Introduction
Is economic prosperity synonymous with mental well-being?
This common assumption has been floating around for a while — but how true is it? In an increasingly interconnected world, economic downturns and booms are felt by everyone. Our project uses over three decades of global data to explore the complex relationship between economic conditions and mental health outcomes.
We combined the WHO Global Suicide Rates dataset (via Kaggle) with World Bank economic indicators (GDP per capita, employment-to-population ratio, inflation) and the UNDP Human Development Index — capturing health, education, and income dimensions of human development globally.
We also engineered derived variables: SuicideDiff (year-over-year change in suicide rate), GDPperCapitaGrowthPct, and EmpRatioChange to capture dynamic trends rather than static snapshots.
Exploratory Data Analysis
What the data looks like
Before diving into the research questions, we explored the dataset extensively — cleaning missing values, understanding distributions, and mapping regional patterns.
The headline chart tells a nuanced story. Rising GDP did correlate with falling suicide rates globally — but not uniformly, and not without exceptions. This motivated our deeper regional and crisis-level analysis.
Correlation analysis
We ran correlation heatmaps to understand how economic indicators relate to suicide metrics — first globally, then zooming into Europe where the patterns are strongest.
The European V-shape
GDP and suicide rate have a non-linear relationship in Europe: middle-income countries show the highest rates. This is likely because rapid industrialisation and social dislocation create stress that very poor countries (with tight community bonds) and very wealthy countries (with robust mental health infrastructure) don't experience in the same way. This finding directly informed our regression modelling choices.
Research Question 1
How do crises affect suicide rates?
Our first hypothesis was intuitive: if a crisis hit, suicide rates would spike. To test this, we defined crisis years using two criteria:
GDP Crisis
GDP per capita dropped ≥ 2%, growth went negative, or it was a known global recession year (1998, 2008, 2020).
Inflation Crisis
Inflation exceeded 10%, or spiked by ≥ 5% from the previous year.
The stagnation effect
We ran a Welch's t-test comparing year-over-year suicide rate changes in crisis vs non-crisis years. The result was statistically significant (t = 2.49, p = 0.013) — but the direction was surprising.
"Economic crises don't spike suicide rates — they stagnate them. The global downward trend in suicide rates effectively stops during crisis years."
| Period | Mean SuicideDiff | Interpretation |
|---|---|---|
| Non-Crisis Years | −0.248 | Steady global improvement |
| Crisis Years | −0.014 | Progress nearly stops |
The lagged effect
If the immediate effect was stagnation, when did the real damage appear? We ran an OLS regression predicting current suicide rates using GDP growth and inflation from the current year, 1 year ago, and 2 years ago.
| Variable | Coefficient | p-value | Significance |
|---|---|---|---|
| GDP Growth (current year) | +0.039 | 0.020 | Significant |
| GDP Growth (lag 1) | +0.021 | 0.236 | Not significant |
| GDP Growth (lag 2) | +0.019 | 0.289 | Not significant |
| Inflation Rate (current) | +0.005 | 0.389 | Not significant |
| Inflation Rate (lag 1) | −0.005 | 0.367 | Not significant |
| Inflation Rate (lag 2) | +0.010 | 0.003 | Significant ★ |
Key Finding: The 2-Year Delayed Effect
High inflation two years ago is a statistically significant predictor of rising suicide rates today (p = 0.003). People are resilient during the initial shock — but as savings deplete, debts mount, and hope fades, the psychological toll eventually manifests 1–2 years later.
Model fit: R² = 0.011 — expected, since suicide is driven by culture, healthcare access, and stigma, not just economics.
Policy implication: Policymakers cannot declare victory just because suicide rates don't spike in the first year of a recession. Mental health support systems must be maintained well after markets stabilise.
Research Question 2
Do stronger welfare systems buffer employment shocks?
We examined whether countries with higher HDI scores showed smaller suicide rate increases during employment shocks — defined as a drop of ≥ 1 percentage point in the employment-to-population ratio. Countries were split at the median HDI into High and Low groups.
| Group | Mean SuicideDiff | Median SuicideDiff | Count |
|---|---|---|---|
| High HDI | −0.139 | +0.065 | 137 |
| Low HDI | +0.337 | +0.098 | 153 |
Directionally Compelling, Not Conclusive
High-HDI countries averaged a slight decline in suicide rates (−0.14) during employment shocks, while low-HDI countries averaged an increase (+0.34). The OLS interaction model confirmed the direction — but the interaction term did not reach significance (p = 0.137).
This result should be treated as suggestive, not conclusive. The pattern is consistent with the theory that welfare systems buffer unemployment shocks — but the data doesn't confirm it definitively.
Methodology
How we built this analysis
Data Sources
WHO suicide data (Kaggle, 1990–2022), World Bank economic indicators, UNDP HDI dataset, Gini coefficient data.
Feature Engineering
Constructed SuicideDiff, GDPperCapitaGrowthPct, EmpRatioChange, lagged inflation/GDP variables, and binary crisis flags.
Statistical Tests
Welch's t-test for group comparisons. OLS regression with lagged predictors and interaction terms via statsmodels.
Data Cleaning
Forward-fill within country, dropped countries with entire columns missing. Final dataset: ~4,700 country-year observations.
Tech stack
Limitations
What this analysis cannot tell us
- Suicide rates are shaped by many factors beyond economics — culture, mental health infrastructure, stigma, social support. Macroeconomic indicators explain only a small slice of the variance (R² ≈ 0.01).
- Reporting accuracy varies across countries and time periods, especially in lower-income countries where data collection infrastructure may be weaker.
- The HDI × employment shock finding is directionally interesting but does not cross the conventional significance threshold. It should not be cited as confirmatory evidence.
- Our crisis definition uses binary flags, which necessarily simplifies the continuous and cumulative nature of economic stress.
- We assume the dataset contains accurately reported statistics — but reporting rates and definitions of suicide can differ by country and year.
The Team
Group 21
This project was a collaboration between five students as part of a data science course.