Income Inequality and Its Determinants in Microenterprises in Baja

Proceedings of 8th Annual London Business Research Conference

Imperial College, London, UK, 8 - 9 July, 2013, ISBN: 978-1-922069-28-3

Income Inequality and Its Determinants in Microenterprises in Baja California, Mexico

Jocelyne Rabelo Ramírez* and Ana Barbara Mungaray Moctezuma**

Several authors consider the microenterprise sector and its development as a mechanism to reduce poverty levels, due to their ability to generate income and employment. In this analysis we argue that microenterprises contributes both to economic growth and social development in Baja California, Mexico showing that their development is important to support entrepreneurship and reduce the population in poverty. However, it is required to give them training, technical assistance, articulate them to the formal markets and give them financial support to reduce their marginalization levels. According to the Gini Index the income that they earn is unequal, although they share the features of being informal and marginalized. We review and explain the differential in income microenterprises in Baja California that participated, during 2009, in a Public Policy Program called “Microenterprise Assistance Program for Employment Support in Baja California”, using the Fields’ decomposition method. The findings disclose that are the variables sex, education, improvements in equipment and the quality of their products, which explains a higher proportion of microenterprises income. Thus, to potentiate microenterprises development, it is required an inclusive public policy which strength education’s levels (as a result of technical training), access to health services and formal markets and tries to integrate women to sector in an equal manner.

JEL CODE: D63, D33, M21

1. Introduction Mexico is a country with large regional inequalities where the north and the south polarize due to their development levels, income, access to goods and basic utilities, and poverty. In México, 44.5% of the population lives in poverty, either extreme or moderate, according to the study made by CONEVAL (2010). This inequality is reflected at a regional level, where northern states are below the extreme poverty average (32.3%) and in the southern states this percentage rise to 64%. This shows that there is a more favored northern border, nevertheless, there are differences within the six states that form part of this region (Baja California, Sonora, Chihuahua, Coahuila, Nuevo Leon and Tamaulipas) which confirms the fact that in Mexico there are notable contrasts; for example, if the population in poverty is considered, Nuevo Leon is the state with the smallest moderate (19.3%) and extreme (1.9%) poverty levels and the largest percentage of population outside poverty (37.8%), whereas Tamaulipas *School of Economics and International Relations, Autonomous University of Baja California, Mexico. E-mail: [email protected] **School of Economics and International Relations, Autonomous University of Baja California, Mexico. Email: [email protected]

mailto:[email protected]

mailto:[email protected]



has the biggest moderate poverty (33.8%) and Chihuahua the largest extreme poverty (6.6%) (See table 1).

Table 1: Northern Border Poverty Population Percentage, 2010.

Poverty BC Coahuila Chihuahua Nuevo Leon Sonora Tamaulipas

Population in poverty situation 32.1 27.9 39.2 21.1 33.8 39.4

Population in moderate poverty situation 28.9 25.0 32.6 19.3 28.6 33.8

Population in extreme poverty situation 3.1 2.9 6.6 1.9 5.2 5.5

Vulnerable population on account of social needs 39.3 26.4 23.5 33.0 32.7 27.9

Vulnerable population on account of income 6.1 12.6 12.6 8.1 6.4 9.1

Not poor nor vulnerable population 22.6 33.0 24.6 37.8 27.1 23.7

Source: CONEVAL, 2010. Furthermore, Baja California has the largest vulnerable population percentage on account of social needs (39.3%), and the largest vulnerable population on account of incomes, which is evidence of that polarization. Moreover, among the Border States, Baja California has the smallest percentage of population non poor or vulnerable population. The Gini index is another indicator that confirms the population inequality related to income, in which the closest to one, the larger the inequity in income distribution. In four of the six northern border states (Baja California, Coahuila, Nuevo León y Sonora), a growth in the inequality distribution of income from 2008 to 2010 distribution is observed (see table 2); Baja California displays the strongest impact, where the Gini index rose from 0.485 in 2008 to 0.56 in 2010.

Table 2: Gini Index for Mexico’s Northern Border States, 2008-2010.

