📈 economics

Development stage shapes economic growth dynamics in developing and developed economies

This study analyzes 140 nations from 1990 to 2020 to demonstrate that economic growth drivers differ significantly by development stage, with developing economies relying primarily on capital formation and trade openness, while developed economies depend on human capital and foreign direct investment due to diminishing returns on physical capital.

Original authors: Sheikh Abdul Kader, Nurul Mohammad Zayed, Md. Zahirul Islam, Vitalii Nitsenko, Ilona Bartuseviciene, Tetiana Dugar, Stanislav Soloviov

Published 2026-07-10

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CC BY 4.0

Original authors: Sheikh Abdul Kader, Nurul Mohammad Zayed, Md. Zahirul Islam, Vitalii Nitsenko, Ilona Bartuseviciene, Tetiana Dugar, Stanislav Soloviov

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine the global economy as a massive, bustling construction site where every country is trying to build a skyscraper of wealth. For decades, economists thought everyone was using the exact same blueprint: just pile up more bricks (capital), hire more workers, and open the gates wider (trade). But this new study, looking at 140 countries over 30 years (from 1990 to 2020), suggests that blueprint is a bit of a myth. The researchers found that the "secret sauce" for building a skyscraper changes completely depending on whether you are building a small shed or a 100-story tower.

The "Shed" Builders: Developing Economies
Think of developing economies as countries in the early stages of construction. They are still laying the foundation and putting up the steel beams. For these builders, the study suggests that the most powerful tools are Gross Capital Formation (which is like pouring concrete and buying heavy machinery) and Trade Openness (opening the gates to bring in materials from everywhere).

The data shows that for these countries, every extra bit of investment in physical stuff has a huge impact. The study found that Gross Capital Formation has a coefficient of 0.184, and Trade Openness has a coefficient of 0.125. In plain English, this means that if a developing country builds more factories or opens its borders to more trade, its growth rate jumps up significantly. It's like a new construction crew that gets a fresh delivery of bricks; they can build twice as fast.

However, the study also hints at a tricky trap for these builders: Natural Resource Rents. While having oil or gold might seem like a shortcut, the data suggests a weak link to slower growth (a coefficient of -0.045). It's like relying on a single, lucky strike of gold instead of building a real business; without good management, it might actually slow you down.

The "Skyscraper" Builders: Developed Economies
Now, picture the developed economies. They've already built their steel frames and poured their concrete. Their buildings are tall, but they can't just keep adding more bricks to make them grow faster; the building is already full. The study suggests that for these advanced builders, the game has changed.

For them, the magic ingredients are Human Capital (the skills and health of the workers) and Foreign Direct Investment (money coming in from abroad that brings new ideas). The study found that Human Capital has a coefficient of 0.152 and Foreign Direct Investment has a coefficient of 0.198. This means that in rich countries, growth comes from having smarter, healthier workers and high-quality investments that bring new technology, not just from buying more machines.

In fact, the study suggests that simply adding more physical capital (like more machines) doesn't help much in these countries anymore. It's like trying to make a finished skyscraper grow taller by adding more bricks to the lobby; it just doesn't work because the building is already at its limit. The "marginal productivity" of those extra bricks is too low.

The "One-Size-Fits-All" Myth
The biggest thing this paper argues against is the idea that there is one universal rule for economic growth. You can't just copy the policy of a rich country and paste it onto a developing one, or vice versa. The study suggests that the rules of the game are different depending on where you are in the development process.

The researchers used a method called "fixed-effect regression" to look at the data from 1990 to 2020, a period that included big global shocks like financial crises and pandemics. They checked their work carefully, making sure the numbers weren't just a fluke. They even ran "robustness checks" (like double-checking the math with different tools) and found the same pattern: developing countries need investment and trade, while developed countries need skills and innovation.

What This Means for the Future
The study suggests that if you are a leader in a developing country, you should focus on building infrastructure and opening up trade. If you are in a developed country, you should focus on education, research, and making sure your workers are healthy and skilled.

It's not a magic bullet that solves all economic problems, but it does suggest that we need to stop using the same map for different territories. The path to a taller economic skyscraper looks very different depending on whether you are just breaking ground or trying to add a new observation deck to the top.

Technical Summary: Development Stage Shapes Economic Growth Dynamics

Problem Statement
The paper addresses a critical gap in the economic growth literature: the assumption that the determinants of economic growth operate uniformly across all nations. While existing research extensively analyzes factors such as physical capital, human capital, trade openness, and Foreign Direct Investment (FDI), most studies either focus exclusively on developed or developing nations, or treat these factors as having invariant effects across different stages of development. Consequently, there is limited understanding of how global shocks and domestic policy responses interact with structural growth determinants differently in developed versus developing economies. The study posits that growth outcomes are asymmetric; countries do not merely respond differently to external shocks but also possess distinct structural drivers for growth based on their development stage.

