I grew up in Auraiya, Uttar Pradesh, India asking why some people's choices are freer than others. Economics gave me the tools to investigate that question properly.
MSc in Development Economics at Nottingham, then research work at IDS Jaipur with India's Time Use Survey data, and now a research internship at IFAD in Rome, reviewing whether rural development interventions actually work, for whom, and why.
I'm building toward a PhD in development economics. This GitHub is the evidence trail: real problems I worked on, documented honestly, including the parts that didn't go as planned.
My research sits at the intersection of gender, labour, household economics, and measurement. How we count things, what we miss when we count badly, and what becomes visible when we count better.
My MSc dissertation looked at whether rainfall shocks increase domestic violence against women in India. The income stress channel made sense theoretically. Less rain, less agricultural income, more tension at home, more violence.
But the data told a different story.
What I expected: Rainfall shock โ lower income โ more violence โ
What I found: Social sector expenditure โ MORE reported violence โ
States that spent more on health and education had higher reported domestic violence. That is not what you'd expect if spending was helping.
I spent a lot of time after my dissertation reading about this. The IPV literature, measurement theory, and institutional economics. And slowly I started to think that what I found wasn't evidence of more violence โ it was evidence of more reporting. When women have a clinic to go to, a school nearby, people they can tell โ they report violence that was always happening but previously invisible.
I'm calling this the institutional trust mechanism. It's a hypothesis, not a proven finding. Testing it properly is what I want to do in a PhD.
๐ Dissertation code and findings
I'm not going to pretend I'm already there. But I know where I'm going and I'm building toward it deliberately.
2023โ24 MSc Development Economics, University of Nottingham โ
2025 Research work at IDS Jaipur and remotely โ
2026 Research internship at IFAD (UN), Rome โ (until July)
2026 Python for Data Science โ Stellenbosch University (completing Apr 2026)
2026 QGIS spatial data course โ Ecospatial Lab (April)
2026 Maths prep โ calculus, linear algebra, optimisation (ongoing)
2026โ27 Pre-doctoral or RA position (applying right now)
2027 PhD applications โ fully funded, development economics
Every project in this portfolio is a step on that map. Nothing here is for show.
Nothing here is a tutorial or a textbook exercise. These were real problems.
|
**MSc Dissertation | Stata ** 20 years of data across 25 Indian states. Fixed-effects regressions, robustness checks, the whole thing. The finding that started the question I can't stop asking. |
Python | Built at IFAD 70+ multilingual PDFs, 200 pages each. I built a tool to extract the right section automatically. It works. My consultant said it'll keep being useful long after I leave. |
|
R | RA Application Task I replicated a published paper in R from scratch after my Stata licence expired. DHS data, panel weights, cooking fuel, women's decision-making. All four outputs. |
Stata | IDS Jaipur 10.6 million observations. Raw hierarchical text files. Six data levels. I built the pipeline to merge all of it into something usable for gender research. |
|
PRISMA | IDS Jaipur 4,328 records screened. Bibliometric mapping in VOSviewer. Two systematic reviews on how time is distributed between men and women and what that means for labour inequality. |
Writing | Ongoing I read economics papers and write about them. Not summaries โ actual engagement with what the research is doing and what it means. Bandiera et al. (2022), UK parental leave policy, more coming. |
skills = {
"Stata" : "โโโโโโโโโโโโโโโโโโ Intermediate to Advanced",
"R" : "โโโโโโโโโโโโโโโโโโ Intermediate",
"Python" : "โโโโโโโโโโโโโโโโโโ Beginner-Intermediate",
"Colab" : "โโโโโโโโโโโโโโโโโโ Just learning (SUN workshop, Apr 2026)",
"Excel" : "โโโโโโโโโโโโโโโโโโ Advanced",
"LaTeX" : "โโโโโโโโโโโโโโโโโโ Intermediate",
"QGIS" : "โโโโโโโโโโโโโโโโโโ Coming in April 2026",
"Canva" : "โโโโโโโโโโโโโโโโโโ Advanced (yes, I design too)",
"LLMs" : "โโโโโโโโโโโโโโโโโโ Regular use โ Claude, NotebookLM, Gemini"
}Methods: Fixed-effects panel econometrics ยท PRISMA systematic review ยท Bibliometric network analysis ยท Large-scale survey harmonisation ยท PDF processing ยท Data visualisation ยท Graphic design
I want to be honest about how I built the IFAD extractor because I think it matters.
When the taxonomy project came up, my consultant mentioned that Python had been tried before for this and hadn't worked well. The plan was to do it manually. I said I'd try to make it work.
I worked through it with Claude. We tried the automatic approach first โ reading the table of contents, finding the page numbers. It worked for some files, but missed pages in others. I suggested trying a manual backup approach where you just specify the start and end page yourself. That worked better. We kept testing and refining.
The decisions about what to build, how to approach it, and when to try a different strategy โ those were mine. Claude helped me write Python I was still learning. I also used NotebookLM and Gemini at different points to understand concepts.
I think that's honest. And I think knowing how to use AI tools well โ when to use them, how to direct them, how to check what they produce โ is a skill worth naming, not hiding.
My consultant's response when it was done:
"Your work has been a great help to us. I'm sure when we move to other replenishment cycles, your Python code will bring even greater value."
That was nice to hear. But what I liked most was that the tool will keep working after I leave.
โ See the code
Python for Data Science
Stellenbosch University โ School for Data Science and Computational Thinking
MarchโApril 2026 โ using Google Colab
Pandas, Matplotlib, NumPy, Scikit-learn, Seaborn, Statsmodels
Completed April 2026. โ
QGIS โ Basic and Advanced
Ecospatial Lab
April 2026 โ spatial data, maps, geographic analysis
Coming up next.
Mathematics
Self-study โ calculus, linear algebra, optimisation
This is the hard one. But it's necessary for PhD-level econometrics
and I'm working on it.
Something I noticed: I started the Python workshop already having built a working tool. The workshop is giving me proper vocabulary and structure for things I was doing instinctively. I think sometimes that's the right way to learn โ do it first, understand it properly second.
| Year | What | Where |
|---|---|---|
| 2026 | The Invisible Cage: Statistical Blindness and the Care Crisis | Centre for Gender Equality, Institute for Humanities |
| 2024 | Rainfall, Agriculture and Domestic Violence in India | Open-access journal |
| 2025โ26 | Two systematic reviews on gendered time use and labour inequality (with M. Mahamallik) | Pre-submission |
| 2025โ | Paper reviews on Substack | Ongoing |
Location: Rome, Italy
Role: Research and Administration Intern at IFAD (UN) โ until July 2026
Main work: Impact assessment taxonomy, gender barriers research
Learning: Python workshop (finished), QGIS (coming up), maths (ongoing)
Applying to: Pre-doctoral and RA roles starting August/September 2026
End goal: Fully funded PhD in development economics, 2027
If you work on gender economics, household data, development policy, or anything in that space โ I'd genuinely love to talk. I'm also always happy to hear from people navigating the MSc to PhD path.
I respond to every message.
๐ฌ porwal.purnima18@gmail.com ๐ linkedin.com/in/purnimaporwal ๐ purnima-porwal-dtduwf8.gamma.site