Stability Over Speed

The Problem With Headline Numbers

GDP rebound figures dominate post-COVID economic commentary.

A country posts 8% growth in 2021 and the headline reads: recovery complete.

But recovery speed and recovery stability are not the same thing.

This analysis was built to test that gap using World Bank data across five major economies from 2018 to 2023, combining GDP growth and inflation into a single time-aligned model for cross-country comparison.

The Data Problem

World Bank GDP and inflation datasets are published in incompatible formats.

GDP year values were stored as string fields.

Inflation year values used integer formats.

Joining them directly produces silent errors the kind that make analysis look correct while the underlying data is structurally misaligned.

Before any insight was possible, the model had to be structurally fixed.

The objective: build a clean, time-aligned relational model that supports reliable cross-country comparison without introducing distortion at the join stage.

Transformation Workflow

The pipeline was executed in BigQuery using SQL.

The goal was not just data cleaning it was building a model that could support reliable analytical joins without silent errors propagating downstream.

1. Raw Data Ingestion

Downloaded GDP growth and inflation CSV files from the World Bank and loaded them into BigQuery as source tables.

2. Schema Cleaning & Standardization

• Renamed ambiguous fields

• Extracted numeric year values using REGEXP_EXTRACT

• Cast year fields to consistent INT64 format

  
  

This ensured relational compatibility across datasets.

3. Relational Integration

Joined GDP and inflation tables on standardized Country and Year keys, producing a unified time-series dataset.

4. Analytical Filtering

Scoped the dataset to 2018–2023 to focus on pre- and post-COVID economic behavior.

5. Visualization Layer

Built comparative dashboards in Tableau to analyze:

• GDP growth trends

• Inflation trends

• Cross-country performance patterns

What the Data Actually Showed

• 2020 Contraction: 

  All five economies experienced a sharp GDP decline in 2020. France and Singapore recorded the largest contractions within the selected group.

• 2021 Rebound: 

  A strong recovery was observed across all economies in 2021, with Singapore recording the highest GDP growth rate (9.75%) during the rebound year.

• Growth Stability: 

  China was the only economy in the dataset to maintain positive GDP growth (2.34%) in 2020 despite the global contraction.

• Inflation Surge: 

  Inflation remained moderate before 2020 but increased significantly in 2022, particularly in the United States and Germany.

• Growth–Inflation Relationship: 

  The Inflation vs. GDP visualization indicates a moderately positive association during the recovery period, with variation across countries.

Strategic Interpretation: Decision Simulation

The data showed a consistent pattern across all five economies: the faster the rebound, the more sustained the inflation pressure that followed.

Recovery was uneven not just in speed, but in stability.

Some economies rebounded quickly but faced sustained inflation pressure, increasing uncertainty and tightening risk. Others showed steadier inflation alongside gradual growth, indicating more stable conditions.

The signal became clearer when viewed together:

1. Growth alone is not enough.

2. Without inflation context, headline recovery figures can be misleading.

3. If used to guide expansion or budget allocation, I would prioritize recovery stability over rebound speed.

4. It is the interaction between growth and inflation over time that reveals relative risk across markets.

   
   

For expansion decisions or budget allocation across markets, this matters.

A GDP rebound number without inflation context is an incomplete signal.

The interaction between growth and price stability over time is where the real risk picture emerges.

Key Outcome

What This Project Demonstrates

A pipeline that takes structurally incompatible public datasets and produces a clean, time-aligned analytical model ready for cross country comparison.

The technical work schema normalisation, type alignment, relational joins  was not the end goal. 

It was the prerequisite for trustworthy analysis.

The finding: 

Recovery speed is not the same as recovery strength. 

Headline GDP figures without inflation context are an incomplete basis for decisions.