When hiring employees, an employer might use information from the group to these employees belong as a proxy for productivity related unobserved variables, such as the probability of becoming a parent. We put this conjecture to test by collecting data from over 50 countries and 40 years. We find that delaying fertility leads to a fall in gender inequality, a finding that is consistent with statistical discrimination.
Statistical discrimination is a possible, rational motive behind the persistent differences in earnings between men and women. Employers could women to bear a larger share of the burden associated with having children, and subsequently discount that on wages. We test the empirical validity of this claim using data from over 50 countries and 40 years. Using IV we find causal evidence consistent with this hypothesis. Postponing birth by one year leads to large falls in the adjusted gender wage gap.
Statistical discrimination at young age: new evidence from four decades of in...GRAPE
Statistical discrimination offers a compelling narrative on gender wage gaps during the early stages of the career. Expecting absences related to child-bearing and child-rearing, the employers discount productivity to adjust for the probable losses such as costs associated with finding substitutes, leaving customers, etc. If that is the case, lower and delayed fertility should imply lower discount in wages, and consequently reductions in the gender pay gap among entrants. We put this conjecture to test against the data. We provide a novel set of estimates of adjusted gender wage gaps among youth for 56 countries spanning four decades. We estimate that postponing childbirth by a year reduce the adjusted gap 2 percentage points (15%). We show that this estimate is consistent with statistical discrimination, but for some countries the estimates of AGWG imply that either statistical discrimination is not accurate or taste-based mechanisms are also at play.
Statistical gender discrimination: evidence from young workers across four de...GRAPE
Statistical discrimination offers a compelling narrative on gender wage gaps among younger workers. Employers could discount women's wages to adjust for probable costs linked to childbearing. Given trends towards lower and delayed fertility one should observe a lower discount in wages and a reduction in the gender wage gap among entrants. We test this conjecture using estimates of adjusted gender wage gap among young workers from 56 countries. We find that postponing childbirth by a year reduces the adjusted gap by two percentage points (15%). We further benchmark the implied gender inequality with the help of time-use data.
What are the welfare and macroeconomic effects of family policies? How do they depend on policy composition? I answer that questions in overlapping generations model calibrated to the US. I account for the idiosyncratic income risk, redistribution via social security, and tax and benefit system. I explicitly model child-related tax credit, child care subsidies, and child allowance. I show the expansion of the family policy yields higher welfare. The expenditure on the optimal policy accounts for approximately 3% of GDP. Even though the optimal family policy is three times bigger than the status quo policy, taxes decrease when the optimal policy is implemented. Therefore, reform is self- financing. The structure of family policy is crucial for welfare evaluation. Tax credit and child allowance generate higher welfare gains than child care.
Estimating gender wage gap in the presence of efficiency wages -- evidence fr...GRAPE
Gender wage gap (adjusted for individual characteristics) as a phenomenon means that women are paid unjustifiably less than men, i.e. below their productivity. Meanwhile, efficiency wages as a phenomenon mean that a group of workers is paid in excess of productivity. However, productivity is typically unobservable, hence it is proxied by some observable characteristics. If efficiency wages are effective only in selected occupations and/or industries, and these happen to be dominated by men, measures of adjusted gender wage gaps will confound (possibly) below productivity compensating of women with above productivity efficiency wage prevalence. We propose to utilize endogenous switching models to estimate adjusted gender wage gaps. We find that without correction for the prevalence of efficiency wages, the estimates of the adjusted gender wage gaps tend to be substantially inflated.
Child-related transfers: is there a room for welfare improvement?GRAPE
How does income risk affect the optimal size of the child-related transfer system? I answer this question in an overlapping generations model with endogenous fertility and PAYG social security. I show that the optimal size of the child-related transfer is increasing in income risk.
First, in the stylized model, I provide the intuition behind this result. Second, I quantify the size of welfare gains due to child-related transfer reform in a full-fledged model calibrated to the US economy.
Expansion of child-related transfer yields to welfare gain even with constant income dispersion. In a scenario with higher income dispersion, welfare gains increase from 1.08% to 1.2% of lifetime consumption.
Third, I show that in a scenario with high-income dispersion, even higher welfare gains may be obtained if the child-related transfer system has a more redistributive nature.
Professor Jonathan Bradshaw. Child Well-being. CHIMAT Annual Conference: Informed Decisions and Intelligent Investment: The Future of Child and Maternal Health Services, Royal York Hotel, York, 18 March 2010.
Statistical discrimination is a possible, rational motive behind the persistent differences in earnings between men and women. Employers could women to bear a larger share of the burden associated with having children, and subsequently discount that on wages. We test the empirical validity of this claim using data from over 50 countries and 40 years. Using IV we find causal evidence consistent with this hypothesis. Postponing birth by one year leads to large falls in the adjusted gender wage gap.
Statistical discrimination at young age: new evidence from four decades of in...GRAPE
Statistical discrimination offers a compelling narrative on gender wage gaps during the early stages of the career. Expecting absences related to child-bearing and child-rearing, the employers discount productivity to adjust for the probable losses such as costs associated with finding substitutes, leaving customers, etc. If that is the case, lower and delayed fertility should imply lower discount in wages, and consequently reductions in the gender pay gap among entrants. We put this conjecture to test against the data. We provide a novel set of estimates of adjusted gender wage gaps among youth for 56 countries spanning four decades. We estimate that postponing childbirth by a year reduce the adjusted gap 2 percentage points (15%). We show that this estimate is consistent with statistical discrimination, but for some countries the estimates of AGWG imply that either statistical discrimination is not accurate or taste-based mechanisms are also at play.
Statistical gender discrimination: evidence from young workers across four de...GRAPE
Statistical discrimination offers a compelling narrative on gender wage gaps among younger workers. Employers could discount women's wages to adjust for probable costs linked to childbearing. Given trends towards lower and delayed fertility one should observe a lower discount in wages and a reduction in the gender wage gap among entrants. We test this conjecture using estimates of adjusted gender wage gap among young workers from 56 countries. We find that postponing childbirth by a year reduces the adjusted gap by two percentage points (15%). We further benchmark the implied gender inequality with the help of time-use data.
