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things to do: # analyze data Over the past century, the United States has witnessed two large-scale social trends involving [[Women in Entrepreneurship|women in tables - meet w ed to build wiki page similar to rachelentrepreneurship]] that have had a significant impact on the country's# build program that will sort economic growth. First, huge numbers of women have made their way into the Dr data into males and females - see [https://wwwofficial labor force.ssaAround this time 50 years ago (February 1966), women's labor force participation rate was 39.gov/oact/babynames/decades/names1970s6%, but in February 2016, 56.html top 1970s names], 8% of women participated in the labor force [https://wwwresearch.ssastlouisfed.gov/oactorg/babynamesfred2/decadesseries/names1980s.html top 1980s namesLNS11300002], [https://www.ssaThis demonstrates substantial growth in women's entry to the labor force.gov/oact/babynames/decades/names1990sSecond, women are achieving a higher degree of education than in years past.html top 1990s names]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. [httpshttp://www.ssapewresearch.govorg/fact-tank/oact2014/babynames03/decades06/womens-college-enrollment-gains-leave-men-behind/names2000s.html top 2000s names]This has provided women with similar access to the same jobs as men.
<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, This issue brief aims to examine the role of women are achieving a higher degree of education than in years past. As labor market barriers to women have been loweredentrepreneurship today by examining their jobs (or lack thereof) in entrepreneurship related fields, and examine the benefits effectiveness of a college education grew more for current policy related to women than men, and females 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 access to the same jobs as menentrepreneurship.
However, these trends have slowed ==Status Quo== ===Our research=== We examined all leaders in companies from their early twenty1980-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 2016 who have the same magnitude. With thistitles of either chariman, CEO, CFO, COO, CIO, CTO, board member, President, 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 creationVice President, the long-term pessimism about growth in the United StatesFounder, and the rising share of women among educated workersDirector. Of company members with those titles, it seems clear that the future of American economic growth is in the hands of only 29.8% were women. Encouraging Of those women to enter into fields of entrepreneurshipleaders, 22% were CEOs, 14% chairwomen, 27% CFOs, 26% COOs, 31% CIOs, 12% CTOs, 25% board members, 20% presidents, 34% vice presidents, particularly high-growth entrepreneurship23% founders, might be the United States' silver bulletand 39% directors.</onlyinclude>(from tables, PercentWomenXCompany, where X is job title)
This issue brief aims to examine the role Grouped by state, Michigan has highest percentage of women in entrepreneurship today by examining their jobs (or lack thereof) leadership in entrepreneurship and examine the effectiveness of current policy related to women its companies, coming in entrepreneurshipat 37.5%. Texas has 26.6%. Wyoming has a whopping 0%.(from womenstates)
==Status Quo==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.
*put our research info here*===Info from external sources===
→Our research
[[Women in Entrepreneurship Lit Review]]
=The Paper=
==Introduction==
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.
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)
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.
==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==
*Data on likelihood of follow-on round
==Variables and tablesstill to do:== Table Entrep2:*Prefix*FirstName*Title Todo:*Rename #this table to something meaningful! - DONE*Get distinct prefixes data still discounts a (Mr, Mrs, Drsmall) - DONE*Get distinct titles**Choose the titles! **Either make a lookup table or find the patterns**Build a new variable to add the 'clean titlepercentage of data (doctors who didn'*Create t have a man/women variable (0 if man, 1 if womencommon name) - DONE**Load up your census names - DONE**Find the distinct man/women names -DONE. built SQL table w name plus 0#have data organized,1 value.**Write an SQL query now we need to figure out how to JOIN a man/woman variable when title = DR*Build the output table extract it in SQL CREATE TABLE WomenCEOs AS SELECT year, SUM(manwoman)/COUNT(manwoman) AS PercentWomenCEOs FROM tablename WHERE cleantitle='CEO' GROUP BY Year; Table Entrep1:*Prefix*FirstName*Job Title Todo:*Same as above, but different lookups meaningful terms for job titlethe report.
