The role of permit relaxation policy in boosting micro-small business income during the COVID-19

Purpose — This study investigates the effect of permit relaxation policy on micro and small businesses income by considering other factors, such as business capital, labor, business area, business sector, location ownership and business facilities. Method — This study employs quantitative methods by analyzing panel data related to the application for micro and small business permits, specifically focusing on the relaxation program, which was administered by the Department for Investment and Integrated One Stop Services of the Jakarta Capital City Government. The data covers the period from 2020 to 2022 and encompasses all areas, including five cities and one regency, with permits issued by 267 Service Units in Jakarta. Result — The findings of this study, derived from regression analysis and bivariate analysis, reveal a notable positive impact of business permits obtained through the relaxation program on the increase in business income. Specifically, businesses that obtained permits from the relaxation program experienced a higher income of 5.27% compared to those without permits. Furthermore, factors such as capital, labor, and the business sector collectively contribute to a significant positive effect on enhancing business income. Contribution — This research contributes to the existing literature by addressing the gap in previous studies that have not examined the impact of permit relaxation policy on the income of micro and small businesses. It offers valuable insights and knowledge to enhance understanding in this area of study.


INTRODUCTION
The significance of Micro, Small, and Medium Enterprises (MSMEs) in driving economic growth is crucial as they contribute to the Gross Domestic Product (GDP) and investment in Indonesia. Additionally, the role of small microenterprises in the economy is closely tied to employment generation, as they create job opportunities and absorb labor.
The number of Micro, Small, and Medium Enterprises (MSMEs) in DKI Jakarta Province has been consistently growing. According to data from the Badan Pusat Statistik (2016), the number of MSMEs in DKI Jakarta was recorded as 1,151,080 and increased to 1,735,000 by 2022, as managed by the Ministry of Cooperatives and SMEs (2022). However, despite this growth, there has not been a corresponding increase in income for these businesses. Analysis of permit data from the Department for Investment and Integrated One Stop Services, Jakarta Capital City Government reveals a declining trend in the average income of micro and small businesses from 2019 to 2021. This can be attributed to the impact of the pandemic, which led to layoffs and individuals turning to the MSME sector as a means of sustaining their livelihoods by engaging in trade of daily necessities, culinary businesses, and other activities. Consequently, while there has been an increase in the number of MSMEs, their income has not followed a similar upward trajectory.
The Indonesian economy experienced a negative impact due to the COVID-19 pandemic, evident in the decline of DKI Jakarta's regional original income from IDR 62.3 trillion in 2019 to IDR 55.9 trillion in 2020, as well as a decrease in the gross regional domestic product from IDR 1,836 trillion in 2019 to IDR 1,792 trillion in 2020. The pandemic's effects were particularly significant for Micro, Small, and Medium Enterprises (MSMEs). According to a survey conducted by Badan Pusat Statistik (2020) in the third quarter of 2020, illustrated in figure 1, 67.77% of businesses experienced a decrease in income, and 39% of businesses had to cease their operations as a result of the pandemic. Increase in income; 10,07 Permits are a necessary requirement for Micro, Small, and Medium Enterprises (MSMEs) to establish the legal framework for their operations. Implementing policies that offer easy and free-of-charge permits can incentivize entrepreneurs to enthusiastically initiate or sustain their businesses, thereby boosting their income during challenging times like the pandemic. Such simplified and costeffective permit procedures help reduce production costs. Additionally, the emergence of creativity, coupled with various business strategies such as homebased or online selling, along with government support programs for MSMEs, can further encourage the establishment of new businesses.
In order to enhance the business environment, the government is continuously introducing innovations in the permit system. This includes simplifying requirements and expediting the permit process through the implementation of an electronic system. These efforts align with the objectives outlined in Law had a notable positive effect on business growth in Mexico. Similarly, Bripi (2016) also observed a similar outcome in Italy, indicating that an easy permit policy that eliminates obstacles during new business registration significantly contributes to the growth of new businesses.
These findings align with the research conducted by Tian et al. (2019), who discovered a positive relationship between the timeliness of permit registration and company performance, specifically in terms of sustained operation and profitability. Similarly, Bruhn (2011) found that business permit policies, such as implementing a permit system, positively influenced the income of entrepreneurs in Mexico. However, these studies have predominantly focused on the food industry and service sector, leaving a research gap in examining a wider range of business sectors specializing in micro and small enterprises, which this study aims to address.
This study aims to examine how permit relaxation policies impact the income of micro-small businesses, taking into account various factors including capital, labor, business area, business sector, ownership of business locations, and business facilities.
The contribution of this research is to expand the existing literature by examining the impact of permit relaxation policies on the income of micro-small businesses, an area that has received limited attention in previous studies. To achieve this, panel data was manually constructed to gather observational data for measuring the effects of permit relaxation policies. Furthermore, this study aims to advance the methodological approach by utilizing a quantitative analysis of Micro Small Business Permit data, which differs from the predominantly qualitative methods employed in prior research.

