What is the Demographic Debt Dashboard?

OVERVIEW

This website demonstrates how demographic trends, especially demographic aging can be integrated into long-run macroeconomic forecasts. Modern public finance systems were constructed during periods when populations were young and expanding. However, in recent decades fertility rates have fallen below replacement levels in nearly all advanced economies leading to fewer young people, while large cohorts move into retirement. As a result, the traditional balance between contributors and beneficiaries has shifted in ways that place immense pressure on government budgets.

As populations age, fewer workers support a growing number of elderly who rely on pension programs, healthcare systems, and other entitlement benefits. Governments face difficult policy choices as a result. They could reduce benefits or raise the retirement age, but both measures are politically challenging as the elderly tend to hold significant political power and will resist changes to the programs they depend on. Raising taxes is another option, but this is also very unpopular and risks placing additional burdens on younger generations already facing affordability challenges.  In many countries, these constraints leave policymakers with limited alternatives other than borrowing to meet existing obligations.

This dynamic helps explain why government debt has increased substantially in many advanced economies in recent decades. Borrowing can provide short-term relief, but persistent demographic pressures make long-run fiscal sustainability more difficult. The world is continuing to age rapidly, and as of today no widely accepted policy solution has emerged to fully offset the effects of demographically driven debt.

This website uses a dataset of 69 countries from 1990 to 2023, incorporating demographic structures, macroeconomic indicators, and institutional quality into a forecasting model in order to illustrate how population aging may shape future debt trajectories across the globe. The goal is not to make policy recommendations, but to help readers visualize the long-term fiscal implications of demographic aging using data-driven projections. 

WHAT DOES THIS WEBSITE OFFER?

Instead of relying on a single model specification for all countries, this dashboard provides 20 different variants of a demographics driven forecasting model, each built with a distinct sample of countries and years. These models offer multiple perspectives on how demographic aging may influence long-run government debt.

WHY USE MANY MODELS INSTEAD OF ONE?

When forecasting a macroeconomic variable like government debt, accuracy depends heavily on the number of past observations available for the input variables. Macroeconomic and demographic data are typically released annually, which means that any single country dataset contains relatively little information. For example, this website's model forecasts debt until 2050 using data from 1990 to 2023. If the model relied on only one country, it would be making a 27-year prediction based on just 33 years of data, which is far from sufficient for long-term forecasting. 

To address this limitation, the models incorporate data from "similar" countries. Pooling countries together increases the number of observations and can substantially improve forecast accuracy. However, this approach comes with a tradeoff. Adding countries increases the statistical power of the model, but including countries that are too dissimilar can reduce how representative the model is for the country being forecasted, ultimately hurting accuracy. 

The solution used here is to create multiple model specifications. All models share the same econometric framework but differ in which countries and time periods they include. By evaluating these models side by side, we can identify which specifications produce the most reliable forecasts and understand how sensitive the results are to sample selection.