participation of 0.41, which is roughly equal to 14% of the sample average ofthis variable in the SCCS.

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Table 1: Historic plough use and historic female participation in agriculture.

Landclearance

Soil

prepara.on Plan.ng Croptending Harves.ng

(1) (2) (3) (4) (5) (6) (7)

Historicploughuse -0780*** -1095*** -0280 -1055*** -1150*** -0895** -0704**

(0108) (0250) (0204) (0353) (0342) (0367) (0307)

Observa.ons 698 132 137 132 139 129 139

R-squared 0098 0171 0040 0092 0097 0148 0156

Caringfor

smallanimals

Caringforlarge

animals Mi lking Cooking Fuel gathering Waterfetching

Burden

carrying

(8) (9) (10) (11) (12) (13) (14)

Historicploughuse 0349 0220 0738 0085 -0940** -0219 -1160***

(0560) (0276) (0711) (0149) (0410) (0240) (0374)

Observa.ons 95 96 48 182 166 159 144

R-squared 0034 0049 0030 0019 0041 0046 0151

Notes: The un unit of observa.on is ethnicity Coefficients are reported with robust standard errors in brackets ***, ** and * indicate significance

at the 1, 5 and 10% levels Column 1 reports evidence from the Ethnographic Atlas; Columns 2-14 report evidence from the Standard Cross

Cultural Sample Par.cipa.on in agriculture is a variable taking on integer values between 1 and 5 that quan.fies sex differences in agricultureand

is increasing in female par.cipa.on in agriculture Columns 3-14 are variables taking on interger values between 1 and 5 and are increasing in

femalepar.cipa.onoftheac.vity

PanelADependentvariables:Femalepar.cipa.oninthefollowing(agriculture-related)tasks:

PanelBDependentvariables:Femalepar.cipa.oninthefollowing(addi.onal)tasks:

Par.cipa.oninagriculture

Boserup (1970), as well as the observations of anthropologists like Baumann (1928) and Whyte

(1978).

3. Linking the past to the present: Data and methodology

We now turn to an examination of the long-term impact of historical plough use. We link

the historic ethnographic data, measured at the ethnicity level, with our outcomes of interest,

measured at the location-level, either countries or districts within countries today. To do this,

we need an estimate of the location and distribution of ethnicities across the globe today. We

construct this information using two datasets: the 15th edition of the Ethnologue: Languages of the

World (Gordon, 2005) and the Landscan 2000 database. The former reports the current geographic

distribution of7,612 different languages, each of which we manually matched to the appropriate

ethnic group from the Ethnographic Atlas. The database provides a shape file that divides the

worlds land into polygons, with each polygon indicating the location of a specific language.

We also use the Landscan 2000 database, which reports estimates of the worlds population for

30 arc-second by 30 arc-second (roughly 1km by 1km) grid-cells globally.11 We combine the

11The Landscan 2000 database was produced by Oakridge Laboratories in cooperation with the US Government andNASA.

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Ethnologue shape file with the Landscan raster file to obtain an estimate of the global distribution

of language groups across the globe today. This information is then used to link the historic

ethnicity-level data to our current outcomes of interest, measured at the location-level.

We illustrate our procedure with the example of Ethiopia. Figure 1a shows a map of the land

inhabited by different ethnic groups, i.e. groups speaking different languages. Each polygon

represents the approximate borders of a group (from Ethnologue). One should not think of the

borders as precisely defined boundaries, but rather as rough measures indicating the approxi-

mate locations of different language groups. The map also shows the Landscan estimate of the

population of each cell within the country. A darker shade indicates greater population.

From the Ethnographic Atlas we know whether each ethnic group used the plough. Define

Iploughe to be a variable equal to one if ethnic group e used plough agriculture and zero otherwise.

We first match to each of the 7,612 language groups globally, one of the 1,267 ethnic groups for

which we have plough-use data. After the matching procedure, we know for each language group

whether their ancestors engaged in plough agriculture. This information is shown in figure 1b.

We then use information on the location of modern district and country boundaries to con-

struct district-level and country-level averages of the historic plough measure. The procedure

is shown visually for the district-level averages in figures 2a and 2b. Intuitively, the procedure

creates a population-weighted average plough measure for all grid-cells within a district. This

provides an estimate of the fraction of the population currently living in a district (or country)

with ancestors that traditionally engaged in plough agriculture.

To be more precise, let Ne,i,d,c denote the number of individuals of ethnicity e living in grid-cell

i located in district d in country c. We then construct a population-weighted average ofIploughe for

all ethnic groups living in a district d. The district-level measure of the fraction of the population

with ancestors that traditionally used the plough, Ploughd,c, is given by:

Ploughd,c = e

i

Ne,i,d,c

Nd,c Iploughe (1)

where Nd,c is the total number of people living in district d in country c. The same procedure is

used to construct a country-level measure Ploughc as well, except that an average is taken over

all grid-cells in country c.

Figure 3a shows the global distribution of languages based on the Ethnologue data, as well

as historic plough use for each group. The figure also shows inhabited land in dark grey. One

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4

Legend

Ethnologue languages

(a) Population density and language groups

4

Legend


Plough not used

Plough used

(b) Population density, language groups and their traditional plough use

Figure 1: Populations, language groups, and historic plough-use within Ethiopia.

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4

Legend

District boundaries

District boundaries


Plough not used

Plough used

(a) Population density, language groups their traditional plough use, and districts today

4

Legend

Historic plough use

0.00-0.01

0.01-0.39

0.39-0.76

0.76-0.94

0.94-1.00

(b) District averages of plough use among inhabitants ancestors

Figure 2: Traditional plough-use across districts within Ethiopia

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problem with the Ethnologue data is that the information is missing for some parts of the world.