What are the welfare and macroeconomic effects of family policies? How do they depend on policy composition? I answer that questions in overlapping generations model calibrated to the US. I account for the idiosyncratic income risk, redistribution via social security, and tax and benefit system. I explicitly model child-related tax credit, child care subsidies, and child allowance. I show the expansion of the family policy yields higher welfare. The expenditure on the optimal policy accounts for approximately 3% of GDP. Even though the optimal family policy is three times bigger than the status quo policy, taxes decrease when the optimal policy is implemented. Therefore, reform is self- financing. The structure of family policy is crucial for welfare evaluation. Tax credit and child allowance generate higher welfare gains than child care.
Estimating gender wage gap in the presence of efficiency wages -- evidence fr...GRAPE
Gender wage gap (adjusted for individual characteristics) as a phenomenon means that women are paid unjustifiably less than men, i.e. below their productivity. Meanwhile, efficiency wages as a phenomenon mean that a group of workers is paid in excess of productivity. However, productivity is typically unobservable, hence it is proxied by some observable characteristics. If efficiency wages are effective only in selected occupations and/or industries, and these happen to be dominated by men, measures of adjusted gender wage gaps will confound (possibly) below productivity compensating of women with above productivity efficiency wage prevalence. We propose to utilize endogenous switching models to estimate adjusted gender wage gaps. We find that without correction for the prevalence of efficiency wages, the estimates of the adjusted gender wage gaps tend to be substantially inflated.
Child-related transfers: is there a room for welfare improvement?GRAPE
How does income risk affect the optimal size of the child-related transfer system? I answer this question in an overlapping generations model with endogenous fertility and PAYG social security. I show that the optimal size of the child-related transfer is increasing in income risk.
First, in the stylized model, I provide the intuition behind this result. Second, I quantify the size of welfare gains due to child-related transfer reform in a full-fledged model calibrated to the US economy.
Expansion of child-related transfer yields to welfare gain even with constant income dispersion. In a scenario with higher income dispersion, welfare gains increase from 1.08% to 1.2% of lifetime consumption.
Third, I show that in a scenario with high-income dispersion, even higher welfare gains may be obtained if the child-related transfer system has a more redistributive nature.
Professor Jonathan Bradshaw. Child Well-being. CHIMAT Annual Conference: Informed Decisions and Intelligent Investment: The Future of Child and Maternal Health Services, Royal York Hotel, York, 18 March 2010.
Renu Singh's presentation at UNICEF Innocenti's Inception Scoping Workshop for Evidence on Educational Strategies to Address Child Labour in India & Bangladesh, held in New Delhi in November 2019.
Na zaproszenie Pani Profesor Elżbiety Gołaty, prorektora Uniwersytetu Ekonomicznego w Poznaniu Paweł Strzelecki przedstawił zebranym specjalistom zajmującym się statystyką i demografią wyniki symulacji efektów różnych scenariuszy wzrostu dzietności za pomocą modelu makroekonomicznego nakładających się pokoleń (OLG). Szczególnie ożywioną dyskusję wzbudziła możliwość kwantyfikacji dobrobytowych skutków polityki prorodzinnej oraz efekty makroekonomiczne w dłuższym terminie. Dyskusja dotyczyła także możliwości pomiaru stanu zdrowia ludności za pomocą dostępnych danych. Bardzo dziękujemy za możliwość podzielania się wynikami badań oraz bardzo ciekawe uwagi.
Dr Ellina Samantroy's presentation at UNICEF Innocenti's Inception Scoping Workshop for Evidence on Educational Strategies to Address Child Labour in India & Bangladesh, held in New Delhi in November 2019.
Sajeda Amin's presentation at UNICEF Innocenti's Inception Scoping Workshop for Evidence on Educational Strategies to Address Child Labour in India & Bangladesh, held in New Delhi in November 2019.
Motherhood Wage Penalty During the Times of TransitionOlena Nizalova
Controlling for individual unobserved heterogeneity, a number of human capital characteristics, actual time in the labor force, and selection into employment, we find that the overall motherhood wage penalty is approximately 19%, which is much lower than in the countries with similar de jure family policies and cultural norms. Contrary to the previous literature, we find that postponing first birth till after 30 increases motherhood wage penalty and that females with the lowest educational attainment suffer the most supporting earlier findings of an insurance role of education.
We provide causal evidence that delaying fertility leads to a decrease in the adjusted gender wage gap. To avoid possible reverse causality, we employ an instrumental variable approach. We introduce several instruments, among them a novel one: international variation in the introduction of the contraceptive pill. Our estimates are large: a one-year delay in fertility leads to a 12% fall in the gender wage gap
Fertility, contraceptives and gender inequalityGRAPE
Our analysis shows that increasing the age at first birth is associated with a substantial decline in gender wage gaps: postponing first birth by a year reduces the gap by around 15%. In order to establish causality, we propose a novel instrument that exploits international variation in approval of oral contraceptives (the pill). Our estimates are consistent with a model of statistical discrimination where employers offer lower wages to women to hedge the expected costs associated with childbearing and childrearing.
We study the relationship between gender inequality among youth and fertility timing. We show that postponing fertility by one year leads to a substantial reduction of gender inequality. This finding is consistent with a simple statistical discrimination model, where employers offer lower wages when they anticipated costs related to fertility, and that these costs are higher for female employees.
Delayed fertility and statistical discrimination against womenGRAPE
Statistical discrimination offers a compelling narrative on gender wage gaps during the early stages of the career. Expecting absences related to child-bearing and child-rearing, the employers discount productivity to adjust for the probable losses such as costs associated with finding substitutes, leaving customers, etc. If that is the case, lower and delayed fertility should imply lower discount in wages, and consequently reductions in the gender pay gap among entrants. We put this conjecture to test against the data. We provide a novel set of estimates of adjusted gender wage gaps among youth for 56 countries spanning four decades. We estimate that postponing childbirth by a year reduce the adjusted gap 2 percentage points (15%). We show that this estimate is consistent with statistical discrimination, but for some countries the estimates of AGWG imply that either statistical discrimination is not accurate or taste-based mechanisms are also at play.
