Robust evidence for link between GEG/GWG and necessity self-employment among women
Weak or no evidence for aspirations
Previous results were due to country specificity (no macro effects once accounting for country fixed effects)
Pushed into necessity? Gender gaps in the labor market and entrepreneurship o...GRAPE
Theoretical literature on entrepreneurship hints that labor market inequality may constitute a relevant push factor for necessity self-employment, as opposed to aspirational self-employment. Drawing on empirical confirmation, this insight is used in many policy recommendations. We provide a new approach to test and quantify the link between labor market inequality and self-employment. We exploit rich and diverse international data on patterns of self-employment from the Global Entrepreneurship Monitor. We focus on measures of labor market inequality for women, utilizing estimates of adjusted gender wage and gender employment gap, comparable for a large selection of countries and years. Our results show that greater gender disparities in access to and in compensation for wage employment are associated with necessity self-employment, but the effect is small. We find no link for the aspirational self-employment.
Resolution Foundation held an event on job polarisation with guest speakers Craig Holmes, Economist at Pembroke College, Oxford and Andrea Salvatori, Research Fellow at the University of Essex.
Career instability in a context of technological changeGRAPE
Automation has affected our daily routine including our works in many ways. Many tasks can now be done by machines, allowing a man to perform the job that was done previously by several of them. The question, then, is what happen to those others. Did they experience more difficulties in finding new employment? Did they switch to new flourishing occupations?
Productivity and inequality effects of rapid labor reallocationGRAPE
What happens when an economy faces a shock so severe that shakes the employment structure? Sure, workers move across sectors and overall productivity might increase, but at what cost? Here we exploit the quasi-natural experiment following transition to understand what are the short and long run effects of labor market reallocation. Our results suggest that inequalities increase in the short run,without a significant increase in productivity. In the long run, the effects seem to be negligible.
Can we really explain worker flows in transition?GRAPE
While many studied job flows in transition economies, our knowledge of what happened since the fall of the URSS is still limited to a few countries and a few years. In this presentation we use the Life in Transition Survey to look at a more general picture. Our findings suggest that most of reallocation came in the form of demographic changes - the entrance of young better prepared cohort and the movement to retirement of older cohort.
Pushed into necessity? Gender gaps in the labor market and entrepreneurship o...GRAPE
Theoretical literature on entrepreneurship hints that labor market inequality may constitute a relevant push factor for necessity self-employment, as opposed to aspirational self-employment. Drawing on empirical confirmation, this insight is used in many policy recommendations. We provide a new approach to test and quantify the link between labor market inequality and self-employment. We exploit rich and diverse international data on patterns of self-employment from the Global Entrepreneurship Monitor. We focus on measures of labor market inequality for women, utilizing estimates of adjusted gender wage and gender employment gap, comparable for a large selection of countries and years. Our results show that greater gender disparities in access to and in compensation for wage employment are associated with necessity self-employment, but the effect is small. We find no link for the aspirational self-employment.
Resolution Foundation held an event on job polarisation with guest speakers Craig Holmes, Economist at Pembroke College, Oxford and Andrea Salvatori, Research Fellow at the University of Essex.
Career instability in a context of technological changeGRAPE
Automation has affected our daily routine including our works in many ways. Many tasks can now be done by machines, allowing a man to perform the job that was done previously by several of them. The question, then, is what happen to those others. Did they experience more difficulties in finding new employment? Did they switch to new flourishing occupations?
Productivity and inequality effects of rapid labor reallocationGRAPE
What happens when an economy faces a shock so severe that shakes the employment structure? Sure, workers move across sectors and overall productivity might increase, but at what cost? Here we exploit the quasi-natural experiment following transition to understand what are the short and long run effects of labor market reallocation. Our results suggest that inequalities increase in the short run,without a significant increase in productivity. In the long run, the effects seem to be negligible.
Can we really explain worker flows in transition?GRAPE
While many studied job flows in transition economies, our knowledge of what happened since the fall of the URSS is still limited to a few countries and a few years. In this presentation we use the Life in Transition Survey to look at a more general picture. Our findings suggest that most of reallocation came in the form of demographic changes - the entrance of young better prepared cohort and the movement to retirement of older cohort.
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.
We explore the topic of female entrepreneurship, its character (necessity or opportunity driven) and gender inequality (wage and employment). We find that when the gender gaps are larger women are more likely to start own firm, but they claim that this decision is driven only by necessity.
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.