Federal Entity GINI

2008 2010

Baja California 0.453 0.506

Coahuila 0.470 0.477

Chihuahua 0.532 0.473

Nuevo León 0.489 0.498

Sonora 0.471 0.479

Tamaulipas 0.485 0.450

Mexican United States 0.505 0.509

Source: Own elaboration with information from CONEVAL, 2008-2010

Additionally, all those intraregional differences are also reflected at an enterprise level, with the existence of a stratum of big enterprises successfully linked (directly or indirectly) to global networks, whereas a large number of micro and small enterprises that generate jobs are unable to access the benefits of a globalizing environment and constitute one of the more heterogeneous and dynamic sectors not just in Mexico, but in all Latin-American (Orlando & Pollack, 2000).



Several authors (Orlando & Pollack, 2000) (Premchander, 2003), consider micro-enterprises and their development as a mechanism to reduce poverty levels, because of their capacity to generate jobs and income. Though, they are also considered by other authors (Gerxhani, 2004; Schneider and Enste, 2001) as the enterprise stratum that captures the population that have not been able to get a job in the formal sector given their low training levels and, in general, for their informal life conditions (reflected in the absence of property rights, for example). The discussion regarding informal economy has to do with a characterization that includes the activities developed in markets outside a legal frame. Gerxhani (2004) states the existence of situations where agents of the informal sector are not conscious of their condition, since the State does not reach its environment or they do not count with the information that allows them to decide if they should move or not from one market to another. This approach refers particularly to the activities of self-employment that usually occur in urban areas of developing countries. Micro-enterprises considered in this analysis are characterized as informal, since they are out of the reach of the State. Nevertheless, this micro-enterprise sector contributes as much to the economic growth as to social development of this country. It shows that its development is fundamental in fortifying entrepreneurship, not only in Mexico, but in the State of Baja California and diminishing the levels of poverty of the most vulnerable population. However, the State must promote training, entrepreneurial knowledge transfer, technical assistance and the approach to institutions that articulate them to formality and have access to funding sources so that, this way, marginalization levels are reduced. Considering that in crisis scenarios, the establishment of a micro-enterprise is the way out of unemployment problems, the proliferation of this type of enterprises responds to survival practices (Mungaray et al., 2002) which allow them to replace the lost or not offered employment, or, to compensate the deterioration of real salary (Mungaray & Ramirez, 2007).

2. Microenterprise in Baja California With the purpose of fortifying micro-enterprise development in Baja California and as part of the public policy of the State’s Government, since 2009 the “Microenterprise Assistance Program for Employment Support in Baja California” has been implemented alongside the Autonomous University of Baja California. The programs’ objective is to bring technical training, monitoring, economic support and access to public health to the informal micro-entrepreneurs of the State. The abovementioned coincides with the argument of authors such as Frey, 1989; Loayza, 1996; Schneider and Enste, 2001 who explain, among other things, that an important element for the countries development is the capacity that the government has to integrate informal markets to the formal sector of the economy. The beginnings of this program dates back to 1999, when the Research, Assistance and Education for Micro and small enterprise appears, as a social service program that offered technical assistance to marginalized micro-enterprises of Tijuana, Baja California through the students of the management-economics area. This program is consolidated in such