Statistical discrimination offers a compelling story to understand gender wage gaps, at least during the early stages of the career. Employers believe that women will get pregnant with a positive probability, which leads to potential losses, eg. costs associated with finding substitutes, potential losses in customers, etc. Employers then have an incentive to offer women lower wages, in order to discount for future losses. If that is the case, lower and delayed fertility should imply lower discount in wages, and consequently reductions in the gender pay gap among entrants.
In order to test for this hypothesis, we collect individual level data from European countries dating back to the early 1990. Having compiled these data, we compute the adjusted gender wage gap for workers at the early stages of their career, that is for those aged 25 to 29. These adjuste differences are obtained using the non-parametric approach pioneered by Nopo. We then regress these measures on macro data on fertility changes. If the statistical discrimination hypothesis is correct, we should expect that the secular decline in fertility observed in Europe over the last 30 years is correlated with lower estimates of the gender wage gap. Our estimates suggest that this is indeed the case. Using the age at first birth as a proxy for fertility, we find that postponing childbirth by an additional year leads to a reduction of .18 in the adjusted gap.
One caveat with this result is that fertility can be endogeneous to wages. If women were to receive higher wages, they might choose to postpone childbirths. To address this issue, we instrument our measure of fertility with the number of years since the introduction of the pill in the country. This measures varies across countries and over time, while at the same time it is fairly exogeneous, as the introduction of the pill occurred several generations back, normally in the mid-60 and 70s. First stage regressions reveal that the instrument correlates well with mean age at first birth. Second stage estimates are still significant, though they are smaller in magnitude. We conclude that recent changes in fertility helped to reduce the gender wage gap among women entering to the labor market.
After couples have their first child, parents become more likely to agree with statements showing traditional gender norms. In this research I study how common this finding is across countries,and whether differences across countries can shed light on the reasons
Childbearing and attitudes towards gender normsGRAPE
The research studies whether major life events affect the perception of social norms. Specifically, I focus on how giving birth to a first child affects attitudes towards gender norms. I find that after childbirth people become more likely to agree with traditional division of household chores. Effects are contingent on country and demographic characteristics
Impacts of Cash Transfers on Adolescents' & Young Women's Well-Being Globally...The Transfer Project
Tia Palermo's presentation for the joint UNICEF & Gates Foundation Tanzania Adolescent Symposium in Dar es Salaam on 7 February 2018.
Using evidence from around the world, Tia outlines what we know about cash transfers impacts on youth and young women's well-being.
Renu Singh's presentation at UNICEF Innocenti's Inception Scoping Workshop for Evidence on Educational Strategies to Address Child Labour in India & Bangladesh, held in New Delhi in November 2019.
Na zaproszenie Pani Profesor Elżbiety Gołaty, prorektora Uniwersytetu Ekonomicznego w Poznaniu Paweł Strzelecki przedstawił zebranym specjalistom zajmującym się statystyką i demografią wyniki symulacji efektów różnych scenariuszy wzrostu dzietności za pomocą modelu makroekonomicznego nakładających się pokoleń (OLG). Szczególnie ożywioną dyskusję wzbudziła możliwość kwantyfikacji dobrobytowych skutków polityki prorodzinnej oraz efekty makroekonomiczne w dłuższym terminie. Dyskusja dotyczyła także możliwości pomiaru stanu zdrowia ludności za pomocą dostępnych danych. Bardzo dziękujemy za możliwość podzielania się wynikami badań oraz bardzo ciekawe uwagi.
Dr Ellina Samantroy's presentation at UNICEF Innocenti's Inception Scoping Workshop for Evidence on Educational Strategies to Address Child Labour in India & Bangladesh, held in New Delhi in November 2019.
Sajeda Amin's presentation at UNICEF Innocenti's Inception Scoping Workshop for Evidence on Educational Strategies to Address Child Labour in India & Bangladesh, held in New Delhi in November 2019.
Motherhood Wage Penalty During the Times of TransitionOlena Nizalova
Controlling for individual unobserved heterogeneity, a number of human capital characteristics, actual time in the labor force, and selection into employment, we find that the overall motherhood wage penalty is approximately 19%, which is much lower than in the countries with similar de jure family policies and cultural norms. Contrary to the previous literature, we find that postponing first birth till after 30 increases motherhood wage penalty and that females with the lowest educational attainment suffer the most supporting earlier findings of an insurance role of education.
We provide causal evidence that delaying fertility leads to a decrease in the adjusted gender wage gap. To avoid possible reverse causality, we employ an instrumental variable approach. We introduce several instruments, among them a novel one: international variation in the introduction of the contraceptive pill. Our estimates are large: a one-year delay in fertility leads to a 12% fall in the gender wage gap
Fertility, contraceptives and gender inequalityGRAPE
Our analysis shows that increasing the age at first birth is associated with a substantial decline in gender wage gaps: postponing first birth by a year reduces the gap by around 15%. In order to establish causality, we propose a novel instrument that exploits international variation in approval of oral contraceptives (the pill). Our estimates are consistent with a model of statistical discrimination where employers offer lower wages to women to hedge the expected costs associated with childbearing and childrearing.
We study the relationship between gender inequality among youth and fertility timing. We show that postponing fertility by one year leads to a substantial reduction of gender inequality. This finding is consistent with a simple statistical discrimination model, where employers offer lower wages when they anticipated costs related to fertility, and that these costs are higher for female employees.
Delayed fertility and statistical discrimination against womenGRAPE
Statistical discrimination offers a compelling narrative on gender wage gaps during the early stages of the career. Expecting absences related to child-bearing and child-rearing, the employers discount productivity to adjust for the probable losses such as costs associated with finding substitutes, leaving customers, etc. If that is the case, lower and delayed fertility should imply lower discount in wages, and consequently reductions in the gender pay gap among entrants. We put this conjecture to test against the data. We provide a novel set of estimates of adjusted gender wage gaps among youth for 56 countries spanning four decades. We estimate that postponing childbirth by a year reduce the adjusted gap 2 percentage points (15%). We show that this estimate is consistent with statistical discrimination, but for some countries the estimates of AGWG imply that either statistical discrimination is not accurate or taste-based mechanisms are also at play.
