Women Entrepreneurs in the race of rural development: A macro-economical study based on emerging India

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Women Entrepreneurs in the race of rural development: A macro-economical study based on emerging India Sanzida Afrose Department of Business Administration, Metropolitan University, Abstract : From

1 Women Entrepreneurs in the race of rural development: A macro-economical study based on emerging India Sanzida Afrose Department of Business Administration, Metropolitan University, Abstract : From the pragmatic age in the centuries old Indian civilization, the women in the subcontinent are worshiped as the symbol of goddess, respected as adored mothers, honored as lovely wives, taken care as princess daughters. But when this huge number of women work force are remained aloof in terms of contribution to the one of largest emerging economy of the largest democracy, then simple question arises: Is there democracy for Indian Women and are they freely allowed to contribute for their motherland. This paper investigates the contribution of the Indian women entrepreneurs to the development of standard of living in the rural economy of India. To do this investigation macroeconomical co-integration approach has been adopted. Keywords: Women Entrepreneurs, Rural Development, Macro-economy, Co-Integration I. INTRODUCTION Knowledge, as a major tool in the modern era of competitive economies, is getting importance day by day. It suggests that the higher growth rates, both for organization and economy, must be linked to innovative activity and unrestrained competition. So, entrepreneurial activity is the most vital aspect of this organization. Entrepreneurship, day by day, is being recognized as a prime engine of economic growth. By combining the existing resources with innovative & excellent ideas, entrepreneurs add value through the commercialization of new & innovative products, the creation of brand new jobs, and the construction of new firms. It has been indicated by the Global Entrepreneurship Monitor that nations engaged in higher levels of entrepreneurial activities enjoy healthy economic growth. In a word, entrepreneurs contribute to the macro-economy by commercializing the new ideas. In the India, among 1.3 billion of the population almost half are female. But due to cultural drawbacks almost all of them are aloof from the workforce. But to ensure the a better standard of living in this era of globalization an well figured per capita GNI is obligatory. So keeping aside this huge female workforce is a huge setback for emerging Indian economy. The intentions to entrepreneurship of well educated young people, both in urban and rural community, are important because they are the most probable segment to influence the events of the future and the most importantly to be future leaders to lead the nations. Nonetheless, male entrepreneurship is likely to represent the base line of macro-economic. But younger female entrepreneurial intentions are more likely to represent the social changes. Accordingly, capturing the intentions of young well educated females must be vital, not only in terms of what themselves might do, but also in evaluating & reacting how the cultural phenomenon is changing and, moreover their role in influencing the cultural behaviors of the today s society and coming future as well. In this study, we have investigated the Indian women entrepreneurs and their contribution to the welfare of the All Rights Reserved 337

2 II. LITERATURE REVIEW It has been found that, working women in the developing countries have huge contribution for the family welfare and children rearing [1-8]. Thomas [9]described that in Brazil, when patrimony income of family patrimony income remained in the hands of the mother, the marginal effect of the income was approximately 20 times higher on the family s welfare factors than the income was under the control of the father. Financial resources that were acquired by the woman also did appear to bring forth a long-time reduction in the factor of fertility and birth-spacing as well as the allocation of resources towards the children of the family, generating an gradual improvement in welfare of the family [10-16]. According to the research of the World Bank (2011), women entrepreneurs in the world are controlling almost 35.30% of companies throughout the world. So, since the year 2000, these women entrepreneurs have in the position of ownership and operation of a large portion of companies in developing economies [17] (Jones, 2012). We have calculated the impact of the proportion of women entrepreneurs based on six welfare indicators: Fertility rate, total (births per woman); Infant mortality rate (0-1 year) per 1,000 live births; Improved Sanitation Facilities, Rural (% of rural population with access); Improved Water Source Rural (% of rural population with access); Maternal mortality ratio per 100,000 live births & Seats held by women in national parliament, percentage. Aterido, Beck and Iacovone (2011), few empirical researches have tried to find out the causal effect of entrepreneurship of women. They have demonstrated that in 37 African economies, in a few companies where women are having partial ownership optioned to the use of financial services. This may have happened because of the level of responsibilities and the roles played by them in their households, to their poor level of educational qualifications, and moreover to their low level of income in the face of interest rates which might have been too high [18]. Development of entrepreneurship contributes to reduction of poverty, more specifically when employment is created through the start up of new entrepreneurship or by the expansion of existing organizations and they contributes to the increase of social wealth. Because it develops new types of industry, creates brand new jobs, open access to new markets, bring innovative technology, provides new forms of institution, and finally net increase in real productivity does occur, increases income which eventually results in higher standards of living for the country s population [19] then it seems logically to state that if the number of entrepreneurs of any given country increases, the indicators of poverty must decrease and vice verse. Entrepreneurship as a whole contributes to social wealth by developing new types of industry, creating brand new jobs, opening access to new markets, bringing innovative technology, providing new forms of institution, and finally by occurring net increase in real productivity. The jobs that are created through the activities of the entrepreneurs, on the other hand lead to the way for equitable distribution of income which increase the standard of living for the people. The benefits of entrepreneurship are increasingly recognized. It is said that development in the private sector plays a vital role in the reduction of poverty. The private sector, SME as well, always important to create and to sustain the jobs that are necessary for the poor people to work in and to earn the income that are needed to purchase goods and service[20]. So, it s tough to find out clear reason to qualify all of All Rights Reserved 338

