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Olivia nelson

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European Bank for Reconstruction and Development

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The Gender Equality Index is a unique measurement tool that synthesises the complexity of gender equality as a multi-dimensional concept into a user-friendly and easily interpretable measure. It was developed by the European Institute for Gender Equality. Access the Gender Equality Index at http://eige.europa.eu/content/gender-equality-index

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Seats in National Legislature Held by Women

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Seats in National Legislature Held by Women

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Jackie Rynda

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Jackie Rynda

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Jackie Rynda

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Olivia Nelson

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Jackie Rynda

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Olivia Nelson

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Olivia Nelson

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Jackie Rynda

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Olivia Nelson

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Gender Development Index (GDI) | Human Development Reports

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The GDI shows how much women are lagging behind their male counterparts and how much women need to catch up within each dimension of human development. It is useful for understanding the real gender gap in human development achievements and is informative to design policy tools to close the gap.

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Olivia Nelson

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Women's increased labor force participation represents a significant change in the U.S. economy since 1950. As of 2014, nearly six in ten women aged 16 and older (57.0 percent) worked outside the home (U.S. Bureau of Labor Statistics 2015a), compared with 33.9 percent in 1950 and 43.3 percent in 1970 (Fullerton 1999). Women now comprise nearly half of the U.S. labor force at 46.8 percent (U.S. Bureau of Labor Statistics 2015a). In each state, however, women are still less likely to be in the workforce than men (Table B2.1).

Among all states, Alaska has the highest rate of women's labor force participation; 68.3 percent of women aged 16 and older work. Women in the Midwest have the strongest labor force participation rates overall: Minnesota, Nebraska, North Dakota, South Dakota, and Wisconsin all rank in the top ten. Other top ten jurisdictions include the District of Columbia, Maryland, Massachusetts, and Wyoming (Table 2.1).

Fewer than half of women (49.3 percent) are in the labor force in West Virginia, the state with the lowest labor force participation rate of women in the nation. Southern states overall also have very low rates; Alabama, Arkansas, Florida, Kentucky, Louisiana, and Mississippi also rank in the bottom ten. Two Mountain West states-Arizona and New Mexico-and Oklahoma also fall into this group.

Utah has the largest difference between men's and women's labor force participation rates at 16.7 percentage points. Maine has the smallest at 5.8 percentage points (Table B2.1).

Women's labor force participation has increased in just 11 states and the District of Columbia since 2002. Louisiana and the District of Columbia have shown the largest gains, with increases of 3.6 and 3.3 percentage points, respectively. Idaho and Minnesota have experienced the greatest losses, with declines of 5.6 and 4.8 percentage points (IWPR 2004; Table 2.1).

Among the largest racial and ethnic groups, black women aged 16 and older had the highest national workforce participation rate in 2014 at 59.2 percent. White women had the second highest labor force participation rate at 56.7 percent, followed by Hispanic women (56.0 percent) and Asian women (55.8). Data are not available for Native American women (U.S. Bureau of Labor Statistics 2015c). Among the detailed racial and ethnic groups shown in Table B2.3, Bolivian and Peruvian women have the highest labor force participation rates among Hispanic women at 70.1 and 66.0 percent, respectively, and Cuban women have the lowest rate at 55.9 percent (Table B2.3). Filipino and Laotian women have the highest workforce participation rates among Asian/Pacific Islander women (68.2 and 64.8 percent), and Pakistani and Bangladeshi women have the lowest rates (41.8 and 44.3 percent). Among Native American women, the Chippewa and the Pueblo have the highest workforce participation rates at 59.4 percent and 59.0 percent, respectively, and the Navajo and the Cherokee have the lowest rates (52.2 and 53.9 percent; Table B2.3).

Labor force participation rates also vary by age. Among women, rates are highest for those in their prime working years (aged 25-54); after increasing between 1960 and 1999, however, the labor force participation rate of women in this age group decreased nearly three percentage points between 2000 and 2014 (the labor force participation rate of men aged 25-54 declined by more than three percentage points during this time; Figure 2.6). The labor force participation rate for young women (16-24) reached its high point in 1987 and declined more than nine percentage points between 2000 and 2014, while young men's labor force participation rate declined by more than twelve percentage points, reflecting the longer time this generation now spends in education and also a weak labor market during the Great Recession and in the slow recovery for many young adults. Among women aged 55 years and older-who are much less likely to be in the workforce than younger women-labor force participation has increased over the last three decades, especially so in the 2000s, having remained fairly constant from 1960 until the mid-1980s, when the labor force participation rate of young women was growing rapidly. In 2014, 34.9 percent of older women were in the workforce, compared with 26.1 percent in 2000. Older men, in contrast, experienced a steady decline in their workforce participation rates between 1960 and the mid-1990s, before their labor force participation rate increased between the mid-1990s and 2014, reaching its high point in 2012 (Figure 2.6).

