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Determinants of Inclusive Growth in Java: Evidence from District-Level Panel Data (2019–2023) I Wayan Suparta; Mairizal Salehudin Siatan; Marselina Marselina; Hanif Hanif
Jurnal Ilmiah Peuradeun Vol. 14 No. 1 (2026): Jurnal Ilmiah Peuradeun
Publisher : SCAD Independent

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26811/peuradeun.v14i1.2111

Abstract

This study aims to examine the patterns and determinants of inclusive economic growth across districts and cities in Java Island by explicitly accounting for regional structural heterogeneity. Using secondary panel data from 23 regencies/cities over the period 2019–2023, the analysis employs panel data regression within the Klassen Typology framework to distinguish between developed and rapidly growing regions and developed but depressed regions. The findings indicate that economic growth consistently contributes positively to inclusive growth across regions, although its magnitude varies by regional typology. Human capital, financial inclusion, employment opportunities, and road infrastructure are found to enhance inclusiveness in both regional groups, while income inequality persistently constrains inclusive outcomes. Poverty significantly reduces inclusiveness only in developed and rapidly growing regions, whereas sanitation infrastructure plays a more prominent role in supporting inclusive growth in structurally constrained regions. These results demonstrate that inclusive growth mechanisms are context-dependent and region-specific, highlighting the limitations of uniform development policies. By integrating district-level panel data with a regional typology approach, this study contributes to the inclusive growth literature by emphasizing the importance of structural differentiation in translating economic growth into equitable development outcomes.
The effect of economic freedom, economic complexity and population growth rate on per capita income Crisnina Handayani; Marselina Marselina; Arvina Ratih
Journal of Multidisciplinary Academic Business Studies Vol. 2 No. 3 (2025): May
Publisher : Goodwood Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/jomabs.v2i3.2957

Abstract

Purpose: This study investigates the effects of economic freedom, economic complexity, and population growth on per capita income across different groups of countries classified by income level, namely, high-, upper-middle-, lower-middle-, and low-income countries. Methodology: This study applies panel data regression using a cross-sectional dataset covering 102 countries. Per capita income is employed as the dependent variable, while the independent variables consist of indicators of economic freedom, complexity, and population growth. Separate analyses were conducted for each income group to identify heterogeneous impacts. Results: The findings revealed diverse effects across income levels. In high-income countries, only trade freedom significantly and positively influences the per-capita income. For upper-middle-income countries, none of the variables demonstrated significant effects. In lower-middle-income countries, monetary freedom is positively related to per capita income, whereas economic complexity is negatively related. In low-income countries, business freedom is the only factor that significantly enhances per capita income. Collectively, all independent variables significantly influenced per capita income across all income groups, with adjusted R² values ranging from 28.2% to 59.6%. Conclusions: The study concludes that the drivers of per-capita income vary across income classifications. The structural differences among country groups necessitate context-specific policy approaches rather than one-size-fits-all strategies. Limitations: The use of secondary cross-sectional data and a limited set of explanatory variables may not capture the full dynamics influencing income levels. Contribution: This research enriches the discourse on economic development by offering empirical evidence of differentiated impacts across income groups, providing valuable insights for policymakers in designing tailored economic strategies.