3 phenomenons like unproductive because ex-post they will be a building block to further productive activities. These entrepreneurs may play role to development of the society and poverty reduction factors although a substantial impact on economic growth have not been found by them. But at least, they avoid poverty from increasingly getting worse under certain circumstances or constitute base for future social mobility [21, 22]. III. DATA, METHODOLOGY & RESULTS Time series data has been taken from the year 1990 to Data has been collected from World Bank, IMF, United Nation Databases and publications of Ministry of Micro, and Small & Medium Enterprises of the Government of the Peoples Republic of India. The variables are the following: Women Entrepreneurs percentage to total Entrepreneurs in the country; Fertility rate, total (births per woman); Infant mortality rate (0-1 year) per 1,000 live births; Improved Sanitation Facilities, Rural (% of rural population with access); Improved Water Source Rural (% of rural population with access); Maternal mortality ratio per 100,000 live births, Seats held by women in national parliament, percentage. After conducting the unit root test, a co-integration method of analysis has been approached. In the Phillips- Perron Test of unit root test (Appendix) it has been found that apart from one all the variables are stationary at level. So Autoregressive-Distributed Lag has been applied for deduction. The bound test shows that F Statistics is larger than lower bound and upper bound in 5% level of significance. So there must be integration among the variables in the long run. It is found that both the ISF and IWS are significantly (at 95% level of confidence) to the women entrepreneurs percentage in the long run. FRT and WIPM are also integrated with the women entrepreneurs percentage but in the confidence level at 90%. But in the long run, IMR and MMR are found to be integrated insignificantly with the women entrepreneurs percentage. Apart from FRT and ISF all the variables are not significantly integrated with the women entrepreneurs percentage in the short run. IV. CONCLUSION The question of this study was to analyze the effect of ladies' enterprise on six welfare pointers in India on a time of twenty six years. Keeping in mind the end goal to do as such, we have utilized one of the four factors in the information from the World Bank, IMF, United Nation Databases and productions of Ministry of Micro, and Small and Medium Enterprises of the Government of the Peoples Republic of India. We have illustrated, with the assistance of time arrangement estimation, that this pay producing movement for ladies fundamentally enhanced the welfare of populaces. Notwithstanding, regardless of the possibility that two factors lost their hugeness, no nonsensical sign was noted in their coefficients. This macroeconomic examination supplements the endeavors put forward to actualize intercession strategies went for diminishing the requirements affecting ladies' business. It was especially intriguing to note that by advancing expanded open doors in ladies' business enterprise, these ladies will profit by an individual pay wage which will help them better add to the welfare of their family and especially that of their kids while effectively taking an interest in the feasible advancement of their general public. Accordingly the way of life, more specifically the standard of living will increase. REFERENCES [1] J. Hoddinott, and L. Haddad, Does female income share influence household expenditures? Evidence from Côte d'ivoire, oxford Bulletin of Economics and Statistics, vol. 57, no. 1, pp , [2] J. Strauss, G. Mwabu, and K. Beegle, Intrahousehold allocations: a review of theories and empirical evidence, Journal of African Economies, vol. 9, no. Supplement 1, pp , All Rights Reserved 339