We investigate how women’s attitude and realization of choices towards equal participation in the labor market changes with age, and how these patterns differ between generations in transition and Western economies. As transition countries experienced a drop in employment rates regardless of gender, we study the relative change in the position of women, compared to similarly endowed men. We find that disentangling age, time, and cohort effects is necessary to appropriately assess women’s progress on labor markets in transition. The results indicate that in Western Europe countries women born later have much more equal position on the labor market as compared to older birth cohorts, but this is not the case in transition economies.
Matching it up: non-standard work and job satisfaction.pdfGRAPE
We leverage the flexibility enactment theory to study the link between working arrangements and job satisfaction. We propose that this link is moderated by individual inclination to non-standard working arrangements. Thus, we provide novel insights on the (mis)match between preferred and actual working arrangements. We apply this approach to data from the European Working Conditions Survey and empirically characterize the extent of mismatch in working arrangements across European countries. We shed new light on several phenomena. First, the extent of mismatch is substantial and reallocating workers between jobs could substantially boost overall job satisfaction in European countries. Second, the mismatch more frequently affects women and parents. Finally, we demonstrate that the extent of mismatch differs across European countries, which hints that one-size-fits-all policies, whether they deregulate or curb non-standard arrangements, are not likely to maximize the happiness of workers.
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.
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.
Introduction to Factor Analysis for and With Mixed Methods: British Academy ...Wendy Olsen
In this presentation, we set up the aims and mechanisms of the Workshop on Integrated Mixed Methods Research held at University of Manchester (Nov. 3, 2014); it specifically focuses on Factor Analysis, which creates a scale for a gender norm about labour markets. We show how a classical scale and a factor are similar, how they relate to regression and to labour supply, and how NVIVO can be used to follow up a mixed methods workshop or focus group. This creates a mixed-methods approach to gender norms in the labour market. Quite original and very promising. The workshop was a huge success running from 10 am to 3 pm following by an extra hour discussing how this leads to possible research opportunities.
Gender Levers at the State-Market Nexus: Bringing Organizations Back InTITA research
Lynn Prince Cooke: Gender Equality Levers at the State-Market Nexus: Bringing Organizations Back In. Presentation at TITA Annual Research Meeting, Turku 15.-16.9.2016.
(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(
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.
Economies and societies become more interdependent, the need to enhance our understanding of the world of work becomes increasingly important. Timely and focused information on the world's labor markets is essential. So Developed a project on Employment Trends
When the opportunity knocks: large structural shocks and gender wage gapsGRAPE
Undergoing a large structural shock, labor markets may become less inclusive. We test for this thesis analyzing the behavior of adjusted gender wage gaps in a wide selection of transition countries. We estimate comparable measures of adjusted gender wage gaps for a comprehensive selection of transition countries over a period spanning nearly three decades. We combine these estimates with measures of labor market reallocation in transition economies. We identify the episodes of particularly large labor market reallocations and observe the behavior of the gender wage gaps subsequent these episodes, and exploit the discontinuity between the cohorts participating in the labor market prior to the onset of transition and cohorts of subsequent entrants. Our analysis reveals a distinctive role played by separations from the state-owned manufacturing firms, leading to greater adjusted gender wage gaps. In the medium run the adverse effects of separation hikes from this sector are even more pronounced.
We study how the adjusted gender wage gap, sometimes refer to as discrimination component, changes as women age. We compare several theories and evaluates the validity of their claims against data from Germany. Results indicate that the gender wage gap grows non-monotonically as women age. In consequence, policies aim to address gender differences should also tackle inequalities among workers close to retirement age.
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.
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.
More Related Content
Similar to Pushed into necessity? Gender gaps in the labor market and entrepreneurship of women
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.
We explore the topic of female entrepreneurship, its character (necessity or opportunity driven) and gender inequality (wage and employment). We find that when the gender gaps are larger women are more likely to start own firm, but they claim that this decision is driven only by necessity.
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.
We investigate how women’s attitude and realization of choices towards equal participation in the labor market changes with age, and how these patterns differ between generations in transition and Western economies. As transition countries experienced a drop in employment rates regardless of gender, we study the relative change in the position of women, compared to similarly endowed men. We find that disentangling age, time, and cohort effects is necessary to appropriately assess women’s progress on labor markets in transition. The results indicate that in Western Europe countries women born later have much more equal position on the labor market as compared to older birth cohorts, but this is not the case in transition economies.
