Engendering economic statistics

Global Forum on Gender Statistics, Rome, 10-12 December 2007

Women and economics: household, enterprise and decision-making bodies

Cristina Freguja, Stefania Cardinaleschi, Lucia Coppola, Sara DemofontiIstat

Economics has traditionally been a male-dominated sphere and the gender dimension has been absent in economic statistics and analysis

Lack of: data, standard for surveying, comparable sources…..

...but also “simply” to look at the available data without a gender perspective preclude to draw up a detailed outline of women’s contribution to economics

A growing informative demand is emerging in this domain and consequently gender statistics have to face new challenges

Introduction

Challenges Use of a gender perspective in data analysis

Enrichment of existing data sources with gender specific information

Integration of available data sources

Development of new surveys

Some examples:

women’s contribution to the household income

women’s participation in enterprises

women’s representation in economic decision-making bodies

Introduction

EU-SILC 2004 provides standardized information at individual and household level about income and living conditions for:

Austria, Belgium, Denmark, Estonia, Spain, Finland, France, Greece, Ireland, Italy, Luxembourg, Norway, Portugal, and Sweden

We consider:

Married and cohabiting couples, composed by partners aged 25-54 years

Partners earnings

Data and Methods

Household income

To what extent dual-earner model is spread in the EU countries?

In dual-earner couples, women contribute as much as their partners to the household economic needs?

Which individual and household characteristics are more likely to be associated with dual-earner couples?

Among dual-earner couples, which are the characteristics associated with women’s levels of contribution?

Household income

Research questions

We define and compare:

1) man sole provider couples VS. dual-earner couples

2) man main provider (woman earns less than 40% of the couple earnings);

equal providers (woman earns between the 40% and the 60%

of the couple earnings); woman main provider (woman earns more than 60% of the

couple earnings).

Data and Methods

Household income

An Overview

Distribution of dual earner couples by conutry

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AT BE DK EE ES FI FR GR IE IT LU NO PT SE EU

Dual-Earner couple

Man Sole Provider

Household income

Lowest % of man sole provider:

Denmark, Finland, Norway, Sweden

(lower than 10 %)

Highest % of man sole provider:

Spain, Greece…Luxembourg, Italy, Ireland

(higher than 30%)Distribution of dual earner couples by conutry

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AT BE DK EE ES FI FR GR IE IT LU NO PT SE EU

Dual-Earner couple

Man Sole Provider

Household income

Man Sole Provider vs. Dual Earner Couples

FINDINGS

the dual-earner model is more likely

to be associated with: highly educated women women more educated than their partners cohabiting couples without children in pre-scholar agemedium high levels of household income

ANALYSES

Logistic regression

Household and individual characteristics:partners age and age differencepartners educational level and

educational level differencetype of union (i.e. cohabitation or

marriage) number and age of children economic level of the household

When comparing the association between household and individual characteristics and the dual-earner model, the North-South difference noted in the distribution of

dual-earner couples among EU countries disappears

Household income

An Overview

DUAL EARNER COUPLES: women's contribution to couple earnings by country

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AT BE DK EE ES FI FR GR IE IT LU NO PT SE EU

Woman main provider

Equal providers

Man main provider

Household income

DUAL EARNER COUPLES: women's contribution to couple earnings by country

0%

10%

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AT BE DK EE ES FI FR GR IE IT LU NO PT SE EU

Woman main provider

Equal providers

Man main provider

Household income

Man main provider model: represents the more frequent strategy in most of the countries

Woman main provider model: represents less than 16% of the couples in all countries

Man Main Provider vs. Equal Providers

Woman Main Provider vs. Equal Providers

the woman main provider model is commonly associated with:

highly educated women,

women more educated than their

partners

the poorest quintiles of the income

the man main provider model is commonly associated with:low educated women women less educated than their

partnerspresence of children, especially if

in pre-scholar age

More convenient when the woman has not invested much in human capital, and her specialisation in domestic activities becomes extremely worthy for the presence of young children.

For a woman, becoming the main provider, might be not only the result of high investments in human capital, but also of the need for supporting household economics.

