Difference between revisions of "Women in Entrepreneurship (Issue Brief)"
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Copyright © 2016 edegan.com. All Rights Reserved. |
Women in Entrepreneurship Lit Review
Contents
- 1 Spring 2017
- 2 Spring 2016
- 2.1 The Paper
- 2.2 The Research
- 2.3 creating basic tables
- 2.3.1 adding variable where if person is woman, adds value of 1 to their name
- 2.3.2 for people without a prefix, trying to assign gender variable to them based on list of common names
- 2.3.3 me playing around, these tables not relevant
- 2.3.4 assigning variable to titles
- 2.3.5 massive conglomeration table
- 2.3.6 tables for percent of women in a given job title
- 2.4 table for finding percentage of women in companies by state
Spring 2017
To-do
- Prior
- review/update lit review
- should come from both industry and academic sources
- review/update lit review
- Intro
- Update stats to reflect 2017
- citations
- add something specifically about the importance of women in leadership in vc companies
- Thesis/Issue Brief focus
- This issue brief has two broad goals. First, it will examine the role of women in entrepreneurship fields today by researching their representation in leadership positions of VC-backed companies. Second, it will examine the effectiveness of current policy related to women in entrepreneurship.
- Research
- search in SDC to reflect the current date rather than 2016
- add industry/other variables
- build SQL tables with the following parameters: group by state, role, city, msa, industry
- relationship between women in leadership roles and performance of the firm, where performance measured by no rounds invested/ipo
- state fix-effects
- search in SDC to reflect the current date rather than 2016
- Policy
- Trump's proposed policy changes that will impact vc-backed companies, entrepreneurship/innovation in general, women in the workplace
Timeline
- 1/24 - finish outline, reread tables/data collection process, update lit review
- 1/25 - SDC pull
- 1/30 - rerun through tables w new added variables (i.e. industry, etc)
- 1/31 - read over new data and refine into something presentable, find appropriate parameters for issue brief, etc. maybe start making charts and graphs if time. @ this point check in w ed
- 2/1 - finish making graphs and charts, research trump policy and write it up
- 2/3 - start finalizing paper, putting all the pieces of the puzzle together, any additions or time to fix things that went off schedule, last edits, submit paper to anne for review
SDC Search
pull 1
- Database Selection
- VentureXpert
- Portfolio Companies
- Search Items:
- Date that received company received first investment: 01/01/1980 to 01/01/2017
- venture-related deals
- Company Nation: U.S.
- Custom Report
- Company Founding Date
- Company IPO Date
- Date Received Last Investment
- Date Received First Investment
- Company Name
- Company State
- Company City
- Company VE Primary Industry Class
- Company VE Primary Industry Major Group
- Company 6-digit CUSIP
- Total amt invested in company
- No. Financing Rounds Company Received
- Executive's First Name
- Executive's Last Name
- Executive's Job Title
- Executive's Prefix
- VE Primary Industry Sub-Group 3
- VE Primary Industry Minor Group
- VE Primary Industry Sub-Group 1
- Company IPO
- Company Website
- Saved in 182 in mcnair/projects/women2017 as "pull1"
pull 3
- Database Selection
- VentureXpert
- Portfolio Companies
- Search Items:
- Date that received company received first investment: 01/01/1980 to 01/01/2017
- Venture related deals - select all venture related deals
- Company Nation: U.S.
- custom report
- company founding date
- company ipo date
- date company received last investment
- date company received first investment
- company staet
- company name
- company industry class
- company industry major group
- company industry subgroup 1
- company industry subgroup 3
- Company industry minor group
- company cusip
- total known amt invested in company
- no rouds company received investment
- company ipo status
- company website
- saved in 182 in mcnair/projects/women2017 as "pull3"
pull 4
- Database Selection
- VentureXpert
- Portfolio Companies
- Search Items:
- Date that received company received first investment: 01/01/1980 to 01/01/2017
- Venture-related deals
- Company Nation: U.S.
