Impact of Social Unrest and the Pandemic on Family Micro-Entrepreneurship Success in Chile

Entrepreneurship constitutes a key element of economic vitality, serving as a lever for business development. By addressing the populace's needs, augmenting productivity, and fostering job creation Entrepreneurship is considered transcendent for the economy and it has been recognized as a driving force behind the economy as fostering innovation, contributing to employment generation and income generation, especially in local communities [1]. The interaction between entrepreneurship and economic expansion has been the subject of extensive and exhaustive study, existing research has underscored the enterprise's pronounced impact on catalyzing economic growth [2-5].

In Chile, Micro, Small, and Medium Enterprises (MSMEs) constitute a substantial portion of the nation's commercial landscape, encompassing 98.6% of all enterprises and contributing to 65.3% of formal employment. Globally, MSMEs play a pivotal role, typically constituting the preponderance of commercial entities, wielding considerable influence over employment generation, and driving innovation, thereby underpinning economic expansion and ameliorating poverty rates [6].

In 2001, Law 19,749 was enacted in Chile, created to promote and support family microbusinesses to promote the growth and success of family businesses. Its focus is to provide a legal basis for initiatives and programs that strengthen family micro-businesses within the country, ultimately contributing to economic growth and local entrepreneurship [7], where these enterprises are often characterized by their small-scale operations and family-based ownership structure.

According to this law, the term "smaller-sized enterprises" shall be understood to encompass micro-enterprises, small enterprises, and medium-sized enterprises where Micro-enterprises are those companies whose annual revenues from sales, services, and other operational activities have not exceeded 2,400 UF (95.795,47 USD - Value calculated for September 30, 2023) in the last calendar year; Small enterprises are those whose annual revenues from sales, services, and other operational activities exceed 2,400 UF but do not exceed 25,000 UF (997.869,52 USD) in the last calendar year; and Medium-sized enterprises are those whose annual revenues from sales, services and other operational activities exceed 25,000 UF but do not exceed 100,000 UF (3.991.478,10) in the last calendar year.

However, the appearance of the social upheaval that occurred in October 2019 in Chile and subsequently the arrival of the COVID-19 pandemic in March 2020, has brought havoc upon the MSME sector, with microenterprises emerging as particularly vulnerable due to their limited capacity to withstand protracted periods of inactivity and their heightened susceptibility to liquidity constraints. Strict border closure measures were applied around the world by every government and with it, paralyzed production, consumption decreased, and uncertainty increased [8, 9]. An analysis provided by the Ministry of Economy in its "Descriptive Analysis of the Impact of the Pandemic on Companies in Chile" shows that, between 2019 and 2020, 62.4% of companies grappled with a decline in sales. It is noteworthy that micro businesses bore the brunt of this economic downturn, with 63.1% experiencing diminished sales and a consequential average workforce reduction of -21.2%. While the adverse impact extended to businesses of various sizes, Microbusinesses were the ones that suffered the most damage. The Association of Entrepreneurs of Chile conducted a "Pandemic Impact" survey in April 2021, which revealed that 85.1% of respondents encountered impediments to their entrepreneurial pursuits. Of this cohort, 34.9% reported facing sales reductions, 36% confronted significant challenges involving partial cessation of activities and staff reductions, and 14.2% were faced with the difficulties generated by the indefinite operational suspension. Additionally, 52.5% were compelled to reduce their workforce and 36.8% of survey participants disclosed that their sales had plummeted by more than 50%, with only 15.3% managing to maintain or increase their sales figures. In this survey, the most pronounced risks cited were "Lack of liquidity due to low sales" (77.8%), trailed by "Debt arising from financial institutions" (36%), and "Deficiencies or delays in payments by debtors" (34.1%) [6].

In response to this multifaceted challenge [10], spanning the period from 2020 to 2021, the Government of Chile implemented a list of measures designed to buttress commercial enterprises. These measures encompassed the Covid-19 FOGAPE Credit line, employment subsidies such as Línea Regresa and Línea Contrata, the Employment Protection Law, direct financial support through SME Bonds, and strategic fiscal policies entailing extensions of payment deadlines for obligations and interest freeze, all intended to bolster the liquidity and resilience of companies in the face of the challenges faced by the pandemic.

Law 19.749, enacted in Chile to facilitate the creation of Family Microenterprises (FMME), stands as a legislative measure in the government's commitment to supporting entrepreneurship with a focus on formalization and business establishment. However, despite legislative facilitation, the primary challenges faced by businesses during the pandemic revolved around liquidity, primarily attributed to a significant decline in sales, further exacerbated by indebtedness to financial institutions (36%) and delays or non-compliance in debtor payments (34.1%). While the law aimed to promote the establishment of FMMEs, governmental concern focused on addressing immediate financial obstacles [11].