METHOD
This permit relaxation policy was only issued and implemented in Special Capital Region of Jakarta Province during the COVID pandemic, so this study used relaxation Micro Small Business Permit data which is 3-year panel data (2020-2022) managed by Department for Investment and Integrated One Stop Services, Jakarta Capital City Government covers all areas consisting of 5 cities and 1 regency issued by 267 Service Units in Jakarta.
In determining the research sample, the data for applying permit 1 time was separated from the data for applying permit 2-3 times for the same entrepreneur. For businesses that apply for a permit only once, this data is not used because the effect of the permit relaxation policy cannot be measured. In the first submission data on business characteristics such as capital, income, labor and others are data on business conditions before obtaining permits from the relaxation program. So that in the end we obtained data from business that applied for permits 2-3 times with a total of 3,379 observations. The observation data used is unbalanced panel data with a composition like figure 2 below. The number of entrepreneurs who applied for permits three times in 2020, 2021, and 2022 was 147 observations, or 3%. Data on entrepreneurs who applied for permits two times in 2020-2021 show 952 observations, or 29%, while for those who applied in 2021-2022, there were 2280 observations, or 68%. This research model uses a panel model regression method intended to see the effect of small micro business permit policies on the income of entrepreneur by looking at the changes in 2020-2022 in the following econometric model: Ln_Incomeit is Natural logarithm of the value of Income/revenue in a month for entrepreneur i in year t; β0 = kontanta; β = regression coefficient (1, 2, 3, 4, 5, 6, 7); i = individual entrepreneur; t = year (2020 -2022); αi = error component of an unobserved variable that remains between times; ꞓit = component error.
Permitit is the business has not obtained permit from the relaxation program (0); the business has obtained permit from the relaxation program (1) for entrepeneur i in the year t. Ln_Capitalit is natural logarithm of capital value for entrepreneur i in year t; Laborit is number of workers for entrepreneur i in year t in units of people; Areait is area of business for entrepreneur i and year t in square meters (m2); BusinessSectorit is business sector service (0); trade (1) for entrepreneur i in year t; Ownershipit is Ownership of non-owned business location (0); Own (1) for entrepeuneur i in year t and Facilityit is non-residential business facilities (0); residential homes (1) for entrepeuneur i in year t.

Micro small business performance and business permit
The relationship between the performance of Micro Small Business and the ease of permit policy can be explained from the production theory that the ease of permit issued by DKI Jakarta province is free. If there is no cost, it will reduce the production cost or total cost (TC). This free permit is expected to have an effect on increasing MSMEs' total revenue (TR) when the funds that were originally used to pay permit fees can be used to increase sales, including as an allocation of funds to increase the amount of production adjusting when there is an increase in demand and development for the addition of product variants, so that MSMEs can finally increase their maximum profit. In addition, MSMEs that have permits will find greater market access to increase sales, which in turn can increase income.
in accordance with research conducted by Tian et al. (2019) which analyzes the speed in obtaining permits has a positive influence on company performance, so that it continues to operate and generate profits from the start and Bruhn (2011) where business permit policy in the form of implementing permit system have an influence positive to the income of business. Income as the dependent variable and permit as the main independent variable, the relationship between the two variables is the aim of this study.
H1: The permit of small micro business has a positive effect on income

