Multidimensional and monetary poverty in South Sulawesi Province

The objective of this study is calculate and analyze multidimensional poverty occurred in South Sulawesi in 2011 and 2015, and looking at the comparison calculation results multidimensional poverty and monetary (based on expenditure per capita per month) that occurred in South Sulawesi in 2011 and 2015. This study uses secondary data sources from the National Socio-Economic Survey ( Survei Sosial Ekonomi Nasional-Susenas ) in 2011 and 2015 which have been implemented by Statistics South Sulawesi province to the identification and aggregation of multidimensional poverty. Dimensions, indicators/variables, cuttoff and weights used is based upon the Global Multidimensional Poverty Index with some adjustments at the indicators used. While monetary poverty data source is the official poverty statistic released. The results of this study indicate that (1) multidimensional poverty in South Sulawesi Province is a rural phenomenon as indicated by the three indicators of multidimensional poverty is higher than urban; (2) The dimensions of health is the largest contributor of multidimensional poverty in South Sulawesi; (3) Monetary Poverty create a different description from non-monetary dimensions, the entire district/city in South Sulawesi have the results of multidimensional poverty which higher than the monetary poverty; (4) The decline in the percentage of poor monetary occurred during the years 2011-2015 in the province was followed by a decrease in the percentage of poor multidimensional with a faster decline; (5) Spatially recorded 22 districts/cities in South Sulawesi are in the poor category multidimensional high and very high in 2011, in 2015 only 14 districts were still at that level. This is an open access article under the CC BY-SA license.


INTRODUCTION
The international community includes poverty as one of the targets of world improvement indicators listed in the Millennium Development Goals (MDG's) which ended in 2015 and continued with the newly launched Sustainable Development Goals and will become the target and goal of world development until 2030 where one of the targets is "No Poverty" (abolishing all forms of poverty).In the order of life, poverty has eaten away at many dimensions of human life (Lister, 2021;Odilovich & Najibullah, 2021).Many disabilities result from poverty (Pinilla-Roncancio & Alkire, 2021).Poor nutrition, inadequate housing, unhealthy living conditions, insufficient clean water supply, low educational achievement and absence of quality schools, and general crime are widespread (Hove et al., 2013;Marutlulle, 2021).This means that poverty cannot only be understood as economic deprivation or incompetence.
Poverty is one of the top development priorities that must be overcome.Synergistic and systematic poverty reduction is needed so that all citizens are able to enjoy a decent and dignified life (Dugarova, 2015;Rukin et al., 2018).One important aspect to support poverty reduction strategies is the availability of accurate poverty data.Good poverty data can be used to evaluate government policies on poverty, compare poverty across time and regions, and target poor people with the aim of improving their conditions (Annoni & Weziak-Bialowolska, 2016;Jolliffe, 2014).
According to a global survey conducted by the UN on various countries related to poverty measurement, the majority of countries measure poverty through the income or expenditure approach.The income aspect is considered the most important element when it comes to poverty measures (Decerf, 2021;Hagenaars, 2017).Poverty is discussed or measured as economic deprivation or inadequacy (Bhuyan et al., 2020;Wolff, 2020).Through this approach, poverty is seen as a unidimensional phenomenon that is more monetary in nature.
Since 1984 until now, the Central Bureau of Statistics (BPS) has also taken a monetary approach to measure Indonesia's poverty.Indonesia's poverty is seen as the inability from the economic side to meet the basic needs of food and not food measured in terms of expenditure, which then the limit from the expenditure side is referred to as the Poverty Line.However, the measurement of monetary poverty has drawn criticism from some literature.These criticisms include Alkire and Santos (2009) that income or expenditure-based poverty measurement has weaknesses, including (1) it is assumed that markets always exist for all goods and services, ignoring the existence of public goods and non-market provisions; (2) Ignoring the fact that people have different conversion factors to convert monetary resources into valuable functions; (3) The availability of a certain amount of income does not guarantee that one will use it on basic goods and services useful for avoiding poverty; (4) Income data collected at the household level shows inequality in income distribution within the household, because household members may get a smaller portion due to age, gender, or others.( 5) Revenue data is considered to have weaknesses due to missing observation and misreporting.
In this regard, to study poverty in Indonesia, it is necessary to consider other variables/dimensions of poverty besides income and expenditure, namely multidimensional measures of poverty.The strategic problems of South Sulawesi Province are no different from development problems at the national level, namely the high poverty rate even though it tends to decrease.Historically, from 2002 to 2008, the province's poverty percentage was in the range of 13-14 percent each year.In 2008 it looked like a turning point for the province to reduce its poverty rate to 12 percent.South Sulawesi was able to reduce poverty again to a level of 10.29 percent in 2011.Until now, poverty can be reduced by up to 10.12 percent.However, the 2011-2015 time frame looks as if the poverty rate is already at the saturation point of 9-10 percent.
Moving on from this, it is interesting to conduct research on the calculation of multidimensional poverty in South Sulawesi Province and examine its comparison with existing monetary poverty (poverty line per capita expenditure per month).This research takes a period of two points, namely 2011 and 2015 and will examine up to the Regency/City level in South Sulawesi.The purpose of this study is to calculate and analyze multidimensional poverty that occurred in South Sulawesi in 2011 and 2015, and see the comparison of the results of calculating multidimensional poverty with existing monetary poverty in South Sulawesi in 2011 and 2015.The research is expected to give insight into poverty in Indonesia, especially in Sulawesi, and raise awareness

