DETERMINATION OF INCLUSIVE FINANCE AGAINST POVERTY IN EASTERN INDONESIA

Ely Steven Ingratubun 1 , Basri Hasanuddin 2 , Muhammad Yusri Zamhuri 2 , Paulus Uppun 2 and Abdul Rasyid 3 . 1. Economics Development Program, UMEL Tual College of Economics, Maluku, Indonesia. 2. Faculty of Economics, University of Hasanuddin, Indonesia. 3. Faculty of Economics, University of YAPIS, Papua, Indonesia. ...................................................................................................................... Manuscript Info Abstract ......................... ........................................................................ Manuscript History Received: 04 September 2018 Final Accepted: 06 October 2018 Published: November 2018


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of microfinance for economic empowerment of the poor in the regions as predatory variables. Inclusive finance plays a very strategic role to reduce poverty through various opportunities that can be such as micro-business lending in empowering business groups in the economic sectors in order to increase the per capita income of the poor and the growth of a populist economy in the micro, small and medium enterprises sector. economic growth.
According to Kelkar, Inclusive Finance is a financial service provided that includes access to banking, credit, savings, insurance, payment and remittance services offered by formal financial institutions at affordable costs, especially for disadvantaged and low income groups that tend to be neglected (Kelkar , 2010).
Economic growth as a necessary condition (required) to reduce poverty and sufficient conditions (not required) can be deferred in aspects of economic development in the field of infrastructure development. So economic growth rises, because there is a government economic policy that provides an opportunity for investors to invest to open jobs, so there is absorption of labor in the labor market.
Economic progress is an important factor in the development of countries. In general, economic development includes economic growth (output, and resources) and intensive economic growth, namely increased productivity, implementation of innovation, and job creation. Economic development is a process that can be defined as an increase in social, financial, organizational, physical and natural resource mobilization to improve the quality of product competition, and increase the quantity of society. As a result, many different factors can determine economic growth between countries ( Employment in the form of employment increases against poverty indirectly through economic growth which is one of the things that is very essential in an effort to advance the economy of a nation. The intended business is the provision of sufficient employment in order to compensate for the increase in the workforce entering the labor market.
One of the main themes in the field of employment is employment as an indicator to assess the success of a country's economic development. Job opportunities are influenced by several factors including labor wages, human development index, labor force, and national income. If these factors change, it will affect the level of employment.
To solve this problem, the right policy is needed by identifying groups of people living below the poverty line with their characteristics first. Generally, a condition is called poor if it is characterized by lack or inability to meet the level of basic human needs (basic needs). The poverty includes not fulfilling basic needs which cover primary and secondary aspects. The primary aspect is the lack of assets of knowledge and skills, while the secondary aspects are poor social networks, financial resources, and informal, such as malnutrition, water, housing, poor health care and relatively low education.

Literature Review Theoretical Financial Inclusion and Poverty Relations
In the National Strategy for Inclusive Finance (Bank Indonesia, 2014 Inclusive Finance Booklet), inclusive finance is defined as the right of every person to have full access and service from financial institutions in a timely, convenient, informative and affordable manner, with full respect for their dignity . Financial services are available to all segments of society, with special attention to the poor, productive poor people, migrant workers, and residents in remote areas. Sarma (2012) defines inclusive finance as a process that guarantees the ease of access, availability and benefits of the formal financial system for all members of economic entities. From the definition of inclusive finance above, it can be concluded that inclusive finance is the ease of access to formal financial institutions by all levels of society for economic empowerment.

Relationship between the Dimensions of Inclusive Finance and Economic Growth
To be able to provide a better picture of the measurement of inclusive finance, this research attempts to quantify the poor as the main target of financial inclusion and financial development on the scale of local economic growth in the Eastern Indonesian communities. To encourage inclusive growth in Asia, since economic growth is accompanied by a decrease and increase in inequality (Klassen, 2010).

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In connection with Zhuang and Ali (2011), explaining inclusive growth must be encouraged in two main ways: (i) high and sustainable growth to provide opportunities for employment and (ii) social inclusion to provide equal access to opportunities for the entire community.

Theoretical Relations between Employment and Poverty
Employment is often pointed out as a link channel between economic growth and poverty. Through employment economic growth transmitted onto poverty. Job creation produced by economic growth enhances opportunities employment which in turn increases income of poor people. Higher level of earnings would enable workers to spend more on education, thus raising the capacity and productivity their children, and creating necessary conditions for achieving higher level of economic growth in the future, Islam (2004).

Theoretical study of Poverty
We know that poverty or income indicator is not enough to estimate the standard ofliving in a country. Beyond income and or consumption expenditure, if we look intonon income factors like health, education, sanitation, safe drinking water, creditaccess, basic rights, and varying degrees of discrimination and so on, the incidence of poverty becomes quite high. According to Amartya Sen (2006) has pointed out that identification of poor and aggregation of the statistics to derive poverty line based on low income cut-off point and head count ratio does not work as real index of over all incidence of poverty.