Figure 2.6. Labor Force Participation Rates by Gender and Age, 1960-2014

Insert Figure 2.6

Source: IWPR compilation of Current Population Survey data from the U.S. Bureau of Labor Statistics (2015c).

Part-Time Work

Although the majority of employed women and men in the United States work full-time, women are nearly twice as likely as men to work part-time (29.4 percent compared with 15.8 percent; Table B2.6).

Working part-time makes it less likely that a worker will receive employment benefits such as paid vacation days, paid family or medical leave, paid sick days, health care insurance, or employer contributions to retirement saving funds (Society for Human Resource Management 2011; Van Giezen 2012).

Utah (40.2 percent), Oregon (37.1 percent), and Rhode Island (36.5 percent) have the largest percentages of employed women who work part-time.

The District of Columbia (18.8 percent), Maryland (24.3 percent), and Oklahoma (24.5 percent) have the smallest percentages of employed women who work part-time. The percentage of employed women working part-time in the District of Columbia is roughly half that of Utah.

Women work part-time for various reasons. The majority who work part-time do so by choice (although these choices may be constrained by factors such as their children's school hours and the high costs of child care). For some women, however, part-time work is involuntary; approximately one in five women who usually worked part-time in 2013 said they worked part-time because they could not find full-time work or had their hours at work temporarily reduced (IWPR 2014b).

Whether part-time work is voluntary or not, an increasing number of workers report not knowing from one week to the next how many hours and at what times they are expected to work. They may be expected to be available for full-time work, but without any guarantee of how many hours they actually will be scheduled to work. A recent national survey of younger workers between the ages of 26 and 32 found that approximately 70 percent of hourly and non-hourly women workers experience fluctuations in their hours worked per week. Such fluctuations are particularly common for workers classified as part-time (Lambert, Fugiel, and Henly 2014). In addition to potentially creating havoc with workers' family lives, and their own and children's school schedules, these unpredictable schedules can make it hard to secure a steady income that enables them to meet their financial needs. Unpredictable scheduling also can make it difficult for workers to combine two or more part-time jobs to increase earnings or combine part-time work with their own schooling.

Unemployment

Preliminary data from the Bureau of Labor Statistics show that in 2014, 6.1 percent of women aged 16 and older in the nation's civilian, noninstitutionalized population were unemployed, compared with 6.3 percent of men (U.S. Bureau of Labor Statistics 2015d). These unemployment rates were the lowest for women and men since 2008, when 5.4 percent of women and 6.1 percent of men were unemployed (U.S. Bureau of Labor Statistics 2014b). This decrease in unemployment reflects improvement in the nation's economy following the Great Recession that officially lasted from 2007 to 2009. The lower rates, however, may also reflect the decision of some workers to give up their active search for a job in the face of dim employment prospects (Davis 2014). As noted above, labor force participation rates have fallen, and some adults may have left the labor market out of discouragement.

In the United States, women's unemployment rates vary considerably by race and ethnicity. According to preliminary data, black women in 2014 had the highest unemployment rate among women at 10.5 percent, followed by Hispanic women (8.2 percent), white women (5.2 percent), and Asian women (4.6 percent; data are not available for Native American women). For each racial and ethnic group except Hispanics, women's unemployment rates were lower than men's (U.S. Bureau of Labor Statistics 2015e).

Single mothers and young women also have high levels of unemployment. In 2013, single mothers with children under 18 were more than twice as likely to be unemployed as married mothers with a spouse present (12.0 percent compared with 4.8 percent; U.S. Bureau of Labor Statistics 2014c). According to preliminary data for 2014, the nation's youngest female workers (aged 16-19) had an unemployment rate of 17.7 percent; those aged 20-24 fared better but still had a relatively high unemployment rate (10.1 percent; U.S. Bureau of Labor Statistics 2015d). Many young women face the dual disadvantage of having limited or no prior work experience and a lack of higher educational credentials.

The Employment and Earnings of Immigrant Women

Approximately 21 million female immigrants live in the United States, making up just over 13 percent of the nation's female population. Immigrant women come from all over the world, with the largest shares from Mexico (25.6 percent), the Philippines (5.3 percent), China (4.7 percent), and India (4.6 percent). In their multiple roles as students, professionals and other workers, spouses, parents, and caregivers, immigrant women make important contributions to local communities, the economy, and society.