way that it was propagated in all the state of Baja California and into other states like Nayarit, Sinaloa, Sonora, Yucatan, among others. Nevertheless, in 2009 there was a transition in public policies that offered training health and funding services which were offered to micro-entrepreneurs, to fortify the social basis micro-economic development. It is also worthy to mention that a micro-enterprise must have one to ten employees (including the owner), it has to be far from the scope of the State so it can be considered as informal and it has to be located in a marginalized zone of Baja California. During the year of 2009, within the framework of the program, 3888 micro-entrepreneurs were identified in the State, from which 1014 (18.4%) received assistance and were supported in the process of their formalization. In other words, besides guiding them in production, costs, marketing, among others, they have received information on the benefits of finding themselves in a formal regulatory context and have moved toward this status. In this sense and with the purpose of making an analysis of the micro-entrepreneurs and making the socioeconomic context in which they live, the socioeconomic information of those who were assisted in attendance and formalization was used in order to establish a differentiation by gender, education, economic activity, migratory status, family, decision making and income. From a gender perspective, of the total of micro-entrepreneurs attended to, about 65.3% are women; at a municipal level, in Ensenada the proportion of attended female micro-entrepreneur was of 52.6%, in Tecate 58.6%, 66.3% in Mexicali and in Tijuana 67.7%; it is observed that women are more prone to participate in activities of these kind of markets, and the empirical evidence demonstrates that they are over-represented in the informal activity (Whitson, 2007) when facing high social and familiar costs mainly in the developing countries. The type of work and remuneration level between men and women differs as well; women are the ones being seriously left behind in economic and political participation (Ibarran and Robles, 2004). Comparing the reasons which motivated them to establish a micro-enterprise, differentiating by gender, it can be observed that the main reason for women as well as for men was to increase their income (44% and 33%, respectively). According to Evans and Leighton (1989), the establishment of a micro-enterprise is related to individuals with low wages (as employees) or those that were unemployed and who become self-employed to face it. For female micro-entrepreneurs, 26% initiated their business because they were in this situation. However, the main reason that motivated them to initiate a company was to increase their income (44%). Nevertheless, it is observed in 17% that this motivated their personal growth, 8% made it to continue with family tradition and the rest of them, in order to be their own boss or because of the flexibility that having their own establishment offers (see table 3).



Table 3: Reasons to Start a Business, by Gender, in Baja California 2009.

Reason Woman Man

Personal fulfillment 17% 19%

Unemployed 26% 27%

To increase income 44% 33%

To continue with a company 1% 1%

Familiar tradition 8% 16%

To be their own boss 2% 3%

Flexibility 2% 1%

Source: Own elaboration with data gathered by the Micro-entrepreneurship Assistance Program for Employment Support in Baja California, 2009.

Considering the activity the women used to do before being micro-entrepreneurs, 49% were employees, 7% were students, 38% were housewives, 4% were already micro-entrepreneurs before having that business (see figure 2). Figure 2: Activity Used to Do Before Being Microentrepreneur, Baja California 2009.

Source: Own elaboration with data gathered by the Micro-entrepreneurship Assistance Program for

Employment Support in Baja California, 2009.

From the women who used to be housewives, it can be observed that 53% started their own business to increase their income and 17% for personal fulfillment. According to Orlando & Pollack, 2000, in Mexico, the most vulnerable groups to becoming poor are unmarried women considered as head of a family.

3. Methodology The social based micro-enterprises that participated in the program during 2009, before receiving formal orientation, were considered homogenous because of their lack of regulation in municipal, state, and federal levels. However, these micro-entrepreneurs undertook activities by which they obtained income and that in a great proportion serve as sustenance for their families.



In this sense, and considering the characteristics of the microenterprises of Baja California in this study, the profit (understood like the difference between the sales and daily costs) observed and registered as part of their business operation is considered as independent income which, according to Fields (1979), is the net income that is obtained from the independent work in businesses, domestic or professional services. With the purpose of presenting the income distribution of the 1014 micro-entrepreneurs who decided to become part of the formal market, the Gini indexes were calculated, which is one of the most used measures of economic inequality. Coinciding with Sen (2001), a way to analyze this indicator is by the construction of a Lorenz curve. The Gini index, measures the distance that exists between the Lorenz curve and the line of absolute equality, the sensitivity of this indicator does not depend on the income levels, but of the relative position of each individual in reference with the others (Sen, 2001). This indicator is the mostly used measure of the distribution of the income; it varies between 0 and 1, and the closest to the unit, the greater is the inequality degree in the income distribution (Unikel, L., 1976; Lustig, N., 1984; Chackravorty, 1994). The formula for the calculation of the index is as follows:

1

1

1

1

n

i i

i

n

i

i

P Q

G

P

Where: Pi= accumulated proportion of population Qi= accumulated proportion of the income Once the distribution of microenterprises income is identified, and with the purpose of identifying the variable factors that explain this difference, the Fields’ Decomposition Method (2003) is used, which allows to ponder, based on the estimation of the income’s semi-logarithmic function, the participation of each explanatory variable. In other words, it begins from an income function, based on the Theory of Human Capital, in which the income depends on certain variables (Ibid) like: gender, age, micro-entrepreneur’s education level, business direction, business age, among others. This technique starts with the assessment of remuneration equations (semi-log) where the calculation of a semi logarithmic function is given by:

ii ZY )ln( (1)