Matching it up: non-standard work and job satisfaction.pdfGRAPE
We leverage the flexibility enactment theory to study the link between working arrangements and job satisfaction. We propose that this link is moderated by individual inclination to non-standard working arrangements. Thus, we provide novel insights on the (mis)match between preferred and actual working arrangements. We apply this approach to data from the European Working Conditions Survey and empirically characterize the extent of mismatch in working arrangements across European countries. We shed new light on several phenomena. First, the extent of mismatch is substantial and reallocating workers between jobs could substantially boost overall job satisfaction in European countries. Second, the mismatch more frequently affects women and parents. Finally, we demonstrate that the extent of mismatch differs across European countries, which hints that one-size-fits-all policies, whether they deregulate or curb non-standard arrangements, are not likely to maximize the happiness of workers.
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.
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.
Introduction to Factor Analysis for and With Mixed Methods: British Academy ...Wendy Olsen
In this presentation, we set up the aims and mechanisms of the Workshop on Integrated Mixed Methods Research held at University of Manchester (Nov. 3, 2014); it specifically focuses on Factor Analysis, which creates a scale for a gender norm about labour markets. We show how a classical scale and a factor are similar, how they relate to regression and to labour supply, and how NVIVO can be used to follow up a mixed methods workshop or focus group. This creates a mixed-methods approach to gender norms in the labour market. Quite original and very promising. The workshop was a huge success running from 10 am to 3 pm following by an extra hour discussing how this leads to possible research opportunities.
Gender Levers at the State-Market Nexus: Bringing Organizations Back InTITA research
Lynn Prince Cooke: Gender Equality Levers at the State-Market Nexus: Bringing Organizations Back In. Presentation at TITA Annual Research Meeting, Turku 15.-16.9.2016.
(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(
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.
Economies and societies become more interdependent, the need to enhance our understanding of the world of work becomes increasingly important. Timely and focused information on the world's labor markets is essential. So Developed a project on Employment Trends
When the opportunity knocks: large structural shocks and gender wage gapsGRAPE
Undergoing a large structural shock, labor markets may become less inclusive. We test for this thesis analyzing the behavior of adjusted gender wage gaps in a wide selection of transition countries. We estimate comparable measures of adjusted gender wage gaps for a comprehensive selection of transition countries over a period spanning nearly three decades. We combine these estimates with measures of labor market reallocation in transition economies. We identify the episodes of particularly large labor market reallocations and observe the behavior of the gender wage gaps subsequent these episodes, and exploit the discontinuity between the cohorts participating in the labor market prior to the onset of transition and cohorts of subsequent entrants. Our analysis reveals a distinctive role played by separations from the state-owned manufacturing firms, leading to greater adjusted gender wage gaps. In the medium run the adverse effects of separation hikes from this sector are even more pronounced.
We study how the adjusted gender wage gap, sometimes refer to as discrimination component, changes as women age. We compare several theories and evaluates the validity of their claims against data from Germany. Results indicate that the gender wage gap grows non-monotonically as women age. In consequence, policies aim to address gender differences should also tackle inequalities among workers close to retirement age.
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.
Similar to Pushed into necessity? Gender gaps in the labor market and entrepreneurship of women (20)
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 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.
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.
Exploring Abhay Bhutada’s Views After Poonawalla Fincorp’s Collaboration With...beulahfernandes8
The financial landscape in India has witnessed a significant development with the recent collaboration between Poonawalla Fincorp and IndusInd Bank.
The launch of the co-branded credit card, the IndusInd Bank Poonawalla Fincorp eLITE RuPay Platinum Credit Card, marks a major milestone for both entities.
This strategic move aims to redefine and elevate the banking experience for customers.
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
Financial Assets: Debit vs Equity Securities.pptxWrito-Finance
financial assets represent claim for future benefit or cash. Financial assets are formed by establishing contracts between participants. These financial assets are used for collection of huge amounts of money for business purposes.
Two major Types: Debt Securities and Equity Securities.
Debt Securities are Also known as fixed-income securities or instruments. The type of assets is formed by establishing contracts between investor and issuer of the asset.
• The first type of Debit securities is BONDS. Bonds are issued by corporations and government (both local and national government).
• The second important type of Debit security is NOTES. Apart from similarities associated with notes and bonds, notes have shorter term maturity.
• The 3rd important type of Debit security is TRESURY BILLS. These securities have short-term ranging from three months, six months, and one year. Issuer of such securities are governments.
• Above discussed debit securities are mostly issued by governments and corporations. CERTIFICATE OF DEPOSITS CDs are issued by Banks and Financial Institutions. Risk factor associated with CDs gets reduced when issued by reputable institutions or Banks.
Following are the risk attached with debt securities: Credit risk, interest rate risk and currency risk
There are no fixed maturity dates in such securities, and asset’s value is determined by company’s performance. There are two major types of equity securities: common stock and preferred stock.