4 [3] M. A. R. Quisumbing, and B. F. McClafferty, Food security in practice: Using gender research in development: Intl Food Policy Res Inst, [4] L. MAYOUX, Atteindre les femmes et les autonomiser: défis pour la microfinance39, Microfinance et Genre: Des nouvelles contributions pour une vieille question, pp. 35. [5] I. Guérin, Pratiques monétaires et financières des femmes en situation de précarité: Entre autonomie et dépendance, Lyon 2, [6] S. Gammage, "Gender and transnational asset accumulation in El Salvador." [7] S. H. Chant, New contributions to the analysis of poverty: methodological and conceptual challenges to understanding poverty from a gender perspective: United Nations Publications, [8] M.-C. Buisson, Allocation du temps de travail des femmes au Sénégal-Travaux domestiques et activités génératrices de revenus, [9] D. Thomas, J. Strauss, and M.-H. Henriques, Child survival, height for age and household characteristics in Brazil, Journal of Development Economics, vol. 33, no. 2, pp , [10] N. Schady, and J. Rosero, Are cash transfers made to women spent like other sources of income?, Economics Letters, vol. 101, no. 3, pp , [11] K. O. Mason, The status of women: A review of its relationships to fertility and mortality, [12] D. P. Hogan, B. Berhanu, and A. Hailemariam, Household organization, women's autonomy, and contraceptive behavior in southern Ethiopia, Studies in family planning, vol. 30, no. 4, pp , [13] M. Eswaran, The empowerment of women, fertility, and child mortality: Towards a theoretical analysis, Journal of Population Economics, vol. 15, no. 3, pp , [14] T. Dyson, and M. Moore, On kinship structure, female autonomy, and demographic behavior in India, Population and development review, pp , [15] J. E. Conrad, J. R. Hein, A. K. Chaudhuri et al., Constraints on the development of Proterozoic basins in central India from 40Ar/39Ar analysis of authigenic glauconitic minerals, Geological Society of America Bulletin, vol. 123, no. 1-2, pp , [16] J. C. Caldwell, and P. Caldwell, The cultural context of high fertility in sub-saharan Africa, Population and development review, pp , [17] S. Jones, Gendered discourses of entrepreneurship in UK higher education: The fictive entrepreneur and the fictive student, International Small Business Journal, pp , [18] R. Aterido, T. Beck, and L. Iacovone, Gender and finance in sub-saharan Africa, Are women disadvantaged, [19] S. White, Emerging issues and debates in the reform of the business environment for small enterprise development, Small Enterprise Development, vol. 16, no. 4, pp , [20] L. Rutashobya, and M. Nchimbi, The African Female Entrepreneur, [21] O. AKPAN, and I. SANDY, CAUSES OF FAILURE OF SMALL AND MEDIUM SCALE INDUSTRIES FINANCED BY NIDB IN ONDO STATE BETWEEN 1980 AND 2000, [22] B. Grosh, and G. Somolekae, Mighty oaks from little acorns: Can microenterprise serve as the seedbed of industrialization?, World Development, vol. 24, no. 12, pp , All Rights Reserved 340

5 Appendix: Results UNIT ROOT TEST RESULTS Phillips- Perron Test Variable Name Level First Difference Second Difference Intercept Trend & Intercept Intercept Trend & Intercept Intercept Trend & Intercept FRT P Value IMR P Value ISF P Value IWS P Value MMR P Value WE P Value WIPM P Value All Rights Reserved 341

