The document analyzes the income earning gap between men and women in Canada from 2006 to 2012. It finds that the gap narrowed over this period. Several key factors contributed to the decreasing gap, including women obtaining more education degrees and pursuing higher-paying careers. While family responsibilities still correlate with lower incomes for women, the effect of having children on earnings is smaller than in the past. Overall, women saw faster wage growth and greater representation in higher-income brackets and fields between 2006-2012 compared to men.
This document introduces the Gender, Institutions and Development (GID) database, which aims to better understand factors influencing gender inequality across countries. The GID improves on existing data sources by including institutional variables related to social norms, laws, and traditions that influence women's economic roles. It conceptualizes gender inequality as being determined by social institutions, women's access to resources, economic development levels, and their interactions. The GID incorporates a variety of data sources to document these relationships and allow analysis of how changing institutions and development can impact gender equality over time.
The document summarizes the findings of a survey of 818 American workers about their views on the economy and unemployment. Key findings include:
1) American workers have a grim outlook on the economy and labor market, with most expecting continued recession or depression and high unemployment.
2) The recession has had a major financial impact on most Americans, especially the unemployed, with many taking on debt and making lifestyle changes.
3) Americans blame the recession and policies of former presidents Bush and Obama for high unemployment, but few blame the unemployed themselves.
4) Most Americans report that they, family, or friends have lost jobs in the past three years, showing the widespread impact of job losses.
This paper presents new evidence on intergenerational mobility in the top of the income and earnings distribution. Using a large dataset of matched father-son pairs in Sweden, we find that intergenerational transmission is very strong in the top, more so for income than for earnings. In the extreme top (top 0.1 percent) income transmission is remarkable with an IG elasticity above 0.9. We also study potential transmission mechanisms and find that sons’ IQ, non-cognitive skills and education are all unlikely channels in explaining this strong transmission. Within the top percentile, increases in fathers’ income are, if anything, negatively associated with these variables. Wealth, on the other hand, has a significantly positive association. Our results suggest that Sweden, known for having relatively high intergenerational mobility in general, is a society where transmission remains strong in the very top of the distribution and that wealth is the most likely channel.
Realized capital gains are typically disregarded in the study of income inequality. We show that in the case of Sweden this severely underestimates the actual increase in inequality and, in particular, top income shares during recent decades. Using micro panel data to average
incomes over longer periods and re-rank individuals according to income excluding capital gains, we show that capital gains indeed are a reoccurring addition to rather than a transitory component in top incomes. Doing the same for lower income groups, however, makes virtually no difference. We also try to find the roots of the recent surge in capital gains-driven inequality in Sweden since the 1980s. While there are no evident changes in terms of who earns these gains (high wage earners vs. top capital income earners), the primary driver instead seems to be the drastic asset price increases on the post-1980 deregulated financial markets.
Unemployment is a major problem that has negative economic and social impacts. It is caused by factors like lack of capital investment, poverty, increased population, lack of education or skills matching jobs, and political instability. Unemployment leads to issues like decreased production and income, increased crime and health problems. Solutions include creating more job opportunities, encouraging entrepreneurship, expanding trade and industry, improving education, and attracting foreign investment. Governments aim to reduce unemployment but quick action is still needed to address this significant issue.
The growth in high- and low-skill jobs, coupled with little
growth in the middle-skill groups, has changed the composition
of the workforce. The leftmost bars in Chart 3 show the share of
U.S. workers in each skill category in 1980 and 2010. While both high-skill and low-skill job shares increased, the lower-middle skill group’s job share shrank. In 1980, nearly half of all workers were employed in lower-middle-skill occupations. Among the occupations in this group, machine operators accounted for 10 percent of the U.S. workforce and administrative support workers accounted for 18 percent.
2013 MBAA/NAMS presentation, "Transition from Late-Career Displacement to Employability: How Older Knowledge Workers Confront Labor Market Adversity" John F. Fruner, Baker College
The document summarizes the Chief Economist's discussion on rising global anger due to increasing income inequality, high unemployment, soaring commodity prices, and weakening welfare systems. Popular protests in the Arab world and parts of Europe and the US reflect growing frustration with stagnating incomes, wealth concentrated among the wealthy, and a lack of political will to enact reforms that promote inclusive growth. Continued high inequality risks more social unrest worldwide if policymakers do not address its underlying economic causes through measures like improving education and labor markets.
This document introduces the Gender, Institutions and Development (GID) database, which aims to better understand factors influencing gender inequality across countries. The GID improves on existing data sources by including institutional variables related to social norms, laws, and traditions that influence women's economic roles. It conceptualizes gender inequality as being determined by social institutions, women's access to resources, economic development levels, and their interactions. The GID incorporates a variety of data sources to document these relationships and allow analysis of how changing institutions and development can impact gender equality over time.
The document summarizes the findings of a survey of 818 American workers about their views on the economy and unemployment. Key findings include:
1) American workers have a grim outlook on the economy and labor market, with most expecting continued recession or depression and high unemployment.
2) The recession has had a major financial impact on most Americans, especially the unemployed, with many taking on debt and making lifestyle changes.
3) Americans blame the recession and policies of former presidents Bush and Obama for high unemployment, but few blame the unemployed themselves.
4) Most Americans report that they, family, or friends have lost jobs in the past three years, showing the widespread impact of job losses.
This paper presents new evidence on intergenerational mobility in the top of the income and earnings distribution. Using a large dataset of matched father-son pairs in Sweden, we find that intergenerational transmission is very strong in the top, more so for income than for earnings. In the extreme top (top 0.1 percent) income transmission is remarkable with an IG elasticity above 0.9. We also study potential transmission mechanisms and find that sons’ IQ, non-cognitive skills and education are all unlikely channels in explaining this strong transmission. Within the top percentile, increases in fathers’ income are, if anything, negatively associated with these variables. Wealth, on the other hand, has a significantly positive association. Our results suggest that Sweden, known for having relatively high intergenerational mobility in general, is a society where transmission remains strong in the very top of the distribution and that wealth is the most likely channel.
Realized capital gains are typically disregarded in the study of income inequality. We show that in the case of Sweden this severely underestimates the actual increase in inequality and, in particular, top income shares during recent decades. Using micro panel data to average
incomes over longer periods and re-rank individuals according to income excluding capital gains, we show that capital gains indeed are a reoccurring addition to rather than a transitory component in top incomes. Doing the same for lower income groups, however, makes virtually no difference. We also try to find the roots of the recent surge in capital gains-driven inequality in Sweden since the 1980s. While there are no evident changes in terms of who earns these gains (high wage earners vs. top capital income earners), the primary driver instead seems to be the drastic asset price increases on the post-1980 deregulated financial markets.
Unemployment is a major problem that has negative economic and social impacts. It is caused by factors like lack of capital investment, poverty, increased population, lack of education or skills matching jobs, and political instability. Unemployment leads to issues like decreased production and income, increased crime and health problems. Solutions include creating more job opportunities, encouraging entrepreneurship, expanding trade and industry, improving education, and attracting foreign investment. Governments aim to reduce unemployment but quick action is still needed to address this significant issue.
The growth in high- and low-skill jobs, coupled with little
growth in the middle-skill groups, has changed the composition
of the workforce. The leftmost bars in Chart 3 show the share of
U.S. workers in each skill category in 1980 and 2010. While both high-skill and low-skill job shares increased, the lower-middle skill group’s job share shrank. In 1980, nearly half of all workers were employed in lower-middle-skill occupations. Among the occupations in this group, machine operators accounted for 10 percent of the U.S. workforce and administrative support workers accounted for 18 percent.
2013 MBAA/NAMS presentation, "Transition from Late-Career Displacement to Employability: How Older Knowledge Workers Confront Labor Market Adversity" John F. Fruner, Baker College
The document summarizes the Chief Economist's discussion on rising global anger due to increasing income inequality, high unemployment, soaring commodity prices, and weakening welfare systems. Popular protests in the Arab world and parts of Europe and the US reflect growing frustration with stagnating incomes, wealth concentrated among the wealthy, and a lack of political will to enact reforms that promote inclusive growth. Continued high inequality risks more social unrest worldwide if policymakers do not address its underlying economic causes through measures like improving education and labor markets.
We use newly compiled top income share data and structural breaks techniques to estimate common trends and breaks in inequality across countries over the twentieth century. Our results both confirm earlier findings and offer new insights. In particular, the division into an Anglo-Saxon and a Continental European experience is not as clear cut as previously suggested. Some Continental European countries seem to have experienced increases in top income shares, just as Anglo-Saxon countries, but typically with a lag. Most notably, Nordic countries display a marked “Anglo-Saxon” pattern, with sharply increased top income shares especially when including realized capital gains. Our results help inform theories about the causes of the recent rise in inequality.
The Census Bureau, in partnership with other federal and state agencies, produces data on employment and where employees live. The Longitudinal Employer-Household Dynamics program combines administrative data to provide a larger, more detailed data set on employment and workers' trips from home to work. The data derives primarily from unemployment insurance records, so it is important to note that not all jobs are counted. Examples of jobs not counted in this data set include military in uniform, self-employed workers, informally employed people, and postal employees.
This data set is compiled annually, although the latest release is for 2011. The information presented by MVRPC in these maps is based on the workplace, not the worker’s home. These maps are of all jobs, not just an employee’s primary job.
