Inclusive Growth in Northern and Southern Central Java

Introduction Suryanarayana (2013) states that one of the visions of sustainable development is inclusive growth, which includes increasing production, income, and distribution of income/expenditures. According to Klasen (2010), inclusive growth is growth that is able to provide access and is non-discriminatory to all parties and is can reduce inequality. The growth of a region is said to be inclusive, not only seen from high economic growth but also can be seen from the low level of poverty, equitable income inequality, and high levels of labour. ADB (2011) revealed the background to the realization of inclusive growth among others: (1) growth must be distributed and inclusive at all levels of society and regions as a form of equality and justice; (2) growth, which is still accompanied by inequality, creates a domino effect on social problems, such as the vulnerability of the poor and unemployed to crime, the vulnerability of women to prostitution and the emergence of child labour problems; (3) sustainable growth potential can be reduced if political stability and social AR TI C LE I N F O AB ST R ACT

structure hampered due to inequality access and growth results.
The selection of North and South Central Java became the locus of this research, with various considerations, including the current Central Java provincial government is developing the northern part of Central Java and southern Central Java. This is stated in the Final Draft of the 2018-2023 RPJMD (Central Java Governor Regulation Number 5 of 2019).
One of the general policies in the direction of regional development is the North-South development axis to reduce regional economic inequality. Based on the results of the Location Quotient (LQ) analysis conducted by Ahmad and Kamio (2009), the map of the manufacturing industry with a low level of industrial competition and no potential, is dominated by regencies in the Southern Central Java region. Trenasia.com (2020) states that the development of an industrial area that focuses on the North Central Java region gives the impression of an imbalance between the northern and southern Central Java regions. Therefore, we need to analyze how the level of inclusiveness of growth in the two regions is.
There have been many studies related to inclusive growth in Indonesia using different measurement methods. Several studies on inclusive growth using the method adopted from McKinley (2010) in the Asian Development Bank (ADB) including Ramadhan and Setiadi (2019) in Indonesia, Hapsari (2019 ) in Central Java, Kusumaningrum and Yuhan (2019) in Indonesia, Long and Pasaribu (2019) in Central Java, Pratama et al (2020) in Jambi and Purba et al (2020) in South Sumatra while the studies was using the formula Klasen (2010) by adopting the concept of Poverty-Equivalent Growth Rate (PEGR) had been carried out by Amalina et al (2013) in Indonesia territory of Western and Eastern Indonesia territory , Sholihah (2014) in Indonesia,  in South Sulawesi, Cahyadi et al (2018) in Bali, Bado et al (2019) in South Sulawesi, Purwanti and Rahmawati (2019) in Indonesia and Satrio et al (2019) in West Sumatra. Meanwhile, Sitorus and Arsani (2019) compare the calculation results from 3 different methods, namely the method adopted from ADB, WEF and UNDP by taking research locus in the Indonesian. Munir & Ullah (2018) used the Social Mobility Curve method in Pakistan to look at inclusive growth and panel data regression to see the factors that influence inclusive growth in developing countries. Dirgantoro et al. Prasetyo et al. (2013), Nur et al. (2013), Wahyuni et al. (2014), Wibowo (2014), Sungkar et al. (2015), Sukanto (2015), Sipahutar et al. (2016), Quy (2016) and Rambeli et al. (2016), Anwar (2017) and Hidayat et.al (2020) used the Two-Stage Least Square (2SLS) method. Research related to inclusive growth with other methods was also carried out by Rindayati et al (2007), Lisna et al (2013), Warsilah (2015), Wirawan and Arka (2015), Sulistyowati et al (2017), Nalle (2018), Hidayat (2020) and Fitri (2021). 10.12928/optimum.v11i2.4583 Although there have been many studies on inclusive growth, but research on inclusive growth that compares the North Central Java region and the South Central Java region has never been conducted. The regional division in this study refers to the Central Java Governor Regulation Number 5 of 2019. The objectives of this study include analyzing (1) inclusive economic growth in Central Java; (2) Consistency of inclusive economic growth in Central Java; (3) Comparison of inclusive economic growth between the northern and southern parts of Central Java.

