Post on 16-Dec-2014
description
Trade and female entrepreneurship
Magdalena SmykKatarzyna ŚledziewskaJoanna Tyrowicz
Group for Research in APplied Economics
2
Table of contents
1. Introduction: what do we know?2. What do we want to study?3. Data4. Model5. Results6. Conclusions
3
Motivation
Entrepreneurship: as a way to express aspirations („Jack of all trades”) as a way to avoid barriers on the labour market
If „aspirations” => profitability & competitiveness => strong competitive position of the country
If alternative to unemployment => lack of competitiveness
What does the data say?
4
What do we know so far?
Gender equality and international trade – two strands of the literature:1. Workers (differences in wages and
participation rates): Theory: taking part in the international exchange will
increase costs of discrimination – gender wage gap and gender participation gap should narrow (Becker).
Empirical results: trade liberalization may influence positively (Hazaraki and Otero, 2004) as well as negatively (Ferrufino, 2011) the gender wage gap. In some cases the relationship was statistically insignificant (Ghiara, 1999). Results are different for high- and low-skilled workers.
Impact recognition: studies were based on natural experiments: (e. g. Mexico before and after joining NAFTA)
5
What do we know so far?
Gender equality and international trade– two strands of the literature:2. Owners
Theory: being successful in international trade is correlated with decisions and attributes of the owner (those attributes are potentially connected to gender): why was the firm established? (unemployment vs. business opportunity) owner growth intention management experience firm sector and size innovation attitude
Empirical evidence: only size of the firm is correlated with gender; owner’s gender is not correlated with exporting propensity (Orser et al. 2010)
6
What do we want to know?
Are firms established and managed by women are equally important for country’s strong competitive position?
How?1. We identify female entrepreneurship intensity in
manufacturing sectors and countries. 2. We identify correlation between female
entrepreneurship and country’s competitive position.
7
Data
Two types of data:
export revenues in 15 manufacturing sectors in 67 countries; years 2002-2010
data about entrepreneurs: Global Entrepreneurship Monitor - Adult Population Survey (2002-2010)
8
Global Entrepreneurship Monitor
GEM Adult Population Survey:
at least 2 thousand respondents from each country survey considers business activity, but also aspirations and
future plans three parts: baby business, established business, future plans
GEM is representative of whole adult population
9
Global Entrepreneurship Monitor – our database
Only those who are currently managing a firm or self-employed
67 countries years: 2002-2010 one observation corresponds to one of the 15 manufacturing
sectors (two digits ISIC Rev. 3.1. code) in each country and year additional three groups:
retail products (np. food, textile, paper) intermediates (np. chemicals, rubber, metal, fuel) machines and furniture
10
Relative competitve advantage
11
Basic model
12
Basic model
independent variables: shares of firms in each manufacturing sector:
(in each country and year): () owned by women () with secondary educated owners () established as a business opportunity (not as an alternative to
unemployment) () which owners believe that it is a „successful business”
() which are using new technologies () which products are considered by consumers as new and innovative
and average number of workers ()
13
Descriptive statistics (2002-2010)
0%
20%
40%
60%
14
Female entreprenurship in three main groups
retail products intermediates machines and furniture0%
10%
20%
30%
40%
50%
60%
70%
80%
15
Motivations of choosing self-employment
reta
il pr
oduc
ts
inte
rmed
iate
s
mac
hine
s an
d fu
rnitu
re0%
10%
20%
30%
40%
50%
60%women - business opportunitymen - business opportunitywomen - unem-ploymentmen - unemploymentwomen - combina-tion of those twomen - combination of those twowomen - better perspectivemen - better perspectivewomen - othermen - other
16
Female entrepreneurship and RCA_EU