2008-2012 ACS Census Profile for the Miami Valley regionMVRPC
This document provides a summary of data from the 2008-2012 American Community Survey for several regions in Ohio. It includes statistics on educational attainment, housing costs, income levels, employment status, transportation, and poverty by census tract. Maps show levels for these variables compared to regional averages, with census tracts shaded based on being above, below, or not significantly different from averages.
This paper examines how state-level social welfare expenditures influence labor force participation rates. Using data from the 2009 Current Population Survey and state-level data on social program spending, the author estimates regression models to analyze the relationship between per capita social welfare expenditures and individual labor force participation. The initial results find no significant effects of social welfare spending on participation rates. Further analysis is needed to explore differences between demographic groups. The paper aims to provide new insights on how social welfare policy design can impact work incentives.
The document summarizes key aspects of Boston's economy in 2015, including:
- Total employment in Boston reached its highest level in recent decades and unemployment fell to its pre-recession level in early 2015.
- The three industries with the largest employment growth since the recession were health care, professional services, and education.
- Boston's unemployment rate was lower than both the Massachusetts and US rates in 2014, reaching 5.3% for the year.
The document provides demographic, economic, and labor market data for Anderson County. Some key points:
- The county's population decreased slightly from 2010-2015 due mostly to domestic out-migration.
- Educational attainment has increased while the population has gotten older and more diverse.
- The number of establishments increased slightly, with growth in medium-sized businesses. The accommodation/food services industry saw the largest growth.
- The top five industries employ 70% of workers, led by healthcare/social assistance. Construction and accommodation/food saw job gains while transportation lost jobs.
- Office/administrative and sales occupations make up the largest shares of jobs.
REGRESSION ANALYSIS ON HEALTH INSURANCE COVERAGE RATEChaoyi WU
This document describes a study that uses multiple linear regression to model the rate of uninsured population in counties in Georgia. The study finds that the uninsured rate is closely related to demographic factors like age distribution, income levels, employment rates, gender distribution, and citizenship status. Specifically, counties with larger populations aged 18-24, higher median incomes, lower poverty rates, stronger job markets, and more native-born residents tended to have lower uninsured rates. The researchers used principal component analysis to address correlations between employment-related variables before selecting variables and building the regression model.
This document summarizes and discusses various conceptualizations of women's economic empowerment from different development organizations. It notes that while early definitions of empowerment focused more broadly on increasing women's agency, control over resources, and participation in decision making, more recent definitions have increasingly equated women's economic empowerment specifically with their access to paid work and ability to participate in markets. However, definitions differ in whether economic empowerment is seen as an end in itself or a means to broader development goals, and whether market forces alone are seen as sufficient to achieve empowerment or if structural changes are also needed to ensure fair terms of participation and benefits from growth. The document reviews definitions from organizations like the World Bank, UN, OECD, and
RS Working on the Workforce Sept 2019 To PostARCResearch
workforce data for regional plans and grant-funded projects. In this presentation, staff present summary findings from some of the data work done for the Worksource Regional Plan, Metro Atlanta Workforce Exchange (MAX), and National Workforce Fund Economic Mobility Grant (EMG) projects, as well as share plans for further future analysis.
This document provides a summary of demographic, economic, and labor market data for Jefferson County. The population increased slightly between 2000 and 2013, driven primarily by natural growth and domestic migration. The population is aging, with fewer residents of prime working age. Educational attainment improved modestly over this period. The county saw significant growth in the number of establishments between 2000 and 2011, largely through new business formation. The largest industries are manufacturing, government, retail trade, and healthcare, although manufacturing experienced job losses since 2002.
Top industries for women in us – by nailcenter.usNha Huynh
The US labor force has increasingly provided unique opportunities for professional women, and several industries have exemplified this trend. The growing female share of college degrees has benefited women in the workforce. Read more at: http://nailcenter.us/
The document provides an in-depth analysis of the 2009 US job market. It explores the state of the labor market in light of the economic slowdown in 2008 which caused unemployment to rise from 5% to 7% and over 2 million job losses. It examines unemployment rates globally and different industries in the US that were particularly impacted, such as financial services, manufacturing, and construction. It also looks at future job opportunities in areas like healthcare, technology, and green jobs. Overall, the summary analyzes the state of the US job market in 2009 and how the economic crisis transformed the labor landscape.
This presentation will provide, for the start of 2020, an overview of some of the most relevant trends in our metro economy- topics will include trends in gross domestic product for peer metros, job growth by sector, changes in wage levels, trends in residential permitting, and current forecasts.
Economic growth between the epidemic Maltus' idea and political instability f...AI Publications
The objective of this paper is to study the impact of the rate of demographic growth via the the epidemic Maltus' idea on economic growth on the one hand. And on the other hand, we examine the effect of political stability on economic growth. This work follows a methodology describing empirically while using the GMM dynamic panel method on five-year cross-sectional data (2016-2020) for some countries of North Africa and the Middle East.
The document summarizes key findings from a SHRM poll on the ongoing impact of the recession on federal government agencies. It finds that in 2011, half of federal agencies had no layoffs, though financial health has declined compared to 2010. Two-thirds were hiring, primarily to replace lost jobs. Recruiting was difficult for some positions like technical jobs, and the majority had hired veterans for hard-to-fill roles.
This document summarizes an empirical analysis of the relationship between income inequality, education expenditures, human capital, and economic growth. The analysis uses cross-country data from 1980-2004 for 48 countries. The main findings are:
1) Income inequality is found to negatively impact economic growth directly.
2) The negative relationship between inequality and growth can also be explained indirectly through transmission channels like human capital, private education expenditures, and public education expenditures.
3) Private education expenditures appear to be the most important transmission channel, with higher private spending linked to faster growth. Public education spending has a weaker impact on growth.
4) Overall, the analysis suggests income inequality reduces growth both directly and indirectly through human capital
Workers' confidence in having enough money for a comfortable retirement has stabilized at 16% after reaching a record low of 13% in 2009. Fewer workers report saving for retirement and more report having less than $1,000 in savings, indicating retirement preparations are continuing to erode. However, confidence in investing retirement savings wisely has rebounded somewhat among those who have saved. Overall, stabilization of confidence levels follows economic volatility, but long-term financial preparations for retirement remain inadequate for many.
1) Job loss in the automobile manufacturing industry due to economic downturn has affected workers, their families, and local communities. It has influenced factors like economic development, lifestyle, and family relationships.
2) Approximately 5 million jobs have been lost due to the recession since 2007. Unemployment is expected to rise to 10% in 2009 due to downsizing. States like Michigan, Ohio, and Kansas that rely on automobile manufacturing have been hit hard.
3) The study will examine how job loss impacts the economic status and family relationships of automobile workers, and develop data to understand the effects of downsizing on workers and their families.
Pulaski County experienced steady growth in the number of business establishments between 2000 and 2011. The number of establishments increased by 311, or 31%, due entirely to new businesses being launched within the county. By 2011, there were 1,304 total establishments, the majority of which (55%) had between 2-9 employees. Only 2 establishments had over 500 employees. While economic growth has occurred, most businesses in Pulaski County remain small in size.
This document discusses analyzing the gender income gap in Canada using data from the 2011 National Household Survey. It hypothesizes that the gap may be explained by differences in human capital, occupational segregation, and sociological factors. Tables from the survey data show women are underrepresented in high-paying management jobs and have lower incomes than men even with the same education and work in the same industries. The document proposes using an Oaxaca decomposition model to identify how much of the income gap can be explained by differences in individual characteristics versus unexplained discrimination.
This document provides an analysis of trends in the gender wage gap in the US from 2000 to 2010. It finds that before the financial crisis, the wage penalty was higher for lower-paid female workers compared to higher-paid workers, but this trend reversed during the financial crisis as the penalty reduced for lower-paid workers but remained stable for higher-paid workers. The document also reviews several theoretical models that attempt to explain the persistence of a gender wage gap, such as taste-based discrimination and statistical discrimination.
We use newly compiled top income share data and structural breaks techniques to estimate common trends and breaks in inequality across countries over the twentieth century. Our results both confirm earlier findings and offer new insights. In particular, the division into an Anglo-Saxon and a Continental European experience is not as clear cut as previously suggested. Some Continental European countries seem to have experienced increases in top income shares, just as Anglo-Saxon countries, but typically with a lag. Most notably, Nordic countries display a marked “Anglo-Saxon” pattern, with sharply increased top income shares especially when including realized capital gains. Our results help inform theories about the causes of the recent rise in inequality.
The Census Bureau, in partnership with other federal and state agencies, produces data on employment and where employees live. The Longitudinal Employer-Household Dynamics program combines administrative data to provide a larger, more detailed data set on employment and workers' trips from home to work. The data derives primarily from unemployment insurance records, so it is important to note that not all jobs are counted. Examples of jobs not counted in this data set include military in uniform, self-employed workers, informally employed people, and postal employees.
This data set is compiled annually, although the latest release is for 2011. The information presented by MVRPC in these maps is based on the workplace, not the worker’s home. These maps are of all jobs, not just an employee’s primary job.
2008-2012 ACS Census Profile for the Miami Valley regionMVRPC
This document provides a summary of data from the 2008-2012 American Community Survey for several regions in Ohio. It includes statistics on educational attainment, housing costs, income levels, employment status, transportation, and poverty by census tract. Maps show levels for these variables compared to regional averages, with census tracts shaded based on being above, below, or not significantly different from averages.