Methodology:-
This research was conducted in the provinces in Eastern Indonesia consisting of twelve provinces, namely: West Nusa Tenggara, East Nusa Tenggara, North Sulawesi, Central Sulawesi, South Sulawesi, Southeast Sulawesi, Gorontalo, West Sulawesi, Maluku , North Maluku, Papua, and West Papua.
The data used in this study are secondary data (panel data) collected from each province, including data that supports analysis of financial inclusion, economic growth, employment and poverty in Eastern Indonesia. Data analysis is based on data collected from twelve provinces as a secondary data analysis, and is widely used for social and economic research.
Regarding the use of panel data in this study, there are at least three analytical techniques that can be used, namely the OLS Method, the Fixed Effect Method, and the Random Effect Method (Gujarati, 2012).This study uses a panel data regression model that is a model that is feasible to use in estimating the model if various tests, model selection and formation are carried out.

Results and Discussion:-Geographical Conditions in Eastern Indonesia
One of the characteristics of poverty in eastern Indonesia is the huge difference between the relative poverty value and the absolute value of poverty in relation to the geographical location. If in absolute terms more than half the total Indonesian population living in poverty is on the island of Java (which is located in the western part of Indonesia with a densely populated population), in terms of the relative provinces in eastern Indonesia, the percentage of poverty is higher. Table 1 below shows five provinces in Indonesia with the highest relative poverty rates. All of these provinces are located outside the Indonesian Western Region such as the islands of Java, Sumatra and Bali (which are more developed regions than the islands in the Eastern part of Indonesia). In Table 1 shows, the level of poverty in the provinces in the in Eastern Indonesia, where most of the population is living in rural areas with the main job as farmers. Residents in these areas include communities and communities of farmers and fishermen, who have long lived in peripheral areas. In these areas development programs have not met local needs, the economic development process has not developed as it should. Migration to urban areas is the only way to get a job and improve living standards, out and out of the circle of poverty.

Demographic Conditions in Eastern Indonesia
The

Descriptive statistics
This research was conducted to see the relationship between exogenous variables (inclusive finance and private investment) with endogenous variables in this case intervening endogenous variables (economic growth, employment, income inequality and poverty). The data used in this study are secondary data in the form of data based on time series from 2008 to 2017 and data based on provinces (cross section), namely twelve provinces in eastern Indonesia, so this study uses a data panel (pooled the data) which is a combination of time series data and cross section data.
Descriptive statistics in this study are presented to provide information about the characteristics of the research variables which include minimum, maximum, mean, and standard deviation values. To measure the central value of a data distribution is used the measurement of the mean (mean), while to measure the difference in the value of the data studied with the average value used standard deviation.
Based on the results of data processing, it can be seen that there are variations in financial inclusion and private investment data in twelve provinces in Eastern Indonesia in the period of 2008 to 2017, and the standard deviation value of each variable is lower than the mean value as shown in Table 2.

Economic Growth
In the economic growth variable the minimum value is 0.110 and the maximum value is 28.470. This means that from the 95 observation data the lowest economic growth value is 0.110 percent while the highest is 28.470 percent. The average economic growth is 7.3271 with a standard deviation of 4.2799. The standard deviation value is smaller than the average value which indicates the variable economic growth is normally distributed.

Employment
In the variable employment the minimum value is 87,650 and the maximum value is 98,400. This means that from the 95 observational data the lowest employment value is 87.650 percent while the highest is 98.400 percent. The average employment equal to 94.8742 with a standard deviation of 2.2669. The standard deviation value is smaller than the average value which indicates the variable employment is normally distributed.

Poverty
In the poverty variable the minimum value is 0.810 and the maximum value is 37.530. This means that from the 95 observation data the lowest value of poverty is 0.810 percent while the highest is 37.530 percent. The average poverty is 12.5888 with a standard deviation of 10.0111. The standard deviation value is smaller than the average value which indicates the poverty variable is normally distributed.

Description of Research Results
Research using software Eviews 9 has three models used in panel data regression analysis, namely: common effect model, fixed effect model, and random effect model. After the selection of the model, then continued the Classical Assumption test including: Multicollinearity test, Heteroscedasticity test, Autocorrelation test and Normality test to measure the reliability of the research data, and the Statistical Critical Test (F Test and t test) to see the effect of the research variables.

Selection of Panel Data Regression Analysis Methods
The

Testing Classical Assumptions
The classic assumption test is done because in the regression model it is necessary to pay attention to the deviations of classical assumptions, because in essence if the classical assumptions are not met, the variables that explain the model will be inefficient. The classic assumption test in this study was carried out through Multicollinearity Test, Heteroscedasticity Test, Autocorrelation Test, and Normality Test.

