Poverty dynamics in Indonesia: empirical evidence from three main approaches

Purwono, Rudi; Wardana, Wahyu Wisnu; Haryanto, Tri; Mubin, Muhammad

doi:10.1016/j.wdp.2021.100346

Cited by 31 publications

(30 citation statements)

References 18 publications

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“…Mai and Mahadevan (2016) used IFLS data of four waves (covering 1993 to 2007) and found that chronic poverty in Indonesia was 76%. More recent estimates (Purwono et al, 2021) even proposed chronic poverty of nearly 92%an approximation that is distant from the official national figures on poverty.…”

Section: Poverty Calculation Approachesmentioning

confidence: 83%

“…Meanwhile, a component approach study resulted in 17.33%. Purwono et al (2021) estimated chronic poverty in 2008 and 2010 at 28.28% and 47%, respectively, using the SPELL approach and component approaches. However, studies using EDE to compare previous estimations found substantial differences in the results.…”

Section: Poverty Calculation Approachesmentioning

confidence: 99%

“…For example, Mai and Mahadevan (2016) found that, on average, 76% of poverty is chronic. Others suggest similar estimates, although employing data in short periods or resulting in unlikely large estimates (Purwono et al, 2021). Therefore, further research is needed.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Poverty Dynamics in Indonesia: The Prevalence and Causes of Chronic Poverty

Sugiharti¹,

Purwono²,

Esquivias³

et al. 2022

JPSS

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This study aims to determine the chronicity of poverty in Indonesia using the equally distributed equivalent (EDE) poverty gap method, tracking Indonesian households in 2007 and 2014. The results indicate that the largest component of poverty among households was chronic (77%). Compared to transient poverty, chronic poverty is more common across individuals. Unlike previous studies, we used data at the district level to measure the poverty line, discovering that the cost of poverty inequality is lower than often reported. This decision is because disaggregated data (poverty line) can show a more realistic poverty threshold. Using a quantile regression approach, we found evidence that age, gender, employment status, and education were significant factors of chronicity. Other significant factors of chronic poverty include large household size, having no access to services (finance, electricity, information, and mobility), and having limited or no assets. Casual employment in the agricultural sector and living in rural areas increase the probability of poverty, although not necessarily chronic. Poverty alleviation programs, therefore, need to target the right causes as exposure to poverty varies across households.

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Section: Poverty Calculation Approachesmentioning

confidence: 83%

Section: Poverty Calculation Approachesmentioning

confidence: 99%

See 1 more Smart Citation

Poverty Dynamics in Indonesia: The Prevalence and Causes of Chronic Poverty

Sugiharti¹,

Purwono²,

Esquivias³

et al. 2022

JPSS

Self Cite

View full text Add to dashboard Cite

show abstract

“…Consequently, these countries have witnessed a decrease in poverty, but to varying extents. The evolution of poverty degree is primarily determined by two types of measures: single income poverty and its derivative measure method (Dang and Lanjouw, 2018;Ren et al, 2018;Purwono et al, 2021), the Multidimensional Poverty Index (Alkire and Santos, 2014). Several studies have analyzed poverty reduction experiences that have taken place in countries along the Belt and Road.…”

Section: Introductionmentioning

confidence: 99%

The poverty evolution of typical countries along the Belt and Road and implications from China’s poverty reduction experiences

2022

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The world is facing a poverty crisis. Despite the great achievements that have been made in poverty alleviation over the past two decades, the extent of poverty in countries along the Belt and Road is still high. Successful poverty reduction in these countries is crucial to meeting the 2030 SDGs. Improving governance to eradicate poverty is a shortcoming that needs to be addressed urgently in poverty reduction pathways along the Belt and Road. In this study, the Standard Deviational Ellipse method was used to study the spatial trajectory of the poverty gravity center. Results showed that the poverty gravity center moved from east to west by 87.60 km annually, while the poverty population decreased by 1211.14 million along the Belt and Road from 2000 to 2020. In addition, the trajectory of the center has shifted due to the different effects of poverty reduction. Among the countries situated along the Belt and Road, China is the most significant contributor to poverty reduction. Accordingly, this study examined the implications of China’s successful poverty reduction strategies in order to understand how other countries can effectively respond to poverty. Ultimately, we propose that sustainable poverty alleviation development strategies should be established with the objectives of promoting social equity and improving the wellbeing of all people.

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“…Although substantial reductions in poverty have taken place in Indonesia (Muryani & Esquivias, 2021;Purwono et al, 2021;Yusuf & Sumner, 2015), the Gini ratio (a measure of income or wealth inequality within a nation) has deteriorated over the past two decades (van Leeuwen & Földvári, 2016). Inequality in the country remains substantially significant (Erlando et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Dynamics of Income Inequality, Investment, and Unemployment in Indonesia

Esquivias

Sethi

Iswanti

2021

JPSS

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This paper examines the effect of per capita income, investment, and unemployment on income inequality in Indonesia from 2011 to 2019. We use both static and dynamic panel data approaches covering 34 provinces in Indonesia. The results support the Kuznets hypothesis, whereby a more significant per capita income growth is associated with more substantial income inequality in a short period; however, this decreases over time (sign change). Furthermore, a larger real per capita income is associated with lower inequality when accompanied by progress in human capital. Alternatively, foreign direct investment (FDI) and infrastructure expenditure positively relate to income inequality, although FDI eventually helps lower inequality. Similarly, increases in domestic private investment can help to reduce income disparity. Meanwhile, unemployment is negatively associated with income inequality, suggesting that better jobs (rather than more jobs per se) are needed to improve income distribution in the country. Although per capita income, investment, and employment have improved substantially and helped Indonesia raise overall income, economic progress does not seem to have been inclusive. We argue that the panel dynamic model helps to capture the persistence effect of income distribution, suggesting a more precise estimation of income inequality issues than static models.

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Poverty dynamics in Indonesia: empirical evidence from three main approaches

Cited by 31 publications

References 18 publications

Poverty Dynamics in Indonesia: The Prevalence and Causes of Chronic Poverty

Poverty Dynamics in Indonesia: The Prevalence and Causes of Chronic Poverty

The poverty evolution of typical countries along the Belt and Road and implications from China’s poverty reduction experiences

Dynamics of Income Inequality, Investment, and Unemployment in Indonesia

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