This paper examines how state-level social welfare expenditures influence labor force participation rates. Using data from the 2009 Current Population Survey and state-level data on social program spending, the author estimates regression models to analyze the relationship between per capita social welfare expenditures and individual labor force participation. The initial results find no significant effects of social welfare spending on participation rates. Further analysis is needed to explore differences between demographic groups. The paper aims to provide new insights on how social welfare policy design can impact work incentives.
The document summarizes key aspects of Boston's economy in 2015, including:
- Total employment in Boston reached its highest level in recent decades and unemployment fell to its pre-recession level in early 2015.
- The three industries with the largest employment growth since the recession were health care, professional services, and education.
- Boston's unemployment rate was lower than both the Massachusetts and US rates in 2014, reaching 5.3% for the year.
The document provides demographic, economic, and labor market data for Anderson County. Some key points:
- The county's population decreased slightly from 2010-2015 due mostly to domestic out-migration.
- Educational attainment has increased while the population has gotten older and more diverse.
- The number of establishments increased slightly, with growth in medium-sized businesses. The accommodation/food services industry saw the largest growth.
- The top five industries employ 70% of workers, led by healthcare/social assistance. Construction and accommodation/food saw job gains while transportation lost jobs.
- Office/administrative and sales occupations make up the largest shares of jobs.
REGRESSION ANALYSIS ON HEALTH INSURANCE COVERAGE RATEChaoyi WU
This document describes a study that uses multiple linear regression to model the rate of uninsured population in counties in Georgia. The study finds that the uninsured rate is closely related to demographic factors like age distribution, income levels, employment rates, gender distribution, and citizenship status. Specifically, counties with larger populations aged 18-24, higher median incomes, lower poverty rates, stronger job markets, and more native-born residents tended to have lower uninsured rates. The researchers used principal component analysis to address correlations between employment-related variables before selecting variables and building the regression model.
This document summarizes and discusses various conceptualizations of women's economic empowerment from different development organizations. It notes that while early definitions of empowerment focused more broadly on increasing women's agency, control over resources, and participation in decision making, more recent definitions have increasingly equated women's economic empowerment specifically with their access to paid work and ability to participate in markets. However, definitions differ in whether economic empowerment is seen as an end in itself or a means to broader development goals, and whether market forces alone are seen as sufficient to achieve empowerment or if structural changes are also needed to ensure fair terms of participation and benefits from growth. The document reviews definitions from organizations like the World Bank, UN, OECD, and
RS Working on the Workforce Sept 2019 To PostARCResearch
workforce data for regional plans and grant-funded projects. In this presentation, staff present summary findings from some of the data work done for the Worksource Regional Plan, Metro Atlanta Workforce Exchange (MAX), and National Workforce Fund Economic Mobility Grant (EMG) projects, as well as share plans for further future analysis.
This document provides a summary of demographic, economic, and labor market data for Jefferson County. The population increased slightly between 2000 and 2013, driven primarily by natural growth and domestic migration. The population is aging, with fewer residents of prime working age. Educational attainment improved modestly over this period. The county saw significant growth in the number of establishments between 2000 and 2011, largely through new business formation. The largest industries are manufacturing, government, retail trade, and healthcare, although manufacturing experienced job losses since 2002.
Top industries for women in us – by nailcenter.usNha Huynh
The US labor force has increasingly provided unique opportunities for professional women, and several industries have exemplified this trend. The growing female share of college degrees has benefited women in the workforce. Read more at: http://nailcenter.us/
The document provides an in-depth analysis of the 2009 US job market. It explores the state of the labor market in light of the economic slowdown in 2008 which caused unemployment to rise from 5% to 7% and over 2 million job losses. It examines unemployment rates globally and different industries in the US that were particularly impacted, such as financial services, manufacturing, and construction. It also looks at future job opportunities in areas like healthcare, technology, and green jobs. Overall, the summary analyzes the state of the US job market in 2009 and how the economic crisis transformed the labor landscape.
This presentation will provide, for the start of 2020, an overview of some of the most relevant trends in our metro economy- topics will include trends in gross domestic product for peer metros, job growth by sector, changes in wage levels, trends in residential permitting, and current forecasts.
Economic growth between the epidemic Maltus' idea and political instability f...AI Publications
The objective of this paper is to study the impact of the rate of demographic growth via the the epidemic Maltus' idea on economic growth on the one hand. And on the other hand, we examine the effect of political stability on economic growth. This work follows a methodology describing empirically while using the GMM dynamic panel method on five-year cross-sectional data (2016-2020) for some countries of North Africa and the Middle East.
The document summarizes key findings from a SHRM poll on the ongoing impact of the recession on federal government agencies. It finds that in 2011, half of federal agencies had no layoffs, though financial health has declined compared to 2010. Two-thirds were hiring, primarily to replace lost jobs. Recruiting was difficult for some positions like technical jobs, and the majority had hired veterans for hard-to-fill roles.
This document summarizes an empirical analysis of the relationship between income inequality, education expenditures, human capital, and economic growth. The analysis uses cross-country data from 1980-2004 for 48 countries. The main findings are:
1) Income inequality is found to negatively impact economic growth directly.
2) The negative relationship between inequality and growth can also be explained indirectly through transmission channels like human capital, private education expenditures, and public education expenditures.
3) Private education expenditures appear to be the most important transmission channel, with higher private spending linked to faster growth. Public education spending has a weaker impact on growth.
4) Overall, the analysis suggests income inequality reduces growth both directly and indirectly through human capital
Workers' confidence in having enough money for a comfortable retirement has stabilized at 16% after reaching a record low of 13% in 2009. Fewer workers report saving for retirement and more report having less than $1,000 in savings, indicating retirement preparations are continuing to erode. However, confidence in investing retirement savings wisely has rebounded somewhat among those who have saved. Overall, stabilization of confidence levels follows economic volatility, but long-term financial preparations for retirement remain inadequate for many.
1) Job loss in the automobile manufacturing industry due to economic downturn has affected workers, their families, and local communities. It has influenced factors like economic development, lifestyle, and family relationships.
2) Approximately 5 million jobs have been lost due to the recession since 2007. Unemployment is expected to rise to 10% in 2009 due to downsizing. States like Michigan, Ohio, and Kansas that rely on automobile manufacturing have been hit hard.
3) The study will examine how job loss impacts the economic status and family relationships of automobile workers, and develop data to understand the effects of downsizing on workers and their families.
Pulaski County experienced steady growth in the number of business establishments between 2000 and 2011. The number of establishments increased by 311, or 31%, due entirely to new businesses being launched within the county. By 2011, there were 1,304 total establishments, the majority of which (55%) had between 2-9 employees. Only 2 establishments had over 500 employees. While economic growth has occurred, most businesses in Pulaski County remain small in size.
This document discusses analyzing the gender income gap in Canada using data from the 2011 National Household Survey. It hypothesizes that the gap may be explained by differences in human capital, occupational segregation, and sociological factors. Tables from the survey data show women are underrepresented in high-paying management jobs and have lower incomes than men even with the same education and work in the same industries. The document proposes using an Oaxaca decomposition model to identify how much of the income gap can be explained by differences in individual characteristics versus unexplained discrimination.
This document provides an analysis of trends in the gender wage gap in the US from 2000 to 2010. It finds that before the financial crisis, the wage penalty was higher for lower-paid female workers compared to higher-paid workers, but this trend reversed during the financial crisis as the penalty reduced for lower-paid workers but remained stable for higher-paid workers. The document also reviews several theoretical models that attempt to explain the persistence of a gender wage gap, such as taste-based discrimination and statistical discrimination.
This document discusses the impact of gender inequality in education and employment on economic growth. It finds that gender gaps in both education and employment considerably reduce economic growth. Specifically:
- Gender gaps in education reduce human capital accumulation and have negative externalities by increasing fertility and lowering education levels of future generations.
- Gender gaps in employment also distort economies and reduce competitiveness by depriving countries of relatively cheap female labor. They can increase fertility and lower economic growth.
- The costs of gender gaps in education and employment in regions like the Middle East and North Africa and South Asia have amounted to 0.1-1.7 percentage points lower annual growth compared to East Asia. While gender gaps in education have large negative effects
Colleen P Cahill Writing Sample Econometrics II Select Pagescolleenpcahill
This paper analyzes how the return to education and the gender wage gap have changed from 2000 to 2010 using data from the Current Population Survey. Regressions are run comparing each year from 2001 to 2010 to 2000. The results show the return to education remained relatively stable over this period, with a slight decrease in 2007. The gender wage gap narrowed significantly from 2000 to 2003 and from 2004 to 2010, indicating women's wages relative to men's have improved over the past decade. Additional regressions controlling for experience and other factors produced similar results.