Common Stock: These are simple equity securities and bear no complexities which the preferred stock bears. Holders of such securities or instrument have the voting rights when it comes to select the company’s board of director or the business decisions to be made.
Preferred Stock: Preferred stocks are sometime referred to as hybrid securities, because it contains elements of both debit security and equity security. Preferred stock confers ownership rights to security holder that is why it is equity instrument
<a href="https://www.writofinance.com/equity-securities-features-types-risk/" >Equity securities </a> as a whole is used for capital funding for companies. Companies have multiple expenses to cover. Potential growth of company is required in competitive market. So, these securities are used for capital generation, and then uses it for company’s growth.
Concluding remarks
Both are employed in business. Businesses are often established through debit securities, then what is the need for equity securities. Companies have to cover multiple expenses and expansion of business. They can also use equity instruments for repayment of debits. So, there are multiple uses for securities. As an investor, you need tools for analysis. Investment decisions are made by carefully analyzing the market. For better analysis of the stock market, investors often employ financial analysis of companies.
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.
Application Process:
Find a USDA-Approved Lender: Not all lenders offer USDA loans, so it's essential to choose one approved by the USDA.
Pre-Qualification: Determine your eligibility and the amount you can borrow.
Property Search: Look for properties in eligible rural or suburban areas.
Loan Application: Submit your application, including financial and personal information.
Processing and Approval: The lender and USDA will review your application. If approved, you can proceed to closing.
USDA loans are an excellent option for those looking to buy a home in California's rural and suburban areas. With no down payment and flexible requirements, these loans make homeownership more attainable for many families. Explore your eligibility today and take the first step toward owning your dream home.
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
US Economic Outlook - Being Decided - M Capital Group August 2021.pdfpchutichetpong
The U.S. economy is continuing its impressive recovery from the COVID-19 pandemic and not slowing down despite re-occurring bumps. The U.S. savings rate reached its highest ever recorded level at 34% in April 2020 and Americans seem ready to spend. The sectors that had been hurt the most by the pandemic specifically reduced consumer spending, like retail, leisure, hospitality, and travel, are now experiencing massive growth in revenue and job openings.
Could this growth lead to a “Roaring Twenties”? As quickly as the U.S. economy contracted, experiencing a 9.1% drop in economic output relative to the business cycle in Q2 2020, the largest in recorded history, it has rebounded beyond expectations. This surprising growth seems to be fueled by the U.S. government’s aggressive fiscal and monetary policies, and an increase in consumer spending as mobility restrictions are lifted. Unemployment rates between June 2020 and June 2021 decreased by 5.2%, while the demand for labor is increasing, coupled with increasing wages to incentivize Americans to rejoin the labor force. Schools and businesses are expected to fully reopen soon. In parallel, vaccination rates across the country and the world continue to rise, with full vaccination rates of 50% and 14.8% respectively.
However, it is not completely smooth sailing from here. According to M Capital Group, the main risks that threaten the continued growth of the U.S. economy are inflation, unsettled trade relations, and another wave of Covid-19 mutations that could shut down the world again. Have we learned from the past year of COVID-19 and adapted our economy accordingly?
“In order for the U.S. economy to continue growing, whether there is another wave or not, the U.S. needs to focus on diversifying supply chains, supporting business investment, and maintaining consumer spending,” says Grace Feeley, a research analyst at M Capital Group.
While the economic indicators are positive, the risks are coming closer to manifesting and threatening such growth. The new variants spreading throughout the world, Delta, Lambda, and Gamma, are vaccine-resistant and muddy the predictions made about the economy and health of the country. These variants bring back the feeling of uncertainty that has wreaked havoc not only on the stock market but the mindset of people around the world. MCG provides unique insight on how to mitigate these risks to possibly ensure a bright economic future.
Introduction to Indian Financial System ()Avanish Goel
The financial system of a country is an important tool for economic development of the country, as it helps in creation of wealth by linking savings with investments.
It facilitates the flow of funds form the households (savers) to business firms (investors) to aid in wealth creation and development of both the parties
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
How to get verified on Coinbase Account?_.docxBuy bitget
t's important to note that buying verified Coinbase accounts is not recommended and may violate Coinbase's terms of service. Instead of searching to "buy verified Coinbase accounts," follow the proper steps to verify your own account to ensure compliance and security.
what is the future of Pi Network currency.DOT TECH
The future of the Pi cryptocurrency is uncertain, and its success will depend on several factors. Pi is a relatively new cryptocurrency that aims to be user-friendly and accessible to a wide audience. Here are a few key considerations for its future:
Message: @Pi_vendor_247 on telegram if u want to sell PI COINS.