In complement to legislative efforts, the Chilean government, through entities like Corfo, implemented a robust set of initiatives to support SMEs, including programs like Economic Recovery Programs (PAR Impulsa), collaboration with Regional Governments to provide co-financing, supporting over 4,860 commerce businesses with subsidies exceeding $16.373 billion; Guarantees such as Fogain, Cobex, and ProInversión that facilitated SMEs' access to financing for investment, working capital, and refinancing; the "Corfo Mipyme Credit" program, operationalized through non-banking financial intermediaries, and additional initiatives beyond subsidies with a focus on entrepreneurship and job creation. These include platforms like "Pymes en Línea," offering free courses for SMEs' digital transformation, the "Viaje del Emprendedor," which saw a 135% increase in new entrepreneurs registering in 2020, and the "Conecta y Colabora" program aimed at fostering innovation and collaboration (cite Corfo) [12].

This study focuses specifically on the area of family microenterprises (FMEs) and their intricate dynamics. The central objective is to analyze the fundamental variables that support the success of the FME during the period after protests and social demonstrations of the Chilean social unrest of October 18, 2019, followed by the start of the pandemic on March 3, 2020. By examining the interaction between these events and FME outcomes, this research contributes to a better understanding of how FME navigates adversity and thrives within economic challenges and transformations. This study aims to address the following question: What are the key variables influencing the success of family micro-enterprises, especially in the face of socio-economic disruptions such as social upheaval and pandemics?

The findings presented in this study contribute to the current understanding of Family Microenterprises (FMME) in Chile by identifying factors that may influence their performance in times of crisis. The identification of specific variables such as gender and number of children as variables that affect the success of a family business allows us to extend the analysis of conventional assumptions. Furthermore, examining various factors such as the use of technology, family structure, use of management metrics, and where you sell products provides insights into the multifaceted nature of FME dynamics. We hope that these findings and their discussion allow for a better understanding of the challenges faced by FME.

The work is organized as follows: Chapter 1 introduces the subject; Chapter 2 describes the situation of entrepreneurship in Chile. Chapter 3 shows the used data and a descriptive statistic of these is included. Next, the methodology of the study is presented, followed by the results. Finally, the results are discussed, and conclusions are reviewed.

We conducted a survey instrument consisting of 50 questions, encompassing both open-ended and directed inquiries, which were administered directly to entrepreneurs through phone conversations. The questionnaire aimed to gather detailed information about the entrepreneurs, their families, and the key attributes of their enterprises. The collected data included demographic details such as gender, age, educational background, and familial structure, along with business-specific information such as the nature of the business, formalization status, and operational details.

The survey instrument covered various aspects of entrepreneurial activities, including business practices, financial management, marketing strategies, and the utilization of technology. Additionally, it sought insights into the entrepreneurs' experiences during the social upheaval and the COVID-19 pandemic, focusing on the impact on sales and the challenges faced by their enterprises.

The study was conducted during the summer of 2021-2022, targeting micro-entrepreneurs who were beneficiaries of the FME program in a southern sector of the Metropolitan Region. Out of the 175 entrepreneurs eligible for the municipal program, 70 willingly participated in the survey via telephone interviews, representing 40% of the total population. The responses obtained formed the basis of the analyzed database for this study. Table 1 presents the number of enterprises affected during pandemic and social upheaval, according to the economic activity.

Table 1. Number of enterprises according to economic activity

In Table 1, we can observe that the number of enterprises affected by the social upheaval and the pandemic were 49 and 46 respectively, which represents 70% and 65.7%. Additionally, we observe that all the economic activities were affected by both events and in the same order of importance, with the service sector being mostly affected, followed by commerce and lastly the production sector. Specifically, 30% of the service activities were affected during the social upheaval and 34.3% during the pandemic; 25.7% of the commerce activities were affected during the social upheaval and 17.1% during the pandemic; and finally, 14.3% of the production area were affected during both events.

3.1 The model

When the variable to be studied is binary, Logit and Probit models are usually used. A Probit model was utilized due to it being one of the most used in literature and is generally preferred for behavioral studies [18].