Gender Pay Gap and Employment Sector Sourcesof Earnings Dis.docxhanneloremccaffery
Gender Pay Gap and Employment Sector: Sources
of Earnings Disparities in the United States, 1970–2010
Hadas Mandel & Moshe Semyonov
Published online: 23 August 2014
# Population Association of America 2014
Abstract Using data from the IPUMS-USA, the present research focuses on trends in
the gender earnings gap in the United States between 1970 and 2010. The major goal of
this article is to understand the sources of the convergence in men’s and women’s
earnings in the public and private sectors as well as the stagnation of this trend in the
new millennium. For this purpose, we delineate temporal changes in the role played by
major sources of the gap. Several components are identified: the portion of the gap
attributed to gender differences in human-capital resources; labor supply;
sociodemographic attributes; occupational segregation; and the unexplained portion
of the gap. The findings reveal a substantial reduction in the gross gender earnings gap
in both sectors of the economy. Most of the decline is attributed to the reduction in the
unexplained portion of the gap, implying a significant decline in economic discrimi-
nation against women. In contrast to discrimination, the role played by human capital
and personal attributes in explaining the gender pay gap is relatively small in both
sectors. Differences between the two sectors are not only in the size and pace of the
reduction but also in the significance of the two major sources of the gap. Working
hours have become the most important factor with respect to gender pay inequality in
both sectors, although much more dominantly in the private sector. The declining
gender segregation may explain the decreased impact of occupations on the gender
pay gap in the private sector. In the public sector, by contrast, gender segregation still
accounts for a substantial portion of the gap. The findings are discussed in light of the
theoretical literature on sources of gender economic inequality and in light of the recent
stagnation of the trend.
Keywords Gender pay gaps . Public sector. Private sector. Gender discrimination
Demography (2014) 51:1597–1618
DOI 10.1007/s13524-014-0320-y
Electronic supplementary material The online version of this article (doi:10.1007/s13524-014-0320-y)
contains supplementary material, which is available to authorized users.
H. Mandel (*): M. Semyonov
Department of Sociology and Anthropology, Tel-Aviv University, Tel-Aviv, Israel 69978
e-mail: [email protected]
http://dx.doi.org/10.1007/s13524-014-0320-y
Thesis statement
The purpose of this paper is to share research and inform scholars.
Introduction
One of the most significant social changes in recent decades has been the changing
economic status of women. Since the middle of the twentieth century, women have not
only joined the economically active labor force in ever-increasing numbers but also
enhanced their education and improved their occupational status and economic re-
wards. More specifically, during ...
On 26 November 2020, Ms Libby Lyons, CEO of Workplace Gender Equality Agency released *Australia’s Gender Equality Scorecard showing employers action on gender equality had stalled. Libby recently spoke to Omesh Jethwani, Government Projects & Programs Manager.
Women Leading Growth: An Empirical Analysis on the Effects of Women in Leader...Avril Espinosa-Malpica
UBC Economics 490: Seminar In Applied Economics Research Essay
250 years ago the wealthiest country was at most four times richer than the poorest country. Today the richest country is almost 100 times richer than the poorest. In this seminar, I tried to answer this question: Why have some countries grown so quickly over the long run while others have stagnated? To answer this, I focused on understanding and interpreting the effects of women in leadership positions on GDP through economics.
This document discusses the relationship between women's empowerment and economic development. It argues that empowering women can accelerate economic development in two ways: 1) Reducing poverty and inequality empowers women and improves economic outcomes for everyone, and 2) Continuing discrimination against women can hinder development. The document then reviews evidence showing how increasing women's income, education, and rights correlates with better child nutrition, health, and anthropometric outcomes. It also examines how women's empowerment relates to poverty reduction, labor force participation, and economic growth. The conclusion is that empowering women through education plays a major role in developing countries like India by reducing poverty and improving economic growth.
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DETERMINANTS OF FEMALE LABOUR FORCE PARTICIPATION IN FAM AND NON FARM LIVELIH...Hudu Zakaria
This document summarizes a study that examined determinants of female labor participation in farm and non-farm livelihood enterprises in northern Ghana. The study used survey data from over 13,000 individuals in northern Ghana to analyze gender differences in labor participation. Chi-square analysis found significant gender disparities in participation in crop production, livestock, non-farm self-employment, and paid work. Probit regression identified location, household status, marital status, literacy, participation in decision making, income, and control over resources as significant determinants of female participation in farm and non-farm enterprises and paid work. The study recommends empowering females through education, decision making, and control over resources to facilitate their participation.
The document summarizes key findings from India's latest employment data from 2009-2010:
- There was hardly any increase in overall employment between 2004-2005 and 2009-2010, despite high GDP growth, indicating nearly jobless growth.
- The labor force participation rate declined significantly, especially for women, both in rural and urban areas, which cannot be fully explained by higher education enrollment.
- Unemployment rates decreased due to many, especially women, withdrawing from the labor force rather than lack of job opportunities.
- Self-employment declined while casual labor increased, especially in rural areas. Real wages increased across worker categories.
However, declining agriculture employment was not matched by increasing manufacturing jobs,
This document discusses a study that aimed to assess the determinants of poverty in Mkinga District, Tanzania. The study found that nearly 93% of respondents in the area were poor. Using an ordinal regression model and data from 210 households, the study identified several factors associated with poverty in the area, including gender (with women more affected), smaller land size, smaller farm size, larger household size, and higher dependency ratio. The study recommends empowering people, especially women, to participate in economic activities using local resources to alleviate poverty in the district.
MentoringA Key Success Factor for African American WomeAbramMartino96
This document summarizes a study on mentoring as a key success factor for African American women in the U.S. Federal Senior Executive Service. It provides background on underrepresentation of minorities and women in the SES. It reviews literature finding that mentors can boost career potential and discusses challenges faced by African American women such as glass ceilings and concrete ceilings. The purpose is to analyze views of African American women in the SES and developmental grades on success factors. Mentoring is identified as a potential key success factor.
Off-farm employment in rural areas can be a major contributor to rural poverty reduction and decent rural employment. While women are highly active in the agricultural sector, they are less active than men in off-farm employment. This study analyzes the determinants of participation in off-farm employment of women in rural Uganda. The study is based on a field survey conducted in nine districts with the sample size of 1200 individual females. A two-stage Hechman’s sample selection model was applied to capture women’s decision to participate and the level of participation in non-farm economic activities. Summary statistics of the survey data from rural Uganda shows that: i) poverty and non-farm employment has a strong correlation, implying the importance of non-farm employment as a means for poverty reduction; and ii) there is a large gender gap to access non-farm employment, but the gender gap has been significantly reduced from group of older age to younger generation. The econometric results finds that the following factors have a significant influence on women’s participation in off-farm employment: education level of both the individual and household head (positive in both stages); women’s age (negative in both stages); female-headed household (negative in first stage); household head of polygamous marriage (negative in both stages); distance from major town (negative in the first stage); household size (positive in the second stage); dependency ratio (negative in the second stage); access to and use of government extension services (positive in the first stage); access to and use of an agricultural loan (negative in the second stage); and various district dummies variables. The implications of these findings suggest that those policies aimed at enhancing the identified determinants of women off-farm employment can promote income-generating opportunities for women groups in comparable contexts. In order to capitalize on these positive linkages, policies should be designed to improve skills and knowledge by providing education opportunities and increasing access to employment training, assistance services and loans for non-farm activities and by targeting women in female-headed, large and distant households. The government should increase investments in public infrastructure and services, such as roads, telecommunications and emergency support.
Tutkimuksessa tarkastellaan Suomen huipputuloja sukupuolinäkökulmasta. Tutkimuksessa havaitaan, että naiset ovat aliedustettuina tulojakauman huipulla ja naisten osuus huipputuloissa on ollut pitkälti muuttumatonta lukuun ottamatta ylintä yhtä prosenttia. Ylimmässä yhdessä prosentissa naisten osuus on kasvanut 18 vuoden aikana tasaisesti. Naisten palkkatulojen osuus kokonaistulosta on kasvanut samalla kun yrittäjätulojen osuus on laskenut. Tutkimuksessa havaitaan myös, että tuloerot naisten välillä ovat pienemmät kuin miesten välillä. Naiset ovat saavuttaneet miesten tulohuippua mutta tutkimuksessa havaitaan myös, että naisten tuloliikkuvuus huipulta alaspäin on yleisempää kuin miehillä.
This document summarizes a paper on the relationship between women's empowerment and economic development. It discusses two directions of influence: 1) Development alone can help reduce gender inequality by reducing poverty and increasing opportunities. However, it is not enough to achieve full equality and policy action is still needed. 2) Empowering women can stimulate further development by changing societies' choices, though this relationship is not always self-sustaining and requires continuous policy support. The paper reviews evidence on both sides of this relationship and argues the impacts are likely too weak to be self-reinforcing without sustained gender equality policies.
Population dynamics and economic growth in sub saharan africaAlexander Decker
This document summarizes a study that examines the effects of population dynamics (mortality and fertility rates) on economic growth in sub-Saharan Africa from 1970 to 2005. The study uses pooled OLS and dynamic panel data analysis on data from 35 sub-Saharan African countries. The results show that higher total fertility rates had a negative impact on economic growth, while higher life expectancy at birth had a positive influence on economic growth. The region needs to address its high population growth to achieve sustainable economic development.
Assessment on economic growth of development indicators in aseanAlexander Decker
1) The document analyzes the relationship between economic growth and development indicators like mortality rate, life expectancy, and unemployment rate in 5 ASEAN countries from 1980 to 2010 using panel data analysis.
2) It reviews literature showing economic growth is linked to lower unemployment through Okun's Law and increased income is associated with lower mortality rates.
3) The study aims to determine if there is a long-term relationship between economic growth and the selected development indicators in ASEAN countries, as predicted by economic theory.
