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Women’s Contributions to the Workforce: Are New Measures

Needed?

Martha S. Farrar and Fred A. Vogel

_______________________________________________________________________________

Traditionally, the penetration of women into the workforce has been measured by comparing the percentage

by work category of women versus men or by comparing their mean or median incomes. This paper reviews

current indicators that quantify gender-related differences and suggests the need for additional measures to

determine why these differences exist. 

KEY WORDS: gender differences, gender measures, workforce statistic, gender statistics

_______________________________________________________________________________

1 INTRODUCTION1

 Traditionally, the penetration of women

into the workforce has been measured by

comparing the percentage by work category

of women versus men or by comparing their

mean or median incomes. Do these

traditional measurements provide

appropriate indicators to describe women’s

contributions to the workforce? For

instance, to measure women’s contributions

to the workforce, should there be more

gender indicators in the national accounts?

To ensure the best government policy

decisions on economic matters, accurate

measures are essential. Perhaps the best

policy decisions may only be possible if

supporting gender statistics are available.

Participation rates do not adequately

measure women’s contribution to workplace

efficiencies, so how should we measure

women’s contributions to demonstrate what

women add to a job situation? This paper

reviews current indicators that quantify

gender-related differences and suggests the

need for additional measures to determine

why these differences exist. 

2 EXAMPLES OF CURRENT

METHODS

 Only 9.2 percent of the members of the

International Statistical Institute (ISI) are

women (Carlson 1999). Before reaching

any conclusions about this, one should try to

measure the percentage of women that are

“eligible or qualified” to become ISI

members. Over 15 percent of the ISI section

membership is female. If the percent of

women in ISI sections is taken as a rough

estimate of the percent qualified for

consideration as an ISI member, then

women are indeed not properly represented.

For the United States, membership of the

American Statistical Association (ASA)

might also represent a pool of people

eligible for membership in the ISI. If the

number of ASA members reporting their

gender is representative of the total

membership, then 24 percent are women.

Carlson indicates that only 9.9 percent of

ISI members from the U.S. are women,

again perhaps indicating a lack of

representation of women in ISI. Other

measurements to investigate may include

1This paper was presented at the International Statistical

Institute, Seoul, Korea, 2001. The authors are with the

National Agricultural Statistics Service. Fred Vogel is

Deputy Administrator for Program and Products. Martha

Farrar is chief of the Data Collection Branch.
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the percent of articles in statistical journals

that are submitted or written by women.

 The monthly Labor Review (1999) reported

that women only earned 76 percent of men’s

earnings in 1998, but that the gap between

them was closing. The report also indicated

that education levels for men and women

were about the same. The earnings

difference was attributed to the choice of

occupation. Women were more often found

to be teachers, nurses, and so forth, while

men were more often engineers or computer

scientists. What is not known is whether

women are discouraged to seek college

degrees that would lead to higher paying

jobs or if there are other reasons why they

are less likely to enter such professions. For

example, the authors wonder, do women

choose professions that are more tolerant of

part-time work or those that require only

moderate training for re-entry into the

workforce after a period of being absent?

Why do female-dominated professions

command lower salaries than maledominated professions? Are there barriers

at either level? How is this determined and

measured? 

 Issues with women’s contributions to the

workforce may differ in developing

countries. Much of the rural sector in

developing economies lives in poverty.

Agricultural statistics often fail to include

variables required to understand rural

economies, thus policy makers lack

appropriate information. The extent of

women’s contribution to agricultural

production is often not measured because

much of it is unpaid labor, which tends to be

excluded from national accounts. In

subsistence economies, for example, women

do much of the work to produce food and

goods for home consumption. The

Statistical Commission of the United

Nations has added “Home Production of

Goods for Home Consumption” as an

economic activity similar to activities

required to produce goods for market. Such

information is needed to formulate policies

to improve living conditions and economic

opportunities in rural areas. Women and

girls are also the major providers of unpaid

services including the care of children, the

sick and the elderly. The Food and

Agriculture Organization of the United

Nations (FAO) suggests the use of “timeuse” studies, where individuals record all

time worked, as the best tool for measuring

such activities.

 Developing economies often exhibit a

disparity in levels of education between men

and women. It is interesting to note that the

First National Agricultural Census in China

(1999) was designed to obtain gender

related information about farm and rural

households. For example, the census

obtained a count of the number of persons

aged 7 years and over engaged in economic

activities by sex, educational level, and

region. The results showed that the split

between the number of males and females

engaged in economic activities was 52.5 and

47.5 percent, respectively. However, 20.5

percent of the females were illiterate or

semi-illiterate compared to 9.5 percent of

the males. This information should be

invaluable for policy makers as they pursue

ways to develop the rural economies. What

is not measured are the factors contributing

to the gap. In subsistence economies, are

schools available to both sexes? If so, are

some family members excluded from

educational opportunities because their labor

is needed to produce food for home

consumption? Are the excluded family

members more likely to be women? How

would a family’s ability to feed itself be
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affected if public policy required a

minimum level of education for everyone?