Business performance and other influencing factors
In addition to permits, there are other factors that affect the performance of micro and small businesses, in this case income, which has been carried out in several previous studies, such as capital, labor, business area, business sector, ownership of business locations, and business facilities. Business capital as a production input factor influences income as in the study of Manini et al. (2016) who analyzed that capital has a significant effect on increasing MSME business income in Kenya. This is in line with the research of Laili & Setiawan (2020) which analyzes that larger capital will increasingly support a business by adding various product variations and the number of product stocks so that it has a positive effect on increasing income to improve welfare and the economy for MSME.
Another factor is labor as a production input factor that influences income, based on De Oliveira (2016) that an increase in labor has a positive effect on increasing income because MSMEs are an effective source of work. This is in accordance with Musvira et al. (2022) which explains that labor is a factor that has a significant positive influence on MSME income because an increasing number of workers will result in an increasing amount of production, making it possible for MSMEs to receive bigger income.
The entrepreneur's ability to compete in the market can be greatly enhanced by the area space location decision to build a factory or a business, which will benefit business profits, costs, and employee satisfaction based on Lumbwe et al. (2018). The business area component also has an influence on income according to Setiyana & Widanta (2021) that the area of a business has a positive effect on the income of entrepreneur because the size of a business is able to combine various resources, labor, and equipment needed in the business, and the wider the place of business, the more products or goods that can be sold. In addition, in previous research by Syahrain (2019) which examined that business area has a significant positive effect on merchant business income.
The business sector factor or type of business activity also has a relationship with income, such as research by Suminah et al. (2022) which saw a positive effect of business category or type of business factors on the income of MSMEs during the COVID-19 pandemic in Surakarta. As for previous research by Azra (2019) stated that the type of business can significantly affect operating profit where the type of trading business has lower operating profits when compared to non-trade or service business types.
Another factor that influences income is ownership of a business location such as research by Reuschke (2016) which analyzes that home ownership with owned or leased status has an influence on business income and business growth. Mjesfa (2013) analyzes that business with fixed business locations and ownership of their own location have a positive effect on higher income compared to business locations that are not fixed or move around. Hairana (2020) states that the ownership status of own business land will determine the development of the business. The business facilites factor also has a relationship with income, according to Reuschke (2016) which analyzes that businesses that use home facilities have a significant influence on increasing business income. Meanwhile, according to Tinneke et al. (2020) that business location facilities that use their own homes or home-based businesses have a positive effect on increasing business income so this shows that business location facilities are an important factor in determining the income of business. Atun (2016) analyzed business facilities affecting the income of traders because business facilities support business activities.
H2: All control variables in capital, labor, business area, business sector, location ownership, and business facilities have a positive effect on income

Statistical findings
This study uses eight variables where the dependent variable is the income variable and the main independent variable is the dummy variable permit relaxation. The control variables in this study are business capital, labor, business area, business sector, ownership, and business facility. Income variable has an average of IDR 7,642,890, with a minimum of IDR 300,000 and a maximum of IDR 200,000,000. Permit variable is a dummy variable issuing permit relaxation, where 0 means the business has not yet obtained a permit from the relaxation program and 1 means the business has obtained a permit from the relaxation program. Another independent variable is capital, where the average is IDR 15,400,000 with a minimum of IDR 300,000 and a maximum of IDR 500,000,000. For the variable labor, the average number is 1.7, meaning that there are 1-2 people with a minimum of 1 person and a maximum of 21 people, while for the variable area of business, the average is 14.16 m 2 , with a minimum of 0 m 2 , which is for street vendors, and a maximum of 3,000 m 2 .
Another independent variable is the business sector variable, with a minimum of 0, indicating the service sector, and a maximum of 1, indicating the trade sector. Variable location ownership, with a minimum of 0 indicating the status of the rental location and a maximum of 1 indicating the ownership status of the own location. for business facilities variables with a minimum of 0, indicating nonresidential facilities, and a maximum of 1, indicating residential houses.
In this study, a bivariate analysis was also carried out to see the distribution of dependent variables income among independent variables. The distribution of income based on permit can be seen in figure 3, which shows that businesses that have not yet obtained permit from the relaxation program have an average income of IDR 7,302,779, while businesses that have obtained permits from the relaxation program have an average income that has increased to IDR 7,973,278. Distribution of income based on capital by dividing 2 classes from the median value, it is found that businesses with small capital in class 1 which have a range of IDR 300,000 -5,000,000 have an average income of IDR 3,648,640. When capital increases in class 2, which has a range of IDR 5,330,000 to 500,000,000, the average income also increases to IDR 12,600,000. This is because capital is a factor of production input to increase production capacity, so it is related to increasing income. Distribution of income based on labor shows that increasing labor from class 1 labor that is only run by 1 person to a larger class 2 with a range of 2-21 people, average income increases from IDR 5,330,046 to IDR 12,600,000. This means that when labor increases, income also increases because labor is a production input factor related to improving business income. Same conditions on variable business area when business area increases from class 1 with a range of 0-8 m 2 to a larger class 2 with a range of 8.5-3,000 m 2 , income also increases from IDR 5,115,815 to IDR 10,300,000.
The distribution of income based on business sector variables for the service sector has an average income of IDR 8,026,360, while for the trade sector it has an average income of IDR 7,592,420. The trade sector has a smaller average income because it is the largest business sector, at 88% run by entrepreneurs, so it tends to have more competitors and a smaller income. The distribution of income based on the variable ownership of the business location shows for nonowned status or rent, has an average income of IDR 9,151,016. While the status of oneself has an average income of IDR  The business has not received relaxation permit.
The business has received relaxation permit. of their own location have a smaller average income because they usually use their own residential houses to carry out business activities. The scope of marketing is very limited, especially if the house is deep in an alley, which is considered a less strategic location.
The distribution of income based on business facility variable shows that nonresidential business facilities that usually occupy shophouses have an average income of IDR 10,300,000, while business facilities that use their own residential houses have an average income of IDR 6,841,685. Non-residential business facilities have a higher average income because non-residential business facilities such as shophouses usually occupy strategic areas, are in the center of the crowd, and are located on the side of the road where they are easily accessible to many people.