2Running head ANALYZING THE WEALTH Analyzing the .docxrhetttrevannion
2
Running head: ANALYZING THE WEALTH
Analyzing the Wealth Gap among Economic Classes
Bruce Xu
University of Miami
Introduction
The wealth gap, the increasing concentration of wealth in fewer hands, has been called the “defining challenge of our time”(Buttrick and Oishi, 2017). In Hero and Levy’s article(2016), it is also called “the great divergence of America’s rich from its middle class and poor.” In fact, the “mordern” wealth inequality can be traced to the evolution of human survival from foraging to farming more than 10,000 years ago (Patel and Bagchi, 2018). For the United States, its origin was in the early of the 20th century. According to David and Jonathan(2016), the wealth inequality began a long but modest decline since 1929. However, this trajectory reversed throughout the industrialized world during the last 40 years (Buttrick and Oishi, 2017).
Wealth inequality occurs in countries among different kinds of people. This paper discusses the wealth inequality between different classes of people in America. Especially, it analyzes wealth gap between the citizens from middle class and lower class. The middle class of the U.S. are those earning between two-thirds and double the median household income. This means that the category of middle – income is made up of people making somewhere between $40,500 and $122,000, which represents the majority of the American. Those who do not participate in the labor force and rely on public assistance as their main source of income are commonly identified as members of the lower class.This paper provides a literature review on wealth inequality. What’s more, it will examine three themes based on the topic, which are the elements and factors lead to the wealth inequality, the negative impact of the wealth gap in the U.S. on the resident’s life and the possible solutions of this phenomenon.
Literature Review
Elements and factors lead to wealth inequality
Nowadays, wealth inequality has become a national even world –wide problem. Probably most people’s comprehension on the causes of wealth inequality is the wage inequality which is unequal distribution of income. In fact, there are still many other factors lead to wealth inequality. Dirlam (2016) concludes that the reduction of employment in manufacturing had influential effects on wealth inequality. Also, Dirlam (2016) states that the increased differences between management’s and labor’s political resources combine to produce a growth in income inequality. Since 1981, the neoliberal political departure has begun. Those intensely neoliberal national administrations were sympathetic to employers and unfavorable to labor take office. Thus, the reduction in union strength reduced a core labor political resource, which lead to wealth inequality.
Moreover, McKernan (2013) thought the gifts and inheritances play a further role in perpetuating the wealth gap. For higher wealth family, they are able to sent their children to high-quality education.
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Report on Income Earning Gap between Men and Women (2006 - 2012)
1. Report on Income Earning
Gap between Men and
Women (2006 – 2012)
By: Monika E. Sosnowska
February 1, 2013
2. INCOME EARNING GAP BETWEEN MEN AND WOMEN (2006-2012) 2
Overview conclusion without critically analyzing the
existing statistical data, thus having a biased
The research conducted for this report outlook on the topic at hand. It’s a well-known
consisted of most recent Statistics Canada fact that over many generations in the 20th
publications, Statistics Canada CANSIM century, on average, a woman earned
database tables, peer-review sources and substantially less than a man, in part due to the
newspaper articles. All of the sources were social structure of the Canadian society.
obtained electronically; the majority located However, is the income gap still evident in the
through Statistics Canada webpage or through twenty-first century? Furthermore, do variables
the SFU Library (online). All consulted sources such as education, labour choices and family
are listed in the reference list, whereas the responsibilities correlate in any way to the
sources that were employed to support the differences in earnings between the sexes? This
findings are referred to and cited throughout the report will critically analyze the existing
report. Appendices referred to in the body of the scientific data in order to provide an answer to
report follow the reference list and are positioned these two questions.
according to the citation order in the text for easy
reference. Discussion of Major Statistics Canada
Publications
Introduction
Statistics Canada publications were an
The objective of this report is to provide important component in comprehension and
the reader with an improved understanding of the support of the statistics found in the CANSIM
earning gap between men and women in Canada. database and Summary Tables referred to
The research draws on numerous sources, throughout the text. Although a number of
including Statistics Canada publications, publications contributed to an overall
CANSIM database, peer-reviewed and understanding of the topic, not all were
newspaper articles and critically analyzes income employed. Job-education match and mismatch:
trends observed over the last six years. The Wage differential, by Jennifer Yuen, for
analysis should demonstrate either narrowed or instance, supported the information found in
expanded gender wage gap and consider the other newer Statistics Canada publications, thus
correlation between numerous variables wasn’t referred to in the body of the report.
including education, family characteristics and The three publications referred to, closely
labour choices. This preliminary report will supported and simplified the statistical
allow readers to better comprehend the trends information. Why has the gender wage gap
observed over the last few years and encourage narrowed? by Marie Drolet provided a depth of
further critical analysis of social trends in information that closely related to this report and
Canada. was a significant contributor and supporter of the
tables found in the appendices. Drolet discussed
Research Question
the growth of women’s wages, education and age
The earning gap between men and contributors and possible factors behind the final
women is a well-known topic amongst outcomes. Xuelin Zhang’s Earnings of women
Canadians, who often establish their own with and without children utilized statistical
February 15, 2013 Monika E. Sosnowska
3. INCOME EARNING GAP BETWEEN MEN AND WOMEN (2006-2012) 3
information to prove that women with children percentage of women in the lower income
earn substantially less, especially women who brackets declined whilst the percentage of men
have three or more children. The report earning above $35,000 declined (Appendix A
simplified the CANSIM data by utilizing charts Table 3).
and providing a simplified breakdown of the An indicator that women are earning
numbers. Unionization by Sharanjit Uppal, more is their increased representation among the
although not directly related to gender gap top 1 percent of tax filers in Canada. According
discussion, did examine recent union to Beltrame (2013), 21 per cent of women were
membership trends of men and women, among the wealthiest, an increase of 10
consequently providing a positive correlation percentage points between 1982 and 2010. More
between job choices and income for both men recently, women saw an increase in
and women. Collectively, these publications representation from 20.3 to 20.9 per cent
provided a larger comprehension of the statistics between 2008 and 2010. In contrast, the
and the topic itself and thus, significantly percentage of men decreased from 79.7 to 79.1
simplified the data that was generated from (see Appendix A Table 5)
Statistics Canada website. In regards to labour characteristics,
overall participation in labour force slightly
Findings declined between 2008 and 2010. Male
participation declined by 3.9 percentage points
According to Cool (2008), in 2008
whereas women saw a decline of 2.9 percentage
women employed full-year full-time (FYFT) on
points (Appendix B Table 1). A closer
average earned 71% of their male counterparts
comparison between Appendix B Table 1 and
income. Appendix A Table 1 shows a further 2.5
Table 2, which refer to same variables but in
percentage point decrease in gender income gap
different years, shows that labour force
between 2008 and 2010. Actually, between 2001
participation declined 2.5 percentage points for
and 2010 men experienced a slower wage
men and 1.9 percentage points for women
increase compared to women (Fortin et al.,
between 2010 and 2012. Women’s participation
2012). Figures show that during that time the
in FYFT careers has seen a steady increase
average wage for women increased by 12.4 per
between 2006 and 2010. As seen in Appendix B
cent whereas it increased a modest 2.65 per cent
Table 3, in 2006, men outnumbered women by
for men (see Appendix A Table 2). The data in
1,475,000 in the FYFT category but years 2006
Table 2 indicates that the gender wage gap is
to 2010 showed a decrease of 310,000 male
gradually decreasing. Appendix A Table 3
participants and an increase of 117,000 in
demonstrates the trends in income generation for
women participants. By 2010 men outnumbered
both sexes between 2006 and 2010. Women and
women by 1,057,000, a decrease of about 28.3
men were similarly represented in incomes
per cent from the 2006 figures. Furthermore, the
below $59,999, and while men outnumbered
estimated amount of FYFT workers decreased
women in the $60,000 and above income
both for men and women between 2008 and
bracket, between 2008 and 2010 the
2009, which could reflect the loss of jobs during
representation of women in higher incomes
the economic downturn of 2008, but the number
increased by half a percentage point whereas the
of women working FYFT has since recovered,
representation of men decreased. Recently, the
February 15, 2013 Monika E. Sosnowska
4. INCOME EARNING GAP BETWEEN MEN AND WOMEN (2006-2012) 4
the opposite is true for men (Appendix B Table Career choices may contribute to the
3). narrowing gender gap. Conventionally, women
According to Cool (2008), in 2008 36.5 were more likely to earn an income in lower-
per cent of women, compared to 24.1 per cent of paying retail or administrative jobs (Cool, 2008)
men completed university education. Appendix than higher-paying manufacturing and
C Table 1 demonstrates that when equally construction sectors chosen by men (Drolet,
educated, men are more likely than women to be 2011). This trend started to change as women are
employed; however the gap narrows with the increasingly seeking higher-paying careers in
attainment of education. When comparing education and health (Drolet, 2011). Appendix D
education with employment between men and Table 1 breaks down the employment by sector
women ages 25 to 44, the group who completed for men and women, and shows that in 2012,
some secondary education saw a significant women had a higher representation in service-
difference in employment numbers. In that producing sectors such as educational services,
group, three-quarters of men were employed, in health care and social assistance, whereas men
comparison to just over a half of women. Men largely outnumbered women in goods producing
and women in the same age group who sector, especially in construction and
completed high school were slightly closer in manufacturing. Cool (2008) declares that
employment numbers, with 84.5 per cent of men unionized workers on average earn more than
and 68.6 per cent of women employed. With other non-unionized employees. Many of the
those who completed post-secondary sectors that predominantly employ women are
certification, diploma or bachelor’s degree the unionized, including education and health and
employment gap was in single digits and finally, thus, women’s average salaries may increase. In
was very minimal between men and women who contrast, according to Cool (2008), Canada
attained higher university education. Therefore recently saw a reduction of unionized jobs in
as women continue to pursue university manufacturing. According to Uppal (2011), in
education, they are more likely to be employed at 2010 more women than men were in unionized
a similar rate to men. Furthermore, education jobs, 30.8 and 28.2 per cent respectively.
