Trade and female entrepreneurship -WES2014
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Trade and female entrepreneurship -WES2014
- 1. Group for Research in APplied Economics Trade and female entrepreneurship Magdalena Smyk Katarzyna Εledziewska Joanna Tyrowicz
- 2. Table of contents 1. Introduction: what do we know? 2. What do we want to study? 3. Data 4. Model 5. Results 6. Conclusions 2
- 3. 3 Motivation ο§ Entrepreneurship: ο§ as a way to express aspirations (βJack of all tradesβ) ο§ as a way to avoid barriers on the labour market ο§ If βaspirationsβ => profitability & competitiveness => strong competitive position of the country ο§ If alternative to unemployment => lack of competitiveness ο§What does the data say?
- 4. What do we know so far? Gender equality and international trade β two strands of the literature: 1. Workers (differences in wages and participation rates): β Theory: taking part in the international exchange will increase costs of discrimination β gender wage gap and gender participation gap should narrow (Becker). β 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. β Impact recognition: studies were based on natural experiments: (e. g. Mexico before and after joining NAFTA) 4
- 5. What do we know so far? Gender equality and international tradeβ two strands of the literature: 2. Owners β Theory: being successful in international trade is correlated with decisions and attributes of the owner (those attributes are potentially connected to gender): β’ why was the firm established? (unemployment vs. business opportunity) β’ owner growth intention β’ management experience β’ firm sector and size β’ innovation attitude β Empirical evidence: only size of the firm is correlated with gender; ownerβs gender is not correlated with exporting propensity (Orser et al. 2010) 5
- 6. What do we want to know? Are firms established and managed by women are equally important for countryβs strong competitive position? How? 1. We identify female entrepreneurship intensity in manufacturing sectors and countries. 2. We identify correlation between female entrepreneurship and countryβs competitive position. 6
- 7. Data Two types of data: β export revenues in 15 manufacturing sectors in 67 countries; years 2002-2010 β data about entrepreneurs: Global Entrepreneurship Monitor - Adult Population Survey (2002-2010) 7
- 8. 8 Global Entrepreneurship Monitor GEM Adult Population Survey: ο§ at least 2 thousand respondents from each country ο§ survey considers business activity, but also aspirations and future plans ο§ three parts: baby business, established business, future plans ο§ GEM is representative of whole adult population
- 9. Global Entrepreneurship Monitor β our database 9 ο§ Only those who are currently managing a firm or self-employed ο§ 67 countries ο§ years: 2002-2010 ο§ one observation corresponds to one of the 15 manufacturing sectors (two digits ISIC Rev. 3.1. code) in each country and year ο§ additional three groups: ο§ retail products (np. food, textile, paper) ο§ intermediates (np. chemicals, rubber, metal, fuel) ο§ machines and furniture
- 10. Relative competitve advantage ν νΆν΄ν,ν,ν = νν₯νννν‘ν,ν ν=1 ν νν₯νννν‘ν,ν νν₯νννν‘ν,ν ν=1 ν νν₯νννν‘ν,ν , ν€βννν ν β ν ννν‘νν ν β ννν’νν‘νν¦ ν β νννν’ν(ν. ν. ννΈνΆν·, νΈν) 10
- 11. 11 Basic model ν νΆν΄ν,ν,ν = νΌ + ν½1 β ννννννν,ν + ν½2 β ν ννν’ν ν,ν +ν½3 β νννννν‘ν’ννν‘ν¦ν,ν + ν½4 β ν ν’νννν ν νν’νν,ν +ν½5 β ννν€ν‘ννβν,ν + ν½6 β ννν€ννννν’νν‘ν,ν +ν½7 β ν€νννννν ν,ν + νν,ν ν β ν ννν‘νν ν β ννν’νν‘νν¦ ν β νννν’ν (νν. ννΈνΆν·, νΈν)
- 12. 12 Basic model ο§ independent variables: ο§ shares of firms in each manufacturing sector: (in each country and year): ο§ (ννννννν,ν) owned by women ο§ (ν ννν’ν ν,ν) with secondary educated owners ο§ (νννννν‘ν’ννν‘ν¦ν,ν) established as a business opportunity (not as an alternative to unemployment) ο§ (ν ν’νννν ν νν’νν,ν ) which owners believe that it is a βsuccessful businessβ ο§ (ννν€ν‘ννβν,ν) which are using new technologies ο§ (ννν€ννννν’νν‘ν,ν) which products are considered by consumers as new and innovative ο§ and average number of workers (ν€νννννν ν,ν)
