Bureaucratic and Societal Determinants of Female-Led Microenterprises in India
Abstract
:1. Introduction
2. Literature Review
2.1. Gender and Performance
2.2. Gender Inequality, Social Norms, and Grammatical Genders
2.3. Corruption and Gender
3. Hypothesis Building
4. Data and Methods
5. Empirical Analysis
5.1. Descriptive Analysis
5.2. Some other Features of the Data
5.3. Empirical Results
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
VARIABLES | (1) | (2) | (3) | (4) | (5) |
---|---|---|---|---|---|
Education3 | −0.1899 *** | −0.0714 | −0.0333 | −0.0407 | 0.0256 |
(0.06) | (0.06) | (0.06) | (0.08) | (0.08) | |
Education2 | −0.2223 *** | −0.1100 * | −0.0966 * | −0.0867 | −0.1058 ## |
(0.06) | (0.06) | (0.06) | (0.08) | (0.07) | |
Ln sales | −0.0142 | −0.0163 | −0.0053 | −0.0207 | −0.0072 |
(0.01) | (0.01) | (0.02) | (0.02) | (0.03) | |
Firm age | −0.0027 ## | −0.0000 | −0.0008 | −0.0003 | 0.0016 |
(0.00) | (0.00) | (0.00) | (0.00) | (0.00) | |
Manager experience | −0.0048 ** | −0.0013 | −0.0038 | −0.0016 | |
(0.00) | (0.00) | (0.00) | (0.00) | ||
Owner job | 0.1853 *** | 0.1305 *** | 0.1806 *** | 0.1134 ** | |
(0.04) | (0.03) | (0.05) | (0.05) | ||
GL2 | −0.0091 | 0.0570 | |||
(0.09) | (0.21) | ||||
GL3 | 0.0214 | −0.1147 | |||
(0.07) | (0.14) | ||||
GL4 | −0.1683 ** | −0.3160 ** | |||
(0.07) | (0.15) | ||||
Bribe | 0.1327 *** | 0.0792 # | |||
(0.05) | (0.05) | ||||
Observations | 586 | 562 | 562 | 219 | 219 |
1 | For details, see “Contribution of MSMEs to GDP, Ministry of Micro, Small & Medium Enterprises”, https://www.pib.gov.in/PressReleasePage.aspx?PRID=1744032, Release ID: 1744032), Posted On: 9 Auguest 2021 2:54 PM by PIB Delhi, accessed on 15 December 2022. |
2 | For details, see https://sdgs.un.org/goals/goal5, accessed on 10 December 2022. |
3 | For details, see “Khasis: India’s indigenous matrilineal society” https://www.bbc.com/travel/article/20210328-why-some-indians-want-more-mens-rights, accessed on 7 December 2021. |
4 | Business PAN and GST number are unique documents mandatory for every tax-paying entity (businesses, suppliers, dealers etc.). |
5 | For further details, refer to World Bank Implementation Report India, 2022. |
6 | To our knowledge, a linguistic database for Indian languages does not exist. We come to the above conclusions on gender-in-language based on two approaches. Firstly, we gather the required information from list of languages by grammatical genders from Wikipedia (https://en.wikipedia.org/wiki/List_of_languages_by_type_of_grammatical_genders, accessed on 1 December 2022), Secondly, we conduct one-to-one interviews with native speakers and confirm the grammatical gender classifications. |
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Cities | States | Major Spoken Language | GL Score | Dummy Variables |
---|---|---|---|---|
Varanasi | Uttar Pradesh | Hindi | 4 | GL4 |
Sehore | Madhya Pradesh | Hindi | 4 | GL4 |
