📊 The Economics Nobel Over Time – A Visual and Analytical Deep Dive

The Nobel Prize in Economics tells a story beyond medals. Behind each award lies decades of research, evolving paradigms, and the silent trends shaping modern economic thought.

🔍 Key Questions I Explored

• How old are laureates when they receive the prize?
• What themes are most frequently honored?
• Which institutions and countries dominate?
• How has gender diversity evolved?
• What do the places of birth reveal about global research concentration?

🔬 Methodology

• Data: Nobel Prize dataset from Kaggle (compiled by Sazid Rahman)
• Tools: Python – Pandas, Matplotlib, Seaborn, WordCloud

🧠 Highlights

📈 Laureates’ Age Over Time

Most economists are awarded between ages 65 and 70 — a reminder that economics is a cumulative and patient science.

🌎 Countries of Birth

The United States dominates the list of Nobel laureates in economics, followed distantly by the UK, Canada, and France.

🏙️ Cities of Birth

New York, Boston, and Chicago top the chart — revealing the urban roots of many top economists.

🎓 Top Institutions

University of Chicago, Harvard, and MIT lead — both as intellectual hubs and symbols of scientific recognition.

💬 Word Cloud of Motivation Texts

Themes such as theory, contribution, analysis, market, and policy dominate official Nobel motivations.

👥 Gender Representation

Out of dozens of laureates, only a handful are women — but names like Elinor Ostrom, Esther Duflo, and Claudia Goldin represent crucial steps toward inclusion.

📚 Reflections

The Nobel isn’t just a celebration of individual achievement. It reflects:

• The evolving dominant paradigms in economics
• The concentration of academic recognition
• Gaps in geographic and gender inclusion

It’s a mirror to how we value knowledge, and a call to keep questioning what — and who — we recognize in science.

📂 Want to Explore the Code?

🔗 GitHub Repository

📁 Data: Kaggle Dataset - Nobel Laureates

🏷 Tags

#DataScience, #Economics, #NobelPrize, #Python, #Research, #DataViz, #Matplotlib, #GenderInequality, #AcademicRecognition