Regression result
Several tests were conducted to determine the appropriate model for panel data regression, namely the Common Effect Model (CEM), Fixed Effect Model (FEM), and Random Effect Model (REM). The Chow test was performed to select either the CEM or FEM, and the results showed a P-value (Prob>F) of 0, which is less than the significance level of 0.05. Therefore, the null hypothesis (H0) of the CEM was rejected, and the alternative hypothesis (H1) of the FEM was accepted. Hence, the FEM was identified as the most suitable model.
Subsequently, the Hausman test was conducted to choose between the REM and FEM for panel data regression. The obtained P-value (Prob>Chi 2 ) was less than the significance level of 0.05, leading to the rejection of the null hypothesis (H0) of the REM and the acceptance of the alternative hypothesis (H1) of the FEM. Consequently, the FEM was confirmed as the optimal choice for the panel data regression model.
The model's feasibility was tested using the partial t-test, which revealed that several variables had a P-value below 5% significance level. This led to the rejection of the null hypothesis (H0), indicating that some independent variables significantly influenced the dependent variable. Specifically, the permit variable had a significant positive effect on income at a 5% significance level. Other variables, such as capital, labor, and business sector variables, also exhibited significant positive effects on income. The overall model was tested using the Ftest, and the results from the Fixed Effect Model (FEM) regression showed a Pvalue (Prob > F) of 0.0000, indicating that all independent variables collectively influenced the income variable in the study. To assess the robustness of the model, a regression analysis was conducted by adding the business location status variable. The results of the robustness test regression were similar to those of the Fixed Effect Model (FEM) regression, indicating that the research model is strong and robust. Table 1 presents the regression results of the research model. Two regression analyses were performed: the first solely focused on the permit variable's regression to income, which yielded a positive coefficient with a 5% significance level. In the second regression, all control variables, including capital, labor, business area, business sector, ownership of business location, and business facilities variables, were included. The regression coefficient for the primary independent variable, the permit, was smaller in this regression but remained consistent with a 5% significance level.