This is due to uncertainty or a lack of information about the boundaries of language groups in that

location. As it is apparent from the map, this primarily occurs in South America. We undertake

three strategies in order to address this issue. The first is to ignore the missing languages and

calculate country and district measures using the data that exist (i.e., shown in Figure 3a.) This is

the strategy that has been undertaken by other studies using the Ethnologue language data (e.g.,

Michalopoulos (2008)). Our second strategy is to assume that all inhabitants in the unclassified

territories speak the national language of the country. The spatial distribution of historic plough

use using this imputation procedures is reported in figure 3b. Our third strategy is to impute the

language of the inhabitants using information on the spatial distribution of ethnic groups from

the Geo-Referencing of Ethnic Groups (GREG) database (Weidmann, Rod and Cederman, 2010).

Like the Ethnologue, the GREG database provides a shape file that divides the worlds land into

polygons, with each polygon indicating the location of a specific ethnicity. The shortcoming of

the GREG database is that ethnic groups are much less finely identified relative to the Ethnologue

database. The GREG database identifies 1,364 ethnic groups, while the Ethnologue identifies 7,612

ethnic groups.12 The spatial distribution of historic plough use using this procedures is shown in

figure 3c.

In figures 4a4c, we report population weighted country-level averages of historic plough use

for each of the three strategies used to address the missing language data. Some general patterns

appear no matter which methodology we choose. Groups within sub-Saharan Africa generally

did not use the plough. The majority of the European countries used the plough historically,

together with some African countries like Eritrea, Ethiopia and the countries of Northern and

Southern Africa, as well as a number of Asian countries.

In our analysis we use the plough variable without missing values imputed as our baseline

measure. We also show that our results are robust to the use of either variable that imputes the

missing language data. This robustness is explained by the high correlation among the three

plough measures. At the country-level, the correlation between: (i) our baseline variable and the

measure with missing languages imputed using the countrys national language is 0.89; (ii) our

baseline measure and the measure imputed using ethnic groups from the GREG database is 0.91;

12An alternative strategy is to rely only on the coarser GREG classification and map. Our results are robust to thisprocedure as well.

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Legend

Historic plough use

Missing plough data

No plough use

Plough use, not indigenous

Indigenous plough use

Missing language data

Unpopulated land

Populated but no Ethnologue data

(a) Missing language information not imputed

Legend

Historic plough use

Missing plough data

No plough use

Plough use, but not indigenous



Unpopulated

Populated but no language data

(b) Missing language information imputed using the countrys official language

Legend

Historic plough use

Missing plough data

No plough use

Plough use, but not indigenous



Unpopulated

Populated but no language data

(c) Missing language information imputed using GREG ethnic groups

Figure 3: Historic plough use among the ethnic/language groups in the Ethnologue

14


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Legend

Historic plough use

0.000000 - 0.024938

0.024939 - 0.133554

0.133555 - 0.233165

0.233166 - 0.323672

0.323673 - 0.569498

0.569499 - 0.821691

0.821692 - 0.889259

0.889260 - 0.943730

0.943731 - 0.985092

0.985093 - 1.000000

(a) Missing language information not imputed

Legend

Historic plough use

0.000000 - 0.061609

0.061610 - 0.251907

0.251908 - 0.403964

0.403965 - 0.573113

0.573114 - 0.676111

0.676112 - 0.783906

0.783907 - 0.874715

0.874716 - 0.928645

0.928646 - 0.981442

0.981443 - 1.000000

(b) Missing language information imputed using the countrys official language

Legend

Historic plough use

0.000000 - 0.043163

0.043164 - 0.133554

0.133555 - 0.323672

0.323673 - 0.629320

0.629321 - 0.803035

0.803036 - 0.870872

0.870873 - 0.908499

0.908500 - 0.953173

0.953174 - 0.985101

0.985102 - 1.000000

(c) Missing language information imputed using GREG ethnic groups

Figure 4: Average historic plough use among the ancestors of each country15


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and (iii) the two variables with imputed values is 0.99.13

4. OLS estimates

Having constructed country and district-level measures of traditional plough use, we are now

able to examine the relationship between historic plough use and measures of the role of women

in society today. We begin by examining variation at the country level.

A. Country-level estimates

We test our hypothesis by estimating the following equation:

yc = + Ploughc + XCc + X

Hc + c (2)

where y is the outcome of interest, c denotes countries, Ploughc is our measure of the historic

use of the plough among the ancestors of the citizens in country c, and XCc and XHc are vectors of

current controls and historic ethnographic controls, all measured at the country level. XCc includes

the natural log of a countrys real per capita GDP measured in 2000, as well as the variable

squared. This is important since economic development is known to be non-linearly associated

with female labor force participation (Goldin, 1995). We also include an indicator variable that

equals one if the country was formerly communist, since these regimes implemented policies to

eliminate gender differences in the economy.14 The historic ethnographic controls XHc include

agricultural suitability, the presence of domesticated bovine or equine animals, the presence of a

tropical climate (either tropical or subtropical), the levels of jurisdictional hierarchy beyond the

local community, and the economic development of the ethnic groups currently living within the

country (defined above). We construct these variables using the same manner used to construct

the historic plough use variable. The measures capture the historic characteristics of the ancestors

of those in our sample. A more detailed description of each control variable is provided in the

papers appendix.

Table 2 reports the country-level OLS estimates. In columns 1 and 2, the dependent variable

is a countrys female labor force participation rate in 2000. In columns 36, we examine womens

13Descriptive statistics for the three measures are shown in Appendix Table A1.14Alesina and Fuchs-Schundeln (2007) show how the impact of communist regimes on individual beliefs can be long

lasting.