attainment studies indicate that the gender Between 2000 and 2008, unionization rates
income gap also narrows with educated continued to fall for men but remained steady for
individuals (Cool, 2008). This trend is observed women. Thus, the prominence of women in
in Appendix C Table 2 which illustrates that as unionized jobs could be positively correlated
women become more educated, the income gap with lessening the earning gap between men and
between men and women decreases. Because women.
women in 2008 continued to outnumber men in According to Zhang (2009), mothers with
pursue of education (Drolet, 2011), if the higher three or more children make 20 per cent less than
education can be positively correlated to higher childless women. Many mothers continue to
income and if the trend of more women than men balance their work and home life and pursue jobs
attaining higher education, then gender that permit them more flexibility (Cool, 2008).
employment and income gap may decline further Appendix E Table 1 shows that women were, in
over the upcoming decades. fact, more likely than men to work part-time in
order to care for children. Of all part-time
February 15, 2013 Monika E. Sosnowska
5. INCOME EARNING GAP BETWEEN MEN AND WOMEN (2006-2012) 5
working women, 34.1 per cent stated that the Statistics Canada tables were employed to
reason for their lower working hours is due to comprehend the correlations associated with this
child rearing responsibilities. Only 2.1 per cent trend. It can be stated that women’s education
of men assert the same. According to Toronto- positively correlated with lowering wage gap, as
Dominion Bank, the differences in income does a choice of career, especially if the
between men and women is largely tied to workplace is represented by a union. Family
motherhood (Grant, 2010). The fact that many characteristics correlate negatively with income
women limit their working hours to take care of and wage gap between men and women,
children would contribute to the overall gender especially larger families with three or more
income gap as men are more likely to work full- children. The negative correlation in this case
time than women and thus earn larger incomes. could be attributed to the number of hours a
woman spends at work as mothers are more
Conclusion likely than fathers to work part-time. Overall,
over the last few years, women saw a significant
The statistical research conducted found
decrease in the gender wage gap.
that the gender income gap in Canada continued
to decrease between 2006 and 2012. Several
February 15, 2013 Monika E. Sosnowska
6. INCOME EARNING GAP BETWEEN MEN AND WOMEN (2006-2012) 6
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=1110011&paSer=&pattern=&stByVal=1&p1=1&p2=-1&tabMode=dataTable&csid
Statistics Canada. (2012 June, 27). Table 111-0018 Family characteristics, labour characteristics, by sex
and age group, Annual (table). CANSIM (database). Retrieved January 28, 2013, from
http://www5.statcan.gc.ca/cansim/a26?lang=eng&retrLang=eng&id=1110018&paSer=&pattern=
&stByVal=1&p1=1&p2=-1&tabMode=dataTable&csid
Statistics Canada. (2012, June 27). Table 111-0021 Family characteristics, husband-wife families, by
wife's contribution to husband-wife employment income, Annual (table). CANSIM (database).
February 15, 2013 Monika E. Sosnowska
8. INCOME EARNING GAP BETWEEN MEN AND WOMEN (2006-2012) 8
Retrieved January 28, 2013, from http://www5.statcan.gc.ca/cansim/a26?lang=eng&retrLang
=eng&id=1110021&paSer=&pattern=&stByVal=1&p1=1&p2=-1&tabMode=dataTable&csid
Statistics Canada. (2013, January 4). Employment by industry and sex (table). Summary Tables.
Retrieved January 27, 2013, from http://www.statcan.gc.ca/tables-tableaux/sum-
som/l01/cst01/labor10b-eng.htm
Statistics Canada. (2013, January 4). Labour force characteristics by age and sex (table). Summary Tables.
Retrieved January 28, 2013, from http://www.statcan.gc.ca/tables-tableaux/sum-
som/l01/cst01/labor20b-eng.htm
Statistics Canada. (2013, January 4). People employed, by educational attainment (table). Summary
Tables. Retrieved January 28, 2013, from http://www.statcan.gc.ca/tables-tableaux/sum-
som/l01/cst01/labor62-eng.htm
Statistics Canada. (2013, January 4). Reasons for part-time work by sex and age group (table). Summary
Tables. Retrieved January 28, 2013, from http://www.statcan.gc.ca/tables-tableaux/sum-
som/l01/cst01/labor63b-eng.htm
Statistics Canada. (2013, January 28). Table 204-0001 High income trends of tax filers in Canada,
provinces, territories and census metropolitan areas (CMA), national thresholds, Annual
(table).CANSIM (database). Retrieved January 30, 2013, from http://www5.stat
can.gc.ca/cansim/a26?lang=eng&retrLang=eng&id=2040001&paSer=&pattern=&stByVal=1&p1
=1&p2=-1&tabMode=dataTable&csid
Turcotte, Martin. (2011, August 24). Intergenerational education mobility: University completion in
relation to parents’ education level. Canadian Social Trends. No. 92. March. Statistics Canada
Catalogue no. 11-008-XWE. Retrieved from http://www.statcan.gc.ca/pub/11-008-
x/2011002/article/11536-eng.pdf
Uppal, Sharanjit. (2011, October, 26). Unionization 2011. Perspectives on Labour and Income. Autumn
2011, vol. 23, no. 4. Statistics Canada Catalogue no. 75-001-XIE.
Retrieved from http://www.statcan.gc.ca/pub/75-001-x/2011004/article/11579-eng.pdf
Yuen, Jennifer. (2010, April). Job–education match and mismatch: Wage differentials. Perspectives on
Labour and Income. Vol. 11, no. 4. April. Statistics Canada Catalogue no. 75-001-XIE. Retrieved
from http://www.statcan.gc.ca/pub/75-001-x/2010104/pdf/11149-eng.pdf
Zhang, Xuelin. (2009, March). Earnings of women with and without children. Perspectives on Labour
and Income. Vol. 10, no. 3. March. Statistics Canada Catalogue no. 75-001-XIE. Retrieved from
http://www.statcan.gc.ca/pub/75-001-x/2009103/pdf/10823-eng.pdf
February 15, 2013 Monika E. Sosnowska
9. INCOME EARNING GAP BETWEEN MEN AND WOMEN (2006-2012) 9
APPENDIX A
Table 1
Average female and male earnings, and female-to-male earnings ratio, by work activity,
2010 constant dollars
Earnings Work activity 2006 2007 2008 2009 2010
Median earnings, females (dollars) All earners 22,400A 23,000A 23,200A 23,700A 23,900A
Full-year full-time 38,100A 38,500A 39,400A 40,700A 40,900A
workers
Other workers 9,800B 10,000B 10,200B 10,000B 10,400B
Median earnings, males (dollars) All earners 35,400A 35,900A 37,000A 35,100A 35,000A
Full-year full-time 50,500A 51,900A 51,800A 52,000A 52,700A
workers
Other workers 10,800B 10,800B 11,700B 11,500B 11,500B
Female-to-male median earnings All earners 63.3A 64.1A 62.8B 67.6B 68.2B
ratio (percent) Full-year full-time 75.5A 74.2A 76.0A 78.2A 77.6A
workers
Other workers 90.5B 92.1C 87.5C 86.7C 89.9C
Earnings Work activity 2006 2007 2008 2009 2010
Average earnings, females All earners 29,600A 30,400A 30,800A 31,600A 31,700A
(dollars) Full-year full-time 44,100 A
44,900 A
45,500 A
47,300 A
47,300A
workers
Other workers 15,200A 15,800A 15,500A 15,400A 15,700B
Average earnings, males (dollars) All earners 45,800A 46,500A 47,900A 46,100A 46,500A
Full-year full-time 61,300A 63,100A 64,000A 63,500A 64,200A
workers
Other workers 19,700B 19,800B 20,500B 20,200B 20,100B
Female-to-male average earnings All earners 64.7A 65.5B 64.3A 68.6A 68.1A
ratio (percent) Full-year full-time 71.9B 71.2B 71.1B 74.4B 73.6B
workers
Other workers 77.1B 79.6B 75.7B 76.4B 78.2C
Source: Statistics Canada. Table 202-0102
February 15, 2013 Monika E. Sosnowska
10. INCOME EARNING GAP BETWEEN MEN AND WOMEN (2006-2012) 10
Table 2
Average earnings by sex and work pattern
All earners
Women Men Earnings ratio
$ constant 2010 %
2001 28,200 45,300 62.1
2002 28,500 45,400 62.8
2003 28,100 44,700 62.9
2004 28,500 44,900 63.5
2005 29,200 45,600 64.0
2006 29,600 45,800 64.7
2007 30,400 46,500 65.5
2008 30,800 47,900 64.3
2009 31,600 46,100 68.6
2010 31,700 46,500 68.1
Note: Data before 1996 are drawn from Survey of Consumer Finances (SCF) and data since 1996 are taken
from the Survey of Labour and Income Dynamics (SLID). The surveys use different definitions, and as a
result the number of people working full-year full-time in the SLID is smaller than in the SCF.