 A major concern of all countries, including

developing countries is whether its people

have adequate food and nutrition. The U.S.

Department of Agriculture and the U.S.

Census Bureau joined in an effort to

measure food security in the U.S. by adding

a supplement to the monthly current

population survey. The results showed 12

percent of the U.S. population and 12

million households falling below nutrition

standards. What this study did not show,

but was learned from another study, was that

single female heads of households are five

times more likely to suffer from inadequate

nutrition. Thus, an important factor in

combating malnutrition is to understand the

characteristics of the households where it

exists.

3 MEASUREMENTS REQUIRED

 In this paper, we discuss the need for tools

associated with three principal measurement

needs: education, employment, and

economic contribution. Education is critical

as those without it are increasingly at a

disadvantage. Measures of employment

opportunities or lack thereof are needed as

well as measures of underemployment. The

full economic contribution of people to the

national accounts needs to be quantified.

Suggested methods of obtaining gender

information include the use of surveys,

census, opinion polls, and focus groups

among working women. The agricultural

census should be considered as a vehicle to

obtain the necessary measures for rural

areas, especially in developing economies

with subsistence agriculture. Data items

that could be included would measure these

quantities:

• Education levels of all household

members by age and sex.

Information should also be collected

to measure reasons why individual

family members have an education

below a certain level.

• Employment activity for every

household member and income

received. For those not working,

categorical data should also be

obtained to describe reasons for not

having paid employment.

• Economic contribution. The number

of unpaid hours each family member

works to produce food and goods for

home consumption should be

obtained. The value of these items

produced should also be determined.

For example, if the family had to

purchase these items, how much

would the family have to spend, or

how much would it have to pay

someone else to do the labor?

 The three measures - education,

employment, and economic contribution -

are also important in developed economies,

but may require different measures. The

interaction between education and

employment needs to be considered

although income levels between men and

women differ even when education levels

are similar. Traditional employment and

education statistics only quantify the

situation; they do not explain the underlying

reasons. Data collection activities to

measure employment should also attempt to

measure under employment and associated

reasons.

 Education statistics by level of attainment

and chosen field should be accompanied by

reasons for the choices that were made.
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Even more important would be to know

what the attainment and choices would have

been by kind of barrier that prevented one

from that accomplishment.

 Employment statistics by type of work and

income level need to be combined with the

above education statistics. In addition, the

employment statistics should be

complemented with reasons for these

choices to quantify reasons for under

employment. Wilson and Billard (1999),

pointed out that in academia, women spend

more time in rank before promotion than do

men. An important additional measure

would be a comparison of those with

continuous service to those with a break in

service. Organizations need to analyze their

own situation or conduct attitudinal surveys.

The analysis cited by Fellegi (1999)

examined why women in Statistics Canada

at some grade levels were “waiting longer”

for promotions to the next level. Their

study showed fewer women were subjecting

themselves to the formal competition

process. This led Statistics Canada to make

some significant changes to its competition

process. In an corollary study, the USDA

conducted a survey of all employees to learn

why those with disabilities worked at lower

grade levels. A major finding of this study

was the simple fact that employees with

disabilities were not aware of the resources

and services available to them that would

enhance their work performance and

careers.

 Data underlying the national income and

production accounts need to be

disaggregated to measure the contributions

of men versus women. In summary, it is not

enough to quantify gender-related

differences. We need to determine why

these differences exist. Only then can

policy makers take appropriate action to

address gender related inequities and ensure

that women’s contribution to the workforce

is recognized.

4 REFERENCES

Carlson, Beverly (1999). Women in

Statistics: The Profession Speaks.

Economic Commission for Latin America

and the Caribbean.

Fellegi, Ivan (1999). Women’s

Participation in Statistics Discussion.

Bulletin of the International Statistical

Institute.

Food and Agricultural Organization of the

United Nations (1999). Agricultural Census

and Gender Considerations – Concepts and

Methodology. FAO Bulletin.

National Bureau of Statistics, People’s

Republic of China (1999). Abstract of the

First National Agricultural Census in China.

China Statistics Press.

U.S. Department of Agriculture (1999).

Employee Survey on Disability Issues –

Employment and Service Delivery Results

at USDA. USDA Bulletin MP-1559.

USDA, Economic Research Service (2000).

Second Food Security Measurement and

Research Confer ence Volume I:

Proceedings. Edited by Margaret S.

Andrews and Mark A. Prell. Food

Assistance and Nutrition Research Report

Number 11-1.

U.S. Department of Labor, Bureau of Labor

Statistics (1999). Women in the Workforce.

Monthly Labor Review.
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Wilson, Susan R. and Billard, Lynne (1999).

Women in Statistical Science: An Historical

Perspective. Bulletin of the International

Statistical Institute.