trade and female entrepreneurship -wes2014

Trade and female entrepreneurship

Magdalena SmykKatarzyna ŚledziewskaJoanna Tyrowicz

Group for Research in APplied Economics

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Table of contents

1. Introduction: what do we know?2. What do we want to study?3. Data4. Model5. Results6. Conclusions

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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?

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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)

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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)

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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.

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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)

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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

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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

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Relative competitve advantage

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Basic model

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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 ()

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Descriptive statistics (2002-2010)

0%

20%

40%

60%

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Female entreprenurship in three main groups

retail products intermediates machines and furniture0%

10%

20%

30%

40%

50%

60%

70%

80%

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Motivations of choosing self-employment

reta

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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

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Female entrepreneurship and RCA_EU

whole sample 2006

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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

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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

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Results – basic model in product groups

Detale RCA_OECDAspiring countries






female 0,23 -0,32 0,23 -0,34 0,30 -0,29rest – without changes (significant)Intermedia

tes







female 0,68* 0,05 0,92* -0,39 0,68 0,04rest – without changes (significant)Machines RCA_OECD

Aspiring 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

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Results – basic model with interactions (retail products manufacturing as a reference group)







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

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Per se female entrepreneurship does not strongly correlate with

competitiveness

Maybe just some sectors or firms?

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Results – aspirations







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)







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)

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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: [email protected]

More about our research on http://grape.uw.edu.pl

Twitter: @GrapeUW

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Databases

Export revenues: World Integrated Trade Solution

http://wits.worldbank.org/

GEM http://www.gemconsortium.org/Data

trade and female entrepreneurship -wes2014

Economy & Finance

gender equality

international trade

gender participationgap

genderowners gender

established business

motivation entrepreneurship

country survey

discrimination gender