METHOD
This research is an assessment/explore research.The measurement presents figures up to the Regency/City level throughout South Sulawesi.Or in detail it consists of 21 regencies and 3 cities and the aggregation of South Sulawesi Province also according to the classification of urban and rural areas.This type of research uses quantitative methods that examine cross section data.This research was conducted in South Sulawesi Province where data was obtained from the Central Bureau of Statistics of South Sulawesi Province and from books and journals that have something to do with this study.
The source of data used in the preparation of multidimensional poverty aggregation is secondary data, namely data from the National Socioeconomic Survey (Susenas) which has been carried out by the Central Statistics Agency.Meanwhile, the source of monetary poverty data is official poverty data that has been released by BPS through its publications and official website.All data used are data from 2011 and 2015.
Susenas is one of the data collection activities routinely carried out by BPS four times a year (quarterly).The Susenas instrument is divided into two parts, namely the Kor instrument and the Module.Susenas Module instruments are of three types, namely: Consumption/expenditure and household income modules; sociocultural and educational modules; and health and housing modules.
The data analysis method used in this study is descriptive which reviews the results of multidimensional poverty calculation through the Alkire-Foster method, and spatial mapping of poverty in South Sulawesi through ArcGis software, and compares it with the results of monetary poverty that have been officially released.
The calculation and measurement of multidimensional poverty is carried out using the Alkire-Foster method.The calculation is done with the help of SPSS Software (Statistical Package for the Social Sciences).The dimensions, indicators/variables, cuttoffs and weights used refer to the work of Alkire and Santos (2009) in Global MPI with some adjustments to the indicators used.
The selection of indicators/variables, cutt-off of each poverty indicator, weighting of each dimension/indicator and second cuttoff refers to the research of Alkire and Santos (2009) and also consideration of the availability of existing data in Susenas 2011 and 2015 with several modifications.The modifications lie in: first, the cutt-off of poverty indicator of length of schooling, second, indicator of health dimension and third, indicator of household asset ownership.Apart from these three modifications, this study uses indicators, cutt-offs of each indicator, weights and second cuttoffs similar to Alkire and Santos (2009).The second cuttoff used as the final determinant of individual multidimensional poverty status is k = 3 or equivalent to 30 percent of the total number of indicators.This means that to be said to be multidimensionally poor, a person must be deprived/lost at least 30 percent of the total weighted indicators.
The calculation of multidimensional poverty will produce a measure of multidimensional poverty, namely the percentage of poor people in multidimensional or Multidimensional Poverty Headcount (H), the average deprivation experienced by poor people or multidimensional poverty intensity (A) and the level of multidimensional poverty that has been adjusted by intensity or Adjusted Multidimensional Poverty Headcount Ratio (M0).The measures of poverty aggregates in the Alkire-Foster method are derived from FGT measures.From the aggregation steps that have been carried out earlier, the aggregate formula is summarized as follows:

RESULTS AND DISCUSSION Multidimensional Poverty Analysis of South Sulawesi
In 2011 the percentage of multidimensional poor in South Sulawesi was 32.94 percent (2.67 million people).This figure has decreased significantly until in 2015 it was recorded that 25.04 percent of the population of South Sulawesi experienced multidimensional poverty (2.13 million people).In other words, 25 out of 100 South Sulawesi residents experience multidimensional poverty.In 2011 and 2015, urban dwellers saw far less multidimensional poverty.During these two periods, both urban and rural areas experienced relatively similar decreases in the percentage of poverty.The average value of deprivation experienced by the poor (A) in both 2011 and 2015 did not appear to experience a significant difference.Of the 10 indicators that are the measure of calculating multidimensional poverty, the average shortage experienced by the poor is 44-45 percent of the total weighted indicators.Both by region and in total, A grades were only reduced by about 1 percent.The average shortage experienced by city dwellers is noticeably lower than that experienced by villagers.
The multidimensional poverty rate in South Sulawesi Province was 14.90 percent in 2011 and the rate decreased by 3.83 percent to 11.07 percent in 2015.This figure can also be interpreted as the average shortage experienced by the entire population of South Sulawesi of 11.07 percent or 1 indicator of multidimensional poverty.
Judging from the three types of multidimensional poverty indicators, it can be said that poverty in South Sulawesi Province in 2011 and 2015 was a rural phenomenon.The multidimensional poor population is more densely concentrated in rural areas.In 2011 the multidimensional poor population of South Sulawesi was distributed in rural areas by 74.80 percent while in 2015 it was 77.82 percent.
This finding is in line with research conducted by Khan et al. (2011) who calculated multidimensional poverty in Pakistan and Prabowo (2012) who calculated multidimensional poverty in North Sulawesi and Gorontalo.The results of his research stated that poverty is still predominantly a rural phenomenon.From the point of view of multidimensional poverty analysis, rural areas are areas where poverty conditions are worse than urban areas as well as monetary poverty analysis.
Based on data from 2011 and 2015, it is known that about 44 percent of the multidimensional poor with the age of 15 years and over only attended elementary school (SD) and junior high school (SLTP) and about 40 percent did not finish elementary school (SD).So it is natural to say that the majority of poor people aged 15 years and over have low education.According to the business field, the agricultural sector, which contributes a lot to the economy of South Sulawesi, is actually the business field of the majority of poor people today.It is recorded that almost 60 percent of poor people aged 15 years and over who work depend on agriculture for their livelihoods.The proximity of agricultural natural resources to rural areas is the reason the majority of the population still depends on this sector.And the inadequate income obtained from farmers makes the majority of the population poor.The three dimensions calculated in measuring multidimensional poverty have different contribution patterns when viewed from regional classification and changes from the two study periods (see Figure 4).It has been discussed earlier that the 3 main indicators of multidimensional poverty (H, A, and M0) decreased from 2011 to 2015.During this period, the dimensions that affect multidimensional poverty also changed.In 2011, poverty in urban and total areas was contributed more by deficiencies in the health dimension (66.28 percent and 41.14 percent), while poverty in rural areas where the poverty rate was higher than urban poverty was more contributed by deficiencies in the standard of living dimension (36.91 percent).This shows that residents of rural areas still experience many shortcomings in terms of proper sanitation, clean drinking water sources, adequate access to electricity, housing facilities that meet good standards.
In 2015, the development of poverty alleviation seems to have influenced the structure of the influence of dimensions that contribute to multidimensional poverty.Now the health dimension has become the largest contribution to multidimensional poverty in rural areas.This change can also mean that as poverty rates decrease, the dimensions of education and living standards play more of a role in eroding the multidimensional poverty experienced by the population of South Sulawesi.Health problems are the main factor that is still an obstacle for someone to become poor.