A probit model is considered a binary response model in the following way [19]:

$\begin{gathered}P\left(Y=1 \mid X_1, X_2, \ldots, X_k\right)=G\left(\beta_0+\beta_1 X_1\right. \\ \left.+\beta_2 X_2+\ldots+\beta_k X_k\right)=G(X \beta)\end{gathered}$      (1)

$G(z)=\Phi(z)=\int_{-\infty}^z \phi(v) d v$      (2)

where,

$\Phi(z)=\frac{1}{\sqrt{2 \pi}} e^{\frac{-z^2}{2}}$      (3)

corresponds to the density function of the normal (0,1).

In this way, the expression of the model is:

$\begin{aligned} Y=G & (z)=G\left(\beta_0+\beta_1 X_1+\beta_2 X_2+\cdots+\beta_k X_k\right) \\ & =\int_{-\infty}^{\beta_0+\beta_1 X_1+\beta_2 X_2+\ldots+\beta_k X_k} \frac{1}{\sqrt{2 \pi}} e^{\frac{-z^2}{2}} d v\end{aligned}$      (4)

Finally, to estimate the parameters, the maximum likelihood method was used.

In particular for this study, and as mentioned above, to study the variables that influence the family micro-enterprise’s success in the midst of social upheaval and the pandemic in Chile, a Probit, binary nonlinear selection probabilistic model was estimated, where the explained variable corresponds to the success of the enterprise 1 or 0 (where 1 indicates that the social upheaval did not negatively affect business sales and 0 reflects the opposite) in the face of an exogenous shock.

The first estimate refers to the enterprise’s success in the midst of social upheaval and the second estimate refers to the success in the face of the appearance of the pandemic. The explanatory variables considered are the female gender, age, nationality, number of children, usage of the internet or computers in the business, economic sector to which it belongs (commerce, production, or service), and number of people that work in the business. To simplify the specification of the model, we group the variables into two categories: the first category considers those variables related to the entrepreneur and the family, and the second category considers those related to the characteristics of the microenterprise. Thus, the estimated model has the following generic specifications:

$P\left(\right. Success \left._i=1\right)=G\left(\alpha+\beta X_i+\gamma Z_i\right)$      (5)

where, $P$ corresponds to the probability and $G$ is the standard normal accumulated distribution function. Success $s_i$ corresponds to the success variable of the enterprise $i$ (in the face of questions, “The social upheaval affected your business sales?” or “The pandemic affected your business sales?”, the possible responses being “No” or “Si, they increased”). The sub index $i$ reflects each micro-enterprise. $X_i$ refers to a set of explanatory variables related to the entrepreneur and the family, and $Z_i$ corresponds to a set of characteristics of the micro-enterprise $i$. The $\alpha, \beta$ and $\gamma$ parameters were estimated through a maximum verisimilitude method; and the results are interpreted as the marginal effect, therefore, the symbol of the estimated parameter indicates the direction in which the probability moves each time that the explanatory variable increases. In the case of a particular businessman, if the set of attributes are greater, then there is a higher probability that the enterprise is successful in the face of an exogenous shock. Finally, to verify the statistical consistency of the models, the significance level of each variable was calculated, as well as the determination coefficient of each model.

In general, establishing a consensus on the determinants of enterprise success remains elusive due to a multitude of internal and external factors. Key factors extensively studied include creativity, financial opportunities, social media utilization, human capital, and gender, among others [20, 21]. Contrary to a singular focus on training, studies assert that fostering the country's entrepreneurial capacity necessitates a collaborative effort involving the government, private sector, and academia, they can plan future actions for development in the medium and long term [21-23]. It is underscored that enhancing enterprise potential requires improving funding conditions and creating conducive spaces for innovation [21].

While social media offers benefits such as resource access, improved client-provider interactions, increased value, and strategic alliances, influencing enterprise success [24-26], our results deviate by not indicating a significant association between computer or internet use and venture success. The apparent lack of correlation between Internet/computer use and business success is noteworthy and may be attributed to factors like inadequate academic training, the cost of maintaining internet services, and resistance to change [27].

Addressing gender dynamics in entrepreneurship, prior studies have indicated lower performances among female entrepreneurs [28], with males exhibiting a greater propensity to establish enterprises and demonstrating higher entrepreneurial capacity than their female counterparts [29, 30]. However, our specific findings counter this trend, revealing that the female gender is associated with a higher probability of success in family enterprises.

Furthermore, technology is recognized as a fundamental variable influencing the initiation, development, and growth of enterprises [31, 32], facilitating the creation of client-oriented products or services and improving post-sale services [33, 34]. Despite this, our study aligns with previous results by not demonstrating a significant association between computer or internet use and venture success. This lack of correlation underlines the need for a nuanced understanding of the interplay between technology, gender, and other factors influencing enterprise success [27].