Statistical discrimination offers a compelling story to understand gender wage gaps, at least during the early stages of the career. Employers believe that women will get pregnant with a positive probability, which leads to potential losses, eg. costs associated with finding substitutes, potential losses in customers, etc. Employers then have an incentive to offer women lower wages, in order to discount for future losses. If that is the case, lower and delayed fertility should imply lower discount in wages, and consequently reductions in the gender pay gap among entrants.
In order to test for this hypothesis, we collect individual level data from European countries dating back to the early 1990. Having compiled these data, we compute the adjusted gender wage gap for workers at the early stages of their career, that is for those aged 25 to 29. These adjuste differences are obtained using the non-parametric approach pioneered by Nopo. We then regress these measures on macro data on fertility changes. If the statistical discrimination hypothesis is correct, we should expect that the secular decline in fertility observed in Europe over the last 30 years is correlated with lower estimates of the gender wage gap. Our estimates suggest that this is indeed the case. Using the age at first birth as a proxy for fertility, we find that postponing childbirth by an additional year leads to a reduction of .18 in the adjusted gap.
One caveat with this result is that fertility can be endogeneous to wages. If women were to receive higher wages, they might choose to postpone childbirths. To address this issue, we instrument our measure of fertility with the number of years since the introduction of the pill in the country. This measures varies across countries and over time, while at the same time it is fairly exogeneous, as the introduction of the pill occurred several generations back, normally in the mid-60 and 70s. First stage regressions reveal that the instrument correlates well with mean age at first birth. Second stage estimates are still significant, though they are smaller in magnitude. We conclude that recent changes in fertility helped to reduce the gender wage gap among women entering to the labor market.
After couples have their first child, parents become more likely to agree with statements showing traditional gender norms. In this research I study how common this finding is across countries,and whether differences across countries can shed light on the reasons
Childbearing and attitudes towards gender normsGRAPE
The research studies whether major life events affect the perception of social norms. Specifically, I focus on how giving birth to a first child affects attitudes towards gender norms. I find that after childbirth people become more likely to agree with traditional division of household chores. Effects are contingent on country and demographic characteristics
Impacts of Cash Transfers on Adolescents' & Young Women's Well-Being Globally...The Transfer Project
Tia Palermo's presentation for the joint UNICEF & Gates Foundation Tanzania Adolescent Symposium in Dar es Salaam on 7 February 2018.
Using evidence from around the world, Tia outlines what we know about cash transfers impacts on youth and young women's well-being.
Does childbearing makes us more conservative?GRAPE
The research shows that upon becoming parents, mothers (and fathers) embrace more traditional norms in a number of domains. They are more likely to put a higher value on family that before, and they would even conform to a male breadwinner model. The change in attitudes is more pronounced in Central and Eastern European countries, and almost negligible elsewhere. I further show that this is related to a series of characteristics of those countries. Noteworthy, changes are more frequent in countries where women receive less support during motherhood from the state, and where differences in norms across genders are more marked.
Error detection in census data age reportingcimran15
Age is an important demographic variable that must be carefully considered in all demographic survey. The objective of this study is to conduct a comprehensive assessment of the age reporting in Census data. The study gave an estimate of age misrepresentation in the Nigeria 2006 Population and Housing Census Data.
The data used in this study was obtained from the 2006 Population and Housing Census Priority Table, Volume(III)published by the National Population Commission, Abuja, Nigeria, in April
2010.
Age heaping and digit preference were measured using modified Whipple's index and Myers index. Age Sex accuracy was also measured using the United Nation's age-sex accuracy index.
The reported Whipple's index for both sexes was 251 indicating presence of age heaping and it also showed age heaping at terminal digit 0 and 5 as 268 and 233 respectively. The Myers index had an overall index of 50.9, 49 for male and 52.82 for female population.
The evaluation of Nigeria 2006 Population and Housing Census Data based on the technique applied in this study indicates that the data is of poor quality as a result of the presence of age heaping and digit preference in recorded ages. Therefore modern methods such as a systematic data management system, compulsion to register birth, and standard smoothing techniques are thereby recommended for future data collection.
Seminar: Gender Board Diversity through Ownership NetworksGRAPE
Seminar on gender diversity spillovers through ownership networks at FAME|GRAPE. Presenting novel research. Studies in economics and management using econometrics methods.
The European Unemployment Puzzle: implications from population agingGRAPE
We study the link between the evolving age structure of the working population and unemployment. We build a large new Keynesian OLG model with a realistic age structure, labor market frictions, sticky prices, and aggregate shocks. Once calibrated to the European economy, we quantify the extent to which demographic changes over the last three decades have contributed to the decline of the unemployment rate. Our findings yield important implications for the future evolution of unemployment given the anticipated further aging of the working population in Europe. We also quantify the implications for optimal monetary policy: lowering inflation volatility becomes less costly in terms of GDP and unemployment volatility, which hints that optimal monetary policy may be more hawkish in an aging society. Finally, our results also propose a partial reversal of the European-US unemployment puzzle due to the fact that the share of young workers is expected to remain robust in the US.
Revisiting gender board diversity and firm performanceGRAPE
Cel: oszacować wpływ inkluzywności władz spółek na ich wyniki.
Co wiemy?
• Większość firm nie ma równosci płci w organach (ILO, 2015)
• Większość firm nie ma w ogóle kobiet we władzach
Demographic transition and the rise of wealth inequalityGRAPE
We study the contribution of rising longevity to the rise of wealth inequality in the U.S. over the last seventy years. We construct an OLG model with multiple sources of inequality, closely calibrated to the data. Our main finding is that improvements in old-age longevity explain about 30% of the observed rise in wealth inequality. This magnitude is similar to previously emphasized channels associated with income inequality and the tax system. The contribution of demographics is bound to raise wealth inequality further in the decades to come.
