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<onlyinclude>Over the past century, the United States has witnessed two large-scale social trends involving [[Women in Entrepreneurship|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 [https://research.stlouisfed.org/fred2/series/LNS11300002]. 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. [http://www.pewresearch.org/fact-tank/2014/03/06/womens-college-enrollment-gains-leave-men-behind/] This has provided women with similar access to the same jobs as men.
*SecondHowever, women are achieving a higher degree of education these trends have slowed from their early twenty-first century spikes; room for growth is smaller now than in years pastit was before. Economists predict that economic growth from these two trends is unlikely to be repeated to the same magnitude. As labor market barriers With this, everyone is looking for the modern-day economy-boosting equivalent to women have been lowered, 's entry to the labor force. Given the benefits rising share of a college education grew more for women than menamong educated workers, and females outpace males it seems clear that the future of American economic growth is in college enrollmentthe hands of women. [http://www.pewresearch.org/fact-tank/2014/03/06/womens-college-enrollment-gains-leave-men-behind/] This has provided Encouraging women with access to enter into fields of entrepreneurship, particularly high-growth entrepreneurship, might be the same jobs as menUnited States' silver bullet.
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 entering the labor force and achieving higher education. Given the slowing rates of business creation, the long-term pessimism about growth in the United States, and 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.</onlyinclude>
This issue brief aims to examine ==Status Quo== ===Our research=== We examined all leaders in companies from 1980-2016 who have the role 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 in entrepreneurship today by examining their jobs 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. (or lack thereoffrom tables, PercentWomenXCompany, where X is job title) in entrepreneurship and examine the effectiveness of current policy related to women in entrepreneurship.
==Status Quo==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)
Year CEOs Founders Start-ups Partners FundExecsDROP TABLE PercentWomenPresidentCompany; -------------------------------------------------------------CREATE TABLE PercentWomenPresidentCompany AS 1980 2% 2% 4% SELECT sum(mf)/count(mf) FROM ManWomanCompany3 WHERE president = 1% 2%; 1981 ..--.19646
*Table on money raised?DROP TABLE PercentWomenVPCompany;*Data on likelihood of follow-on roundCREATE TABLE PercentWomenVPCompany AS SELECT sum(mf)/count(mf) FROM ManWomanCompany3 WHERE vicepresident = 1;==Variables and tables==--.3468
Table Entrep2:DROP TABLE PercentWomenfounderCompany;*PrefixCREATE TABLE PercentWomenfounderCompany AS*FirstNameSELECT sum(mf)/count(mf) FROM ManWomanCompany3 WHERE founder = 1;*Title--.2394
Todo:DROP TABLE PercentWomendirectorCompany;*Rename this table to something meaningful! - DONECREATE TABLE PercentWomendirectorCompany AS*Get distinct prefixes SELECT sum(Mr, Mrs, Drmf) - DONE*Get distinct titles**Choose the titles! - DONE**Either make a lookup table or find the patterns**Build a new variable to add the 'clean title'*Create a man/women variable count(0 if man, mf) FROM ManWomanCompany3 WHERE director = 1 if women) - DONE;**Load up your census names - DONE**Find the distinct man/women names -DONE. built SQL table w name plus 0,1 value.**Write an SQL query to JOIN a man/woman variable when title = DR*Build the output table in SQL38625
CREATE TABLE WomenCEOs AS SELECT year, SUM(manwoman)/COUNT(manwoman) AS PercentWomenCEOs FROM tablename WHERE cleantitle='CEO' GROUP BY Year;=table for finding percentage of women in companies by state==
Table Entrep1:
*Prefix
*FirstName
*Job Title
Todo:
*Same as above, but different lookups for job title.
On the company side: Year CEOs Founders Start-ups Partners FundExecs ------------------------------------------------------------- 1980 2% 2% 4% 1% 2% 1981 ...
→Our research
[[Women in Entrepreneurship Lit Review]]
=The Paper=
==Introduction==
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.
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. [http://www.theatlantic.com/business/archive/2015/04/women-are-owning-more-and-more-small-businesses/390642/]. 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. [http://www.kauffman.org/~/media/kauffman_org/research%20reports%20and%20covers/2014/11/sources_of_economic_hope_womens_entrepreneurship.pdf]
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.