- custom report
- company name
- executive's name prefix
- executive's first name
- executive's last name
- executive's job title
- saved in 182 in mcnair/projects/women2017 as "pull4"
pull 5
- Database Selection
- VentureXpert
- Portfolio Companies
- Search Items:
- Date that received company received first investment: 01/01/1980 to 01/01/2017
- Venture-related deals
- Company Nation: U.S.
- custom report
- executive's name prefix
- executive's first name
- executive's last name
- executive's job title
- company name
- saved in 182 in mcnair/projects/women2017 as "pull5"
Spring 2016
The Paper
Introduction
Over the past century, the United States has witnessed two large-scale social trends involving women in entrepreneurship that have had a significant impact on the country's economic growth. First, huge numbers of women have made their way into the official labor force. Around this time 50 years ago (February 1966), women's labor force participation rate was 39.6%, but in February 2016, 56.8% of women participated in the labor force [1]. This demonstrates substantial growth in women's entry to the labor force. Second, women are achieving a higher degree of education than in years past. As labor market barriers to women have been lowered, the benefits of a college education have grown more for women than men, and females now outpace males in college enrollment. [2] This has provided women with similar access to the same jobs as men.
However, these trends have slowed from their early twenty-first century spikes; room for growth is smaller now than it was before. Economists predict that economic growth from these two trends is unlikely to be repeated to the same magnitude. With this, everyone is looking for the modern-day economy-boosting equivalent to women's entry to the labor force. Given the rising share of women among educated workers, it seems clear that the future of American economic growth is in the hands of women. Encouraging women to enter into fields of entrepreneurship, particularly high-growth entrepreneurship, might be the United States' silver bullet.
This issue brief aims to examine the role of women in entrepreneurship today by examining their jobs (or lack thereof) in entrepreneurship related fields, and examine the effectiveness of current policy related to women in entrepreneurship.
Status Quo
Our research
We examined all leaders in companies from 1980-2016 who have the titles of either chariman, CEO, CFO, COO, CIO, CTO, board member, President, Vice President, Founder, and Director. Of company members with those titles, only 29.8% were women. Of those women leaders, 22% were CEOs, 14% chairwomen, 27% CFOs, 26% COOs, 31% CIOs, 12% CTOs, 25% board members, 20% presidents, 34% vice presidents, 23% founders, and 39% directors. (from tables, PercentWomenXCompany, where X is job title)
Generally, the percentage of women in "leadership roles" in companies has trended upwards since 1980. (from companywomentot table) However, the number of women CEOs over the past two decades has not dramatically increased or decreased, aside from a dramatic upward spike in women CEOs during 2015. (from PercentWomenCEOCompanybyyear table)
Grouped by state, Michigan has highest percentage of women in leadership in its companies, coming in at 37.5%. Texas has 26.6%. Wyoming has a whopping 0%. (from womenstates)
These data show that of the women listed as "Company Executives", only a very small percentage have positions of power. However, this number has grown since 1980, which demonstrates a slow but positive growth of women in executive positions in general.
Info from external sources
Overall, women-owned businesses account for slightly less than 1/3 of all businesses in the United States. At first glance the statistics portray a positive picture for the field's growth: the number of women-owned firms has grown 68 percent since 2007, compared to only 47 percent for all businesses. [3]. However, these women owned businesses are typically only run by the woman herself; among employer firms, women-owned businesses account for only 16% of the total, and their shares of revenue and employees are in the single digits. [4]
The few women in entrepreneurial leadership roles also have to deal with negative societal perceptions of their jobs. According to data from a 2015 Pew Research Center survey, 43% of Americans believe that the U.S. is not prepared to hire women for top-tier executive positions. A relatively smaller, but still significant, number of Americans (23%) believe that women don’t have the time to hold an executive position, given their “family responsibilities”. [5]
The American public's generally negative perception of women in entrepreneurship presents itself institutionally as well. Even though female founders perform equal to or better than their male counterparts when raising money online, only 10 percent of startups which raised Series A last year had female founders. [6] Texas claims the worst record of supporting women seeking venture capital. Last year, 42 Texas startups got Series A rounds, yet not a single startup had female founders. In terms of venture capital structure, ninety-four percent of decision makers at venture capital funds are male, and 90% of today's venture capital funds never see a female founder. Among chief executives of S.&P. 1500 firms, for each woman, there are four men named John, Robert, William or James. [7] But venture capital firms with women partners are more than twice as likely to invest in companies with a woman on the executive team and three times as likely to invest in companies with women CEOs.