Discussion
The regression analysis reveals that permits have a significant positive coefficient, indicating that small micro businesses that have obtained permits from the relaxation program experience a higher income by approximately 5.27% compared to businesses without permits. The provision of free permits under the program encourages entrepreneurs to be enthusiastic about starting and maintaining their businesses. By reducing production costs and increasing income or total revenue (TR), MSMEs can generate higher profits. Moreover, These findings are consistent with the conditions in 2022, where the COVID-19 pandemic situation gradually improved, and the restrictions on community activities began to ease. As a result, business activities started returning to normal. This aligns with the analysis conducted by Bruhn (2011), which indicates a positive influence of permit policies on business income. Furthermore, the bivariate analysis supports these findings, demonstrating that businesses that obtained permits experienced an average income increase from IDR 7,302,779 to IDR 7,973,278.
The variable "capital" in the regression analysis was transformed into its natural logarithm (Ln). The analysis revealed that capital has a significant positive coefficient, indicating that a 1% increase in business capital leads to a 0.288% increase in the entrepreneur's income. This relationship is expected as capital is one of the input factors that contribute to income growth for entrepreneurs. This finding is consistent with the research conducted by Manini et al. (2016), which also demonstrates a significant impact of capital on business income. Moreover, the bivariate analysis supports these findings, showing that as capital increases, the average income also increases.
The regression analysis reveals that the variable "labor" has a significant positive coefficient. This implies that adding 1 person to the labor force results in a 5.6% increase in business income. Labor is an essential input factor alongside business capital for income growth in businesses. These findings align with the research conducted by De Oliveira (2016), which highlights the positive impact of labor on income, considering that MSMEs serve as effective sources of employment. Additionally, the research conducted by Musvira et al. (2022) supports the notion that labor is a significant factor influencing MSME income. The bivariate analysis also supports these findings, indicating that as labor increases, average income also increases.
Business area has a positive coefficient but not significant which means that the addition of 1 m 2 of business area has an effect on increasing business income by 0.04%. This is in accordance with the research of Lumbwe et al. (2018) and Setiyana & Widanta (2021) stated that the size of the business has an effect on increasing business income. This is in accordance with the bivariate analysis when the business area increases, the average income also increases.
Business sector has a significant positive coefficient which means that business in the trade sector have a higher influence on business income by 17% compared to the service sector. This is because the trade sector is the largest and easiest business activity for many people. This is in accordance with the research of Suminah et al. (2022) that the type of business has an effect on business income. This is slightly different from the bivariate analysis where the average income of the service sector is IDR 8,026,360, which is higher than the trade sector which has an average income of IDR 7,592,420. Because the trade sector tends to have more competitors with almost the same products, so affects income smaller.
Ownership of a business location has a positive coefficient but not significant, meaning businesses with own location ownership have a higher effect on business income of 1.9% compared to rented location because ownership of assets that use their own property makes it easier to start a business or develop a business. This is in accordance with the research of Reuschke (2016) that owning a business location has an effect on increasing business income. This is slightly different from the bivariate analysis where own location ownership has an average income of IDR 6,604,311, which is smaller than businesses that are not owned or rented, which have an average income of IDR 9,151,016. Because businesses with their own location usually use their own residence to carry out business activities so that the scope of marketing is very limited, especially if the location of the house is far in an alley which is considered less strategic.
The regression analysis shows that the variable "business facilities" has a positive coefficient, indicating that businesses utilizing facilities within their own homes have a 0.77% higher income compared to businesses using nonresidential locations, such as shophouses. This suggests that utilizing residential facilities makes it easier to start a business and reduces operational costs. These findings align with the research conducted by Tinneke et al. (2020), which demonstrates that businesses utilizing their own home facilities have a positive impact on increasing business income. However, it's worth noting that the coefficient for business facilities is not statistically significant in the regression analysis. This implies that while there may be a positive relationship between business facilities and income, it is not strong enough to reach statistical significance. This slightly differs from the bivariate analysis, where businesses using non-residential facilities (e.g., shophouses) have a higher average income of IDR 10,300,000 compared to businesses using residential facilities with an average income of IDR 6,841,685. This difference can be attributed to nonresidential facilities often being located in strategic areas with high visibility and accessibility to a larger customer base.

CONCLUSION
The purpose of this study is to investigate the effect of permit relaxation policy on micro and small businesses income by considering other factors, such as business capital, labor, business area, business sector, location ownership and business facilities. After analyzing and discussing the findings, it can be concluded that the permit relaxation policy has a significant positive effect on business income. Capital, labor and the business sector together have a significant positive influence on business income. Business areas, ownership of business locations, and business facilities have a positive but not significantly influence on business income.
This study offers recommendations that implementation of the permit relaxation policy should continue until the pandemic period ends. The form of convenience for simplification of permit procedures by simplifying requirements and assistance provided by motorized officers assists MSMEs in obtaining permits, especially for those who have limitations in digital knowledge because it is needed to access electronic permits that are already online. Capital is a variable that has a significant influence on increasing the businesses income. The availability of business capital is the focus expected by entrepreneurs to survive and continue to grow, so that the government's role in capital is needed in the form of business assistance and regulates the ease of access to this capital by synchronizing the roles of stakeholders, such as financial institutions, permit issuers, and entrepreneurs. The trade sector which has a significant influence on income and is higher than the service sector, should be given attention by the government by looking at the potential for dominant commodities in each region and assisting in marketing strategies to see opportunities to become important export commodities.
Suggestion for further research is for measuring the performance of micro and small businesses should use profit data. In this study, profit or total cost data are not available, only revenue or income data are available. So that the dependent variable used in this study is income variable, resulting in an overestimated regression result because the income value is higher than profit as an indicator of business performance.