==Example output dataConclusion==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 ASSELECT prefix, lastname, datefounded, jobtitle, fundname, fundcity, fundstate,removeinitial(firstname) as firstname,CASE WHEN prefix='Ms' THEN 1::intWHEN prefix='Mr' THEN 0::intELSE Null::int END AS womanman FROM fundreal;--156005 DROP TABLE manwomancompany;CREATE TABLE manwomancompany ASSELECT prefix, lastname, datefounded, jobtitle, companyname, companycity, companystate, industrygroup,removeinitial(firstname) as firstname, amtinvestedthous, rounds,CASE WHEN prefix='Ms' THEN 1::intWHEN prefix='Mr' THEN 0::intELSE 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 ASSELECT 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 womanmanELSE NULL::int END AS womanman FROM manwomanfund LEFT JOIN commonnamesclean ON firstname = nameWHERE firstname IS NOT NULL;--152819 DROP TABLE manwomancompany2;CREATE TABLE manwomancompany2 ASSELECT 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 womanmanELSE 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 ASSELECT EXTRACT(YEAR FROM datefounded), AVG(womanman) AS PercentWomen FROM manwomanfund2 GROUP BY EXTRACT(YEAR FROM datefounded);--37 DROP TABLE companyWomen;CREATE TABLE companywomentot ASSELECT EXTRACT(YEAR FROM datefounded), AVG(womanman) AS PercentWomen FROM manwomancompany2 GROUP BY EXTRACT(YEAR FROM datefounded);--36 DROP TABLE womencompanystate;CREATE TABLE womencompanystate ASSELECT companystate, AVG(womanman) AS WomenPerStateFROM manwomancompany2 GROUP BY companystate;--51 DROP TABLE womenfundstate;CREATE TABLE womencfundstate ASSELECT fundstate, AVG(womanman) AS WomenPerStateFROM manwomanfund2 GROUP BY fundstate;--51 DROP TABLE womencompanycity;CREATE TABLE womencompanycity ASSELECT companycity, AVG(womanman) AS WomenPerCityFROM 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 directorFROM ManwomanCompany2LEFT JOIN titles01 ON manwomancompany2.jobtitle=titles01.title; ==tables for percent of women in a given job title==DROP TABLE PercentWomenCompany;CREATE TABLE PercentWomenCompany ASSELECT sum(mf)/count(mf) FROM ManWomanCompany3;--.29812 DROP TABLE PercentWomenCEOsCompany;CREATE TABLE PercentWomenCEOsCompany ASSELECT sum(mf)/count(mf) FROM ManWomanCompany3 WHERE ceo = 1;--.22597 DROP TABLE PercentWomenChairmanCompany;CREATE TABLE PercentWomenChairmanCompany ASSELECT sum(mf)/count(mf) FROM ManWomanCompany3 WHERE chairman = 1;--.142417 DROP TABLE PercentWomenCFOCompany;CREATE TABLE PercentWomenCFOCompany ASSELECT sum(mf)/count(mf) FROM ManWomanCompany3 WHERE cfo = 1;--.27087 DROP TABLE PercentWomenCOOCompany;CREATE TABLE PercentWomenCOOCompany ASSELECT sum(mf)/count(mf) FROM ManWomanCompany3 WHERE coo = 1;--.26353 DROP TABLE PercentWomenCIOCompany;CREATE TABLE PercentWomenCIOCompany ASSELECT sum(mf)/count(mf) FROM ManWomanCompany3 WHERE cio = 1;--.31707 DROP TABLE PercentWomenCTOCompany;CREATE TABLE PercentWomenCTOCompany ASSELECT sum(mf)/count(mf) FROM ManWomanCompany3 WHERE cto = 1;--.12588 DROP TABLE PercentWomenboardmemberCompany;CREATE TABLE PercentWomenboardmemberCompany ASSELECT sum(mf)/count(mf) FROM ManWomanCompany3 WHERE boardmember = 1;--.2545
DROP TABLE womenstates;
CREATE TABLE womenstates AS
SELECT companystate, sum(mf)/count(mf) FROM ManWomanCompany3 GROUP BY companystate;
===Key Titles=Example output data==
*ChairmanTable on money raised?*CEO (Chief Exec. Officer)Data on likelihood of follow-on round*CFO *COO*CIO/CTO?*On the Board==still to do: ==**Board Member #this data still discounts a (may inc. VCs, etc.small)**Director percentage of data (may inc. VCs, etc.)**All the Cdoctors who didn's**Exec Officer (may inc. VCs, etc.t have a common name)*Senior position:**President ??? Fast look at co's that #have presidentsdata organized, do they also have C's?**Vice-presidentnow we need to figure out how to extract it in meaningful terms for the report.