whole sample 2006
17
Countries – rich and aspiring
Rich Aspiring
USA, Netherlands, Belgium, France, Spain, Switzerland, Austria, Great Britain, Denmark, Sweden, Norway, Germany, Australia, New Zeland, Japan, Canada
Peru,Colombia,Indonesia, Philippines,Turkey, Pakistan,Uganda, Guatemala, Ecuador,Iran,Russia, Greece, Serbia, Croatia, Czech Republic, Poland
18
Results – basic model
RCA_OECDAspiring countries
RCA_OECDRich countries
RCA_EUAspiring countries
RCA_EURich countries
RCA_DEVELOPEDAspiring countries
RCA_DEVELOPEDRich countries
female 0,92*** 0,01 0,92*** 0,06 0,90*** 0,01
seduc -0,09 0,01 0,01 0,05 -0,11 0,00
opportunity -0,09 -0,08 -0,11 -0,09 -0,09 -0,08
successful -0,33 0,83 -0,38 0,53 -0,28 0,81
newtech -0,40 -0,27 -0,39 -0,34 -0,38 -0,27
newproduct 0,05 0,04 0,02 0,06 0,05 0,06
workers -0,05*** -0,00 -0,01*** -0,00 -0,01*** -0,00
export per capita 0,87*** 0,33*** 0,93*** 0,35*** 0,85*** 0,33***
constant 4,34*** 1,64*** 4,49*** 1,63*** 4,25*** 1,61***
* p<0,05; ** p<0,01; *** p<0.001
19
Results – basic model in product groups
Detale RCA_OECDAspiring countries
RCA_OECDRich countries
RCA_EUAspiring countries
RCA_EURich countries
RCA_DEVELOPEDAspiring countries
RCA_DEVELOPEDRich countries
female 0,23 -0,32 0,23 -0,34 0,30 -0,29rest – without changes (significant)Intermedia
tes
RCA_OECDAspiring countries
RCA_OECDRich countries
RCA_EUAspiring countries
RCA_EURich countries
RCA_DEVELOPEDAspiring countries
RCA_DEVELOPEDRich countries
female 0,68* 0,05 0,92* -0,39 0,68 0,04rest – without changes (significant)Machines RCA_OECD
Aspiring countries
RCA_OECDRich countries
RCA_EUAspiring countries
RCA_EURich countries
RCA_DEVELOPEDAspiring countries
RCA_DEVELOPEDRich countries
female 0,79 -0,00 0,67 0,21 0,79 0,03rest – without changes (significant)
* p<0,05; ** p<0,01; *** p<0.001
20
Results – basic model with interactions (retail products manufacturing as a reference group)
RCA_OECDAspiring countries
RCA_OECDRich countries
RCA_EUAspiring countries
RCA_EURich countries
RCA_DEVELOPEDAspiring countries
RCA_DEVELOPEDRich countries
interaction: sector machines * female
-1,56** -0,94*** -1,72*** -1,06*** -1,46** -0,87***
interaction: sector intermediates * female
-2,64*** -0,70*** -2,47*** -0,78*** -2,54*** -0,66***
female 1,42*** 0,33** 1,42*** 0,42*** 1,38*** 0,31**
seduc -0,15 -0,04 -0,04 0,00 -0,16 -0,04
opportunity -0,03 -0,03 -0,05 -0,04 -0,04 -0,03
successful -0,30 1,08 -0,34 0,81 -0,25 1,06
newtech -0,45 -0,29 -0,44 -0,37* -0,42 -0,29
newproduct 0,16 0,08 0,12 0,11 0,15 0,10
workers -0,00*** -0,00 -0,00*** -0,00 -0,00*** -0,00
export per capita 0,89*** 0,39*** 0,95*** 0,41*** 0,87*** 0,38***
constant 4,46*** 1,75*** 4,59*** 1,75*** 4,36*** 1,71***
* p<0,05; ** p<0,01; *** p<0.001
21/30
Per se female entrepreneurship does not strongly correlate with
competitiveness
Maybe just some sectors or firms?
22
Results – aspirations
RCA_OECDAspiring countries
RCA_OECDRich countries
RCA_EUAspiring countries
RCA_EURich countries
RCA_DEVELOPEDAspiring countries
RCA_DEVELOPEDRich countries
share of women, who established firm as a business opportunity
-0,31 -0,27 -0,25 -0,29 -0,25 -0,25
rest – without changes (significant)
RCA_OECDAspiring countries
RCA_OECDRich countries
RCA_EUAspiring countries
RCA_EURich countries
RCA_DEVELOPEDAspiring countries
RCA_DEVELOPEDRich countries
share of women, who established firm because of unemployment
0,21 0,14 0,23 0,15 0,23 0,13
rest – without changes (significant)
23
Conclusions
Female entrepreneurship has little impact on country’s competitive position in manufacturing.
Only in manufacturing retail products (food, textiles, paper), sector, which women choose most frequently, we can find positive correlation between share of female businesses and comparative advantage.
Motivation for which women establish firms are irrelevant to strong competitive position.
Thank you for your attention!
Authors: Magdalena Smyk, Katarzyna Śledziewska, Joanna Tyrowicze-mail: msmyk@wne.uw.edu.pl
More about our research on http://grape.uw.edu.pl
Twitter: @GrapeUW
25
Databases
Export revenues: World Integrated Trade Solution
http://wits.worldbank.org/
GEM http://www.gemconsortium.org/Data