(Gender) tone at the top: the effect of board diversity on gender inequalityGRAPE
The research explores to what extent the presence of women on board affects gender inequality downstream. We find that increasing presence reduces gender inequality. To avoid reverse causality, we propose a new instrument: the share of household consumption in total output. We extend the analysis to recover the effect of a single woman on board (tokenism(
Gender board diversity spillovers and the public eyeGRAPE
A range of policy recommendations mandating gender board quotas is based on the idea that "women help women". We analyze potential gender diversity spillovers from supervisory to top managerial positions over three decades in Europe. Contrary to previous studies which worked with stock listed firms or were region locked, we use a large data base of roughly 2 000 000 firms. We find evidence that women do not help women in corporate Europe, unless the firm is stock listed. Only within public firms, going from no woman to at least one woman on supervisory position is associated with a 10-15% higher probability of appointing at least one woman to the executive position. This pattern aligns with various managerial theories, suggesting that external visibility influences corporate gender diversity practices. The study implies that diversity policies, while impactful in public firms, have limited
effectiveness in promoting gender diversity in corporate Europe.
Tone at the top: the effects of gender board diversity on gender wage inequal...GRAPE
We address the gender wage gap in Europe, focusing on the impact of female representation in executive and non-executive boards. We use a novel dataset to identify gender board diversity across European firms, which covers a comprehensive sample of private firms in addition to publicly listed ones. Our study spans three waves of the Structure of Earnings Survey, covering 26 countries and multiple industries. Despite low prevalence of female representation and the complex nature of gender wage inequality, our findings reveal a robust causal link: increased gender diversity significantly decreases the adjusted gender wage gap. We also demonstrate that to meaningfully impact gender wage gaps, the presence of a single female representative in leadership is insufficient.
Gender board diversity spillovers and the public eyeGRAPE
A range of policy recommendations mandating gender board quotas is based on the idea that "women help women". We analyze potential gender diversity spillovers from supervisory to top managerial positions over three decades in Europe. Contrary to previous studies which worked with stock listed firms or were region locked, we use a large data base of roughly 2 000 000 firms. We find evidence that women do not help women in corporate Europe, unless the firm is stock listed. Only within public firms, going from no woman to at least one woman on supervisory position is associated with a 10-15\% higher probability of appointing at least one woman to the executive position. This pattern aligns with the Public Eye Managerial Theory, suggesting that external visibility influences corporate gender diversity practices. The study implies that diversity policies, while impactful in public firms, have limited effectiveness in promoting gender diversity in corporate Europe.
The European Unemployment Puzzle: implications from population agingGRAPE
We study the link between the evolving age structure of the working population and unemployment. We build a large New Keynesian OLG model with a realistic age structure, labor market frictions, sticky prices, and aggregate shocks. Once calibrated to the European economies, we use this model to provide comparative statics across past and contemporaneous age structures of the working population. Thus, we quantify the extent to which the response of labor markets to adverse TFP shocks and monetary policy shocks becomes muted with the aging of the working population. Our findings have important policy implications for European labor markets and beyond. For example, the working population is expected to further age in Europe, whereas the share of young workers will remain robust in the US. Our results suggest a partial reversal of the European-US unemployment puzzle. Furthermore, with the aging population, lowering inflation volatility is less costly in terms of higher unemployment volatility. It suggests that optimal monetary policy should be more hawkish in the older society.
Evidence concerning inequality in ability to realize aspirations is prevalent: overall, in specialized segments of the labor market, in self-employment and high-aspirations environments. Empirical literature and public debate are full of case studies and comprehensive empirical studies documenting the paramount gap between successful individuals (typically ethnic majority men) and those who are less likely to “make it” (typically ethnic minority and women). So far the drivers of these disparities and their consequences have been studied much less intensively, due to methodological constraints and shortage of appropriate data. This project proposes significant innovations to overcome both types of barriers and push the frontier of the research agenda on equality in reaching aspirations.
Overall, project is interdisciplinary, combining four fields: management, economics, quantitative methods and psychology. An important feature of this project is that it offers a diversified methodological perspective, combining applied microeconometrics, as well as experimental methods.
If you are looking for a pi coin investor. Then look no further because I have the right one he is a pi vendor (he buy and resell to whales in China). I met him on a crypto conference and ever since I and my friends have sold more than 10k pi coins to him And he bought all and still want more. I will drop his telegram handle below just send him a message.
@Pi_vendor_247
The secret way to sell pi coins effortlessly.DOT TECH
Well as we all know pi isn't launched yet. But you can still sell your pi coins effortlessly because some whales in China are interested in holding massive pi coins. And they are willing to pay good money for it. If you are interested in selling I will leave a contact for you. Just telegram this number below. I sold about 3000 pi coins to him and he paid me immediately.
Telegram: @Pi_vendor_247
Abhay Bhutada Leads Poonawalla Fincorp To Record Low NPA And Unprecedented Gr...Vighnesh Shashtri
Under the leadership of Abhay Bhutada, Poonawalla Fincorp has achieved record-low Non-Performing Assets (NPA) and witnessed unprecedented growth. Bhutada's strategic vision and effective management have significantly enhanced the company's financial health, showcasing a robust performance in the financial sector. This achievement underscores the company's resilience and ability to thrive in a competitive market, setting a new benchmark for operational excellence in the industry.
What price will pi network be listed on exchangesDOT TECH
The rate at which pi will be listed is practically unknown. But due to speculations surrounding it the predicted rate is tends to be from 30$ — 50$.
So if you are interested in selling your pi network coins at a high rate tho. Or you can't wait till the mainnet launch in 2026. You can easily trade your pi coins with a merchant.
A merchant is someone who buys pi coins from miners and resell them to Investors looking forward to hold massive quantities till mainnet launch.
I will leave the telegram contact of my personal pi vendor to trade with.
@Pi_vendor_247
What website can I sell pi coins securely.DOT TECH
Currently there are no website or exchange that allow buying or selling of pi coins..
But you can still easily sell pi coins, by reselling it to exchanges/crypto whales interested in holding thousands of pi coins before the mainnet launch.
Who is a pi merchant?
A pi merchant is someone who buys pi coins from miners and resell to these crypto whales and holders of pi..
This is because pi network is not doing any pre-sale. The only way exchanges can get pi is by buying from miners and pi merchants stands in between the miners and the exchanges.
How can I sell my pi coins?