1. Mainnet Launch: As of my last knowledge update in January 2022, Pi was still in the testnet phase. Its success will depend on a successful transition to a mainnet, where actual transactions can take place.
2. User Adoption: Pi's success will be closely tied to user adoption. The more users who join the network and actively participate, the stronger the ecosystem can become.
3. Utility and Use Cases: For a cryptocurrency to thrive, it must offer utility and practical use cases. The Pi team has talked about various applications, including peer-to-peer transactions, smart contracts, and more. The development and implementation of these features will be essential.
4. Regulatory Environment: The regulatory environment for cryptocurrencies is evolving globally. How Pi navigates and complies with regulations in various jurisdictions will significantly impact its future.
5. Technology Development: The Pi network must continue to develop and improve its technology, security, and scalability to compete with established cryptocurrencies.
6. Community Engagement: The Pi community plays a critical role in its future. Engaged users can help build trust and grow the network.
7. Monetization and Sustainability: The Pi team's monetization strategy, such as fees, partnerships, or other revenue sources, will affect its long-term sustainability.
It's essential to approach Pi or any new cryptocurrency with caution and conduct due diligence. Cryptocurrency investments involve risks, and potential rewards can be uncertain. The success and future of Pi will depend on the collective efforts of its team, community, and the broader cryptocurrency market dynamics. It's advisable to stay updated on Pi's development and follow any updates from the official Pi Network website or announcements from the team.
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
Pushed into necessity? Gender gaps in the labor market and entrepreneurship of women
1. Pushed into necessity?
Pushed into necessity?
Gender gaps in the labor market and entrepreneurship of women
Work in progress. All comments welcome
Joanna Tyrowicz and Magdalena Smyk
FAME|GRAPE & University of Warsaw
May 2017
2. Pushed into necessity?
Motivation
Pushed or pulled?
Long standing debate: pushed or pulled
mixed evidence, rarely direct
positive (aspirations) vs. negative - lack of alternatives
3. Pushed into necessity?
Motivation
Pushed or pulled?
Long standing debate: pushed or pulled
mixed evidence, rarely direct
positive (aspirations) vs. negative - lack of alternatives
Story behind “discrimination” – can arguments work?
no: clients’ taste + co-workers’ taste
yes: statistical
Methodological constraints
usually cannot observe that someone was “discriminated against”...
... prior to becoming self-employed
5. Pushed into necessity?
Motivation
Preview of results
Our contribution
1 Split by necessity and aspirations self-employment
2 Exploit cross-country & time variation of labor market gaps
6. Pushed into necessity?
Motivation
Preview of results
Our contribution
1 Split by necessity and aspirations self-employment
2 Exploit cross-country & time variation of labor market gaps
⇒ estimates available for gender employment & wage gaps (GEG, GWG)
7. Pushed into necessity?
Motivation
Preview of results
Our contribution
1 Split by necessity and aspirations self-employment
2 Exploit cross-country & time variation of labor market gaps
⇒ estimates available for gender employment & wage gaps (GEG, GWG)
Intuitions ⇒ hypotheses
Inequality as a push factor may matter for necessity SE ...
... but should not matter for aspirations
Wage inequality may operate weaker than employment inequality
8. Pushed into necessity?
Motivation
Preview of results
Our contribution
1 Split by necessity and aspirations self-employment
2 Exploit cross-country & time variation of labor market gaps
⇒ estimates available for gender employment & wage gaps (GEG, GWG)
Intuitions ⇒ hypotheses
Inequality as a push factor may matter for necessity SE ...
... but should not matter for aspirations
Wage inequality may operate weaker than employment inequality
We find that:
positive & robust effect of GEG/GWG on necessity female entrepreneurship
no link for aspirational entrepreneurship
10. Pushed into necessity?
Insights & theory
Insights from earlier studies
Unemployment as push factor to entrepreneurship
positive - lower opportunity costs (Evans and Jovanovic 1989, Blanchflower and
Meyer 1994)
negative - lack of physical capital (Johansson 2000, Hurst and Lusardi 2004)
11. Pushed into necessity?
Insights & theory
Insights from earlier studies
Unemployment as push factor to entrepreneurship
positive - lower opportunity costs (Evans and Jovanovic 1989, Blanchflower and
Meyer 1994)
negative - lack of physical capital (Johansson 2000, Hurst and Lusardi 2004)
Entrepreneurship among women
different types of products and services (Coleman 2000, Verheul et al. 2006,
Orser et al. 2006)
enhancing women’s relative power in the household (returns from education,
children development, work-life balance; Minniti and Naude 2010)