Though at first glance women-owned business growth seems striking, the numbers are deceptive in that their shares of revenue and employees are in single digits. Furthermore, women who do go into entrepreneurship face societal disapproval of their actions, with a plurality of Americans believing not only that the country is not prepared to hire women to executive positions, but also that women are incapable of holding these positions due to their family responsibilities. Further, women get start-up capital for their companies 2-3 times as often from women-led VC funds, but only 6% of decision makers at VC funds are women. It's no wonder women are vastly underrepresented in this field.
What women need
Almost half-of female founders (48 percent) cite a lack of available mentors or advisers as holding them back. A third say lack of capital is a constraint. [8]
Relevant policy
The Obama administration recognized the importance of expanding the role that women-owned businesses play in the national economy. Some of his initiatives include increasing access to capital, incentivizing small business growth and hiring, encouraging women owned business competition for government contracts, and enhancing long term survival of women owned businesses. Two primary pieces of legislation have bolstered the limited growth that the United States has seen in the field of women entrepreneurs, The Small Business Jobs Act of 2010 and the Women’s Equity in Contracting Act. Both of these seek to help businesses headed up by women win more government contracts.
The president has worked on increasing small business access to capital through the Recovery Act and the Small Business Jobs Act. Through this act, the president has reformed SBA lending practices and built on existing infrastructure. SBA loans are 3-5x more likely to go to women and minorities than traditional business loans. Over 12,000 SBA Recovery loans have gone to women-owned small businesses, totaling more than $3 billion. [9] The president has also increased tax cuts with the aim of helping small businesses invest in their firms and create jobs. Specific to women, the SBA opened several new Women's Business Centers in 2009 and 2010, bringing their total to 114.
Jessica Milli, senior research associate at the Institute of Women’s Policy Research, said things like the Jobs Act and SBA's programs for women "really aim to put women-owned businesses...at a competitive advantage. (They) restrict competition, which has really helped to boost revenues and help more businesses get into the industry.” But such policies can’t, and haven't, solved all the challenges inherent to being a female entrepreneur. Even with targeted legislation, women business owners still face a significant wage gap and continually have smaller amounts of start-up capital than their male peers.
Conclusion As women's prevalence in the United States workforce has increased, the United States has experienced an economic boom. However, women's numbers are still small in entrepreneurial fields, and even more microscopic in leadership positions in those fields. Current policy fails because it doesn't properly address women's lack of access to capital and mentorship. Moving forward, the United States must seek strategies to incentivize more women to enter the entrepreneurial workforce.
The Research
- SQL info can also be found on researcher@128.42.44.181 in the Women folder. Called "women.sql".