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participation in more narrowly specified activities outside of the domestic sphere: entrepreneur-

ship (measured by the share of firms with owners or managers that are female) and national

politics (measured by the proportion of seats held by women in national parliament)15. The even

numbered columns include controls for continent fixed effects, while the odd numbered columns

do not. The estimates show that in countries with a tradition of plough-use, women are less likely

to participate in the labor market, are less likely to own or manage firms, and are less likely to

participate in politics.16

The point estimates (using the odd numbered columns) suggest that an increase in one stan-

dard deviation in plough-use (0.474 for the full sample) is associated with a reduction of female

labor force participation of (15.506 0.474 =) 7.35 (equivalent to 14.2% of the sample average

for FLFP and 47% of the standard deviation); of 5.23 of the share of firms with some female

ownership (16% of the sample average and 38% of the standard deviation); and a reduction of the

participation of women in politics by 2.66 (22% of the sample average and 30% of the standard

deviation).

Columns 7 and 8 report the estimated average effect size (AES) for the three dependent

variables examined in columns 16. We computed the AES following Kling, Liebman, Katz and

Sanbonmatsu (2004). Let k indicate the estimated plough coefficient for outcome variable k and

k the standard deviation of outcome k, the average effect size is equal to 1K

Kk=1

k

k, where K

is the total number of outcome variables. To properly calculate the sample variance of the AES,

the coefficients k are jointly estimated in a seemingly unrelated regression framework.17 AES

estimates reduce the possibility of Type I (that results on any of our outcomes is due to chance)

and Type II error (the risk of low statistical power). The AES estimates confirm the findings

when examining the outcomes individually: historic plough use is associated with less female

participation in activities outside of the home. As well, the implied magnitudes are similar.

According to the AES estimate, a one standard deviation increase in plough use is associated

with an average decrease (for the three outcomes) of0.40 standard deviations.

An alternative way to assess the magnitude of the estimates is to calculate the proportion of

15Details about the sources of the left hand side variables are reported in the Appendix.16Because female participation in national politics may be affected by the type of government, we also control for

each countrys level of democracy in 2000 when this outcome is examined. The extent of democracy is measured usingthe polity2 measure from the Polity IV database, which is a variable that takes on integer values ranging from 10(high autocratic) to +10 (highly democratic).

17See Clingingsmith, Khwaja and Kremer (2009) for an alternative application and further details.

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Table 2: Country level OLS estimates.

(1) (2) (3) (4) (5) (6) (7) (8)

Historic plough use -16.506*** -15.417*** -11.052** -11.540** -5.606*** -4.245* -0.849*** -0.796***

(3.547) (3.561) (4.287) (5.152) (2.128) (2.218) (0.140) (0.137)

Historic controls:

Agricultural suitability yes yes yes yes yes yes yes yes

Domesticated animals yes yes yes yes yes yes yes yes

Tropics yes yes yes yes yes yes yes yes

Political hierarchies yes yes yes yes yes yes yes yes

Economic complexity yes yes yes yes yes yes yes yes

Contemporary controls:

ln income, ln income2 yes yes yes yes yes yes yes yes

Communism indicator yes yes yes yes yes yes yes yes

Polity2 no no no no yes yes no no

Continent fixed effects no yes no yes no yes no yes

Observations 159 159 105 105 125 125 135a

135a

R-squared 0.412 0.429 0.154 0.205 0.279 0.315

Dependent variable:

Average effect size (AES)

Notes : OLS estimates are reported with robust standard errors in brackets. The unit of observation is a country. ***, ** and * indicate significance at the 1, 5

and 10% levels.a

This is the average number of observations in the regressions for the three outcomes.

Female labor force

participation

Share of firms with some

female ownership Females in politics

the total variation they explain. By this metric as well, historic plough use explains a sizable

proportion of differences in gender roles across countries. When female labor force participation

is the dependent variable (column 1 of Table 2), the inclusion of the historic plough use variable

increases the R-squared by 0.086 (from 0.326 to 0.412). Therefore, traditional plough use accounts

for 8.6% of the total variation in FLFP and 12.8% of the residual variation in FLFP that is

unaccounted for by our control variables.18 For the share of firms with female ownership,

traditional plough use accounts for 5% of the total variation and 6% of the residual variation.

For the participation of women in politics, historic plough use explains 3% of the total variation

and 4% of the residual variation.

The estimated coefficients for our control variables are generally as expected. For example

we find evidence of a U-shaped relationship between per capita income and female labor force

participation, as well as the other outcomes. This is consistent with previous studies that also find

this same non-monotonic relationship (Goldin, 1995). We also find that countries that experience

a period of communism have higher rates of female labor force participation.

18This is calculated as: (0.412 0.326)/(1 0.326) = 0.128 or 12.8%.

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Robustness to alternative plough measures

Estimates using either of the two methods for imputing missing language data are qualitatively

identical to the estimates using our baseline variable. Estimates of equation (2) using the two

alternative plough variables are reported in Appendix Table A2. We find the alternative measures

yield nearly identical point estimates that are highly significant. As a final strategy to ensure

that our findings are not being driven by measurement error, we omit 17 countries that have a

significant proportion of missing data.19 The estimates, reported in the appendix in Table A3,

show that the estimated impact of the plough remains robust to the smaller sample.

The persistence of female labor force participation

To this point, we have shown that historic plough use is associated with less female participation

in agriculture historically, and with less female labor force participation today. These two

correlations imply long-term persistence in female participation in activities outside of the home.

As a check for the persistence of cross-country differences in the participation of women in

the labor market, we regress female labor force participation today on the measure of womens

participation in agriculture constructed from the Ethnographic Atlas. The regression also controls

for our full set of covariates from equation (2) above. The partial correlation plot, showing the

relationship between historic female participation in agriculture and FLFP today, is shown in

figure 5. As is apparent from the figure, there is strong persistence over time. Female labor

market participation today and female participation in agriculture in historical societies are very

strongly correlated, even after controlling for our set of covariates.