Multidimensional Poverty by District/City in South Sulawesi
In addition to being decomposed according to urban and rural areas, multidimensional poverty measures can also be decomposed by district/city area.Based on Table 14, in 2011 the percentage of multidimensional poor people by district/city in South Sulawesi was in the range of 23-49 percent, and reduced to the range of 10-44 percent in 2015.The reduction in the percentage of multidimensional poor people is also followed by two other measures, where the average shortage experienced by the poor is in the range of 39-52 percent (in 2011) and 39-47 percent (in 2015).Meanwhile, the adjusted multidimensional poverty rate (M0) by district/city is in the range of 9-24 percent and there has been a significant decrease to the range of 4-21 percent in 2015.2011) in his study in the Philippines which found that poverty reduction performance measured using a monetary approach that tended to stagnate during the period 1988-2009 turned out to show a decrease when viewed using poverty in a multidimensional manner.
In 2011 and 2015 all districts/cities in South Sulawesi had a higher percentage of poor people when measured by considering non-monetary dimensions than if only measured by per capita expenditure per month.This raises the possibility that there are still people who are not monetarily poor who are still deprived in other dimensions of poverty.
In general, poverty in South Sulawesi Province showed better conditions during the 2011-2015 period.Although the percentage of poor people reviewed multidimensionally is much higher than when viewed in monetary terms, the decline in the percentage of poor people (monetary) that occurred during the period 2011-2015 was also followed by a decrease in the percentage of multidimensional poor people (see Figure 5).The point of concern is that the decline in the percentage of the monetary poor occurred more slowly than the decline in the percentage of the multidimensional poor.During the period 2011-2015, the percentage of multidimensional poor in South Sulawesi decreased by 1.97 percent per year.The decrease is 9 times greater than the decrease in the percentage of the monetary poor which decreased by 0.22 percent per year.The greater multidimensional decline in poor people indicates that the increase in per capita income or expenditure of the population during the period 2011-2015 has been able to be transformed into capabilities in education, health and better living standards.In addition, government policies have helped the people of South Sulawesi a lot despite multidimensional poverty.

Multidimensional and Monetary Poverty Mapping
In this mapping, multidimensional poverty will be described with green gradations, while monetary poverty is described with red gradations.The percentage of poor people in each district/city is categorized into four categories, namely low (<15.00percent), medium (15.00-24.99percent), high (25.00-34.99percent) and very high (≥ 35.00 percent).The classification refers to the publication of BPS "Map of Indonesia's Poor People 2000".As it is well known that the results of multidimensional poverty calculations present a percentage of poor people that is much higher than monetary poverty.When looking at both figures (Figures 6 and 7) the multidimensional poverty group also shows a darker color map than monetary poverty.The monetary poverty of the people of South Sulawesi shows that they are already at a low level of poverty, while multidimensional poverty shows that the majority of the poor are at a high and very high level.

Multidimensional
In 2011, 23 out of 24 districts/cities in South Sulawesi had a higher category of multidimensional poor people than the category of monetary poor, 10 of which were even in the very high category.Continuing until 2015, the shift in the category of multidimensional poor groups has not seen significantly matching the category of monetary poor.22 out of 24 districts/cities in South Sulawesi are still categorized as multidimensional poor people which is higher than the category of monetary poor.(both in 2011 and 2015).Meanwhile, according to the business field, the agricultural sector, which contributes a lot to the economy of South Sulawesi, is actually the business field of the majority of poor people today.
In general, both in 2011 and 2015, South Sulawesi's multidimensional poverty was contributed by the health dimension.As poverty decreases, the dimensions of education and living standards play more of a role in eroding the multidimensional poverty experienced by the people of South Sulawesi.Poverty measured by considering only the monetary dimension alone paints a different picture from poverty measured by considering various non-monetary dimensions.
The percentage of multidimensional poor is greater than the percentage of the monetarily poor in both 2011 and 2015 in South Sulawesi.All districts/cities under it also show a higher percentage of multidimensional poor people.This indicates that there are still people who are not monetarily poor experiencing deprivation / deprivation in various other dimensions.Looking at the decline in multidimensional poverty that occurs in South Sulawesi by 1.97 percent every year, all residents of South Sulawesi can be free from multidimensional poverty before 2030.Of course, this projection will ideally occur if the magnitude of the decline is consistent every year.
It was recorded that 22 districts/cities in South Sulawesi were in the high and very high multidimensional poor category in 2011, now in 2015 only 14 districts are still at that level.The districts/cities with the largest percentage of multidimensional poor people in 2011 were Luwu, Bone, and North Toraja, while in 2015 they were North Toraja, Bone, and Soppeng.
The need to review poverty measurement in Indonesia, which has been dominant in relying on monetary measurements.In conducting measurements and analyses related to poverty, it is necessary to consider other dimensions of poverty besides the monetary dimension.
In an effort to alleviate poverty, rural areas must be a top priority, considering that these areas have worse poverty conditions than urban areas.Existing government programs, such as raskin, School Operational Assistance (in the field of education), etc., also need to be supported by forms of programs that improve infrastructure to support the improvement of education, health, and living standards.
The measurement of health dimensions in this study allegedly has weaknesses, namely consumption data which is a derivative result of expenditure data has weaknesses due to missing observation and misreporting as explained by Alkire and Santos (2009: 125) in the weakness of income or expenditure-based poverty measurement.Therefore, future research is expected to be able to obtain strong leading indicators in shaping the health dimension in multidimensional poverty measurement.