12. Pushed into necessity?
Insights & theory
Insights from earlier studies
Unemployment as push factor to entrepreneurship
positive - lower opportunity costs (Evans and Jovanovic 1989, Blanchflower and
Meyer 1994)
negative - lack of physical capital (Johansson 2000, Hurst and Lusardi 2004)
Entrepreneurship among women
different types of products and services (Coleman 2000, Verheul et al. 2006,
Orser et al. 2006)
enhancing women’s relative power in the household (returns from education,
children development, work-life balance; Minniti and Naude 2010)
gendered institutions - women react stronger to institutional barriers (Estrin and
Mickiewicz 2011)
education, empowerment, unadjusted wage gap (Kobeissi 2010)
13. Pushed into necessity?
Insights & theory
Insights from earlier studies
Unemployment as push factor to entrepreneurship
positive - lower opportunity costs (Evans and Jovanovic 1989, Blanchflower and
Meyer 1994)
negative - lack of physical capital (Johansson 2000, Hurst and Lusardi 2004)
Entrepreneurship among women
different types of products and services (Coleman 2000, Verheul et al. 2006,
Orser et al. 2006)
enhancing women’s relative power in the household (returns from education,
children development, work-life balance; Minniti and Naude 2010)
gendered institutions - women react stronger to institutional barriers (Estrin and
Mickiewicz 2011)
education, empowerment, unadjusted wage gap (Kobeissi 2010) ⇒ similarities vs
differences
14. Pushed into necessity?
Insights & theory
How to conceptualize
Extend the model by Fonseca et al (2001)
V - SE payoff, U - work payoff, K - start-up cost and α - distribution of
enterpreneurial skill
Individuals may have a gender
15. Pushed into necessity?
Insights & theory
How to conceptualize
Extend the model by Fonseca et al (2001)
V - SE payoff, U - work payoff, K - start-up cost and α - distribution of
enterpreneurial skill
Individuals may have a gender ⇒ women are disadvantaged in employment /
wages (but not productivity): U(1 − gap).
16. Pushed into necessity?
Insights & theory
How to conceptualize
Extend the model by Fonseca et al (2001)
V - SE payoff, U - work payoff, K - start-up cost and α - distribution of
enterpreneurial skill
Individuals may have a gender ⇒ women are disadvantaged in employment /
wages (but not productivity): U(1 − gap).
m and f - costs of being self-employed are also gender-specific.
17. Pushed into necessity?
Insights & theory
How to conceptualize
Extend the model by Fonseca et al (2001)
V - SE payoff, U - work payoff, K - start-up cost and α - distribution of
enterpreneurial skill
Individuals may have a gender ⇒ women are disadvantaged in employment /
wages (but not productivity): U(1 − gap).
m and f - costs of being self-employed are also gender-specific.
For becoming self-employed:
M: (α − m)V − K > U ⇒ Sm =
U + K
V
+ m,
W: (α − f )V − K > U(1 − gap) ⇒ Sw =
U + K − gap ∗ U
V
+ w
18. Pushed into necessity?
Insights & theory
How to conceptualize
Extend the model by Fonseca et al (2001)
V - SE payoff, U - work payoff, K - start-up cost and α - distribution of
enterpreneurial skill
Individuals may have a gender ⇒ women are disadvantaged in employment /
wages (but not productivity): U(1 − gap).
m and f - costs of being self-employed are also gender-specific.
For becoming self-employed:
M: (α − m)V − K > U ⇒ Sm =
U + K
V
+ m,
W: (α − f )V − K > U(1 − gap) ⇒ Sw =
U + K − gap ∗ U
V
+ w
This yields a gap in
1
1 − F(Sw )
−
1
1 − F(Sm)
= −
gap ∗ U
V
+ (w − m) (1)
negative so long as m is sufficiently smaller than w.
(w − m) is likely to be a country specific effect.
20. Pushed into necessity?
Method
What do we do
1 GEM: separate self-employment out of necessity and aspirational self-employment
2 Indicators of gender wage gap and employment gap adjusted for individual
characteristics
21. Pushed into necessity?
Method
What do we do
1 GEM: separate self-employment out of necessity and aspirational self-employment
2 Indicators of gender wage gap and employment gap adjusted for individual
characteristics
3 Use theoretical model for econometric specification
22. Pushed into necessity?
Method
What do we do
1 GEM: separate self-employment out of necessity and aspirational self-employment
2 Indicators of gender wage gap and employment gap adjusted for individual
characteristics
3 Use theoretical model for econometric specification
4 Multi-level regression (following Estrin and coauthors)
23. Pushed into necessity?
Method
How to measure gender inequality?