Selling pi coins is really easy, but first you need to migrate to mainnet wallet before you can do that. I will leave the telegram contact of my personal pi merchant to trade with.
Tele-gram.
@Pi_vendor_247
USDA Loans in California: A Comprehensive Overview.pptxmarketing367770
USDA Loans in California: A Comprehensive Overview
If you're dreaming of owning a home in California's rural or suburban areas, a USDA loan might be the perfect solution. The U.S. Department of Agriculture (USDA) offers these loans to help low-to-moderate-income individuals and families achieve homeownership.
Key Features of USDA Loans:
Zero Down Payment: USDA loans require no down payment, making homeownership more accessible.
Competitive Interest Rates: These loans often come with lower interest rates compared to conventional loans.
Flexible Credit Requirements: USDA loans have more lenient credit score requirements, helping those with less-than-perfect credit.
Guaranteed Loan Program: The USDA guarantees a portion of the loan, reducing risk for lenders and expanding borrowing options.
Eligibility Criteria:
Location: The property must be located in a USDA-designated rural or suburban area. Many areas in California qualify.
Income Limits: Applicants must meet income guidelines, which vary by region and household size.
Primary Residence: The home must be used as the borrower's primary residence.
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Lecture slide titled Fraud Risk Mitigation, Webinar Lecture Delivered at the Society for West African Internal Audit Practitioners (SWAIAP) on Wednesday, November 8, 2023.
how to sell pi coins effectively (from 50 - 100k pi)DOT TECH
Anywhere in the world, including Africa, America, and Europe, you can sell Pi Network Coins online and receive cash through online payment options.
Pi has not yet been launched on any exchange because we are currently using the confined Mainnet. The planned launch date for Pi is June 28, 2026.
Reselling to investors who want to hold until the mainnet launch in 2026 is currently the sole way to sell.
Consequently, right now. All you need to do is select the right pi network provider.
Who is a pi merchant?
An individual who buys coins from miners on the pi network and resells them to investors hoping to hang onto them until the mainnet is launched is known as a pi merchant.
debuts.
I'll provide you the Telegram username
@Pi_vendor_247
what is the best method to sell pi coins in 2024DOT TECH
The best way to sell your pi coins safely is trading with an exchange..but since pi is not launched in any exchange, and second option is through a VERIFIED pi merchant.
Who is a pi merchant?
A pi merchant is someone who buys pi coins from miners and pioneers and resell them to Investors looking forward to hold massive amounts before mainnet launch in 2026.
I will leave the telegram contact of my personal pi merchant to trade pi coins with.
@Pi_vendor_247
Even tho Pi network is not listed on any exchange yet.
Buying/Selling or investing in pi network coins is highly possible through the help of vendors. You can buy from vendors[ buy directly from the pi network miners and resell it]. I will leave the telegram contact of my personal vendor.
@Pi_vendor_247
1. Statistical discrimination at young age:
Statistical discrimination at young age:
evidence from young workers across four decades and 56 countries
Joanna Tyrowicz [FAME|GRAPE, University of Warsaw & IZA ]
Lucas van der Velde [FAME|GRAPE & Warsaw School of Economics]
Royal Economic Society
April 2022
2. Statistical discrimination at young age:
Motivation
Motivation – textbook case for statistical discrimination
Fertility (-related absences) as premise for gender inequality
fertility plans → hiring decisions
(Becker et al., 2019)
child bearing → wage loss among mothers (not fathers)
(Landais & Kleven, 2019; Cukrowska-Torzewska & Matysiak, 2017; Pertold-Gebicka, 2014)
3. Statistical discrimination at young age:
Motivation
Motivation – textbook case for statistical discrimination
Fertility (-related absences) as premise for gender inequality
fertility plans → hiring decisions
(Becker et al., 2019)
child bearing → wage loss among mothers (not fathers)
(Landais & Kleven, 2019; Cukrowska-Torzewska & Matysiak, 2017; Pertold-Gebicka, 2014)
Demographic trends: ↑ age at first birth and ↓ # of births
⇒ less reasons for statistical discrimination
4. Statistical discrimination at young age:
Motivation
Motivation – textbook case for statistical discrimination
Fertility (-related absences) as premise for gender inequality
fertility plans → hiring decisions
(Becker et al., 2019)
child bearing → wage loss among mothers (not fathers)
(Landais & Kleven, 2019; Cukrowska-Torzewska & Matysiak, 2017; Pertold-Gebicka, 2014)
Demographic trends: ↑ age at first birth and ↓ # of births
⇒ less reasons for statistical discrimination
What we do
study gender wage gaps among labor market entrants
explore the role of delayed fertility
5. Statistical discrimination at young age:
Motivation
Motivation – textbook case for statistical discrimination
Fertility (-related absences) as premise for gender inequality
fertility plans → hiring decisions
(Becker et al., 2019)
child bearing → wage loss among mothers (not fathers)
(Landais & Kleven, 2019; Cukrowska-Torzewska & Matysiak, 2017; Pertold-Gebicka, 2014)
Demographic trends: ↑ age at first birth and ↓ # of births
⇒ less reasons for statistical discrimination
What we do
study gender wage gaps among labor market entrants
explore the role of delayed fertility → implicit test of statistical discrimination
6. Statistical discrimination at young age:
Motivation
Our contribution
We uncover a link from timing of fertility to (adjusted) gender wage gaps
7. Statistical discrimination at young age:
Motivation
Our contribution
We uncover a link from timing of fertility to (adjusted) gender wage gaps
Comparable measures of AGWG (across c & t) for entrants
8. Statistical discrimination at young age:
Motivation
Our contribution
We uncover a link from timing of fertility to (adjusted) gender wage gaps