Immigrant women are less likely than U.S.-born women to be in the labor force (56.2 percent compared with 59.0 percent). While many immigrant women are thriving in the workforce, others encounter challenges that hinder their workforce participation or limit their access to higher quality employment. These challenges include the same barriers all women face-such as the undervaluation of work performed predominantly by women and the lack of a work-family infrastructure-and often additional challenges as well, such as limited English proficiency and, for those who are undocumented, lack of access to legal status (Hess, Henrici, and Williams 2011; Hess and Henrici 2013).

Median annual earnings for immigrant women working full-time, year-round in 2013 were $32,000, which was much less than the earnings for U.S.-born women ($39,000). Among the ten largest sending countries for female immigrants-Mexico, the Philippines, China, India, Vietnam, Korea, El Salvador, Cuba, the Dominican Republic, and Canada-immigrant women's earnings varied considerably. Women from India had the highest earnings at $65,000-well above the median earnings for all women of $38,000-and women from Mexico had the lowest earnings at $22,000. These differences likely stem, in part, from differences in levels of education; immigrant women from India typically have more years of higher education.

Immigrant women overall are less likely than U.S.-born women to work in managerial or professional occupations (32.7 percent compared with 41.1 percent).

Immigrant women are disproportionately represented in service occupations. One in three (32.5 percent) immigrant women work in these occupations, compared with 19.9 percent of U.S.-born women. Immigrant women are also nearly twice as likely as U.S.-born women to work in production, transportation, and material moving occupations (9.9 percent compared with 5.0 percent). They are less likely than U.S.-born women to work in office and administrative support occupations (13.3 percent of employed immigrant women work in these occupations compared with 21.5 percent of employed U.S.-born women) and in professional and related occupations (21.8 percent compared with 27.0 percent).
IWPR calculations based on 2013 American Community Survey microdata.
The Employment and Earnings of Women with Disabilities

Approximately 2.6 million women aged 16 and older in the labor force have disabilities, including cognitive, ambulatory, sight, hearing, and self-care or independent living difficulties. They are 3.6 percent of all women in the labor force.

The labor force participation rate of women aged 16 and older with disabilities in 2013 was 17.1 percent, compared with 62.7 percent of women without disabilities.

Finding work is harder for women with a disability than for other women. In 2013, the rate of unemployment for women with a disability was 13.5 percent, compared with 6.8 percent for women without a disability.

Women with disabilities are more likely to work part-time. The percentage of women with disabilities working part-time in 2013 was 38.4 percent, compared with 28.9 percent of women without disabilities.

Women with disabilities are about as likely as other women to work in sales and office occupations (31.8 and 30.4 percent, respectively) and slightly more likely to work in service occupations (24.8 and 21.6 percent). They are less likely to work in management, professional, and related occupations (34.9 percent of women with disabilities and 41.8 percent of women without disabilities).

Women aged 16 and older with disabilities who work full-time, year-round report lower earnings than those without disabilities ($32,500 compared with $38,000).
Earnings data and data on part-time work are based on IWPR analysis of 2013 American Community Survey microdata; all other data are from the U.S. Bureau of Labor Statistics (2014d).

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Women's Labor Force Participation - Women in the States

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Women's Labor Force Participation Women's increased labor force participation represents a significant change in the U.S. economy since 1950. As of 2014, nearly six in ten women aged 16 and older (57.0 percent) worked outside the home (U.S. Bureau of Labor Statistics 2015a), compared with 33.9 percent in 1950 and 43.3 percent in 1970 (Fullerton ...

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Jackie Rynda

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Subject Matter:

According to Amartya Sen, economic development needs to be defined in terms of 'entitlement' and 'capability'. By entitlement we mean a set of alternative commodity bundles that an individual can command through the totality of rights and obligations that one faces.

Thus, entitlement generates 'capabilities' that represent a person's freedom to achieve various functioning combinations.

In other words, capability is essentially one of freedom. And by economic development Sen suggests capability expansion or expansion of freedoms. For instance, poverty is a failure to achieve certain minimum capabilities. Un-freedoms like hunger, malnutrition, poverty, poor health, economic insecurity, poor schooling and health care, etc., generate inequalities. Despite remarkable growth, a vast section of population of the contemporary society is deprived of basic freedoms. One such un-freedom is gender bias.