6 ARDL TEST RESULTS Dependent Variable: WE Method: ARDL Sample (adjusted): Included observations: 24 after adjustments Maximum dependent lags: 2 (Automatic selection) Model selection method: Akaike info criterion (AIC) Dynamic regressors (2 lags, automatic): FRT IMR ISF IWS MMR WIPM Fixed regressors: C Number of models evalulated: 1458 Selected Model: ARDL(2, 2, 2, 2, 1, 0, 1) Variable Coefficient Std. Error t-statistic Prob.* WE(-1) WE(-2) FRT FRT(-1) FRT(-2) IMR IMR(-1) IMR(-2) ISF ISF(-1) ISF(-2) IWS IWS(-1) MMR WIPM WIPM(-1) C R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood Hannan-Quinn criter F-statistic Durbin-Watson stat Prob(F-statistic) *Note: p-values and any subsequent tests do not account for model All Rights Reserved 342

7 Variables Definition:: WE= Women Entrepreneurs percentage to total Entrepreneurs in the country; FRT=Fertility rate, total (births per woman); IMR=Infant mortality rate (0-1 year) per 1,000 live births; ISF=Improved Sanitation Facilities, Rural (% of rural population with access); IWS=Improved Water Source Rural (% of rural population with access); MMR=Maternal mortality ratio per 100,000 live births, WIPM= Seats held by women in national parliament, percentage ARDL Bounds Test Sample: Included observations: 24 Null Hypothesis: No long-run relationships exist Test Statistic Value k F-statistic Critical Value Bounds Significance I0 Bound I1 Bound 10% % % % Test Equation: Dependent Variable: D(WE) Method: Least Squares Sample: Included observations: 24 Variable Coefficient Std. Error t-statistic Prob. D(WE(-1)) D(FRT) D(FRT(-1)) D(IMR) D(IMR(-1)) D(ISF) D(ISF(-1)) D(IWS) D(WIPM) C FRT(-1) IMR(-1) ISF(-1) IWS(-1) MMR(-1) WIPM(-1) WE(-1) All Rights Reserved 343

8 R-squared Mean dependent var Adjusted R- squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood Hannan-Quinn criter F-statistic Durbin-Watson stat Prob(Fstatistic) Variables Definition:: WE= Women Entrepreneurs percentage to total Entrepreneurs in the country; FRT=Fertility rate, total (births per woman); IMR=Infant mortality rate (0-1 year) per 1,000 live births; ISF=Improved Sanitation Facilities, Rural (% of rural population with access); IWS=Improved Water Source Rural (% of rural population with access); MMR=Maternal mortality ratio per 100,000 live births, WIPM= Seats held by women in national parliament, All Rights Reserved 344

9 ARDL Cointegrating And Long Run Form Dependent Variable: WE Selected Model: ARDL(2, 2, 2, 2, 1, 0, 1) Sample: Included observations: 24 Cointegrating Form Variable Coefficient Std. Error t-statistic Prob. D(WE(-1)) D(FRT) D(FRT(-1)) D(IMR) D(IMR(-1)) D(ISF) D(ISF(-1)) D(IWS) D(MMR) D(WIPM) CointEq(-1) Cointeq = WE - ( *FRT *IMR *ISF *IWS *MMR *WIPM ) Long Run Coefficients Variable Coefficient Std. Error t-statistic Prob. FRT IMR ISF IWS MMR All Rights Reserved WIPM C

10 10 9 Variables Definition:: WE= Women Entrepreneurs percentage to total Entrepreneurs in the country; FRT=Fertility rate, total (births per woman); IMR=Infant mortality rate (0-1 year) per 1,000 live births; ISF=Improved Sanitation Facilities, Rural (% of rural population with access); IWS=Improved Water Source Rural (% of rural population with access); MMR=Maternal mortality ratio per 100,000 live births, WIPM= Seats held by women in national parliament, All Rights Reserved 346

EFFECTS OF REMITTANCE AND FDI ON THE ECONOMIC GROWTH OF BANGLADESH

EFFECTS OF REMITTANCE AND FDI ON THE ECONOMIC GROWTH OF BANGLADESH Riduanul Mustafa 1, S.M. Rakibul Anwar 2 1 Lecturer - Economics, Department of Business Administration, Bangladesh Army International