Growth, Threshold Effects, and the Environmental Kuznets Curve in SAARC Economies: A Heterogeneous Panel Perspective

For decades, economists and environmentalists have debated a single, stubborn question: can a country get richer without making the air dirtier? The prevailing theory, known as the Environmental Kuznets Curve, suggests that the answer is yes, but only after a certain point. The idea is that when a nation is poor, it must burn fuel and build factories to survive, causing pollution to rise alongside income. However, once a country reaches a specific level of wealth, it supposedly begins to clean up. It invests in better technology, shifts toward service industries, and demands cleaner air, causing pollution to fall even as the economy keeps growing. This creates a shape like an upside-down "U" on a graph. But for many developing regions, this theory remains unproven. The data is messy, the countries are different from one another, and the methods used to analyze them often lead to conflicting conclusions.

A new study focused on the South Asian Association for Regional Cooperation, or SAARC, a group of eight nations including India, Pakistan, Bangladesh, and Nepal, attempts to settle this debate. The researchers looked at thirty-five years of data, from 1990 to 2024, to see if this "turning point" where pollution starts to drop actually exists in South Asia. They found that the answer depends entirely on how you look at the numbers. If you treat all eight countries as if they were identical, the turning point disappears and the curve remains elusive. But when you use a method that respects the unique economic structures of each nation while accounting for the fact that they all face the same regional weather and market shocks, the curve appears clearly. The study indicates that these economies are indeed moving toward a cleaner future, but only after crossing a specific income threshold, and only if we stop forcing them into a single, uniform model.

The researchers began by gathering data on carbon dioxide emissions, economic output, and energy use for all eight SAARC members. They knew from the start that these countries were not clones of one another. India is a massive industrial power, while Bhutan and Nepal are smaller, less developed economies. They also knew that these nations are deeply connected; a drought in one affects agriculture in another, and global oil prices hit them all at once. Traditional statistical tools often ignore these differences and connections, assuming that a rule that fits one country fits them all. The authors tested this assumption first and found it to be false. The countries react differently to economic growth, and their economies are too intertwined to be treated as separate, isolated islands.

When the team applied the older, simpler methods that force all countries to follow the same pattern, the results were confusing. The data showed no clear sign that pollution would ever drop as incomes rose. It looked as if the region might be stuck on the upward slope of the curve forever, with pollution rising indefinitely as the economy grows. However, the researchers then switched to a more sophisticated approach designed to handle both the differences between countries and the shared shocks they face. This method allowed each country to have its own unique relationship between wealth and pollution while still looking at the region as a whole.

Under this more flexible lens, the picture changed dramatically. The data revealed a clear, inverted-U shape. The study found that as these economies grow, pollution does rise at first. But once a country's income per person reaches a specific level—roughly equivalent to a GDP per capita of 1.74 to 1.77 in the units used by the researchers—the trend reverses. Beyond this point, further economic growth is associated with a decline in carbon emissions. This turning point was not just a guess; the researchers used a separate statistical technique to confirm that a structural break in the data exists exactly at this income level. The agreement between these two different ways of measuring the same phenomenon gives the finding strong weight.

One of the most consistent findings across all the different methods was the role of energy. Regardless of which statistical tool was used, the amount of energy a country consumes per unit of economic output was the strongest predictor of pollution. The study showed a direct, one-way link: more energy use leads to more emissions. This suggests that the path to cleaner air is not automatic. Simply getting richer will not fix the problem if the way energy is used remains the same. The region relies heavily on coal and biomass, and the data indicates that without a major shift toward cleaner energy sources, the downward slope of the curve will not happen naturally.

The study also explored how these three factors—economic growth, energy use, and emissions—talk to each other. They found a two-way street between growth and pollution. Economic expansion drives up emissions, but high levels of pollution can also hurt the economy by increasing costs and damaging health. Similarly, growth drives energy demand, and the availability of energy drives growth. This feedback loop means that the transition to a cleaner environment requires active management. It will not happen on its own just because a country becomes wealthy. Policymakers must intervene to change the energy mix and upgrade technology.

The implications for the eight nations are significant. The research suggests that a single environmental policy for the entire region would be ineffective. Countries that are still below the income threshold need strict regulations to prevent them from locking themselves into a dirty, pollution-heavy path. Those that have already crossed the threshold are better positioned to focus on upgrading their technology and shifting toward service-based industries. The study also highlights the need for regional cooperation. Since these economies are so interconnected, a shared approach to energy transition and clean technology could lower the costs for everyone.

Ultimately, this paper does more than just confirm a theory for South Asia; it offers a warning to researchers everywhere. It shows that when studying diverse groups of developing nations, the choice of statistical method can make the difference between seeing a solution and seeing a dead end. By respecting the unique nature of each country and the connections between them, the study reveals that the path to a cleaner future is real, but it is narrow and requires careful navigation. The turning point exists, but reaching it depends on recognizing that one size does not fit all.