Q&A 6 Which EAC country has the most stable vs most volatile GDP growth?

6.1 Explanation

Beyond average growth, economists also care about stability.
- A country with steady growth is usually more attractive for investment and policy planning.
- A country with highly volatile growth may face economic shocks, conflicts, or dependence on narrow sectors (e.g., oil, minerals).

We can measure volatility by looking at the standard deviation of GDP growth rates over time.
- High standard deviation → volatile growth
- Low standard deviation → stable growth

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6.2 SQL/MySQL Code

Once you have computed GDP growth rates (using a self-join into a derived table or a stored table), you can measure volatility:

-- Calculate average growth and volatility (std dev) by country
SELECT 
    country,
    ROUND(AVG(gdp_growth_rate), 2) AS avg_growth,
    ROUND(STDDEV(gdp_growth_rate), 2) AS volatility
FROM (
    SELECT 
        curr.country,
        curr.year,
        ((curr.gdp_usd_current - prev.gdp_usd_current) / prev.gdp_usd_current) * 100 AS gdp_growth_rate
    FROM gdp_wdi curr
    JOIN gdp_wdi prev
        ON curr.country = prev.country
       AND curr.year = prev.year + 1
    WHERE curr.country IN ('KE','TZ','UG','RW','BI','CD','SS','SO')
) AS growth_rates
GROUP BY country
ORDER BY volatility DESC;

6.3 Python Code

import pandas as pd

# Load dataset
df = pd.read_csv("data/gdp_wdi_EAC_USA_2000_2024.csv")

# Keep only EAC
eac_codes = ["KE","TZ","UG","RW","BI","CD","SS","SO"]
eac = df[df["country"].isin(eac_codes)].sort_values(["country","year"])

# Calculate GDP growth rates
eac["gdp_growth_rate"] = eac.groupby("country")["gdp_usd_current"].pct_change() * 100

# Compute mean and volatility (std deviation)
stats = eac.groupby("country")["gdp_growth_rate"].agg(["mean","std"]).reset_index()
stats = stats.rename(columns={"mean":"avg_growth","std":"volatility"})

print(stats.sort_values("volatility", ascending=False))

  country  avg_growth  volatility
5      SS    0.214993   28.246220
4      SO    7.554278   19.767841
1      CD    7.639088   16.916869
7      UG   10.263052   15.497807
0      BI    4.528763   11.711263
2      KE   10.310812    8.980763
3      RW    8.662015    8.199373
6      TZ    7.850297    6.481448

6.4 Learning Outcome

By the end of this Q&A you will be able to: - Calculate GDP growth volatility using SQL (via STDDEV). - Use Python to compute and compare growth stability across countries. - Interpret volatility as a measure of economic risk and uncertainty.

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6.5 Takeaway

• Stable growth (low volatility) indicates consistent expansion, often linked to stronger institutions and diversified economies.
• Volatile growth (high volatility) can signal vulnerability to shocks, conflicts, or reliance on a single sector.
• This analysis helps policymakers and analysts understand not just how fast economies grow, but also how reliable that growth is over time.