In light of existing studies, this persistence is perhaps surprising. In fact, Goldin and Sokoloff

(1984) document that within the Northeastern United States, the low relative productivity of

women and children in agriculture (and hence their low participation) spurred industrialization

and their active participation in the manufacturing sector. In their setting, female labor force

participation in agriculture was inversely related to participation in manufacturing, suggesting a

lack of continuity of female labor market participation overtime as industrialization occurs. Our

results, however, show that this example does not appear to be general. Instead, areas with low

female participation in agriculture and plough use because of the persistence of norms and

19The countries include Australia, Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Ecuador, Guatemala,Honduras, Mexico, New Zealand, Nicaragua, Panama, Paraguay, Peru and Venezuela.

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practiced intensive agriculture.20 We also control for the proportion of a countrys population

with ancestors without inheritance rules for land, which we take as an indicator for the absence of

property rights in land.21 The last control variables are two measures that capture the proportion

of a countrys ancestors with patrilocal post-marital residence rules and with matrilocal rules.

These capture the extent to which societys were matrilineal versus patrilineal.22

Columns 13 of Table 3 report estimates of equation (2) with the additional controls included.

We report the estimates with female labor force participation as the dependent variable. 23 The

estimated impact of the traditional plough use remains robust to the inclusion of the additional

controls: the coefficient remains negative and statistically significant, and its magnitude changes

little from the baseline value of 16.5.

It has been hypothesized that the status of women may be affected by the extent to which

families are nuclear as opposed to including extended relatives. It has been argued that cultures

with large-extended families typically have more hierarchical and less egalitarian structures. Since

hierarchies tend to be dominated by men, this results in a subordinate status of women (Engels,

1902, Boserup, 1970, Barry, Bacon and Child, 1957).24 We control for the potential impact of

family structures by controlling for the proportion of a countrys ancestors that lived in nuclear

or extended families.25 Estimates with these additional controls are reported in column 4. The

estimate for historic plough use remains robust.

It is possible that the status of women is also affected by the extent to which a society

20The measure is constructed from variable v28 in the Ethnographic Atlas, which classifies societies based on theiragricultural intensity into one of the following categories: no agriculture, casual agriculture, extensive or shiftingagriculture, horticulture, intensive agriculture and intensive irrigated agriculture. Our control captures societiesbelonging to the last two categories.

21The original Ethnographic Atlas question (v75) measures the inheritance distribution for land and identifies thefollowing categories: equal or relatively equal, exclusively or predominantly to the one adjudged best qualified,ultimogeniture, primogeniture and absence of inheritance of real property. Our measure identifies ethnic groupsbelonging to the last categories.

22The measures are constructed from variable v12 of the Ethnographic Atlas, which groups societies into the followingcategories: avunculal, ambilocal, optionally uxorilocal or avunculocal, optionally patrilocal, matrilocal, neolocal, nocommon residence, patrilocal, uxorilocal or virilocal.

23

The estimates for the other outcomes of interest are also robust to the inclusion of the additional controls.24A similar but different theory stresses competence rather than authority. In large families with many adults, agender division of labor can more easily develop. In nuclear families with only a husband and a wife, it is more likelythat either adult will need to substitute for the other. Therefore, the wife will be involved in activities ordinarily doneby men.

25The information is taken from variable v8, which classifies ethnic groups family structures into the following cat-egories: (i) independent (monogamous) nuclear family, (ii) independent (polygynous) nuclear family, (iii) independentpolyandrous families, (iv) polygynous (with co-wives), (v) polygynous (without co-wives), (vi) minimal extendedfamilies, (vii) small extended families, (viii) large extended families. We construct a variable for the proportionof nuclear families (including indipendent monogamous and polygynous nuclear families) and a variable for theproportions of extended families (including minimal, small and large extended families).

21


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Table 3: Robustness of OLS estimates to alternative controls.

(1) (2) (3) (4) (5)

Historicploughuse -14.734*** -16.814*** -17.073*** -14.570*** -15.417***

(4.856) (3.769) (3.568) (3.568) (3.692)

Prac@cesintensiveagriculture yes

Absenceofprivateproperty yes

Patrilocalsociety,matrilocalsociety yes

Nuclearfamily,extendedfamily yes

Propor@onofsubsistencefrom:hun@ng,herding yes

Baselinehistoricandcontemporarycontrols yes yes yes yes yes

Observa@ons 159 156 159 159 159

R-squared 0.41 0.41 0.42 0.46 0.43

(6) (7) (8) (9) (10)

Historicploughuse -12.041*** -16.435*** -15.767*** -18.474*** -15.375***

(3.967) (3.536) (3.538) (4.112) (3.844)

Propofpopbelongingtofivemajorreligions yes

Oilproduc@onpercapita yes

Trade/GDP yes

Agric.,manuf.andservicesshareofGDP yes

Frac@onofEuropeandescent yesObserva@ons 157 157 159 157 151

R-squared 0.57 0.43 0.42 0.42 0.42

Dependentvariable:FLFP

Notes: OLS es@mates are reported with robust standard errors in brackets. The unit of observa@on is a country. ***, ** and * indicate

significanceatthe1,5and10%levels.

European ancestry.29

Overall, the estimated impact of the plough remains highly robust across the ten specifications

in Table 3. The coefficient is always negative and statistically significant, and the point estimate

remains reasonably stable, ranging from 0.12 to 0.18. Although we do not report the estimates

here, we also find that the other two outcomes variables the share of firms with female

ownership and the participation of women in politics also remain robust to the inclusion of all

these controls. As well, the results also remain robust if the controls are included with continent

fixed effects.

B. Individual-level estimates

We now turn to our specification that examines variation across individuals, linking them to a

tradition of plough agriculture using the district they live in. This analysis relies on data from the

World Value Survey (WVS), a compilation of national individual-level surveys on a wide variety

of topics, including attitudes and preferences, as well as information on standard demographic

29An alternative, more blunt strategy, is to omit all European and the neo-Europe countries (Australia, New Zealand,Canada, the US) from the sample. As reported in Appendix Table A4, the results are also robust to this strategy.