Though HDI incorporates some aspects of human development, inequalities in opportunities between men and women are missed out in HDI. Because of gender bias in health care, mortality rates of women are high compared to men. It is the adverse sex ratio as observed in Asia and North Africa which is attributed to 'missing women' concept. Above all, in respect of allocation of health care, schooling, food and nutrition, the neglect of women is rampant. All the.se reflect gender-related inequality.

With the advancement of economic progress as well as social progress, such clear cut bias against women should have declined. Unfortunately, such trend is on the rise. Capability deprivation results in gender inequality. Through sex- selective abortion, female fetuses are eliminated so that no female child is born. In 1998, as a re- suit, for the world as a whole, shortfall of women relative to men exceeded 100 million. This is called 'missing women'.

The 2012 World Development Report puts this figure to 3.9 million in low income countries. Substantive freedoms that a male member enjoys are denied to female member. For example, women eat less and get little medical attention. Educational gender gap is also perceptible. Women have no or little power or authority over any household decision-making process. Outside the home, women are politically marginalised. All these reflect gender disparity.

To measure the extent of this disparity or inequality, the UNDP in 1995 took a new initiative to construct an index called 'gender-related development index' (GDI). In addition, in order to close this gap, women used to be empowered. To measure the extent of empowerment of women, the UNDP devised 'gender empowerment index' (GEI) also in 1995.

The HDI measures achievements in human development in terms of three indicators, but ignores differences between men and women. Gender differentials in achievement are studied with the index called GDI. Like the HDI, GDI measures achievements in the same three dimensions and variables in respect of men and women.
These three dimensions may now be recapitulated:
(i) A long and healthy life, as measured by life expectancy at birth;

(ii) Knowledge, as measured by the adult literacy rate and the combined primary, secondary and tertiary gross enrolment ratio; and

(iii) Estimated earned income measured by US $ .

Before calculating GDI, an index requires to be created for each of these dimensions.
To calculate these dimension indices, minimum and maximum values for female and male indices in each dimension are calculated in accordance with the following formula:
Dimension index = actual value - minimum value/maximum value - maximum value

The gender disparity, lower the GDI. Countries that have achieved some success in expanding capabilities for both men and women will have higher GDI. A country having a GDI less than 0.500 indicates larger gender disparity.

How GDI is understood has been presented in terms of Fig. 5.2.

How is GDI Constructed?

In HDI, the life expectancy index at birth of a country is calculated. But in the case of GDI, life expectancy at birth for both male and female are calculated. After determining life expectancy at birth for male and female, these are combined in a way that 'penalises' differences in achievement between men and women. The index thus obtained is called 'equally distributed life expectancy index'.
The formula of this index is:
Equally distributed index = {[female population share (female index 1- ɛ)] + [male population share (male index 1- ɛ)]}

ɛ measures the inequality aversion. In the GDI, ɛ is assumed to be equal to 2. If e = 0 then GDI equals HDI. As e tends to infinity gender inequality widens.
The calculation procedure of GDI involves the following four steps:
(i) Calculating the Equally Distributed Life Index:

Out of 102.9 crore Indian population in 2001 census, male members (53.2 crore) exceeded female members. Life expectancies at birth for Indian women and men were 66.9 years and 63.9 years. Thus,

The equally distributed life index = ([0.483 (0.657- ¹)- ¹ + [0.517 + (0.690-1)])- ¹= 0.674

(ii) Calculating the Equally Distributed Education Index:

First, the adult literacy rates for women and men are determined. Secondly, the combined primary, secondary and tertiary gross enrolment ratios for women and men are calculated.

Now we will calculate the education index for both women and men. To do this, two-thirds weight to the adult literacy index and one-third weight to the gross enrolment index are assigned to obtain both female and male education indices.

Education index = 2/3 (adult literacy index) + 1/3 (gross enrolment index)

Female education index = 2/3 (0.537) + 1/3

(0.753) = 0.551

Male education index = 2/3 (0.753) + 1/3 (0.660) = 0.722
Finally, the female and male education indices are combined to obtain the equally distributed education index:
(iii) Calculating the Equally Distributed Income Index:

Finally, female and male income index (based on PPP US$) is calculated.
Income index is calculated according to the following formula:
Income index
Combining the female and male income indices, we calculate equally distributed income index:

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ADVERTISEMENTS: Let us make an in-depth study of the subject matter and construction of gender-related development index. Subject Matter: According to Amartya Sen, economic develop­ment needs to be defined in terms of 'entitlement' and 'capability'. By entitlement we mean a set of alternative commodity bundles that an individual can command through the totality of rights ...