Comparable measures of AGWG (across c & t) for entrants
Causal evidence: several instruments
Duration of compulsory education (multiple reforms)
9. Statistical discrimination at young age:
Motivation
Our contribution
We uncover a link from timing of fertility to (adjusted) gender wage gaps
Comparable measures of AGWG (across c & t) for entrants
Causal evidence: several instruments
Duration of compulsory education (multiple reforms)
Military conscription (many changes)
10. Statistical discrimination at young age:
Motivation
Our contribution
We uncover a link from timing of fertility to (adjusted) gender wage gaps
Comparable measures of AGWG (across c & t) for entrants
Causal evidence: several instruments
Duration of compulsory education (multiple reforms)
Military conscription (many changes)
New IV: international variation in “pill” admission
(in the US: Goldin & Katz, 2002; Bailey, 2006; Oltmans-Ananat & Hungerman, 2012)
11. Statistical discrimination at young age:
Motivation
Our contribution
We uncover a link from timing of fertility to (adjusted) gender wage gaps
Comparable measures of AGWG (across c & t) for entrants
Causal evidence: several instruments
Duration of compulsory education (multiple reforms)
Military conscription (many changes)
New IV: international variation in “pill” admission
(in the US: Goldin & Katz, 2002; Bailey, 2006; Oltmans-Ananat & Hungerman, 2012)
Fertility observed in the generation of the mothers
12. Statistical discrimination at young age:
Data & method
What we would like to do
We would like to estimate the following regression
AGWGc,t = βi + β × Fertilityc,t + γXc,t + ϵc,t
13. Statistical discrimination at young age:
Data & method
What we would like to do
We would like to estimate the following regression
AGWGc,t = βi + β × Fertilityc,t + γXc,t + ϵc,t
Fertility: use mean age at first birth
TFR is noisy → we want the “risk” by employers at 20 < age < 30
14. Statistical discrimination at young age:
Data & method
What we would like to do
We would like to estimate the following regression
AGWGc,t = βi + β × Fertilityc,t + γXc,t + ϵc,t
Fertility: use mean age at first birth
TFR is noisy → we want the “risk” by employers at 20 < age < 30
AGWG: obtain own estimates
→ adjust raw GWG for 20 < age < 30
But: fertility decisions endogenous to labor force participation & AGWG
15. Statistical discrimination at young age:
Data & method
What we would like to do
We would like to estimate the following regression
AGWGc,t = βi + β × Fertilityc,t + γXc,t + ϵc,t
Fertility: use mean age at first birth
TFR is noisy → we want the “risk” by employers at 20 < age < 30
AGWG: obtain own estimates
→ adjust raw GWG for 20 < age < 30
But: fertility decisions endogenous to labor force participation & AGWG → need to instrument
16. Statistical discrimination at young age:
Data & method
(I) Fertility data
We use mean age at first birth (MAB) as a measure of fertility
Direct link to probability of becoming a parent
Less noisy than alternatives
Total fertility rate, age specific fertility, childlessness
Data collected from a variety of sources
Eurostat, UNECE, OECD, Human Fertility Database + bureaus of statistics + papers
17. Statistical discrimination at young age:
Data & method
(II) Measuring the adjusted gender wage gap
Nopo decomposition
A flexible non-parametric approach based on exact matching
Reliable even when when small set of covariates
Reliable even when cannot correct for selection bias
AGWG within common support
18. Statistical discrimination at young age:
Data & method
(II) Measuring the adjusted gender wage gap
Nopo decomposition
A flexible non-parametric approach based on exact matching
Reliable even when when small set of covariates
Reliable even when cannot correct for selection bias
AGWG within common support
We need individual level data
19. Statistical discrimination at young age:
Data & method
(II) Measuring the adjusted gender wage gap
Collecting individual level data
1 Harmonized data sources:
IPUMS + LISSY + EU (SILC, SES, ECHP)
2 Longitudinal data
Canada, Germany, Korea, Russia, Sweden, the UK, Ukraine and the US
3 Labor Force Surveys and Household Budget Surveys:
Albania, Argentina, Armenia, Belarus, Chile, Croatia, France, Hungary, Italy, Poland,
Serbia, the UK and Uruguay
4 LSMS (The World Bank):
Albania, B& H, Bulgaria, Kazakhstan, Kyrgistan, Serbia and Tajikistan
20. Statistical discrimination at young age:
Data & method
(II) Measuring the adjusted gender wage gap
Collecting individual level data
1 Harmonized data sources:
2 Longitudinal data
3 Labor Force Surveys and Household Budget Surveys:
4 LSMS (The World Bank):
In total:
– unbalanced panel 56 countries from early 1980s onwards
– ∼ 1258 measures of the Adjusted GWG
details
21. Statistical discrimination at young age:
Data & method
(III) Instruments
Compulsory schooling ⇒ fertility (Black et al. 2008, Cygan-Rehm and Maeder 2013)
Source: Compulsory schooling: UNESCO + papers for earlier years
22. Statistical discrimination at young age:
Data & method
(III) Instruments
Compulsory schooling ⇒ fertility (Black et al. 2008, Cygan-Rehm and Maeder 2013)
Source: Compulsory schooling: UNESCO + papers for earlier years
Military conscription ⇒ the timing of family formation
Source: Mulligan and Shleifer (2005) + Military Balance
23. Statistical discrimination at young age:
Data & method
(III) Instruments
Compulsory schooling ⇒ fertility (Black et al. 2008, Cygan-Rehm and Maeder 2013)
Source: Compulsory schooling: UNESCO + papers for earlier years
Military conscription ⇒ the timing of family formation
Source: Mulligan and Shleifer (2005) + Military Balance
Mothers’ fertility (intergenerational transmission of norms)
Source: The World Bank
24. Statistical discrimination at young age:
Data & method
(III) Instruments
Compulsory schooling ⇒ fertility (Black et al. 2008, Cygan-Rehm and Maeder 2013)
Source: Compulsory schooling: UNESCO + papers for earlier years
Military conscription ⇒ the timing of family formation
Source: Mulligan and Shleifer (2005) + Military Balance