creating basic tables
DROP TABLE companyreal; CREATE TABLE companyreal( datefounded date, companyname varchar(100), prefix varchar(5), firstname varchar(100), lastname varchar(100), jobtitle varchar(100), companystate varchar(100), companycity varchar(100), industrygroup varchar(100), amtinvestedthous float, rounds int );
\COPY companyreal FROM 'womencompanieslast-normal.txt' WITH DELIMITER AS E'\t' HEADER NULL AS CSV --129536
DROP TABLE fundreal; CREATE TABLE fundreal( datefounded date, fundname varchar(100), prefix varchar(5), firstname varchar(100), lastname varchar(100), jobtitle varchar(100), fundstate varchar(100), fundcity varchar(100), fundtargetsizemil float, firmname varchar(100) );
\COPY fundreal FROM 'womenfundslast-normal.txt' WITH DELIMITER AS E'\t' HEADER NULL AS CSV --156005
adding variable where if person is woman, adds value of 1 to their name
DROP TABLE manwomanfund; CREATE TABLE manwomanfund AS SELECT prefix, lastname, datefounded, jobtitle, fundname, fundcity, fundstate, removeinitial(firstname) as firstname, CASE WHEN prefix='Ms' THEN 1::int WHEN prefix='Mr' THEN 0::int ELSE Null::int END AS womanman FROM fundreal; --156005
DROP TABLE manwomancompany; CREATE TABLE manwomancompany AS SELECT prefix, lastname, datefounded, jobtitle, companyname, companycity, companystate, industrygroup, removeinitial(firstname) as firstname, amtinvestedthous, rounds, CASE WHEN prefix='Ms' THEN 1::int WHEN prefix='Mr' THEN 0::int ELSE Null::int END AS womanman FROM companyreal; --129536
for people without a prefix, trying to assign gender variable to them based on list of common names
DROP TABLE manwomanfund2; CREATE TABLE manwomanfund2 AS SELECT datefounded, prefix, firstname, lastname, fundname, jobtitle, womanman AS origwomanman, mf, fundcity, fundstate, CASE WHEN womanman IS NULL AND mf IS NOT NULL THEN mf WHEN womanman IS NOT NULL THEN womanman ELSE NULL::int END AS womanman FROM manwomanfund LEFT JOIN commonnamesclean ON firstname = name WHERE firstname IS NOT NULL; --152819
DROP TABLE manwomancompany2; CREATE TABLE manwomancompany2 AS SELECT datefounded, prefix, firstname, lastname, companyname, jobtitle, womanman AS origwomanman, mf, companycity, companystate, industrygroup, rounds, amtinvestedthous, CASE WHEN womanman IS NULL AND mf IS NOT NULL THEN mf WHEN womanman IS NOT NULL THEN womanman ELSE NULL::int END AS womanman FROM manwomancompany LEFT JOIN commonnamesclean ON lower(firstname) = lower(name) WHERE firstname IS NOT NULL; --123278
--%, state, city, round no
me playing around, these tables not relevant
DROP TABLE fundWomenCEOs; CREATE TABLE fundwomentot AS SELECT EXTRACT(YEAR FROM datefounded), AVG(womanman) AS PercentWomen FROM manwomanfund2 GROUP BY EXTRACT(YEAR FROM datefounded); --37
DROP TABLE companyWomen; CREATE TABLE companywomentot AS SELECT EXTRACT(YEAR FROM datefounded), AVG(womanman) AS PercentWomen FROM manwomancompany2 GROUP BY EXTRACT(YEAR FROM datefounded); --36
DROP TABLE womencompanystate; CREATE TABLE womencompanystate AS SELECT companystate, AVG(womanman) AS WomenPerState FROM manwomancompany2 GROUP BY companystate; --51
DROP TABLE womenfundstate; CREATE TABLE womencfundstate AS SELECT fundstate, AVG(womanman) AS WomenPerState FROM manwomanfund2 GROUP BY fundstate; --51
DROP TABLE womencompanycity; CREATE TABLE womencompanycity AS SELECT companycity, AVG(womanman) AS WomenPerCity FROM manwomancompany2 GROUP BY companycity;
assigning variable to titles
DROP TABLE titles01; CREATE TABLE titles01( title varchar(100), chairman int, CEO int, CFO int, COO int, CIO int, CTO int, boardmember int, president int, vicepresident int, founder int, director int );
