Cap-and-trade and carbon emissions
Environmental economicsDo carbon-pricing schemes cut emissions without holding back growth? Three global datasets merged in Python and tested with OLS.
Read case studyJames Pieter Djibu. Economics & data.
Economics student at Nagoya University, combining financial modeling, SQL and econometrics to find what drives performance.
Currently
Turning economic theory into evidence. Four pieces of work are open right now.
- Tokopedia strategic analysis
- Macroeconomic drivers of the IHSG
- A/B testing & cluster-robust standard errors
- Wooldridge: OLS derivation, unbiasedness & residuals
Selected Case Studies
Minimum wage and Indonesia's gig economy
Labor economics, in progressA 2011 study found that unemployment pushes workers into the gig economy. This project tests whether that still holds in Indonesia today.
Read case study
Water quality from a photo
AI development, Gold Medal at Eskom ExpoA smartphone app that screens water from a single photo: dominant colours, classified by a neural network trained on 5,053 labelled values.
Read case studyAreas of Expertise
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Financial Modeling
Building DCF and cash-flow models with sensitivity and scenario analysis to show how valuations shift under different risk assumptions.
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Data Analytics & SQL
Querying and cleaning complex datasets in SQL to surface market trends and operational bottlenecks, then turning them into clear recommendations.
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Econometric Research
Using regression and time-series methods in Stata and Python to test economic theories against real-world data. Try the Okun's law Model Lab See the cap-and-trade OLS
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Applied Machine Learning
Training neural networks in Python with TensorFlow and Keras. A colour classifier trained on 5,053 labelled RGB values reached 88% test accuracy. See the water-quality model
Model Lab
Okun's law says faster growth cuts unemployment. Estimate it on real data and see where it breaks.
Change in the unemployment rate regressed on real GDP growth by OLS, annual data 1992–2024, six economies. Source: World Bank World Development Indicators (unemployment is the modelled ILO estimate), retrieved 30 October 2026.
β = −0.041
In Indonesia, growth and unemployment barely move together: the slope is not distinguishable from zero (p = 0.148).
The slope is too imprecise to say what growth keeps unemployment steady.
| Coef. | Std. err. | t | p | 95% CI | |
|---|---|---|---|---|---|
| Intercept | 0.208 | 0.161 | 1.29 | 0.206 | [−0.121, 0.537] |
| GDP growth | −0.041 | 0.028 | −1.48 | 0.148 | [−0.097, 0.015] |
n = 33 · R² = 0.066 · classical standard errors · 1992–2024
Self-employed: share of all employment in 2024, modelled ILO estimate. Rows with a hollow dot are not significant at 5%.
Reading the result
In 1998 Indonesia's economy shrank 13.1%, yet measured unemployment rose by less than one point. About half of all workers are self-employed, so lost jobs show up as informal and gig work rather than open unemployment. That is the link my minimum-wage project re-tests.
A two-variable OLS on annual data describes how growth and unemployment move together; it is not a causal estimate. The ILO figures are modelled, and 2025 values, which are projections, are left out.
Show the data for Indonesia
Record
Full résumé- Since 2025 Global After School Japan English Language Teacher
- 2023–24 Ministry of Education and Culture, Indonesia Indonesian Scientific Society Research Team
- 2022 PT PINS Indonesia · Telkom Indonesia Business Administration Intern
- Gold Medal, Eskom Expo
- Silver Award, Queen’s Commonwealth Essay Competition
- Best Innovation for AI Award
- Top 20, NASFIA National Competition
- Mathematics, Data Science & AI Certificate, Nagoya University
About Me
I’m an economics student in the G30 program at Nagoya University, interested in how macroeconomic forces show up in real labor markets and in the environment. My current project looks at minimum wage in Indonesia and the macroeconomic factors that drive it, and tests whether a 2011 study’s finding that unemployment pushes workers into the gig economy still holds today.
I enjoy turning messy data into something I can reason with. In my first year, I studied corporate social responsibility initiatives alongside the economics of environmental policy, cleaning a real dataset and forecasting outcomes under a cap-and-trade system. I work with Stata, Python and SQL, and I’m looking for internships and research roles where I can keep connecting economic theory to evidence.