Where:

1...21 J

(2)

And:

iiJiii xxxZ ...1 21 (3)

that is to say,

j

iijiji XY *ln (4)



This considers the benefits logarithm (lnYit) according to a group of variables (X ijt). From this on, the Fields Decomposition is obtained as a result of the ratio between the covariance in the income and each variable, and the variance of income, that is, the relative weight of each variable, as follows:

j u

j iijj

jYVar

YZBCovS

)(ln

ln,*( (5)

Where:

itYln: income logarithm

: associated component to each factor i

: each factor that explains income S: variable j ratio that is explained by the Z variable. The analysis includes those microenterprises (1008) that reported profits higher than zero and the variables were obtained from the counting card1, as from the diagnostic2 and they are categorized as qualitative or quantitative. For purposes of this analysis, the qualitative variables are transformed into dichotomous variables, in order to ponder their participation in explaining the differential in the micro-entrepreneurs income. The variables taken into consideration are the following: Qualitative: -Municipality (mun): variable captured by the state of Baja California where the micro business operates, these are Tijuana, Ensenada, Mexicali, Rosarito, or Tecate -Streets stand (streets): This refers to a microenterprise that commercializes their products or offers their services in a public space, immovable or semi-movable. For this variable one is assigned if it is a permanent street stand and zero if it is a peddler type of stand (independent of family owned). -Sole enterprise activity (only act): Shows the productive condition of the microenterprise owner, being considered as the only one activity when they work exclusively in their business; to this condition one is assigned and zero when they engage in other activities aside from setting up their business. -Price as product strategy (price): This variable shows if the micro-entrepreneur considers the price of his products or services as part of the sales strategy. It is understood if the micro-entrepreneur uses the price in which he sells his product as a product strategy, to this situation the value of one is assigned.

1 "Data recollection instrument which goal is to learn the geographic location, type and general data of the surveyed unit and the

micro-entrepreneur..." (CIADMYPE, 2009)

2 Data recollection instrument which is focus on obtaining the employee and entrepreneur’s profile, it also provides operation

information from the business.



-Determines the product price based on cost (cost base): Shows if the price determined by the micro-entrepreneur, had considered the costs of production; in case it is determined based on the type of consumer or in other words the price taker, will be assigned a value of zero. -Market potential (mkt pot): It is a variable that identifies if the micro-entrepreneur considers that its business has potential for expansion considering its market size (situation in which one is assigned). -Advertising (advertising): This qualitative variable is disclosed if the micro-entrepreneur uses some sort of advertising and marketing strategy, whatever they may be, scenario in which one is assigned. -Changes of machinery (chang mach): It is a variable that identifies if the micro-entrepreneur has made changes in machinery, regardless of how many are there. -Product improvement (upgrade): This variable identifies whether, since it began operations, the micro-entrepreneur has made changes to its product, which lead to improvements to this product. -Expand the business (expectations): This variable considers expectations of the micro-entrepreneur, identifying if the expansion of its economic unit is part of his vision; in case that the micro-entrepreneur does not consider to expand its business the number zero is assigned. -Gender (gender): This variable seeks if the micro-entrepreneurs' gender defines a difference in the income, for the analysis it is assigned a zero if the owner is a woman and a number one for men. Studies such as Mungaray and Rabelo’s (2008) have found evidence that the difference in the income is for gender. -Secondary Education (second): The variable determines if the micro-entrepreneur has secondary education (if it is completed or not). -High school education or more (high school): The variable determines if the owner of the micro-entrepreneurship has at least high school education. Arguments based on Mungaray and Ramirez Urquidy (2007), who argue that higher incomes for workers and greater efficiency and productivity of enterprises is associated with investment of formal education, among others. -Native of Baja California (native): variable that identifies if the micro-entrepreneurs are native of the state. Quantitative: -Business age (b age): quantitative variable discloses how many years the microenterprise has been operating. -Economic-Dependent (eco-dep): This socioeconomic variable discloses how much people depend on the activity performed the micro-entrepreneur.