\COPY titles01 FROM 'impotitleslast.txt' WITH DELIMITER AS E'\t' HEADER NULL AS CSV
DROP TABLE title02;
massive conglomeration table
DROP TABLE ManWomanCompany3; CREATE TABLE ManWomanCompany3 AS SELECT Manwomancompany2.*, CASE WHEN chairman IS NOT NULL THEN 1::int ELSE 0::int END AS chairman, CASE WHEN CEO IS NOT NULL THEN 1::int ELSE 0::int END AS CEO, CASE WHEN CFO IS NOT NULL THEN 1::int ELSE 0::int END AS CFO, CASE WHEN COO IS NOT NULL THEN 1::int ELSE 0::int END AS COO, CASE WHEN CIO IS NOT NULL THEN 1::int ELSE 0::int END AS CIO, CASE WHEN CTO IS NOT NULL THEN 1::int ELSE 0::int END AS CTO, CASE WHEN boardmember IS NOT NULL THEN 1::int ELSE 0::int END AS boardmember, CASE WHEN president IS NOT NULL THEN 1::int ELSE 0::int END AS president, CASE WHEN vicepresident IS NOT NULL THEN 1::int ELSE 0::int END AS vicepresident, CASE WHEN founder IS NOT NULL THEN 1::int ELSE 0::int END AS founder, CASE WHEN director IS NOT NULL THEN 1::int ELSE 0::int END AS director FROM ManwomanCompany2 LEFT JOIN titles01 ON manwomancompany2.jobtitle=titles01.title;
tables for percent of women in a given job title
DROP TABLE PercentWomenCompany; CREATE TABLE PercentWomenCompany AS SELECT sum(mf)/count(mf) FROM ManWomanCompany3; --.29812
DROP TABLE PercentWomenCEOsCompany; CREATE TABLE PercentWomenCEOsCompany AS SELECT sum(mf)/count(mf) FROM ManWomanCompany3 WHERE ceo = 1; --.22597
DROP TABLE PercentWomenChairmanCompany; CREATE TABLE PercentWomenChairmanCompany AS SELECT sum(mf)/count(mf) FROM ManWomanCompany3 WHERE chairman = 1; --.142417
DROP TABLE PercentWomenCFOCompany; CREATE TABLE PercentWomenCFOCompany AS SELECT sum(mf)/count(mf) FROM ManWomanCompany3 WHERE cfo = 1; --.27087
DROP TABLE PercentWomenCOOCompany; CREATE TABLE PercentWomenCOOCompany AS SELECT sum(mf)/count(mf) FROM ManWomanCompany3 WHERE coo = 1; --.26353
DROP TABLE PercentWomenCIOCompany; CREATE TABLE PercentWomenCIOCompany AS SELECT sum(mf)/count(mf) FROM ManWomanCompany3 WHERE cio = 1; --.31707
DROP TABLE PercentWomenCTOCompany; CREATE TABLE PercentWomenCTOCompany AS SELECT sum(mf)/count(mf) FROM ManWomanCompany3 WHERE cto = 1; --.12588
DROP TABLE PercentWomenboardmemberCompany; CREATE TABLE PercentWomenboardmemberCompany AS SELECT sum(mf)/count(mf) FROM ManWomanCompany3 WHERE boardmember = 1; --.2545
DROP TABLE PercentWomenPresidentCompany; CREATE TABLE PercentWomenPresidentCompany AS SELECT sum(mf)/count(mf) FROM ManWomanCompany3 WHERE president = 1; --.19646
DROP TABLE PercentWomenVPCompany; CREATE TABLE PercentWomenVPCompany AS SELECT sum(mf)/count(mf) FROM ManWomanCompany3 WHERE vicepresident = 1; --.3468
DROP TABLE PercentWomenfounderCompany; CREATE TABLE PercentWomenfounderCompany AS SELECT sum(mf)/count(mf) FROM ManWomanCompany3 WHERE founder = 1; --.2394
DROP TABLE PercentWomendirectorCompany; CREATE TABLE PercentWomendirectorCompany AS SELECT sum(mf)/count(mf) FROM ManWomanCompany3 WHERE director = 1; --.38625
table for finding percentage of women in companies by state
DROP TABLE womenstates; CREATE TABLE womenstates AS SELECT companystate, sum(mf)/count(mf) FROM ManWomanCompany3 GROUP BY companystate;
Example output data
Year CEOs Founders Start-ups Partners FundExecs ------------------------------------------------------------- 1980 2% 2% 4% 1% 2% 1981 ...
- Table on money raised?
- Data on likelihood of follow-on round
still to do:
- this data still discounts a (small) percentage of data (doctors who didn't have a common name)
- have data organized, now we need to figure out how to extract it in meaningful terms for the report.