Data-Driven Policy for Reducing Poverty and Inequality (from National Seminar on Statistics 2025)

Development encompasses more than economic growth; it represents a holistic effort to improve human well-being. Reliable data are indispensable for evaluating whether people today are better off than in the past, and for assessing how effectively development policies address poverty and inequality. One of the enduring challenges in development is ensuring that the gains from economic growth are shared equitably across society.

In Indonesia, this challenge remains pressing. The Gini ratio, a key measure of income inequality, stood at 0.375 in March 2025, indicating a moderate but persistent gap between the rich and the poor. Although lower than in many developing economies, this figure reveals that wealth and opportunities remain unevenly distributed, often leading to social tension and inequality of opportunity.

The Role of Data in Development Policy

Data produced by the Central Statistics Agency (Badan Pusat Statistik, BPS) form the foundation of Indonesia’s evidence-based policymaking. Through large-scale censuses and national surveys, BPS provides vital information for understanding economic and social structures.

Key datasets include:

  • Censuses (Population, Agricultural, and Economic), conducted every ten years to capture long-term demographic and economic trends.
  • Susenas (National Socio-Economic Survey) and Sakernas (National Labour Force Survey), which provide high-frequency data on poverty, income, education, and employment.

These sources enable policymakers to identify poverty pockets, assess inequality trends, and design targeted interventions grounded in empirical evidence.

Inequality and Social Mobility

Inequality in society can be related to spatial aspects where the spatial disparities remain a defining characteristic of inequality in Indonesia. For instance, while Malang Regency recorded a relatively low poverty rate of 8.98 per cent in 2024, it had the highest number of poor residents in East Java—more than 240,000 individuals.

Does Inequality Matter? Source: OECD

Poverty maps developed by The SMERU Research Institute using BPS data illustrate that economic growth tends to cluster around urban areas such as Malang City and Batu, whereas remote rural communities remain economically marginalised. This spatial pattern underscores the importance of geographically targeted development strategies.

Inequality is not confined to a single generation. The Great Gatsby Curve, popularised by economist Alan Krueger, highlights a strong relationship between income inequality and intergenerational immobility: societies with higher inequality tend to have lower social mobility.

In Indonesia, income mobility exists but remains limited. The persistence of inequality is largely attributed to differences in inheritance, education, and access to resources. Data from the Indonesia Longitudinal Ageing Survey (2023) show that parents’ educational attainment strongly predicts their children’s education levels—indicating that educational inequality is transmitted across generations.

Recent studies provide further insights into the mechanisms of inequality transmission. Research on early marriage and its effects on children’s education and labour outcomes, using Susenas data and techniques such as Propensity Score Matching (PSM) and the Blinder–Oaxaca decomposition, finds that children of parents who married early are more likely to leave school prematurely and enter the labour market at a younger age.

Moreover, parental education exerts a strong positive influence: each additional year of schooling for parents increases their children’s education by about 0.45 years. Conversely, larger household size and rural residence have negative effects on schooling outcomes. These findings suggest that cultural norms, household resources, and geographic conditions collectively shape educational opportunities and long-term income potential.

Conclusion

Data-driven policymaking is fundamental for designing effective strategies to combat poverty and inequality. Through comprehensive census and survey systems, Indonesia possesses the analytical tools needed to uncover the structural, spatial, and intergenerational dimensions of inequality.

By identifying who and where the poor are, policymakers can design targeted interventions—ranging from social protection programmes and educational equity policies to rural development initiatives—that promote inclusive growth. Reliable and well-utilised data ensure that development policies move beyond statistics to deliver tangible, equitable improvements in people’s lives (TS). 


Note: Full text of this paper was presented on National Seminar on Statistics 2025. Malang, 17 September 2025.

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