-Knowledge acquisition (know): This variable represents the time, measured in years, that the micro-entrepreneur needed to acquire the skills that allow him to operate his business. As for the effect of each of these variables on the income received, theoretically it is expected to be the variables gender, education and experience of the entrepreneur, the ones that have the greatest impact on the spread of earned income.

4. Results A large proportion of the micro-entrepreneurs open a business in order to increase their revenue or because they are unemployed, their background shows evidence of economic rationality, because if the daily average earnings are compared to the general minimum wage (SM) for the area to which Baja California belongs to and differentiating by gender, female micro-entrepreneurs earn on average $ 306 pesos per day, while men $514 pesos (this difference is a sign of inequality in perceived wages distinguished by gender). If these averages are compared to the minimum wage ($ 54.9) and even with the same) in the region (fluctuating between $ 80 and $ 160 per day, both average earnings are higher, which supports the rationality of male and female entrepreneurs when setting up their business, a situation that is further increased macroeconomic crisis scenarios. On average, the income of the 1014 formal microenterprises of Baja California, without gender distinction, was of $417.09 Mexican pesos per day. This represents 7.6 times the minimum wage; given that an elevated proportion is assigned to the support of micro-entrepreneurs and their families. And, if compared with the salary earned on a “maquiladora”, for example, the micro-entrepreneurs rationality is given when calculating its opportunity cost by establishing a micro-entrepreneurship or by working on factory. The minimum income earned by a micro-entrepreneur was of $13.36 and the maximum was of $7,000.00, which shows an unequal distribution of these incomes, even though the assisted micro-entrepreneurships, during 2009, show similar characteristics and is foreseen that the benefits earned are considered relatively homogeneous (See table 4).

Table 4: Statistic Describing the Benefits of Formal Micro-Entrepreneurships in 2009.

Statistic Benefit

Mean 417.09

Stan. Dev. 947.00

Minimum 13.36

Maximum 7000.00 Source: Own elaboration with data gathered by the Micro-entrepreneurship Assistance Program for


________________________ 4 Two micro-entrepreneurs were excluded by reporting losses during the period. From the Gini indicator estimate (0.613) the concentration on the micro-enterprises benefits can be observed (See table 5). This value shows that from the micro-entrepreneurs aided by the program, where there are a few who obtain very high incomes,



and a great number of micro-enterprises that operate in survivor conditions, restricted probably because by the time of receiving the assistance, were out of the reach of the State due to their informal condition. Even though, still with different growth opportunities, these micro-entrepreneurs also decided to regulate their situation. In this sense, there is inequality on formal and assisted micro-entrepreneurs incomes distribution in the Program.

Table 5: Gini Index of Micro-Entrepreneurs in Baja California 2009.

Index

Gini 0.613 Source: Own elaboration with data gathered by the Micro-entrepreneurship Assistance Program for


With this information, the Fields decomposition for the 12.56% of the inequality on the microenterprises incomes is explained by the variables considered in the analysis. Even when the micro-entrepreneurs were operating on informal conditions, gender explains by 2.28% the differential in the income obtained. This result shows evidence that even though men and women decide to run an enterprise, the benefit that they could obtain differs. This result coincides with Mungaray and Rabelo (2008) where salary discrimination because of gender exists within the informal sector of Tijuana. In average, men receive $207.5 more than women per week, in other words, men earn 18.16% more than women on basic wage per week. Besides, the fact that micro-entrepreneurs have done changes to machinery and equipment explains the 2.54% in the income differential, which shows evidence that ingenious has an impact in the income received. Other fact that explains, in a 1.45%, the income differential is the fact that micro-entrepreneurs consider that market potential exists, while using any kind of advertising explains the 1.20% from the divergence in the micro-enterprise income (See table 6). In fact, expectations also play a key role while explaining a differed income, when expanding their enterprise it grows 0.71% One variable that on micro-enterprises studies is taken into account is scholarship. In studies, such as Mungaray (2002), was found that scholarship impacts on the development of the micro-enterprise and the results of the herein analysis are consistent with them, given that 1.22% from the income difference is explained by scholarship (high school, primarily).