Household income

An appropriate combination of results from different data sources may provide evidence of relevant gender dynamics

Study by ISTAT on women entrepreneurs (2001)

Data from 1. Industry and Services Census carried out in 1997, 2. Labour Force survey3. Multipurpose survey on Everyday Life

Enterprises

1. only a quarter of enterprises were managed by women and their enterprises were generally smaller and concentrated in services to families

2. women-run enterprises were less integrated into the market: they made fewer agreements, received and requested fewer orders, had lower average yields and smaller sales-costs ratios

3. 53,3% of entrepreneur or self-employed women worked more than 60 hours per week, when considering work both within and outside the family; the same percentage for men was 26% (on average, men and women work respectively 54 and 64 hours)

BUT……1. smaller proportion of time devoted to the enterprise by women, in spite of a

higher total number of hours worked (58.5% of male entrepreneurs work 46 hours and more per week, while only the 40.6% of female entrepreneurs do so)

Enterprises

The activities inside and outside home lead to double burden, and the overload of work prevents female entrepreneurs from dedicating appropriately to their enterprises

The situation does not seem to show signs of important improvements in last years

The results from the Labour Cost Survey (LCS) carried out in 2004, that for the first time collected information on the sex of the entrepreneur, confirm that the women-run enterprisers play a role that is still secondary respect to the men’s ones

Results from the time budget survey show a persistent asymmetry between the commitment of women and men in terms of familiar work, even if we can observe that participation of men to the domestic work is slowly increasing

The workload inside home continues to have a big relevance in explaining the reality of women-run enterprises

Enterprises

The last twenty years have seen a huge increase in the number of women participating in the labor force almost everywhere and in all sectors…

…but the women’s representation at a decision-making level is much lower then men’s in major institutions

The participation of women in high level economic decision-making is fundamental to give women and men an equal share of power and influence in policy making processes

This is not only a demand for simple justice or democracy but can also be considered as a necessary condition for women's interests to be taken into account (Beijing Platform, 1995)

Economic decision-making

Economic decision makers

are those who occupy institutional positions in decision-making bodies, they are actively involved in the deliberation and determination of economic policies and they are responsible for implementing them on behalf of the State or the institution they represent

Economic decisions made by either private or public actors, determine both present and

future economic performance and assets, with obvious implications for everyone’s daily life

Economic decision-making

Aims

Adoption of adequate measures on the basis of the most appropriate monitoring indicators

Institutionalization of formal requirements to collect and provide data by sex

National Statistical Institutes responsible for pre-testing and revising the data collection instruments, designing and supervising the data collection process as well as the data validation and analysis

Economic decision-making

Developed by the EU Italian Presidency to measure the representation of women and men in economic decision-making bodies

Economic decision-making

Governors and deputy/vice-governors of the Central Banks

Members of the decision-making bodies of the Central Banks

Ministers and deputy ministers/vice-ministers of the Economic Ministries

Presidents and vice-presidents of the Labour Confederations

Total governing bodies of the Labour Confederations

Presidents and vice-presidents of the Employer Confederations

Members of total governing bodies of the Employer Confederations

Chiefs of executive boards of the 50 top firms publicly on the national stock exchange

Members of executive boards of the 50 top firms publicly on the national stock

exchange

Indicators

The proportion and the number of women and men among…

Summarizing

New challenges are emerging for official statistics at international level:

1. look at the available data in a new perspective: as an instance, an appropriate analysis of EU-SILC based on a “couple perspective”, allows for understanding the interrelationship between partners and the balance between gender roles;

2. enrich existing data sources with pertinent variables and integrate different data sources: for example, as far as the enterprises are concerned, countries should collect sex disaggregated data about the entrepreneurs, collect information that allow to highlight critical aspects women have to face; to measure the contribution of women work in the household, by attributing an economic value to the familiar work;

3. carry out new surveys: for instance, referring to the economic decision-making bodies, it would be very important to guarantee the collection of data through the National Statistical Institutes, adopting a set of indicators able to measure the representation of women and men in this domain.