Jaipur | Rajasthan | Hindi | 4 | GL4 |
Ludhiana | Punjab | Punjabi | 4 | GL4 |
Surat | Gujarat | Gujarati | 3 | GL3 |
Hyderabad | Telangana | Telugu | 3 | GL3 |
Mumbai | Maharashtra | Marathi | 3 | GL3 |
Kochi | Kerala | Malayalam | 2 | GL2 |
Tezpur | Assam | Assamese | 1 | GL1 |
Variables | Description | Observations | Mean | Std. Dev. | Min | Max |
---|---|---|---|---|---|---|
female | Dummy variable taking value 1 if firm has a female owner or top manager | 998 | 0.13 | 0.34 | 0 | 1 |
GL scores | Grammatical genders in language scores (refer Table 1) | 998 | 3.10 | 1.01 | 1 | 4 |
bribe | Dummy variable taking value 1 if firm was requested a bribe payment | 347 | 0.33 | 0.47 | 0 | 1 |
bribe avIR | Industry-region average bribe values | 697 | 0.31 | 0.40 | 0 | 1 |
ln sales | Log of sales in previous financial year | 976 | 13.91 | 1.04 | 10.46 | 17.73 |
Education dummy3 | Dummy variable taking value 1 if owner has a bachelor’s degree or a diploma. | 998 | 0.48 | 0.50 | 0 | 1 |
Education dummy2 | Dummy variable taking value 1 if owner has completed primary or secondary schooling | 998 | 0.45 | 0.50 | 0 | 1 |
Education dummy1 | Dummy variable taking value 1 if owner has no schooling or incomplete primary schooling | 998 | 0.07 | 0.26 | 0 | 1 |
firm age | 2021-year operations begun | 957 | 12.97 | 9.56 | 1 | 67 |
manager experience | No. of years of experience top manager has | 955 | 12.23 | 9.21 | 1 | 50 |
owner job | Dummy variable taking value 1 if owner has a full-time job with wage | 996 | 0.10 | 0.29 | 0 | 1 |
financially constrained | Dummy variable taking value 1 if the firm is financially constrained | 998 | 0.65 | 0.48 | 0 | 1 |
Cities | Percentage of Firms in Total | Firms with Female Entrepreneurs (%) | Percentage of Firms Paid at Least one Bribe a | Percentage of Households Faced Corruption b | No. of Reported Cases of Corruption per 10 Lakh Population c |
---|---|---|---|---|---|
Hyderabad | 10.82 | 73.15 | 56.48 | 74 | 2.23 |
Kochi | 10.02 | 17.00 | 4.00 | 4 | 0.00 |
Tezpur | 12.32 | 11.38 | 14.63 | 18 | 0.04 |
Mumbai | 11.32 | 7.96 | 4.42 | 57 | 0.51 |
Surat | 11.32 | 4.42 | 7.08 | 37 | 3.65 |
Sehore | 12.22 | 3.28 | 13.11 | 23 | 0.04 |
Varanasi | 10.22 | 1.96 | 0.00 | 19 | 2.22 |
Jaipur | 10.72 | 0.93 | 1.87 | 14 | 2.36 |
Ludhiana | 11.02 | 0.00 | 0.91 | 42 | 2.86 |
Total | 100 | 13.13 | 11.52 | 31 | 3.09 |
Percentage of Firms Responding to the Bribe Demand Questions | ||
---|---|---|
How much of an Obstacle is Corruption | Male Entrepreneurs | Female Entrepreneurs |
No obstacle | 38.70 | 46.81 |
Minor obstacle | 30.24 | 67.92 |
Moderate obstacle | 23.39 | 60.00 |
Major obstacle | 23.21 | 57.14 |
Very severe obstacle | 24.00 | 50.00 |
Average | 31.26 | 58.02 |
Description | Male Entrepreneurs (Percentage) | Female Entrepreneurs (Percentage) |
---|---|---|
Firms in Manufacturing | 30 | 32 |
Firms in Retail | 52.8 | 50.4 |