Table 6: Semi-Log Regression, Micro-Entrepreneurs of Baja California, 2009.

Variable B t-Statistic Significance Proportion

Streets 0.262 1.815 0.070 0.11%

Only act 0.222 1.865 0.063 0.01%

Price -0.150 -1.501 0.134 0.58%

Cost based 0.223 2.214 0.027 1.31%

Mkt pot 0.184 1.527 0.127 1.45%

Advertising 0.158 1.602 0.110 1.20%

Chang mach 0.420 3.384 0.001 2.54%

Upgrade 0.136 1.308 0.192 0.83%

Expectations 0.122 1.127 0.260 0.71%

Gender 0.502 5.154 0.000 2.28%

Second 0.191 1.589 0.113 0.20%

High School 0.353 2.922 0.004 1.22%

Native 0.086 0.947 0.344 0.12%

Total 12.56% Source: Own elaboration with data gathered by the Micro-entrepreneurship Assistance Program for


It can be seen from the analysis, that regardless which economic activity they do, the elements that allow micro-entrepreneurs to gain more profit are the improvements to the machinery and equipment, if advertising is used by those with higher education levels, and that there are no gender differences. In this sense, a public policy that strengthens the micro-entrepreneurs capacities without gender distinction and provides more information and capacitation in a way that they can rely on the elements to strengthen micro-entrepreneurship development in Baja California. Also, as a result of this analysis and in accordance with Kimhi (2009), policies that strengthen entrepreneurship could be successful in the reduction of inequality if they are directed to the strata of people of low-income and less educated segments of the population. Additionally, all policies directed to the reduction of poverty in the micro-entrepreneurship sector have a double challenge: to increase production and sales of the microenterprises throughout micro-entrepreneurship development and to promote the improvement of income and work conditions to the self-employed, employees, women and youth of the sector” (Orlando & Pollack, 2000)

Inequality in Profit and Its Explanation by Gender While making the income of microenterprises analysis, distinguishing by gender the value of the Gini Index (see table 7) needs to be taken into account, the profit between women micro-entrepreneurs (0.279) is more homogeneous than men (0.311), which can be attributed to the activities that they do and to psychological matters when making decisions that sometimes include women.



Table 7: Gini Index by Gender, Baja California, 2009.

Gini

Women 0.279

Men 0.311 Source: Own elaboration with data gathered by the Micro-entrepreneurship Assistance Program for

Employment Support in Baja California, 2009

Making the Fields decomposition by gender, we have a 13.3% difference of income between women micro-entrepreneurs explained by variables like sales strategies, product quality, machinery changes and education level; while a 22% of the profit of microenterprises is explained by the strategic product variables: quality, economic dependents, municipality, machinery changes, time that it took her to learn, amongst other things. This way, the variables that explain in greater proportion the existence of profit differences between women micro-entrepreneurs are: if the micro-entrepreneur uses as a strategy of her product quality (3.1%), if she makes machinery changes (2.9%), if she has a high school level at least as education (2.1%), the municipality in which the business is located (1.3%), amongst other things, which allows us to explain the 13.3% of the differential in profit made by the women micro-entrepreneurs that took part in the program (see table 8).

Table 8: Semi-Log Regression, Women Micro-Entrepreneurs of Baja California, 2009.

Variable B t-Statistics Significance Proportion

Municipality -.074 -1.476 .141 1.3%

Employees .114 1.016 .311 0.2%

Streets .264 1.703 .089 0.1%

Product Strategy: quality

.308 2.997 .003 3.1%

Can change product -.128 -1.243 .215 0.1%

Advertising .153 1.374 .171 0.9%

Changes .387 3.115 .002 2.9%

Expansion expectation

.105 .930 .353 0.4%

No education -.224 -1.918 .056 1.9%

High school or more .294 2.156 .032 2.1%

Health services .134 1.264 .207 0.2%

Total 13.3% Source: Own elaboration with data gathered by the Micro-entrepreneurship Assistance Program for


Additionally, if a woman micro-entrepreneur has no education or if she can change the product, she has an inverse relationship with the profit, while using quality as the product strategy, using advertising, making changes to the machinery and equipment, having expansion expectations and having a high school level at the least as education have a positive effect in the income. In fact, they having no education explains de 1.9% of the net income differential, and the negative impact present in this variable as well.