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characteristics, such as gender, age, education, labor market status, income, religion, etc.30 Using

the WVS we construct, for females, an indicator variable that equals one if she is in the labor

force, which includes full-time, part-time or self-employment. Women are not in the labor force

if they report being retired, a housewife or a student.31

We also examine two measures of individuals (male and female) attitudes about the appropri-

ate role of women in society. The first measure is based on each respondents view of the following

statement: When jobs are scarce, men should have more right to a job than women. The

respondents are then asked to choose between agree, disagree, neither or dont know. We omit

observations for which the respondents answered neither or dont know, and code disagree

as 0 and agree as 1.32 Therefore, the variable is increasing in the extent to which a respondents

view is characterized by gender inequality.

We also consider a second variable derived from a survey question where the respondents

are given the following statement On the whole, men make better political leaders than women

do. Respondents are then asked to choose between strongly disagree, disagree, agree, agree

strongly, or dont know. We omit observations in which the respondent answered dont know

and create a variable that takes on the value of 1 for strongly agree, 2 for disagree, 3 for agree

and 4 for agree strongly. This variable, like the first is increasing in the respondents view of

gender inequality.

We find the two subjective value measures particularly appealing because they could reflect

the values potentially underlying cross country differences in female outcomes. The first question

reflects values of female access to jobs, which may underlie part of the observed differences in

female labor force participation rates across countries. The second question reflects values about

the ability of women to take on roles of leadership and responsibility, which may determine ob-

served differences in female participation in politics and female firm ownership and management.

Therefore, there is a close link between the objective measures from the country-level analysis and

30The five waves of the WVS were carried out in the following years: 1981-1984, 1990-1993, 1995-1997, 1999-2004 and20052007. The coverage varies depending on the wave (starting with 22 countries in 1980, reaching 81 countries in thefourth wave and 57 in the fifth). In our analysis, we use the four most recent waves of the World Values Survey, since thefirst wave does not contain information on the district in which the respondent lives. Because regional classificationsoften vary by wave, we choose the wave with the most finely defined regions.

31The results are qualitatively identical if we exclude retired women and students from the sample.32We omit observations that respond neither because it is ambiguous whether this represents an intermediate view

or whether they have chosen not to answer the question or whether they do not know their answer. If we interpretthis response as reflecting an intermediate position and code a variable that takes on the values 0, 1, and 2, then weobtain qualitatively identical results to what we report here.

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Table 4: Individual-level OLS estimates.

Averageeffectsize

(AES)

(1) (2) (3) (4)

Historicploughuse -0.214*** 0.245*** 0.397*** 0.451***

(0.034) (0.029) (0.075) (0.063)

Individualcontrols yes yes yes yes

Currentcountrycontrols yes yes yes yes

Historicdistrictcontrols yes yes yes yes

ConnentFE yes yes yes yes

Observaons 38,832 71,656 59,288 65,472

R-squared 0.186 0.209 0.178

Notes: The table reports OLS esmates, with standard errors clustered at the country level. Individual controls are age, age

squared, educaon, gender (for gender aXtudes only), marital status, and income. Current country controls include ln

income, ln income squared and a communism indicator variable. Historic district controls include agricultural suitability,

domescated animals, tropical areas, polical hierarchies, and economic complexity. The AES reported in column 4 is for

thetwosubjecvebeliefmeasuresfromcolumns2and3.***,**and*indicatesignificanceatthe1,5and10%levels.

FLFP

Whenjobsare

scarse

Menbe`er

policalleaders

Dependentvariables:

the subjective measures in the individual-level analysis.

Examining these three outcomes female participation in the labor force, attitudes about

female employment, and attitudes about female leadership skills we estimate the following

individual-level equation:

yi,d,c = r(c) + Ploughd + XCc + XHd + Xi+ i,d,c (3)

where i denotes an individual, d denotes a district within a country c, and r(c) denote the

continent of country c. Ploughd is our measure of the historic use of the plough among the

ancestors of individuals living in district d. XCc are the same current country-level controls as in

equation (2), and XHd includes the same historic ethnographic variables as in equation (2), but

measured at the district level. Xi denotes current individual-level controls: age, age squared, as

well as fixed effects for marital status, educational attainment, and income levels. The equation

also includes continent fixed effects, denoted r(c). To be as conservative as possible, we cluster

the standard errors at the country level.

Tables 4 reports OLS estimates of equation (3). Consistent with the country-level estimates,

we find a negative relationship between historic plough use and female labor force participation

today, and a positive relationship between historic plough use and current attitudes reflecting

gender inequality. In terms of the magnitude of the effects, they are similar to the cross-country

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estimates. An one-standard-deviation increase in the plough variable implies a reduction in

female labor force participation of 0.09 (which is roughly equal to 16% of the sample average)

and an increase in the gender attitudes variables of 0.10 and 0.21 (which are 21% and 8% of the

sample averages, respectively).

5. IV estimates

The core concerns with the OLS correlations reported to this point are selection and omitted

variables bias. For example, locations that historically had attitudes prone to less equal gender

roles may have been more likely to invent or adopt the plough (in this case our OLS estimates

would be biased away from zero). On the other hand, locations that were economically more

developed were more likely to adopt the plough. Because today these areas are richer and more

prone to attitudes about gender role equality, this will tend to bias our OLS towards zero.

Our first strategy to address these concerns was to control for observable characteristics. This

was done in the previous section. Here we pursue an alternative strategy using instrumental vari-

ables. As instruments we rely on a determinant of historic plough use that has been emphasized

in the anthropological literature: specific characteristics of the geo-climatic environment which

determined the type of crops that could grow in a particular location (Pryor, 1985). Because

the use of the plough involves a trade-off between larger up-front fixed costs, but an ability to

cultivate large amounts of land over a short period of time, the benefit of the plough is greater

for crops that have short cultivation periods (even multiple cropping per year) and require large

amounts of land for a fixed yield of calories. Further the benefit of the plough is reduced when

the crops are grown in swampy, sloped, rocky, or shallow soils, all of which make the plough

much less efficient or impossible to use. Taking these factors into consideration, Pryor (1985) has

classified crops into those whose cultivation benefits greatly from the adoption of the plough

i.e., plough positive crops and those whose cultivation benefits less plough-negative crops.