Kemiskinan Moneter Tahun 2015
Kemiskinan Multidimensi Tahun 2015 Poverty Headcount q = Number of poor individuals n = Number of inhabitants A = Average deprivation shared among poor CI(K) = Total deprivation of poor individuals M0 = Multidimensional Poverty Rate

Figure 2 .
Figure 2. Percentage of Poor People Aged 15 years and over by Last Education Completed, 2011 and 2015 (%)

Figure 3 .
Figure 3. Percentage of Poor People Aged 15 years and over Working by Business Field, 2011 and 2015 (%)

Figure 4 .
Figure 4. Contribution of Education, Health and Living Standards Dimensions to Adjusted Multidimensional Poverty Levels (M0), 2011 and 2015

Figure 5 .
Figure 5. Percentage of Multidimensional and Monetary Poor in South Sulawesi Province, 2011 and 2015 (%) Figures 6 and 7 map the percentage categories of poor people in a multidimensional and monetary manner in 2011 and 2015.The figure clearly shows the stark difference between poverty as measured by multidimensional and monetary measures of poverty.

Figure 6 .
Figure 6.Mapping of South Sulawesi Province by District/City and Monetary and Multidimensional Poverty Category, Year 2011

Figure 7 .
Figure 7. Mapping of South Sulawesi Province by District/City and Monetary and Multidimensional Poverty Category, Year 2015CONCLUSIONThree types of multidimensional poverty indicators show that poverty in South Sulawesi Province in 2011 and 2015 was a rural phenomenon.This is further corroborated by the fact that the poor population is more distributed in rural areas.The majority of multidimensional poor people aged 15 years and over are poorly educated(both in 2011 and 2015).Meanwhile, according to the business field, the agricultural sector, which contributes a lot to the economy of South Sulawesi, is actually the business field of the majority of poor people today.In general, both in 2011 and 2015, South Sulawesi's multidimensional poverty was contributed by the health dimension.As poverty decreases, the dimensions of education and living standards play more of a role in eroding the multidimensional poverty experienced by the people of South Sulawesi.Poverty measured by considering only the monetary dimension alone paints a different picture from poverty measured by considering various non-monetary dimensions.The percentage of multidimensional poor is greater than the percentage of the monetarily poor in both 2011 and 2015 in South Sulawesi.All districts/cities under it also show a higher percentage of multidimensional poor people.This indicates that there are still people who are not monetarily poor experiencing deprivation / deprivation in various other dimensions.Looking at the decline in multidimensional poverty that occurs in South Sulawesi by 1.97 percent every year, all residents of South Sulawesi can be free from multidimensional poverty before 2030.Of course, this projection will ideally occur if the magnitude of the decline is consistent every year.It was recorded that 22 districts/cities in South Sulawesi were in the high and very high multidimensional poor category in 2011, now in 2015 only 14 districts are still at that level.The districts/cities with the largest percentage of multidimensional poor people in 2011 were Luwu, Bone, and North Toraja, while in 2015 they were North Toraja, Bone, and Soppeng.The need to review poverty measurement in Indonesia, which has been dominant in relying on monetary measurements.In conducting measurements and analyses related to poverty, it is necessary to consider other dimensions of poverty besides the monetary dimension.In an effort to alleviate poverty, rural areas must be a top priority, considering that these areas have worse poverty conditions than urban areas.Existing government programs, such as raskin, School Operational Assistance (in the field of education), etc., also need to be supported by forms of programs that improve infrastructure to support the improvement of education, health, and living standards.The measurement of health dimensions in this study allegedly has weaknesses, namely consumption data which is a derivative result of expenditure data has weaknesses due to missing observation and misreporting as explained byAlkire and Santos (2009: 125)  in the weakness of income or expenditure-based poverty measurement.Therefore, future research is expected to be able to obtain strong leading indicators in shaping the health dimension in multidimensional poverty measurement.

Table 4 .
Multidimensional Poverty of South Sulawesi Province by City District, 2011 and 2015