Data Types and Sources
The calculation of inclusive growth uses data from BPS, namely Gross Regional Domestic Product (GRDP) at Constant Prices, the number of poor people, the Gini coefficient, per capita income which is approximated by per capita expenditure data, the number of working people and the labour force. These data can be accessed through the website jateng.bps.go.id. Research on inclusive growth with similar data at different locus has also been carried out by Amalina et al (2013) and Basri et al (2019). The data used in this study are the latest data, namely 2017-2020, for calculating inclusive growth in 2018-2020. The initial data used is 2017 data because data related to the number of working population and labour force in 2016 is not available until the district level. This was due to the 2016 National Labour Force Survey (Sakernas) data which is insufficient for analysis at the district level. The northern and southern regions of Central Java in this study refer to the Central Java Governor Regulation Number 5 of 2019.

Table 1. Regional Division according to Central Java Governor Regulation Number 5 of 2019
The analytical method which is used to answer the problems in this study is a descriptive analysis method with a quantitative approach, where after the research data is processed using Excel and SPSS software an analysis is carried out to draw conclusions so that an overview of the object being studied is obtained. According to Sugiyono (2014:21), descriptive statistical analysis methods are used by describing or describing the data that has been collected with conclusions that are not general or generally accepted.

Inclusive Growth Measurement Method
To calculate the effect of increasing economic growth on decreasing the number of poor people, decreasing income inequality and increasing labour, using the analytical method developed by Klasen (2010), namely the Poverty-Equivalent Growth Rate (PEGR) method. Growth Inclusive Natural in Reducing Poverty Amalina et al (2013) formulate the calculation with the following formula: Where IGp is coefficient of inclusive growth in reducing poverty; Gp is elasticity of poverty to average income; Gpg is the elasticity of poverty on economic growth; Ĝg is coefficient of economic growth.
IGp is a measure of inclusiveness in reducing poverty, which is stated inclusive growth if IGp > Gg (coefficients inclusive growth to reduce poverty is greater than coefficients of economic growth). To calculate elasticity is using the same way with the PEGR concept.
The elasticity of poverty to average income (Gp) can be calculated as: P12 is the percentage change in the number of poor people in period 1 and period 2 can be calculated as: where P (Z, X) is a function of the number of poor people (Z) and the average income of the population (X).
Ψ is the percentage change in the average income of the population can be calculated as: The poverty elasticity of economic growth (Gpg) can be calculated as: Where Ĝg is the coefficient of economic growth is calculated as the change in Gross Regional Domestic Product (GDP) in a period, so that economic growth can be written as follows: Inclusive Growth in Reducing Inequality The calculations formulated by Amalina et al (2013) are: Where IGin is coefficient of inclusive growth in reducing inequality; Gin is inequality elasticity of average income; Gin.g is elasticity of inequality to economic growth; Ĝg is coefficient of economic growth.

IG n is a measure of inclusiveness in reducing inequality which is stated inclusive growth
if the IGin > Gg (coefficients inclusive growth in reducing inequality is greater than coefficients economic growth).
The inequality elasticity of average income (Gin) can be calculated as: Where In12 is the change in inequality in period 1 and period 2 can be calculated as: Where In (inequality) is a function of the Gini index (GINI) and the average income of the population (X), which is written as follows: The elasticity of inequality to economic growth (Gin.g) can be calculated as: Growth Inclusive in Enhancing Labour Abrsoption According to Amalina et al (2013) the calculation is done by: Where IGem is coefficient of inclusive growth in absorbing labour; Gem is labour absorption elasticity; Gem.g is elasticity of labour to economic growth; Gg is coefficient of economic growth.
IGem is the inclusiveness of growth in absorbing labour, so that growth is declared inclusive if the IGem value > Gg (coefficient of inclusive growth in absorbing labour is greater than the coefficient of economic growth). Vol 11. No.2 September 2021 p. 19-35 The elasticity of labour to the labour force (Gem) can be calculated as:

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Where Em12 is change in the percentage of labour absorption in period 1 and period 2 can be calculated as: With Em (labour absorption) is a function of the number of people working (Worker) and the number of labour force (AK), which is written as follows: AK* is change in the percentage of the workforce can be calculated as: The elasticity of labour absorption on economic growth (Gem.g) can be calculated as:

Result and Discussion
Economic growth is said to be inclusive if the growth is able to make an impact on people's welfare. Inclusive growth can be proven if it can reduce the level of poverty, reduce income inequality and increase labour. In this study, inclusive analysis is divided into several sub-discussions. The first discussion is related to inclusiveness in Central Java and its consistency. The next three sub-discussions describe the level of inclusiveness of growth in each indicator, namely poverty, inequality and labour. The next section discusses the comparison of inclusiveness levels in Northern and Southern Central Java. Figure 1 shows that the level of inclusiveness in Central Java during the 2018-2020 period is inconsistent, both in reducing poverty, reducing inequality and employment. This can be seen from the value of the inclusiveness coefficient on the three sizes which tend to fluctuate. Inclusiveness towards reduction of poverty occurred in the year 2018 , evidenced by the value of the coefficient of inclusive language that was more substantial when compared to the value of the coefficient of growth of the economy . Although the inclusive coefficient value in reducing poverty in 2019 was positive because it was smaller than the coefficient of economic growth, meaning that poverty reduction will continue to occur in line with increasing economic growth, but most of the benefits were still enjoyed by nonpoor people . There in 2020, the value of the coefficient of reduction of poverty and the coefficient of growth of the economy were equally worth negative , but the value of the coefficient of growth of the economy was smaller than the coefficient of reduction of poverty  Vol 11. No.2 September 2021 p. 19-35 10.12928/optimum.v11i2.4583 . It is demonstrated that the decline in the growth of the economy in the year 2020 was small when compared to the increase in the number of the population was poor .

Inclusiveness Growth Economy Java Central
Meanwhile, Figure 1 also shows that during the period 2018-2020 there was no inclusiveness towards reducing inequality. This was evidenced by the coefficient inclusive of the decline in inequality during that period, much lower if compared to the coefficients of the growth of the economy . In 2018, the inclusiveness coefficient on inequality was negative, meaning that existing economic growth tends to increase inequality. Meanwhile in 2019, the inclusive coefficient on inequality was positive but it was still lower than the economic growth coefficient, indicating that the benefits of economic growth were not evenly distributed causing inequality. Meanwhile, in 2020, the growth coefficient was negative, meaning that the economic growth that occurs was not able to reduce inequality, and even tends to exacerbate the inequality in the distribution of people's income .

Economic Growth Inclusiveness in Reducing Poverty
One of the rejected measure growth inclusive is can reduce poverty. Inclusivity in reducing poverty in this study can be seen from the value of the coefficient of inclusiveness to poverty (IGP) . The results of the Inclusive Index Coefficient Processing show that the number of districts/cities in Central Java with inclusive growth in reducing poverty in 2018 is more than in 2019. This can be seen from the increasing number of districts in Central Java that were able to maintain inclusiveness in reducing poverty, including Cilacap, Banjarnegara, Magelang , Sukoharjo, Rembang, Jepara, Demak and Kendal. But there were also districts that year before non inclusive growth to reducing poverty, precisely in 2019 turned into an inclusive, namely : Kebumen , Blora , Temanggung and Magelang City. While in 2020, the entire districts have value of the coefficient of growth of negative economic. It was meaningful in 2020, the growth of the economy which was occurred did'nt afford to lower poverty and even tend to the poverty level was getting higher .

Economic Growth Inclusiveness in Reducing Inequality
Indicators another in the growth of inclusive is the ability of economic growth in reducing inequality. Inclusive growth is said to reduce inequality if economic growth can be enjoyed by all people. Based on the results of the Inclusive Index Coefficient Processing, in 2018, only 8 districts/cities whose growth was not inclusive of poverty reduction. Contrast with condition of the previous year, in 2019, it was only 12 districts had a growing inclusive to the reduction of inequality, namely: Cilacap, Banjarnegara, Kebumen, Magelang, Sukoharjo, Blora, Rembang, Jepara, Demak, Kendal and Magelang City. All districts in Central Java in 2020 had a negative growth coefficient, which means that the economic growth that occurs is unable to carry out its role in reducing inequality, even widening existing inequality.

Inclusiveness of Economic Growth in Labour Absorption
The third indicator of inclusive growth is being able to absorb more labour. Economic growth is said to be inclusive of labour if the coefficient of inclusive growth of labour (IGem) is greater than the coefficient of economic growth (Gg year later the number decreased to only 2 districts are Cilacap and Tegal City. In 2020, economic growth in all districts will not be able to absorb more workers, and even tend to increase unlabour. This can be seen from the negative economic growth coefficient in all districts.

Comparison of Economic Growth Inclusiveness in North and South Central Java
The inclusiveness coefficient of an indicator in a region can change from year to year.
This also happened in the northern part of Central Java and southern Central Java, as shown in Figure