Plough-positive crops, which tend to be cultivated on larger expanses of land (per calorie of

output), have shorter growing seasons, and grow on flat, deep, soil that is not too rocky or

swampy, include wheat, teff, barley and rye. On the other hand plough negative crops, which

tend to yield more calories per acre, have longer growing seasons, and can be cultivated on more

marginal land, include sorghum, maize, millet, roots and tubers, and tree crops (Pryor, 1985, p.

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732).33

Because the cultivation of plough-positive and plough-negative crops is an endogenous out-

come, we do not use this as our instrument. Instead, we measure geo-climatic conditions that are

unaffected by human actions, but which impact the suitability of a location for growing both types

of crops. Our strategy uses two instruments. The first is a measure of the average suitability of

the geo-climatic conditions of the location of each observations ancestors for cultivating wheat,

barley and rye, which are plough-positive cereal crops. The second is the same measure of

ancestral suitability, but for cultivating millet and sorghum, which are plough-negative cereal

crops. We choose to identify off of conditions related to cereal crops that are plough-positive and

plough-negative because we feel that these are the most comparable. The crops being compared

are all cereals that have been grown in the Old World for millennia.

Given our instruments, identification relies on the assumption that holding overall crop pro-

ductivity constant (which we condition on), the type of cereal crop that a location can grow

only impacts long-term gender attitudes through the adoption of the plough. In other words,

the plough-positive and plough-negative cereal crop distinction is only important for long-term

gender roles because it impacted the historic adoption of the plough.

We obtain information on the suitability of a location for cultivating plough-positive and

plough-negative cereal crops from the FAOs Global Agro-Ecological Zones (GAEZ) 2002 database

(Fischer, van Nelthuizen, Shah and Nachtergaele, 2002). The database reports suitability for the

cultivation of numerous crops for 5 arc minutes by 5 arc-minute grid-cell globally. The measures

are constructed from a host of data on the geo-climatic conditions of a location: precipitation,

frequency of wet days, mean temperature, daily temperature range, vapor pressure, cloud cover,

sunshine, ground-frost frequency, wind speed, soil slope, and soil characteristics. These data are

then combined with the specific growing requirements of crops to produce a measure of whether

the crop could be grown in that location, and if so, how productively. It is important to note

that the climate models are very sophisticated and therefore the crop suitability measures are not

simple functions of the geographic characteristics the models use. In addition, the measures are

objectively calculated, and not affected by where crops are actually cultivated.34

We construct the instruments by first identifying the land traditionally inhabited by each ethnic

33In his study, Pryor shows empirically that the existence of plough positive crops is positively correlated with theadoption of the plough.

34For a detailed discussion of the data and a different application see Nunn and Qian (2011).

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group in the Ethnographic Atlas, which reports the historical latitude and longitude of the centroid

of each ethnic group. We then identify all land within 200 kilometers of the centroid, and assume

that this is a reasonable representation of the land traditionally inhabited by the group. We

then measure the amount of land within this area that can grow each of the cereal crops that

comprise the instruments. Let xwe , xbe, xre, xse, and xme be the amount of land that can cultivate

wheat, barley, rye, sorghum and millet, respectively. Further, let xall be the amount of land that

could grow any crop (i.e., the amount of arable land). The ethnicity-level measures of suitability

for plough-positive crops is given by: Areapose =13 (x

we + x

be + x

re)/x

alle . While ethnicity-level

measure of suitability for plough-negative crops is: Areanege =12 (x

se + x

me )/x

alle . Intuitively, the

instruments measure the average suitability for type of crop, normalized by the overall suitability

for cultivation in general.

Using the procedure explained in equation (1), we then construct district and country-level

averages of our plough-positive and plough-negative instruments. Intuitively, the instruments

measure the proportion of a country or districts population whose ancestor had a climate that

could grow plough-positive cereals (wheat, barley and rye) and plough negative cereals (sorghum

and millet).

To provide the reader with a better sense of the instruments, Figure 6 shows the locations in

the world that are classified as being suitable for the cultivation of the plough positive cereals

wheat, barley and rye while Figure 7 shows suitability for the plough-negative cereals

millet and sorghum. A number of facts are apparent from the maps. The first is that there are

many parts of the world that can grow plough-positive crops, but not plough-negative crops and

vice versa. This provides an indication that the instruments may have variation independent

from each other and therefore some predictive power. Second, relative to plough-positive crops,

plough-negative crops appear to be relatively better suited for tropical and subtropical climates

and plough-positive crops better suited for temperate climates. If these differences in climate

caused other important differences between societies which affect gender attitudes today, then

the exclusion restriction will not be satisfied. This is part of the motivation behind the set of

covariates that we control for in both the OLS and IV estimates. Recall, that the controls include

the proportion of land, historically inhabited by an ethnic group, that was tropical or subtropical.

We also control for a number of historic measures of political/economic development, which may

have been correlated with the presence of a tropical climate. Finally, our regressions also include

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Wheat

Not suitable

Suitable

(a) Wheat suitability

Not suitable

Suitable

(b) Barley suitability

Rye

Not suitable

Suitable

(c) Rye suitability

Figure 6: Maps displaying the global suitability of plough-positive crops, wheat, barley and rye.

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Millet

Not suitable

Suitable

(a) Millet suitability

Sorghum

Not suitable

Suitable

(b) Sorghum suitability

Figure 7: Maps displaying the global suitability of plough-negative crops, millet and sorghum.