Mothers’ fertility (intergenerational transmission of norms)
Source: The World Bank
Authorization of contraceptive pills ⇒ female education, family and labor supply
(US: Goldin and Katz 2002, Bailey 2006, Ananat and Hungerman 2012)
Source: Finlay, Canning and Po (2012)
25. Statistical discrimination at young age:
Data & method
(III) Instruments - a small bit of history
The pill first invented in 1940s in the UK, the first approved patent in the US in 1960
26. Statistical discrimination at young age:
Data & method
(III) Instruments - a small bit of history
The pill first invented in 1940s in the UK, the first approved patent in the US in 1960
Adoption timing varied a lot, even in Europe
27. Statistical discrimination at young age:
Data & method
(III) Instruments - a small bit of history
The pill first invented in 1940s in the UK, the first approved patent in the US in 1960
Adoption timing varied a lot, even in Europe
Eastern European countries were forerunners
Portugal and Spain lagged behind (late 60’s and 70’s)
The latest: Norway
28. Statistical discrimination at young age:
Data & method
(III) Instruments - a small bit of history
The pill first invented in 1940s in the UK, the first approved patent in the US in 1960
Adoption timing varied a lot, even in Europe
Admission ̸= access (→ timing)
29. Statistical discrimination at young age:
Data & method
(III) Instruments - a small bit of history
The pill first invented in 1940s in the UK, the first approved patent in the US in 1960
Adoption timing varied a lot, even in Europe
Admission ̸= access (→ timing)
E.g. former socialist countries: admitted but unavailable
Prescriptions vs otc
The UK originally admitted it only for married women
30. Statistical discrimination at young age:
Data & method
(III) Instruments - a small bit of history
The pill first invented in 1940s in the UK, the first approved patent in the US in 1960
Adoption timing varied a lot, even in Europe
Admission ̸= access (→ timing)
Until today persistent differences in use as contraceptive
∼ 38% in W. Europe; ∼ 14% E. Europe but 48% (!) in Czech Republic
31. Statistical discrimination at young age:
Data & method
Estimation procedure
AGWGi,s,t = α + β × time + γ [
MABi,t + ξs + ϵi,s,t
MABi,t = ϕ + θPILLi,t + ϱEDUi,t + µCONSCRi,t + ςM FERTi,t + εi,t
Variation in pill authorizaton: one data-point for each country
We use 2SLS for panel data as in Baltagi and coauthors (1981, 1992, 2000)
It is a random effects model (FGLS)
but... instrumentation is different
Additional instruments are redundant in White sense
→ standard errors adjusted to unbalanced panels
32. Statistical discrimination at young age:
Results
Raw correlation between MAB and AGWG
AGWGc,t = 0.88 − 0.028 MABc,t + ϵc,t
(0.046) (0.001)
More descriptives
33. Statistical discrimination at young age:
Results
The effect of delayed fertility on AGWG - IVs
Gender wage Youth, MAB, AGWG Youth All
gap IV OLS TFR, AGWG, OLS
(1) (2) (3) (4) (5) (6) (7)
Fertility -0.026*** -0.042*** -0.031*** -0.023*** -0.020* -0.055* 0.020
(0.007) (0.011) (0.013) (0.009) (0.012) (0.030) (0.018)
R-squared 0.275 0.280 0.277 0.271 0.617 0.559 0.836
F − statistic 12,162 6,891 263.6 289.4 - - -
Observations 1,067 1,081 1,120 1,100 1,128 1,186 1,226
Cluster SE Yes Yes Yes Yes Yes Yes Yes
Time trends Yes Yes Yes Yes Yes Yes Yes
IVs All CS, MS Pill MF - - -
More demanding AGWG
34. Statistical discrimination at young age:
Results
The effect of delayed fertility on AGWG - Robustness checks
HDFE Quantile Regression Heterogeneous fertility
(1) (2) (3) (4) (5) (6)
Q25 Q50 Q75 Intercepts Slopes
MAB -0.012 *** -0.023 *** -0.022 *** -0.032 ***
[-0.02,-0.00] [-0.03,-0.01] [-0.03,-0.01] [-0.04,-0.02]
MAB< Q25 0.133 *** -0.018
[0.07,0.20] [-0.05,0.02]
MAB ∈ [Q25, Q75] 0.027 -0.019
[-0.03,0.08] [-0.05,0.01]
MAB> Q75 -0.019
[-0.05,0.01]
35. Statistical discrimination at young age:
Results
Finding a benchmark
How do our estimates compare to differences in costs faced by employers?
36. Statistical discrimination at young age:
Results
Finding a benchmark
How do our estimates compare to differences in costs faced by employers?
We need information on
Probability of becoming a parent
→ Age-specific fertility rates
Differences in cost of childbearing / rearing
→ Time-use surveys / ISSP
→ Diff-in-Diff : men vs women, parents vs childless
38. Statistical discrimination at young age:
Summary
Summary
Do employers discriminate statistically? Tentatively yes
Delayed fertility among youth → GWG ↓
39. Statistical discrimination at young age:
Summary
Summary
Do employers discriminate statistically? Tentatively yes
Delayed fertility among youth → GWG ↓
IV estimates ∼ −0.03 (out of AGWG ∼ 0.12 on average)
Estimates stable and robust across model specifications
40. Statistical discrimination at young age:
Summary
Summary
Do employers discriminate statistically? Tentatively yes
Delayed fertility among youth → GWG ↓
IV estimates ∼ −0.03 (out of AGWG ∼ 0.12 on average)
Estimates stable and robust across model specifications
IV and OLS similar, but F-statistics strong
41. Statistical discrimination at young age:
Summary
Summary
Do employers discriminate statistically? Tentatively yes
Delayed fertility among youth → GWG ↓
IV estimates ∼ −0.03 (out of AGWG ∼ 0.12 on average)
Estimates stable and robust across model specifications
IV and OLS similar, but F-statistics strong
Benchmarking: ∆c × π “explains away” AGWG sometimes
→ employers may receive signals correctly, but rarely do
42. Statistical discrimination at young age:
Summary
Questions or suggestions?
Thank you!
w: grape.org.pl
t: grape org
f: grape.org
e: lvandervelde[at]grape.org.pl
45. Statistical discrimination at young age:
Summary
Trends in gender wage gaps
All age groups Youth
Raw GWG Adjusted GWG Raw GWG Adjusted GWG
(1) (2) (3) (4)
Year -0.160 -0.0308 -0.164** -0.158**
(0.101) (0.0662) (0.0773) (0.0705)
Observations 1,151 1,151 1,128 1,128
R-squared 0.204 0.117 0.105 0.108
Mean value 16.28 17.60 7.93 12.23
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