Source: Statistics Canada, CANSIM, table 202-0102
February 15, 2013 Monika E. Sosnowska
11. INCOME EARNING GAP BETWEEN MEN AND WOMEN (2006-2012) 11
Table 3
Distribution of earnings, by sex, 2010 constant dollars
Sex Earnings group 2006 2007 2008 2009 2010
Males Median earnings (dollars) 35,400A 35,900A 37,000A 35,100A 35,000A
Median total income (dollars) 41,000A 41,200A 41,800A 40,900A 41,500A
Number of all earners (x 1,000) 10,005A 10,169A 10,277A 10,228A 10,353A
Median earnings of full-year full- 50,500A 51,900A 51,800A 52,000A 52,700A
time workers (dollars)
Number of full-year full-time 5,258A 5,329A 5,517A 5,065A 4,957A
workers (x 1,000)
Percentage under $5,000 12.7B 12.3B 11.6B 12.9B 13.2B
$5,000 to $9,999 (percent) 7.9B 8.0B 7.5B 7.6B 7.5B
$10,000 to $14,999 (percent) 6.6B 6.5B 6.5B 7.0B 7.1C
$15,000 to $19,999 (percent) 5.8B 5.7C 5.3C 6.2B 5.9C
$20,000 to $24,999 (percent) 5.3C 5.3B 5.5C 5.5C 5.7C
$25,000 to $29,999 (percent) 5.5C 5.7B 5.3C 5.3C 5.0C
$30,000 to $34,999 (percent) 5.7B 5.5C 5.7C 5.4C 5.4C
$35,000 to $39,999 (percent) 5.3B 5.6B 5.6C 5.4C 5.2C
$40,000 to $44,999 (percent) 5.5B 5.1B 5.4C 4.8C 4.8C
$45,000 to $49,999 (percent) 4.7C 4.6C 4.5C 4.7C 4.3C
$50,000 to $59,999 (percent) 8.0B 8.5B 8.6B 8.1B 8.2B
$60,000 and over (percent) 26.9A 27.2A 28.3A 27.2A 27.8A
Females Median earnings (dollars) 22,400A 23,000A 23,200A 23,700A 23,900A
Median total income (dollars) 28,700A 29,400A 29,800A 30,700A 30,800A
Number of all earners (x 1,000) 8,832A 9,061A 9,176A 9,223A 9,340A
Median earnings of full-year full- 38,100A 38,500A 39,400A 40,700A 40,900A
time workers (dollars)
Number of full-year full-time 3,783A 3,914A 4,043A 3,824A 3,900A
workers (x 1,000)
Percentage under $5,000 16.5B 15.8B 15.4B 15.9B 15.7B
$5,000 to $9,999 (percent) 12.0B 11.7B 11.8B 11.3B 11.0B
$10,000 to $14,999 (percent) 9.5B 10.0B 9.6B 9.6B 9.9B
$15,000 to $19,999 (percent) 8.3B 8.1B 8.1B 7.5B 7.8B
$20,000 to $24,999 (percent) 7.5B 7.2B 7.4B 7.3B 7.3B
$25,000 to $29,999 (percent) 6.4B 7.1C 6.6B 6.1C 6.6B
$30,000 to $34,999 (percent) 6.8B 6.3B 6.2C 6.1C 6.0C
$35,000 to $39,999 (percent) 5.7B 5.8B 6.0B 6.2B 5.9C
$40,000 to $44,999 (percent) 5.1C 5.4B 5.1C 4.9C 5.5C
$45,000 to $49,999 (percent) 4.2C 4.1C 4.4C 4.3C 4.4C
$50,000 to $59,999 (percent) 6.6B 6.3B 6.3B 7.0B 6.5B
$60,000 and over (percent) 11.4B 12.3B 13.1B 13.8B 13.6B
Source: Statistics Canada, CANSIM, table 202-0101
February 15, 2013 Monika E. Sosnowska
12. INCOME EARNING GAP BETWEEN MEN AND WOMEN (2006-2012) 12
Table 4
High income trends of tax filers in Canada, provinces, territories and census metropolitan
areas (CMA), national thresholds
Income concepts=Total income
Income groups Statistics 2008 2009 2010
Top 1 percent income Threshold value (current dollars) 202,600 198,000 201,400
group Number of tax filers (persons) 249,755 252,300 254,730
Percentage, males 79.7 79.2 79.1
Percentage, females 20.3 20.8 20.9
Percentage married or in common-law 82.8 82.8 82.7
relationship
Percentage married or in common-law 86.7 86.8 86.7
relationship, males
Percentage married or in common-law 67.7 67.8 67.7
relationship, females
Median age (years) 51 51 51
Median income (current dollars) 291,000 278,700 283,400
Average income (current dollars) 461,800 424,900 429,600
Share of income 11.5 10.7 10.6
Share of income, males 9.5 8.7 8.7
Share of income, females 2.0 1.9 1.9
Percentage of income from wages and 63.8 62.4 63.9
salaries
Percentage of income from wages and 67.1 65.6 66.9
salaries, males
Percentage of income from wages and 48.0 47.8 50.2
salaries, females
Percentage in the same quantile last year 72.1 71.3 72.1
Percentage in the same quantile five years 52.5 52.7 52.7
ago
Bottom 99 percent Threshold value (current dollars) 202,600 198,000 201,400
income group Number of tax filers (persons) 24,725,060 24,976,58 25,217,1
5 45
Percentage, males 47.8 47.7 47.7
Percentage, females 52.2 52.3 52.3
Percentage married or in common-law 56.7 56.9 56.9
relationship
Percentage married or in common-law 59.0 59.2 59.2
relationship, males
Percentage married or in common-law 54.6 54.8 54.8
relationship, females
Median age (years) 46 46 47
Median income (current dollars) 28,100 28,000 28,400
Average income (current dollars) 36,000 35,900 36,600
Share of income 88.5 89.3 89.4
Share of income, males 50.1 49.9 49.9
Share of income, females 38.4 39.4 39.5
Percentage of income from wages and 69.6 68.5 68.4
salaries
Percentage of income from wages and 72.7 71.1 71.3
salaries, males
Percentage of income from wages and 65.5 65.1 64.7
salaries, females
Percentage in the same quantile last year 99.7 99.7 99.7
Percentage in the same quantile five years 99.6 99.6 99.5
ago
Source: Statistics Canada, CANSIM, table 204-001
February 15, 2013 Monika E. Sosnowska
13. INCOME EARNING GAP BETWEEN MEN AND WOMEN (2006-2012) 13
APPENDIX B
Table 1
Family characteristics, labour characteristics, by sex and age group
Age group=All age groups
Sex Labour characteristics 2008 2009 2010
Both sexes Total labour income 18,516,390 18,514,640 18,579,750
Labour participation rate (rate) 70.0 69.2 68.8
Males Total labour income 9,583,680 9,564,930 9,597,260
Labour participation rate (rate) 75.2 74.3 73.8
Females Total labour income 8,932,710 8,949,710 8,982,480
Labour participation rate (rate) 65.1 64.5 64.1
Source: Statistics Canada, CANSIM, table 111-0018
February 15, 2013 Monika E. Sosnowska
14. INCOME EARNING GAP BETWEEN MEN AND WOMEN (2006-2012) 14
Table 2
Labour force characteristics by age and sex (2012)
Unemployment rate Participation rate Employment rate
%
Both sexes 7.2 66.7 61.8
15 to 24 years 14.3 63.6 54.5
15 to 19 years 20.1 49.5 39.6
20 to 24 years 11.0 76.1 67.7
25 years and older 6.0 67.2 63.2
25 to 44 years 6.3 87.1 81.6
25 to 34 years 6.9 86.3 80.4
35 to 44 years 5.6 87.9 82.9
45 to 64 years 5.8 75.7 71.3
45 to 54 years 5.6 85.7 80.9
55 to 64 years 6.3 63.8 59.8
65 years and older 4.6 12.6 12.0
55 years and older 6.0 36.9 34.7
Unemployment rate Participation rate Employment rate
Males 7.7 71.3 65.8
15 to 24 years 15.9 63.5 53.4
15 to 19 years 22.0 48.3 37.7
20 to 24 years 12.5 77.1 67.4
25 years and older 6.3 72.8 68.3
25 to 44 years 6.4 92.0 86.1
25 to 34 years 7.5 91.2 84.4
35 to 44 years 5.4 92.8 87.8
45 to 64 years 6.2 80.0 75.0
45 to 54 years 6.0 88.8 83.5
55 to 64 years 6.7 69.3 64.7
65 years and older 4.7 17.1 16.3
55 years and older 6.3 42.9 40.2
Unemployment rate Participation rate Employment rate
Females 6.8 62.2 57.9
15 to 24 years 12.6 63.6 55.6
15 to 19 years 18.2 50.8 41.6
20 to 24 years 9.3 75.0 68.0
25 years and older 5.7 61.9 58.4
25 to 44 years 6.1 82.2 77.2
25 to 34 years 6.2 81.4 76.3
35 to 44 years 5.9 83.0 78.1
45 to 64 years 5.4 71.5 67.6
45 to 54 years 5.2 82.6 78.3
55 to 64 years 5.8 58.5 55.1
65 years and older 4.5 8.8 8.4
55 years and older 5.6 31.6 29.8
Source: Statistics Canada, CANSIM, table 282-0002.