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other potential determinants of plough use that may also affect gender attitudes today, including

historic population density, as measured by settlement patterns, as well as a measure of overall

agricultural suitability.35

An important final point arises from the fact that the plough-positive and plough-negative

cereals used in the construction of our instruments were all originally grown in the Eastern

hemisphere and were not cultivated in the Americas until after 1500. This is not a concern

to identification, but it is a fact that makes the first stage relationship weaker than it would

be otherwise. For the large proportion of the population in the Americas whose ancestors are

from the Eastern hemisphere, the instrument will provide predictive power. It is only for the

indigenous populations of the Americas that the instrument will not vary plough adoption. This

should be kept in mind when interpreting the IV estimates as a local average treatment effect

(LATE). In other words, the estimates are an average effect among the ethnic groups whose

plough adoption was affected by the geo-climatic suitability for growing the cereal crops. Because

the crops were not indigenous to the Americas, we would not necessarily expect the indigenous

groups from the Americas to be within the group.

A. Country-level estimates

Table 5 reports IV estimates of the specifications from Table 2. The first stage estimates are

reported in the lower panel and the second stage estimates are in the top panel. The first stage

estimates show that the historic suitability for the cultivation of plough-positive cereals is always

positively correlated with the adoption of the plough, while suitability for the cultivation of

plough-negative cereals is generally negatively correlated with plough use. In all specifications,

the difference between the two coefficients is statistically significant. The F-test for joint signifi-

cance of the two instruments is also reported in the table. The F-statistics range from about 511,

suggesting that for some specifications there is a potential concern about weak instruments. For

this reason, in Panel A, we also report conditional likelihood ratio (CLR) confidence intervals and

LIML estimates in addition to the regular 2SLS estimates.

The IV estimates, reported in Panel A of the table, confirm the OLS estimates. Historic plough

use is associated with less female labor force participation, less female ownership of firms, and

less female participation in politics. The magnitude of the IV coefficients are consistently greater

35See Bobek (1962) and Boserup (1970) for more on these determinants.

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Table 5: Country level IV estimates.

(1) (2) (3) (4) (5) (6) (7) (8)

Historicploughuse(2SLS) -25.853** -26. 423** -19.939* -26.274* -16.820* -23.089* -1.451*** -1.946***

(10.051) (12.465) (11.932) (14.439) (9.243) (12.331) (0.467) (0.635)

Historicploughuse(LIML) -27.099 -28.25 -28.761 -43.12 -16.826 -23.16

p-value 0.01 0.03 0.03 0.02 0.05 0.03

CLRintervals [-54.88,-7.02] [-66.24,-3.47] [-71.65,-2.70] [-142.60,-6.77] [-47.06,0.29] [-75.07,-2.55]

Historiccontrols yes yes yes yes yes yes yes yes

Contemporarycontrols yes yes yes yes yes yes yes yes

ConnentFEs no yes no yes no yes no yes

Observaons 157 157 104 104 124 124 133 133

R-squared 0.393 0.427 0.014 0.128 0.167 0.045

P lo ug h- po si ve e nv iro nm ent 0 .41 2* ** 0. 377 *** 0 .65 6* ** 0. 561* ** 0 .401 ** * 0. 34 0* **

(0.119) (0.101) (0.150) (0.143) (0.140) (0.117)

Plough-negaveenvironment -0.120 -0.079 -0.017 0.001 -0.032 -0.026

(0.091) (0.075) (0.101) (0.075) (0.103) (0.087)

Equalcoeff(p-value) 0.00 0.00 0.00 0.00 0.00 0.01

F-stat (excl instr) 10.76 7.90 11.68 7.71 5.63 4.54

Hausmantest(p-value) 0.15 0.19 0.44 0.29 0.18 0.09

Notes: IV esmates are reported with robust standard errors in brackets. The unit of observaon is a country. Historic controls include agricultural suitability, domescated

animals, tropics, polical hierarchies and economic complexity. Contemporary controls include ln income, ln income squared, a communism indicator, and polity (in columns 5

and 6 only). The number of observaons for the AES esmates is the average number observaons in the regressions for each outcome. ***, ** and * indicate significance at

the1,5and10%levels.

PanelA.Secondstage.Dependentvariable:

PanelB.Firststage.Depvar:Historicploughuse

Averageeffectsize(AES)

Femallaborforce

parcipaon

Shareoffirmswithsome

femaleownership Femalesinpolics

than the OLS estimates. This is potentially explained by selection arising from the endogeneity

of plough adoption. All else equal, historically advanced societies were more likely to adopt the

plough. Further, they are more likely to also be advanced today with higher per capita incomes

and more female participation in the labor market. Therefore, selection introduces a positive

relationship between historic plough use and female labor force participation today, biasing the

negative OLS estimates towards zero.

Robustness checks

There are a number of potential concerns associated with our IV strategy. The primary concern is

that the difference between plough-positive and plough-negative environments may be correlated

with geographic features that affect gender attitudes today through channels other than theplough. We check the likelihood of this concern by controlling for a host of geographic charac-

teristics that are potentially correlated with the suitability of the environment for plough-positive

and plough-negative crops. Our controls36 include terrain slope, soil depth, average temperature

and average precipitation of locations inhabited by each countrys ancestors.

36The details of these controls, including their sources are provided in the appendix.

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Table 6: Robustness of IV estimates to additional geographic controls.

(1) (2) (3) (4) (5)

Historicploughuse -33.573*** -25.539** -27.842*** -18.427** -25.089***

(11.777) (10.371) (8.841) (9.068) (9.300)

Terrainslope yes yes

Soildepth yes yes

Averagetemperature yes yes

AverageprecipitaGon yes yes

Baselinehistoricandcontemporarycontrols yes yes yes yes yes

ObservaGons 157 154 157 157 157

R-squared 0.29 0.38 0.38 0.38 0.44

Dependent variable: FLFP

Notes: OLS esGmates are reported with robust standard errors in brackets. The unit of observaGon is a country. ***, ** and * indicate

significanceatthe1,5and10%levels.