Direct Effect Analysis of Panel Data Regression
Next to test the individual partial regression coefficients of each independent variable will be tested with the following criteria:The hypothesis used is: H0 = β1> 0: there is a positive relationship between the dependent variable and the independent variable.H1 = β1 <0: there is a negative relationship between the dependent variable and the independent variable.Decision criteria are: 1. t count <t table and probability> 0.05: H0 is accepted. This means that independent variables individually do not significantly influence the dependent variable 2. t count> t table and probability <0.05: H0 is rejected. This means that the independent variables individually affect the dependent variable significantly.
Based on the results of processing the data obtained the value of t count for the inclusive financial variable (X1economic growth (Y1), employment (Y2), and poverty (Y3) as follows:

Results of the Estimated Indirect Effect of Research Variables
The results of the estimation of the indirect effect of the research variables indicate that the effect of financial inclusion on poverty through economic growth of (0.03125) is not significant, the effect of financial inclusion on poverty through significant employment (1.04985), the effect of financial inclusion through poverty economic growth, significant employment of (0.01549), the effect of financial inclusiveness on poverty through significant economic growth of 0.01343, the effect of financial inclusion on poverty through the absorption of significant workforce of 0.25894, financial inclusive of poverty through economic growth and significant labor absorption of 0.00382.
The effect of economic growth on poverty through the absorption of a significant workforce of 0.04895, and the effect of employement on significant poverty of 0.06897.Based on the value of the direct and indirect influence of each research variable, the total influence between variables was obtained both the influence of the independent variables on the dependent variable and the influence of the independent variables on the dependent variable through intervening variables as can be known.
Based on the effect of total financial inclusion inclusive of poverty directly and indirectly through economic growth of (0.970392) not significant, the effect of total financial variables inclusive of poverty directly and indirectly through employment is (0.954632) significant.

Analysis and Implications of the Effects of Inclusive Finance on Poverty, Direct and Indirect Through Economic Growth and Employment
The direct effect of financial inclusion on poverty shows a negative and significant effect. This is according to the hypothesis because of negative and significant influences. It is hypothesized that the effect of financial inclusiveness on poverty is negative as the results of the analysis show that inclusive finance has a negative and significant effect on poverty. This means that the higher financial inclusiveness in each province in eastern Indonesia, causes poverty to decline, whereas the lower the financial inclusion in each province in eastern Indonesia causes poverty to 316 increase. This is because poverty is getting higher in each province in eastern Indonesia, indicating that financial inclusion is decreasing (low community savings).
Based on empirical data, there is a tendency that the average financial inclusion is not optimal for the poor. This is illustrated theoretically where poverty is measured on a large scale or small level of community income which is used as a financial benchmark for poverty. In the results of this study, it shows that the increasing financial inclusiveness, the lower the level of poverty in each province in eastern Indonesia.
The findings of this study illustrate that inclusive finance in each of the provinces in eastern Indonesia has not been well optimized by the community, because the level of public consumption is greater than saving (saving) decreases, resulting in higher poverty impacts. This is in line with the results of the study by Kamalesh Shailesh C. Chakrobarty (2011) said financial inclusion promoted savings and developed a culture of saving, increased access to credit, both entrepreneurship and consumption and also enabled efficient payment mechanisms, thereby strengthening the financial base of financial institutions capable of providing economic benefits as a resource and the availability of efficient and allocative payment mechanisms.

Analysis and Implications of Economic Growth on Poverty, Direct or Indirect Through Employment
The direct effect of economic growth on poverty shows negative and insignificant. This is according to the hypothesis because of negative and insignificant influences. It is hypothesized that the effect of economic growth on poverty is the same as the results of the analysis showing that economic growth has a negative and not significant effect on poverty. This means that the higher economic growth in each province in eastern Indonesia does not affect poverty, but it affects the absorption of labor, on the contrary the lower economic growth in each province in eastern Indonesia has no effect on poverty but energy absorption work has increased. This is because poverty is getting lower in each province in eastern Indonesia, indicating that economic growth is increasing, the creation of increased employment (high community savings) will be created.
The results are in line with the pattern of the co-integration panel's work approach and the fully modified OLS approach, Christopoulos and Tsionas, (2003) that in 10 developing countries. It stipulates that the financial crisis has a balance relationship with the real economy. In addition, the financial crisis caused GDP growth. Similarly, Kiran, Yavuz and Guris, (2009) investigate if the cointegration relationship exists between finance and growth. Covering ten more developing countries in the period 1968-2007, adopting the co-integration panel technique developed by Pedroni, the results revealed that inclusive finance was positive and significantly affected growth.

Conclusion:-
Poverty is directly affected by financial inclusion and employment while direct economic growth has no influence on poverty or indirectly through economic growth. The findings match the hypothesis. Increased financial inclusion will affect economic growth. Likewise, furthermore, economic growth will affect the absorption of energy while economic growth does not directly affect poverty because it cannot create a trickle down effect, supposedly through employment.
Poverty is directly and indirectly affected by financial inclusion into employment. The findings are in accordance with the hypothesis, where inclusive finance will have an effect, if there is an increase in local community savings and high work productivity in the labor sector.