February 15, 2013 Monika E. Sosnowska
15. INCOME EARNING GAP BETWEEN MEN AND WOMEN (2006-2012) 15
Table 3
Estimated numbers of earners by sex (2006 to 2010)
2006 2007 2008 2009 2010
thousands
All earners 18,837 19,230 19,452 19,451 19,693
Women 8,832 9,061 9,176 9,223 9,340
Men 10,005 10,169 10,277 10,228 10,353
Full-year full-time workers 9,041 9,243 9,560 8,889 8,858
Women 3,783 3,914 4,043 3,824 3,900
Men 5,258 5,329 5,517 5,065 4,957
Source: Statistics Canada, CANSIM, table 202-0101.
February 15, 2013 Monika E. Sosnowska
16. INCOME EARNING GAP BETWEEN MEN AND WOMEN (2006-2012) 16
APPENDIX C
Table 1
People employed, by educational attainment (2012)
Both sexes Men Women
%
Total 61.8 65.8 57.9
15 to 24 years 54.5 53.4 55.6
25 to 44 years 81.6 86.1 77.2
45 and over 51.5 56.5 46.8
Less than Grade 9 20.0 27.4 13.5
15 to 24 years 26.0 29.2 21.4
25 to 44 years 50.5 63.9 34.3
45 and over 15.8 22.0 10.9
Some secondary school 39.5 46.3 32.1
15 to 24 years 35.2 36.1 34.2
25 to 44 years 64.9 73.3 52.4
45 and over 34.4 43.9 25.3
High school graduate 61.1 68.1 54.3
15 to 24 years 63.4 63.7 62.9
25 to 44 years 77.7 84.8 68.6
45 and over 51.7 58.8 46.1
Some postsecondary 60.6 62.6 58.5
15 to 24 years 56.5 53.6 59.4
25 to 44 years 75.5 80.8 69.3
45 and over 54.0 58.5 49.9
1
Postsecondary certificate or diploma 70.6 73.6 67.7
15 to 24 years 74.5 73.7 75.3
25 to 44 years 85.2 88.9 81.6
45 and over 59.2 62.0 56.6
Bachelor's degree 74.8 76.9 73.1
15 to 24 years 71.2 67.3 73.8
25 to 44 years 85.4 89.8 82.1
45 and over 63.8 65.9 61.7
Above bachelor's degree 75.4 75.1 75.6
15 to 24 years 70.3 71.3 70.2
25 to 44 years 86.0 88.4 83.9
45 and over 66.7 66.8 66.6
Source: Statistics Canada, CANSIM, table 282-0004 and Catalogue no. 89F0133XIE.
February 15, 2013 Monika E. Sosnowska
17. INCOME EARNING GAP BETWEEN MEN AND WOMEN (2006-2012) 17
Table 2
Female-to-male earnings ratios, by selected characteristics, 2010 constant dollars
Selected characteristics 2006 2007 2008 2009 2010
All age groups 75.5A 74.2A 76.0A 78.2A 77.6A
All marital statuses 75.5A 74.2A 76.0A 78.2A 77.6A
Never married 96.0C 95.8C 87.3B 96.1B 96.1B
Married 70.1A 70.0A 72.3A 72.6A 71.8A
Other marital status 75.2C 75.0C 76.0B 80.2C 83.3C
All education levels 75.5A 74.2A 76.0A 78.2A 77.6A
Some secondary6 62.0C 67.4C 70.4C 73.3C 69.5D
Graduated high school6 73.4B 72.3B 76.5B 78.6C 84.8C
Some postsecondary 76.9C 81.2C 77.9C 79.4C 74.1C
Postsecondary certificate or diploma8 71.7A 72.3B 74.9B 74.4B 73.7B
University degree9 75.3B 74.9B 78.6B 79.9B 77.1B
Source: Statistics Canada, CANSIM, table 202-0104
February 15, 2013 Monika E. Sosnowska
18. INCOME EARNING GAP BETWEEN MEN AND WOMEN (2006-2012) 18
APPENDIX D
Table 1
Employment by industry and sex (in percent)
2012
Number employed
Both sexes Men Women
%
All industries 100.0 100.0 100.0
Goods-producing sector 22.1 32.9 10.2
Agriculture 1.8 2.3 1.1
Forestry, fishing, mining, quarrying, oil and gas1 2.1 3.3 0.8
Utilities 0.8 1.2 0.4
Construction 7.2 12.2 1.8
Manufacturing 10.2 14.0 6.0
Services-producing sector 77.9 67.1 89.8
Trade 15.1 14.8 15.4
Transportation and warehousing 4.9 7.1 2.4
Finance, insurance, real estate and leasing 6.2 5.1 7.5
Professional, scientific and technical services 7.4 8.2 6.6
Business, building and other support services2 3.9 4.2 3.7
Educational services 7.4 4.8 10.2
Health care and social assistance 12.2 4.1 21.1
Information, culture and recreation 4.5 4.8 4.2
Accommodation and food services 6.3 4.9 7.8
Other services 4.5 3.9 5.3
Public administration 5.5 5.2 5.7
Source: Statistics Canada, CANSIM, table 282-0008.
February 15, 2013 Monika E. Sosnowska
19. INCOME EARNING GAP BETWEEN MEN AND WOMEN (2006-2012) 19
APPENDIX E
Table 1
Reasons for part-time work by sex and age group
Men
2012
Men
Total 15-24 25-44 45 and over
%
Own illness 3.7 0.7 5.2 6.7
Caring for children 1.3 x 3.9 1.2
Other personal/family responsibilities 1.4 0.6 2.1 2.1
Going to school 37.2 73.4 20.5 0.9
Personal preference 25.1 4.3 15.5 58.4
Other voluntary 2.8 1.3 5.3 3.2
1
Other 28.4 19.7 47.5 27.4
Total employed part-time 1,086.5 480.1 236.8 369.6
(thousands)
% employed part-time2 11.8 39.4 5.9 9.3
Source: Statistics Canada, CANSIM, table 282-0014 and 282-0001 and Catalogue no 89F0133XIE.
Women
2012
Women
Total 15-24 25-44 45 and over
%
Own illness 3.4 0.5 2.7 6.2
Caring for children 13.1 1.2 34.1 5.2
Other personal/family responsibilities 3.8 0.5 4.2 6.0
Going to school 24.7 71.4 8.6 1.0
Personal preference 26.3 4.6 14.7 52.9
Other voluntary 2.1 1.2 2.8 2.2
1
Other 26.6 20.6 32.9 26.3
Total employed part-time 2,208.3 668.6 692.9 846.8
(thousands)
% employed part-time2 26.5 55.2 19.3 24.0
Source: Statistics Canada, CANSIM, table 282-0014 and 282-0001 and Catalogue no 89F0133XIE.
February 15, 2013 Monika E. Sosnowska
20. INCOME EARNING GAP BETWEEN MEN AND WOMEN (2006-2012) 20
Table 2
Family characteristics, husband-wife families, by wife's contribution to husband-wife
employment income
Wife's contribution to Husband-wife families2 2008 2009 2010
husband-wife family
employment income2,3,4
Number of husband-wife Total husband-wife families6 6,504,820 6,559,500 6,599,070
families with employment Husband-wife families with no children6 2,700,460 2,754,110 2,787,420
income Husband-wife families with 1 child6 1,507,520 1,510,670 1,512,780
Husband-wife families with 2 children6 1,607,400 1,607,990 1,610,820
Husband-wife families with 3 or more 689,440 686,730 688,040
children6
Median contribution of the Total husband-wife families6 29,200 29,780 30,400
wife to husband-wife family Husband-wife families with no children6 28,910 29,340 29,780
employment income Husband-wife families with 1 child6 28,900 29,400 30,070
(dollars)8 Husband-wife families with 2 children6 31,020 31,830 32,880
Husband-wife families with 3 or more 25,910 26,480 27,280
children6
Source: Statistics Canada, CANSIM, table 111-0021
February 15, 2013 Monika E. Sosnowska
21. INCOME EARNING GAP BETWEEN MEN AND WOMEN (2006-2012) 21
Table 3
Family characteristics, by family type, family composition and characteristics of parents
Family type2,8,9 Parent 2006 2007 2008 2009 2010
characteristics
Couple families8 All parental age 7,629,330 7,727,870 7,832,060 7,926,210 7,989,380
groups5
Median total income 70,400 73,420 75,880 75,320 76,950
(dollars)4,11
Lone-parent All parental age 1,391,330 1,379,310 1,383,470 1,389,570 1,401,870
families9 groups5
Median total income 33,000 34,540 35,990 36,100 37,050
(dollars)4,11
Male lone-parent All parental age 237,050 234,670 242,210 243,270 247,020
families9 groups5
Median total income 46,100 48,240 49,670 49,070 50,450
(dollars)4,11
Female lone- All parental age 1,154,270 1,144,640 1,141,260 1,146,310 1,154,850
parent families9 groups5
Median total income 30,900 32,360 33,750 33,950 34,900
(dollars)4,11
Source: Statistics Canada, CANSIM, table 111-0011
February 15, 2013 Monika E. Sosnowska
22. INCOME EARNING GAP BETWEEN MEN AND WOMEN (2006-2012) 22
Chart 1
Unionization rates of workers age 25 to 54
February 15, 2013 Monika E. Sosnowska