The IV estimates (see Table 6) remain robust to the inclusion of these additional factors. In all

specifications, the estimated impact of past plough use on current female labor force participation

is negative and statistically significant. Further, the point estimates remain very similar to the

baseline estimate of25.9.

We also check the robustness of our IV estimates to the set of additional controls from Table 3.

These estimates are reported in Table 7. The IV estimates, like the OLS estimates of the impact of

the plough on female labor force participation, also remain robust to the additional controls. 37

B. Individual-level estimates

Table 8 reports IV estimates of equation (3), which examines variation across individuals in the

WVS. Consistent with the country-level IV estimates, at the individual-level we continue to find

persistent impacts of historic plough use. We estimate a negative effect of past plough use on the

participation of women in the labor force, and a positive effect on the prevalence of attitudes of

gender inequality. Like the country-level estimates, at the individual level we also find that the

IV estimates are larger than the OLS estimates.

6. Cultural transmission as a mechanism: Evidence from US immigrants

We now turn to an examination of the causal mechanisms underlying our results. Although

our focus is on the evolution and persistence of cultural norms, it is possible that part of the

long term effect of historic use plough may arise because it facilitated the development of

37The results are also robust for the two other outcome variables.

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Table 7: Robustness of IV estimates to alternative controls.

(1) (2) (3) (4) (5)

Historicploughuse -42.454* -25.563** -28.014*** -25.332*** -28.969***

(22.737) (10.317) (10.584) (9.250) (10.861)

Intensityofagriculture yesAbsenceofprivateproperty yes

Patrilocalandmatrilocalsociees yes

Hunngandherdingoflargeanimals yes

Nuclearandextendedfamilies yes

Baselinehistoricandcontemporarycontrol yes yes yes yes yes

Observaons 157 154 157 157 157

R-squared 0.27 0.41 0.38 0.40 0.38

(6) (7) (8) (9) (10)

Historicploughuse -18.269** -21.806* -25.974*** -25.606** -25.362**

(9.003) (11.188) (10.014) (9.303) (9.930)

Fraconofmajorreligiousdenomin. yes

FraconofEuropeandescent yes

Oilproducon yes

Trade/GDP yes

Agric.,manuf.andservicesshareofGDP yes

Baselinehistoricandcontemporarycontrol yes yes yes yes yes

Observaons 155 148 157 156 149

R-squared 0.55 0.44 0.40 0.40 0.43

SecondstageIVesmates:Dependentvariable:FLFP

Notes: IV esmates are reported with robust standard errors in brackets. The unit of observaon is a country. ***, ** and *

indicatesignificanceatthe1,5and10%levels.

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Table 8: Individual-level IV estimates.

Whenjobsare

scarce

Menbe.er

poli2calleaders

Averageeffectsize

(AES)

(1) () (3) (4)

Historicploughuse -0585** 0576** 1383*** 138***

(04) (09) (036) (0386)

Historicploughuse(LIML) -0611 0576 1418p-value 000 000 000

CLRintervals [-0700,-054] [0501,065] [1308,1531]

Individualcontrols yes yes yes yes

Currentcountrycontrols yes yes yes yes

Historicdistrictcontrols yes yes yes yes

Con2nentFE yes yes yes yes

Observa2ons 36,370 67,347 55,454 61,400

R-squared 0154 0170 0105

Plough-posi2veenvironment 073*** 04*** 0338***

(0073) (0079) (0088)Plough-nega2veenvironment -0075* -0041 -0094*

(0044) (0040) (0055)

Equalcoeff(p-value) 000 000 000

F-stat(exclinstr) 713 474 79

Hausmantest(p-value) 000 003 000

PanelBFirststageDependentvariable:Historicploughuse

Notes: The table reports IV es2mates, with standard errors clustered at the country level The instruments are plough-

posi2ve climate and plough-nega2ve climate Individual controls are age, age squared, educa2on, gender (for gender

atudes only), marital status, and income Current country controls include ln income, ln income squared and a

communism indicator variable Historic district controls include agricultural suitability, domes2cated animals, tropical

areas, poli2cal hierarchies, and economic complexity The AES reported in column 4 is for the two subjec2ve belief

measuresfromcolumnsand3***,**and*indicatesignificanceatthe1,5and10%levels

PanelASecondstageDependentvariable:

FLFP

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institutions and markets which are less conducive to the participation of women in activities

outside of the domestic sphere. Through this channel, the plough causes less female participation

in market activities because it affects the costs and benefits of these activities, not because it affects

individuals beliefs about whether these are appropriate activities for women.

Our individual-level estimates showing an impact of the plough on gender-role attitudes

provide evidence that the plough has ultimately impacted beliefs and values. However, these

may only differ because of differences in external factors (e.g., institutions, policies, markets, etc),

which in turn shape individual beliefs. To isolate the causal impact of the plough on individual

beliefs and values, we examine variation among second generation immigrants a group of

individuals from diverse cultural backgrounds, with different histories of ancestral plough use,

but all facing the same external environment, including markets, institutions and policies. Using

data from the March Supplement of the Current Population Survey (CPS), we examine whether

women with an ancestry of plough agriculture, are less likely to be in the labor force. 38 We

identify the ancestry of women in the sample using their parents country-of-birth. This yields

three possible measures using either the mothers country of birth, the fathers country of birth,

or restricting the sample to women for which both parents country of birth is the same. The

different definitions also provide evidence for whether cultural transmission is stronger from the

father to the daughter, the mother to the daughter, or when both occur.

To examine the impact of the plough on immigrant populations we estimate the following

equation:

yi,s,c = s + Ploughc + XCc + X

Hc + Xi+ i,s,c (4)

where i denotes second generation women currently living in state s, whose country of origin

is country c. As in equation (2), Ploughc denotes the historic plough-use of those in country c.

The dependent variable, yi,s,c, is an indicator variable that equals one if individual i is in the

labor market. XCc and XH

Documents

Women and the Plough, Agriculture and Gender