- 13. 13 Descriptive statistics (2002-2010) 70% 60% 50% 40% 30% 20% 10% 0% share of female-owned firms share of female owners with higher education share of owners with higher education share of "bussiness opportunities" share of frims with innovative product
- 14. 14 Female entreprenurship in three main groups 80% 70% 60% 50% 40% 30% 20% 10% 0% retail products intermediates machines and furniture
- 15. 15 Motivations of choosing self-employment 60% 50% 40% 30% 20% 10% 0% retail products intermediates machines and furniture women - business opportunity men - business opportunity women - unemployment men - unemployment women - combination of those two men - combination of those two women - better perspective men - better perspective women - other men - other
- 16. 16 Female entrepreneurship and RCA_EU whole sample 2006
- 17. 17 Countries β 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. 18 Results β basic model RCA_OECD Aspiring countries RCA_OECD Rich countries RCA_EU Aspiring countries RCA_EU Rich countries RCA_DEVELOPED Aspiring countries RCA_DEVELOPED Rich 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. 19 Results β basic model in product groups Detale RCA_OECD Aspiring countries RCA_OECD Rich countries RCA_EU Aspiring countries RCA_EU Rich countries RCA_DEVELOPED Aspiring countries RCA_DEVELOPED Rich countries female 0,23 -0,32 0,23 -0,34 0,30 -0,29 rest β without changes (significant) Intermediates RCA_OECD Aspiring countries RCA_OECD Rich countries RCA_EU Aspiring countries RCA_EU Rich countries RCA_DEVELOPED Aspiring countries RCA_DEVELOPED Rich countries female 0,68* 0,05 0,92* -0,39 0,68 0,04 rest β without changes (significant) Machines RCA_OECD Aspiring countries RCA_OECD Rich countries RCA_EU Aspiring countries RCA_EU Rich countries RCA_DEVELOPED Aspiring countries RCA_DEVELOPED Rich countries female 0,79 -0,00 0,67 0,21 0,79 0,03 rest β without changes (significant) * p<0,05; ** p<0,01; *** p<0.001
- 20. 20 Results β basic model with interactions (retail products manufacturing as a reference group) RCA_OECD Aspiring countries RCA_OECD Rich countries RCA_EU Aspiring countries RCA_EU Rich countries RCA_DEVELOPED Aspiring countries RCA_DEVELOPED Rich 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. Per se female entrepreneurship does not strongly correlate with competitiveness Maybe just some sectors or firms? 21
- 22. 22 Results β aspirations RCA_OECD Aspiring countries RCA_OECD Rich countries RCA_EU Aspiring countries RCA_EU Rich countries RCA_DEVELOPED Aspiring countries RCA_DEVELOPED Rich countries share of women, who established firm as a business opportunity -0,31 -0,27 -0,25 -0,29 -0,25 -0,25 rest β without changes (significant) RCA_OECD Aspiring countries RCA_OECD Rich countries RCA_EU Aspiring countries RCA_EU Rich countries RCA_DEVELOPED Aspiring countries RCA_DEVELOPED Rich countries share of women, who established firm because of unemployment 0,21 0,14 0,23 0,15 0,23 0,13 rest β without changes (significant)
- 23. 23 Conclusions ο§Female entrepreneurship has little impact on countryβs competitive position in manufacturing. ο§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. ο§ Motivation for which women establish firms are irrelevant to strong competitive position.
- 24. Thank you for your attention! Authors: Magdalena Smyk, Katarzyna Εledziewska, Joanna Tyrowicz e-mail: msmyk@wne.uw.edu.pl More about our research on http://grape.uw.edu.pl Twitter: @GrapeUW
- 25. 25 Databases ο§ Export revenues: World Integrated Trade Solution http://wits.worldbank.org/ ο§GEM http://www.gemconsortium.org/Data
Editor's Notes
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