Firms in Services | 17.2 | 17.6 |
Owners also have a full-time salaried job | 6.4 | 44.5 |
Owners have a diploma (technical/non-technical) or a bachelors’ degree | 50.1 | 28.2 |
Owners do not have any education or have an incomplete primary education | 4.5 | 35.3 |
VARIABLES | (1) | (2) | (3) | (4) | (5) | (6) |
---|---|---|---|---|---|---|
Education3 | −0.1065 ** | −0.0376 | −0.0194 | −0.0512 | −0.0169 | −0.0162 |
(0.04) | (0.04) | (0.04) | (0.07) | (0.07) | (0.07) | |
Education2 | −0.1201 *** | −0.0593 ## | −0.0550 ## | −0.0735 | −0.0800 | −0.0745 |
(0.04) | (0.04) | (0.04) | (0.07) | (0.06) | (0.06) | |
Ln sales | 0.0001 | −0.0014 | −0.0061 | −0.0122 | −0.0098 | −0.0117 |
(0.01) | (0.01) | (0.01) | (0.02) | (0.02) | (0.02) | |
Firm age | −0.0028 ** | −0.0006 | 0.0001 | 0.0009 | 0.0027 | 0.0027 |
(0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | |
Manager experience | −0.0038 *** | −0.0006 | −0.0032 | −0.0004 | −0.0003 | |
(0.00) | (0.00) | (0.00) | (0.00) | (0.00) | ||
Owner job | 0.1615 *** | 0.1041 *** | 0.1627 *** | 0.1029 ** | 0.1025 ** | |
(0.03) | (0.03) | (0.04) | (0.04) | (0.04) | ||
GL2 | 0.0697 | 0.1049 | 0.1127 | |||
(0.06) | (0.14) | (0.14) | ||||
GL3 | 0.1054 *** | −0.0300 | −0.0262 | |||
(0.04) | (0.09) | (0.09) | ||||
GL4 | −0.0801 ** | −0.1884 * | −0.1813 * | |||
(0.04) | (0.10) | (0.10) | ||||
Bribe | 0.1215 *** | 0.0821 ** | 0.0784 ** | |||
(0.04) | (0.04) | (0.04) | ||||
Financially constrained | 0.0269 | |||||
(0.05) | ||||||
Observations | 935 | 894 | 894 | 295 | 295 | 295 |
(1) | (2) | (3) | |
---|---|---|---|
Variables | Margins | Margins | Margins |
Education3 | 0.0259 | 0.0244 | 0.0190 |
(0.05) | (0.05) | (0.05) | |
Education2 | 0.0026 | −0.0184 | −0.0187 |
(0.05) | (0.05) | (0.05) | |
Ln sales | 0.0035 | 0.0033 | −0.0000 |
(0.01) | (0.01) | (0.01) | |
Firm age | 0.0012 | 0.0014 | 0.0015 |
(0.00) | (0.00) | (0.00) | |
Manager experience | −0.0039 * | −0.0010 | −0.0012 |
(0.00) | (0.00) | (0.00) | |
Owner job | 0.1407 *** | 0.1097 *** | 0.1013 *** |
(0.03) | (0.03) | (0.03) | |
GL4 dummy | −0.1596 *** | −0.1544 *** | |
(0.04) | (0.04) | ||
Bribe avIR | 0.1579 *** | 0.0973 *** | 0.0927 *** |
(0.03) | (0.03) | (0.03) | |
Financially constrained | 0.0506 * | ||
(0.03) | |||
Observations | 613 | 613 | 613 |
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Devlina; Sahu, S.K. Bureaucratic and Societal Determinants of Female-Led Microenterprises in India. Adm. Sci. 2023, 13, 68. https://doi.org/10.3390/admsci13030068
Devlina, Sahu SK. Bureaucratic and Societal Determinants of Female-Led Microenterprises in India. Administrative Sciences. 2023; 13(3):68. https://doi.org/10.3390/admsci13030068
Chicago/Turabian StyleDevlina, and Santosh Kumar Sahu. 2023. "Bureaucratic and Societal Determinants of Female-Led Microenterprises in India" Administrative Sciences 13, no. 3: 68. https://doi.org/10.3390/admsci13030068