Gender wage gaps
Nopo et al (2011) for 64 countires (cross-section)
Tyrowicz & van der Velde (2016) for app. 500 data points (time and
cross-section)
24. Pushed into necessity?
Method
How to measure gender inequality?
Gender wage gaps
Nopo et al (2011) for 64 countires (cross-section)
Tyrowicz & van der Velde (2016) for app. 500 data points (time and
cross-section)
Gender employment gaps
Goraus , Tyrowicz & van der Velde (2016) for app. 1200 data points (time and
cross-section)
25. Pushed into necessity?
Method
How to measure gender inequality?
Gender wage gaps
Nopo et al (2011) for 64 countires (cross-section)
Tyrowicz & van der Velde (2016) for app. 500 data points (time and
cross-section)
Gender employment gaps
Goraus , Tyrowicz & van der Velde (2016) for app. 1200 data points (time and
cross-section)
Gender equality index from ISD
robustness check
26. Pushed into necessity?
Method
Data on entrepreneurship and self-employment
Global Entrepreneurship Monitor
Adult Population Survey - representative for working population
At least two thousand respondents from each participating country (100+)
Questions (among others) on entrepreneurship activities, aspirations and plans
Three parts of the survey:
new firms ⇒ someone who has just established a firm
established firms ⇒ characteristics
business plans for the future ⇒ aspirations
27. Pushed into necessity?
Data
Matching between GEM and our data sources
GEM and GEG/GWG data available for diverse countries / years
Exact matching: that same year & country in both
Yields: 25 countries for GEG and 21 countries for GWG (dominated by
developed)
28. Pushed into necessity?
Data
Matching between GEM and our data sources
GEM and GEG/GWG data available for diverse countries / years
Exact matching: that same year & country in both
Yields: 25 countries for GEG and 21 countries for GWG (dominated by
developed)
If exact unavailable, inexact matching: +/- 5 years of GEM data relative to
GEG/GWG data
Yields 26 countries for GEG & GWG
29. Pushed into necessity?
Data
Matching between GEM and our data sources
GEM and GEG/GWG data available for diverse countries / years
Exact matching: that same year & country in both
Yields: 25 countries for GEG and 21 countries for GWG (dominated by
developed)
