COVID-19, Inequality, Poverty and Unemployment in Rural Areas
Stimulation of social assistance programs, local economic development and the like in the era of the COVID-19 pandemic must start from precise data that is able to identify families who really need the programs.
The World Health Organization (WHO) has announced that the world is at a dangerous point in the COVID-19 pandemic. More than 4 million people have died of the illness.
Problems of social order in public health and inequality in vaccine production and distribution around the world have made the Delta variant of the COVID-19 virus a threat. This virus does not only affect urban residents but also rural residents.
The reason is very clear. The health facilities cannot support this situation!
In Indonesia, many hospitals located in city centers and suburbs are filled with residents who have come from rural areas. They compete with the city residents for hospital beds. This is because self-isolation facilities, village polyclinics, community health centers (puskesmas) and assistants to puskesmas have been unable to accommodate rural residents infected with this new variant of the coronavirus.
The reason is very clear. The health facilities cannot support this situation!
The above-mentioned situation is a brief note of the impact of COVID-19 on public health. What is the latest impact of COVID-19 on the social and economic conditions of rural dwellers?
Precise Village Data
I am grateful that in the past year, God Almighty has given me health and the opportunity to travel to villages on the islands of Sumatra, Java and Bali. The visits to these villages were aimed at collecting Precise Village Data (DDP) with village youths.
DDP is our idea and has full support from the leadership of IPB University. DDP combines numerical and spatial data simultaneously based on families in each community unit. DDP aims to help village officials plan, identify and solve various classic problems in rural areas, namely development targets and objectives, targets for social assistance (bansos), poverty and others.
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> Employment Opportunities for the Urban Poor
> Poverty Alleviation Strategy
As basic data, DDP is used to analyze a number of things, including looking at the impact of COVID-19 on the socioeconomic life of residents in rural areas. It does not only deal with the accuracy of the social assistance but also with the number of poor families and others, which have become controversial. DDP can measure inequality and show the quality of life of each individual and families in rural areas.
Methodologically, DDP is able to deny and at the same time answer the weaknesses of the inequality measurement approach, the Gini ratio, which so far can only be calculated at the global, national and regional levels.
By using DDP, I have seen that Indonesia is at an alarming point. Even though the Gini ratio (inequality) is below 0.4 (low inequality), the percentage of poverty and unemployment in rural areas is quite high, namely 15.07 to 20.07 percent of poor families and 6.12 to 13.25 percent of unemployed families during the COVID-19 pandemic.
Percentage of total income
Generally, socioeconomists use the Gini ratio to calculate income inequality in a population and determine the quality of life of the poorest to richest groups.
By using the DDP, the rural Gini ratio in three islands in Indonesia is identified as below 0.4 (low income inequality). In rural Sumatra, which has a plantation farming typology, the Gini ratio is 0.39 with an average per capita income of Rp 1.6 million per month.
Meanwhile, for the rural areas of Java and Bali, which have the typology of wet rice agriculture and horticulture, the Gini ratio is 0.36 with an average monthly income of Rp 2.3 million (Java) and Rp 3 million (Bali).
It is interesting to note that 50 percent of families in rural Sumatra, Java and Bali earn only 23-26 percent of the total income in each village. In rural Sumatra, the total income of all household heads per month is around Rp 488.4 million. In rural Java it is Rp 5.8 billion, and in rural Bali it is Rp 5.4 billion.
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> The Poor Are Not Optimally Helped
Then, the poorest 20 percent of family groups on the three islands get only 5 to 6 percent of the total income and the poorest 40 percent get only 16 to 18 percent of the total income. The richest 20 percent of family groups earn 55 to 58 percent of the total income.
In the context of the COVID-19 pandemic, the above-mentioned data and information warns us that low inequality can, at any time, shift to moderate to high inequality. This can happen if the regulations for mitigating the socioeconomic impacts of COVID-19 are not well targeted or do not have a clear orientation. With regard to this, social assistance programs and the like in the future need to be prepared carefully.
Poverty and unemployment
One of the advantages of DDP is that it is able to show the position of inequality and the quality of life of family groups in each community unit. In rural Sumatra, which has a plantation farming typology, the highest Gini ratio at the community unit level is 0.41 and the lowest is 0.36.
Meanwhile, in rural areas of Java and Bali with the typology of wet rice agriculture and horticulture, the highest Gini ratio at the community unit level is 0.44 (in Java) and 0.40 (in Bali), and the lowest is 0.31 (in Java) and 0.29 (in Bali). Of the two categories of Gini ratio at the community unit level, there is a pattern of poverty and unemployment due to the COVID-19 pandemic.
First, a high Gini ratio is followed by high rate of poverty and unemployment. In rural areas of Sumatra, Java and Bali, the family population that contributes to the high Gini ratio at the community unit level has a family poverty distribution of 1.6 to 6.46 percent and unemployment of 0.68 to 4.08 percent of the total families.
For poverty, rural Sumatra provides the highest contribution, namely 6.46 percent of the total families. It is followed by rural areas in Java and Bali, respectively, with 2.45 percent (in Java) and 1.64 percent (in Bali) of the total families. Meanwhile, for unemployment, rural Bali has the smallest contribution (0.68 percent of total families). Then it is followed by rural Java with 2.65 percent of the total families. Meanwhile, rural Sumatra has the highest contribution, namely 4.08 percent of the total families.
Second, a low Gini ratio is followed by a low rate of poverty and unemployment. In rural areas of Sumatra, Java and Bali, the family population that contributes to the low Gini ratio at the community unit level has a family poverty distribution of 1.25 to 4.76 percent and unemployment of 0.96 to 2.13 percent of the total families.
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This pattern provides information that poverty in rural Sumatra is higher than in rural Java and Bali, namely 4.76 percent of the total families. It is followed by rural areas in Bali and Java, respectively, with 3.50 percent and 1.25 percent.
Meanwhile, for unemployment, rural Java had the largest contribution at 2.13 percent of total families. It is followed by rural Sumatra with 1.02 percent and rural Bali with 0.96 percent.
Precise policy needed
Indonesia only briefly enjoyed being an upper middle income country. Recently, the World Bank announced that Indonesia\'s position had fallen back to a lower middle income country.
Certainly, there are many factors that have influenced this, including the unavoidable COVID-19 pandemic. Not to mention the heavy task that Indonesia must complete regarding the achievement of the 17 Sustainable Development Goals (SDGs) by 2030. It seems that the government must make precise policies that seriously respond to the impact of COVID-19 on the socioeconomic conditions of the community.
The question is, what is the form of these precise policies?
Precise policies are based on precise data to understand the context in the field. Precise data is built from villages to allow the government\'s work to be focused and to sort and mobilize the components of the nation to respond to the impact of COVID-19.
Precise policies are citizen-oriented, as the subject of development in rural areas. This is so because poverty and unemployment exist in rural areas. Stimulation of social assistance programs, local economic development and the like in the era of the COVID-19 pandemic must start from precise data that is able to identify families in rural areas who really need the programs.
In other words, development targets and objectives are appropriate, namely for those in the poorest 20 percent and 40 percent of the population, not the other way around. Hopefully!
Sofyan Sjaf, Rural Sociologist of IPB University
This article was translated by Hyginus Hardoyo.