Why High Development Doesn’t Necessarily Mean High Emissions

When delegates meet at COP31 in Antalya from November 9 to 20, 2026, climate finance, technology transfer, capacity-building and separate reporting tracks for industrialized and other parties will all be on the provisional agenda. Together, those items return negotiators to the same question: how can countries share the effort of cutting emissions while preserving the development gains still needed by poorer populations?

One comparison from 2019 captures the divergence. Singapore and Sweden recorded almost identical Human Development Index scores, 0.943 and 0.947. Yet Singapore’s consumption-based carbon dioxide emissions were 27.493 metric tons per person, more than four times Sweden’s 6.695 tons. Comparable outcomes in health, education and income can therefore coexist with profoundly different carbon footprints.

That pattern is the subject of The Champagne Curve of Climate and Development Inequalities, cowritten with Thomas Porcher, Raphaël-Homayoun Boroumand, Antoine Giraldi and Simon Porcher. This study examines 119 countries from 2000 to 2022 through a fixed-effects panel model, following changes within countries while accounting for stable national differences. Its purpose is practical: to identify the level of well-being from which countries should be expected to reduce emissions.

How Consumption Changes the Picture

Much of the earlier literature asks how pollution changes as gross domestic product rises. We shift the focus from economic output to the Human Development Index, or HDI. This United Nations measure combines life expectancy, education and income into a score between zero and one. It provides a broader test of whether carbon consumption is associated with longer, more educated and materially secure lives.

The emissions measure is also key. Consumption-based emissions start with the carbon dioxide released inside a country, subtract the emissions embodied in exports and add those embodied in imports. The carbon used to make a product is assigned to the country where that product is consumed. This reduces the distortion created when wealthy economies import carbon-intensive goods while production emissions appear on another country’s account.

The Curve Opens Above 0.8

When HDI is plotted against consumption-based emissions per person, the points resemble champagne spraying from a sabered bottle. Below an HDI of 0.6, countries cluster around relatively low and similar emissions. Between 0.6 and 0.8, the distribution begins to fan out. Our analysis links those differences to choices about energy production, transport and imported resources. Above 0.8, carbon footprints become highly heterogeneous even among countries with similarly high human development.

Our 2019 figures make the spread tangible. The United States combined an HDI of 0.930 with 17.007 metric tons of consumption-based carbon dioxide per person. France stood at 0.905 and 6.428 tons. Switzerland reached 0.962 and 14.180 tons. The countries differ in many respects, yet the comparison shows that a very high HDI can coexist with a wide range of carbon footprints. Beyond the threshold, the association between additional carbon consumption and additional human development weakens sharply.

A New Map of Climate Capacity

In our research, we use the shape of the curve to propose three groups. Countries below 0.6 have limited transformation capacity because emissions remain closely connected to basic development. Those between 0.6 and 0.8 have moderate capacity, with policy choices increasingly shaping their path. Countries above 0.8 have advanced capacity because comparable levels of well-being already coexist with very different levels of carbon consumption.

This classification is intended to make climate obligations more progressive. Lower-HDI countries would retain room to improve health, education and living standards. Middle-band countries could be encouraged to choose production and consumption systems aligned with the Paris Agreement. High-HDI countries would carry stronger obligations, including a more substantial carbon price, because they have greater scope to reduce their footprint while preserving human development. We leave the design of that fairer, progressive price to future research.

We also identify a perverse incentive that policy design would have to prevent. If a higher HDI triggered a higher carbon price, governments might be tempted to restrain investment in education or other social goods to remain in a less demanding category. We therefore call for mechanisms that keep the cost of climate policy from competing with investment that improves human development.

What the Evidence Can Support

The statistical work tests a relationship rather than a universal law. In our study, we compare consumption-based carbon dioxide with energy use, then use partial-dependence analysis and linear-log and polynomial regressions. Consumption-based emissions emerge as the stronger predictor of HDI. For the 2019 cross-section, the polynomial fit records an R-squared of 0.826, compared with 0.782 for the linear-log fit. The non-linear model therefore describes the observed pattern more closely, while the analysis remains correlational.

Population size, natural resources and technological development can influence both emissions and HDI. Country averages can also conceal social inequalities. The carbon measure covers fossil-fuel and industrial carbon dioxide, while excluding land-use change; international aviation and shipping are included only in the global total. Countries without sufficiently reliable trade data are absent from consumption-based estimates, although our paper reports that they account for about 3% of the global total. These boundaries define the reach of the finding and the questions that further research must address.

In a recent HEC Breakthroughs podcast, I summed up the implication: “Above a certain threshold,” I explained, “there is no need to compromise between achieving development and reducing greenhouse gas emissions.” That responsibility rests squarely with wealthier countries. As I underlined in the podcast: “What we show is that for industrialized countries, you can absolutely reduce your level of greenhouse gas emissions without compromising the well-being of the population, the prosperity of the country.”

As COP31 approaches, the Champagne Curve gives negotiators a development-based way to revisit the allocation of effort. It preserves room for countries below 0.6 to improve basic living standards, highlights the choices facing countries between 0.6 and 0.8, and directs the strongest expectations toward the high-HDI economies where carbon footprints diverge most. For me, that responsibility is squarely on wealthier countries. What we show in our research is that for industrialized countries, you can absolutely reduce your level of greenhouse gas emissions without compromising the well-being of the population, the prosperity of the country.