Methodology
The study employs a quantitative panel data analysis covering 140 countries (classified as developing or developed based on World Bank income groups) over the period 1990–2020. The dataset is sourced from the World Bank's World Development Indicators (WDI).

Econometric Model: The authors utilize a Fixed-Effect (FE) regression model to control for unobserved country-specific heterogeneity (e.g., geography, legal traditions) and time-specific global shocks (e.g., financial crises, pandemics). The baseline model is specified as:
$GDPG_{it} = \beta_0 + \beta_1GCF_{it} + \beta_2LAB_{it} + \beta_3TRADE_{it} + \beta_4FDI_{it} + \beta_5NRR_{it} + \beta_6HC_{it} + \mu_i + \lambda_t + \epsilon_{it}$
Where $GDPG$ is the dependent variable (annual GDP growth), and the independent variables include Gross Capital Formation (GCF), Labor Force (LAB), Trade Openness (TRADE), FDI, Natural Resource Rents (NRR), and Human Capital (HC).
Diagnostic Procedures: The analysis follows a rigorous sequence:
1. Descriptive Statistics: To identify baseline differences between groups.
2. Multicollinearity Check: Variance Inflation Factor (VIF) tests confirmed no severe multicollinearity (Mean VIF = 2.82).
3. Cross-Sectional Dependence: Pesaran's CD test rejected the null hypothesis of independence, necessitating methods that account for global interlinkages.
4. Stationarity: The Cross-sectionally Augmented Im-Pesaran-Shin (CIPS) unit root test indicated a mix of stationary and non-stationary variables, validating the use of second-generation tests.
5. Model Selection: The Hausman test strongly rejected the random-effects model, confirming that country-specific attributes are correlated with explanatory variables, thus justifying the Fixed-Effects approach.
Robustness Checks: The authors tested the stability of results by (1) substituting the Human Capital proxy with secondary school enrollment, (2) using lagged explanatory variables to mitigate reverse causality, and (3) excluding FDI from the model.

Key Results
The regression analysis reveals a distinct asymmetry in growth determinants between the two economic groups:

Developing Economies: Growth is primarily driven by Gross Capital Formation (GCF) ( $\beta = 0.184$ ) and Trade Openness ( $\beta = 0.125$ ). These results align with neoclassical growth theory, suggesting that physical investment and market integration are the most potent drivers for economies still building infrastructure and productive capacity. Natural Resource Rents showed a weak negative coefficient, offering marginal evidence of a "resource curse" effect, though not statistically definitive.
Developed Economies: Growth is predominantly driven by Human Capital (HC) ( $\beta = 0.152$ ) and Foreign Direct Investment (FDI) ( $\beta = 0.198$ ). In contrast to developing nations, physical capital formation has a smaller, though positive, impact, and trade openness is not statistically significant. This supports endogenous growth theory, indicating that advanced economies rely on knowledge, innovation, and high-quality investment rather than simple capital accumulation.
Full Sample: When analyzed collectively, all factors (GCF, TRADE, FDI, HC) show positive significance, masking the underlying structural differences that the subgroup analysis uncovers.

Key Contributions
The paper makes three primary contributions to the literature:

Synthesis of Growth Theories: It empirically demonstrates that neoclassical and endogenous growth theories are not competing explanations but are context-dependent. Neoclassical mechanisms (capital accumulation) dominate in developing contexts, while endogenous mechanisms (human capital and innovation) dominate in developed contexts.
Challenging Homogeneity: The study challenges the assumption of invariant growth determinants across countries. It provides evidence that the "one-size-fits-all" policy approach is flawed, as the same variable (e.g., FDI or Trade) yields different magnitudes of impact depending on the institutional and developmental stage of the host economy.
FDI and Absorptive Capacity: The findings support the absorptive capacity argument (Borensztein et al., 1998), showing that FDI's growth-enhancing effect is stronger in developed economies where institutional quality and human capital allow for better utilization of foreign capital.

Significance and Policy Implications
The authors assert that the study's significance lies in its alignment with the Sustainable Development Goals (SDGs), specifically SDG 8 (Decent Work and Economic Growth) and SDG 9 (Industry, Innovation, and Infrastructure). The paper argues that policy prescriptions must be tailored to the specific stage of development:

For Developing Economies: Policy should prioritize productive investment (infrastructure, machinery), trade liberalization, and economic diversification to mitigate resource dependence risks.
For Developed Economies: Policy should shift focus toward innovation, education, health systems, and attracting high-quality, technology-intensive FDI.

The study concludes that growth divergence persists not merely due to external shocks, but because the structural drivers of growth differ fundamentally between income groups. Therefore, successful growth strategies must be grounded in the specific structural realities and institutional capacities of each economy rather than mechanically copying policies from other development stages.

Technical Summary: Development Stage Shapes Economic Growth Dynamics

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