If exact unavailable, inexact matching: +/- 5 years of GEM data relative to
GEG/GWG data
Yields 26 countries for GEG & GWG
Check: ISD data yield 80 countries
30. Pushed into necessity?
Data
Descriptive statistics for women in the sample
Coverage by ISD GEG exact GWG exact
SE 5.8% 3.4% 3.7%
Necessity SE 1.6% 0.6% 0.8%
Opportunity SE 3.9% 2.6% 2.7%
EGA 23.5% 13.7% 12.1%
31. Pushed into necessity?
Data
Descriptive statistics for women in the sample
Coverage by ISD GEG exact GWG exact
SE 5.8% 3.4% 3.7%
Necessity SE 1.6% 0.6% 0.8%
Opportunity SE 3.9% 2.6% 2.7%
EGA 23.5% 13.7% 12.1%
Tertiary education 33.3% 34.4% 35.8%
Knows entrepreneur 32.6% 30% 30.5%
Knows business angel 2.5% 1.7% 2%
32. Pushed into necessity?
Data
Descriptive statistics for women in the sample
Coverage by ISD GEG exact GWG exact
SE 5.8% 3.4% 3.7%
Necessity SE 1.6% 0.6% 0.8%
Opportunity SE 3.9% 2.6% 2.7%
EGA 23.5% 13.7% 12.1%
Tertiary education 33.3% 34.4% 35.8%
Knows entrepreneur 32.6% 30% 30.5%
Knows business angel 2.5% 1.7% 2%
GEG exact match 23% 23% 32.6%
GWG exact match 20.2% 20.2% 20.2%
ISD 0.76 0.79 0.79
33. Pushed into necessity?
Data
Descriptive statistics for women in the sample
Coverage by ISD GEG exact GWG exact
SE 5.8% 3.4% 3.7%
Necessity SE 1.6% 0.6% 0.8%
Opportunity SE 3.9% 2.6% 2.7%
EGA 23.5% 13.7% 12.1%
Tertiary education 33.3% 34.4% 35.8%
Knows entrepreneur 32.6% 30% 30.5%
Knows business angel 2.5% 1.7% 2%
GEG exact match 23% 23% 32.6%
GWG exact match 20.2% 20.2% 20.2%
ISD 0.76 0.79 0.79
Countries 80 25 21
Country-year groups 394 185 53
34. Pushed into necessity?
Results
Necessity self-employment for women (multi-level regression)
Necessity SE (1) (2) (3) (4) (5)
for women
Country-year groups 185 53 191 175 185
Observations 339,702 101,616 344,308 326,663 339,702
GEG exact match 0.0060***
35. Pushed into necessity?
Results
Necessity self-employment for women (multi-level regression)
Necessity SE (1) (2) (3) (4) (5)
for women
Country-year groups 185 53 191 175 185
Observations 339,702 101,616 344,308 326,663 339,702
GEG exact match 0.0060***
GWG exact match 0.0021
36. Pushed into necessity?
Results
Necessity self-employment for women (multi-level regression)
Necessity SE (1) (2) (3) (4) (5)
for women
Country-year groups 185 53 191 175 185
Observations 339,702 101,616 344,308 326,663 339,702
GEG exact match 0.0060***
GWG exact match 0.0021
GEG inexact match 0.0064***
37. Pushed into necessity?
Results
Necessity self-employment for women (multi-level regression)
Necessity SE (1) (2) (3) (4) (5)
for women
Country-year groups 185 53 191 175 185
Observations 339,702 101,616 344,308 326,663 339,702
GEG exact match 0.0060***
GWG exact match 0.0021
GEG inexact match 0.0064***
GWG inexact match 0.0046*
38. Pushed into necessity?
Results
Necessity self-employment for women (multi-level regression)
Necessity SE (1) (2) (3) (4) (5)
for women
Country-year groups 185 53 191 175 185
Observations 339,702 101,616 344,308 326,663 339,702
GEG exact match 0.0060***
GWG exact match 0.0021
GEG inexact match 0.0064***
GWG inexact match 0.0046*
ISD gender equality -0.0205***
39. Pushed into necessity?
Results
Necessity self-employment for women (multi-level regression)
Necessity SE (1) (2) (3) (4) (5)
for women
Country-year groups 185 53 191 175 185
Observations 339,702 101,616 344,308 326,663 339,702
GEG exact match 0.0060***
GWG exact match 0.0021
GEG inexact match 0.0064***
GWG inexact match 0.0046*
ISD gender equality -0.0205***
Necessity SE - men 0.6242*** 0.6315*** 0.6237*** 0.9931*** 0.6346***
Age -0.0001*** -0.0001*** -0.0001*** -0.0001*** -0.0001***
Tertiary education 0.0004 0.0000 0.0004 0.0003 0.0003
Knows entrepreneur 0.0071*** 0.0079*** 0.0072*** 0.0072*** 0.0071***
Knows business angel 0.0118*** 0.0103*** 0.0116*** 0.0111*** 0.0118***
Constant 0.0010 0.0049*** 0.0011 -0.0021 0.0185***
40. Pushed into necessity?
Results
Opportunity self-employment and entrepreneurial growth aspirations (MLR)
(1) (2) (3) (4) (5) (6)
Opportunity SE for women =1 EGA
GEG inexact match 0.002 0.030
GWG inexact match 0.005 -0.021
ISD gender equality 0.029* 0.048
y variable - men 0.480*** 0.639*** 0.728*** 0.819*** 0.767*** 0.904***
Age -0.001*** -0.001*** -0.001*** -0.006*** -0.006*** -0.006***
Tertiary education 0.013*** 0.012*** 0.017*** 0.027*** 0.024*** 0.035***
Knows entrepreneur 0.040*** 0.040*** 0.049*** 0.055*** 0.058*** 0.070***
Knows bus angel 0.056*** 0.055*** 0.066*** 0.058*** 0.052*** 0.070***
Constant 0.007** -0.001 -0.027** 0.195*** 0.223*** 0.142***
Country-year groups 191 175 394 189 173 391
Observations 344,308 326,663 535,615 25,373 24,737 46,737
43. Pushed into necessity?
Conclusions
Conclusions
Robust evidence for link between GEG/GWG and necessity self-employment
among women
Weak or no evidence for aspirations
Previous results were due to country specificity (no macro effects once accounting
for country fixed effects)
44. Pushed into necessity?
Conclusions
Conclusions
Robust evidence for link between GEG/GWG and necessity self-employment
among women
Weak or no evidence for aspirations
Previous results were due to country specificity (no macro effects once accounting
for country fixed effects)
45. Pushed into necessity?
Conclusions
Conclusions
Robust evidence for link between GEG/GWG and necessity self-employment
among women
Weak or no evidence for aspirations
Previous results were due to country specificity (no macro effects once accounting
for country fixed effects)
What to do next?
Obtain counterfactual scenarios
Evaluate the effects of excess necessity on productivity