On the other hand, considering the analysis made for men micro-entrepreneurs, using price as the main strategy is the variable that explains the most the differential on income, which has an inverse relationship, that is, those men micro-entrepreneurs that use price as a strategy have lower income. Furthermore, the time that it took him to learn explains the 2.27% of the difference in income, while the fact that they exclusively dedicate themselves to the operation of the microenterprise makes a 1.24% (see table 9).

Table 9: Semi-Log Regression, Men Micro-Entrepreneurship Baja California, 2009

Variable B Estadístico t Significancia Proporción

Municipality

-0.153 -1.771 0.080 3.51%

Economic unit: familiar unit 0.172 0.838 0.404 0.16%

Business age -0.037 -0.958 0.340 0.98%

Sole entrepreneurial activity 0.379 1.717 0.089 1.24%

Time for learning 0.051 1.804 0.074 2.27%

Economically Dependent. 0.105 1.895 0.061 2.01%

Product strategy: price -0.998 -2.974 0.004 4.25%

Price given at production cost 0.406 1.888 0.062 0.04%

Market Potencial 0.569 2.005 0.048 0.04%

22.04% Source: Own elaboration with data gathered by the Micro-entrepreneurship Assistance Program for


5. Conclusion

Taking into account the findings of this analysis, in order to strengthen micro-entrepreneurship development, public policy in a region or country should be aimed towards strengthening education levels (training), access to health services, micro-entrepreneurs' innovation and their business as well as providing information about the benefits of being within the formal framework. It should be mentioned that this analysis has identified the elements that have an affect between the income discrepancy of the micro-entrepreneurs before associated with formal and trained markets, however, there is the need to analyze the situation of these agents once they have had technical assistance and financial support to analyze whether the strengthening of these elements have a positive effect in reducing the spread of the income generated by these entrepreneurs. On the other hand, it has been shown that even in informal markets there are income differences attributed to gender, which may be related to the type of activities that men and women or conditions such as shift working hours (day), the sale mechanisms (credit, for example) or that the woman does not consider herself as a small business owner who brings her family income. Given the nature of these businesses, are equal in that they are outside the formal framework in more marginalized areas, however, within the micro, there are variables such as level of education, changes in the machinery and equipment, sex, which according to the evidence, impact on the income inequality.



The Gini index (0.613) when is analyzed for both, man and women, shows evidence of income concentration, which value is higher than the Gini index for formal market in the State (0.503) and it has been found that the variables that most impact have on difference in income is the gender, if you changes to the machinery or equipment are made and if the owner believes that there is a potential market. On the other hand, the profit between women entrepreneurs is more equitable than men and is the level of education, quality of products and the improvements made to machinery or equipment, elements that further explain the income gap between them. That is, the women entrepreneurs are variables such as product quality, changes in the machinery, whether or not to they have studies, municipality, advertising the greatest proportion determine the differences in the earned income. While in men the quality and product strategy, the municipality where the business is located, how long it took to learn, number of dependents, and the business is impacting a greater percentage in the income inequality. Previous studies have found that educational levels impact the performance of the micro-entrepreneurships, this analysis revealed that the entrepreneurs that have high school studies, allows a differential in earnings, so that positive impacts wherefore, it is suggested that an element that could strengthen a more equitable distribution of micro-entrepreneurship income is training micro-entrepreneurs. Correspondingly, the issue of gender equity in income impacts of micro-entrepreneurs, observing that even in informal markets is women who are further marginalized. In this sense, to increase microenterprise development of the social base, it is required a comprehensive and inclusive public policy that strengthens education (reflected in technical training), access to health services, access to formal markets, incorporation of women into the productive sector in a more equitably way.

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Income Inequality and Its Determinants in Microenterprises in Baja

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