Fellowship Overview
The Lumiere Research Foundation offers a highly selective summer research program connecting undergraduate students with graduate-level mentors to conduct original academic research. As an Economics Research Scholar, I conducted independent research on Nepal's macroeconomic vulnerability to external shocks, culminating in an original research paper and presentation to an international audience of 200+ scholars.
Recognition: Graduated among top 5% of research fellowship cohort (out of 150+ scholars globally) and received Individual Research Grant of $3,000 to support continued research.
Research Project
Title
The Impact of Global Oil Price Shocks on Nepal's Foreign Exchange Reserves and Inflation
Research Question
How do global oil price shocks affect Nepal's foreign exchange reserves and inflation, and what are the implications for economic stability and policy?
Motivation
As a landlocked, oil-importing developing nation, Nepal faces significant vulnerability to global commodity price fluctuations. Understanding these transmission mechanisms is crucial for:
- Foreign exchange reserve management
- Import policy formulation
- Inflation targeting strategies
- Economic security and resilience planning
Methodology
Data Collection
Compiled comprehensive 43-year dataset (1980-2023) including:
- Oil Prices: Brent crude monthly averages (primary explanatory variable)
- Foreign Exchange Reserves: Nepal's gross international reserves (dependent variable)
- Inflation: Consumer Price Index year-over-year changes (dependent variable)
- Control Variables: GDP growth, remittance inflows, exchange rate, trade balance
Econometric Techniques
1. Vector Autoregression (VAR) Modeling
# VAR(4) Model Specification
library(vars)
library(urca)
# Prepare time series data
data_ts <- ts(macro_data[, c("oil_price", "reserves",
"cpi", "remittances",
"exchange_rate")],
start = c(1980, 1), frequency = 12)
# Test for optimal lag length
VARselect(data_ts, lag.max = 12)
# Estimate VAR(4) model
var_model <- VAR(data_ts, p = 4, type = "const")
summary(var_model)
VAR(4) model selected based on Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC), capturing:
- Interdependencies between oil prices, reserves, and inflation
- Feedback effects and dynamic adjustments
- 4-month lag structure in economic responses
2. Granger Causality Testing
Tested causal relationships to establish direction of influence:
# Granger causality tests
causality(var_model, cause = "oil_price")
# Results:
# Oil price -> Reserves: F-statistic = 8.42, p < 0.001
# Oil price -> Inflation: F-statistic = 6.17, p < 0.01
# Reserves -> Oil price: F-statistic = 1.23, p = 0.34
Key Finding: Oil price changes Granger-cause both reserve levels and inflation, confirming unidirectional causal relationship.
3. OLS-CUSUM Stability Testing
Employed Cumulative Sum (CUSUM) test to check for structural breaks:
- Identified 2008 financial crisis as potential structural break
- Tested model stability across different time periods
- Validated consistency of relationships over 43-year span
4. Impulse Response Functions
Generated IRFs to visualize shock transmission:
# Impulse response analysis
irf_oil <- irf(var_model,
impulse = "oil_price",
response = c("reserves", "cpi"),
n.ahead = 24,
boot = TRUE, runs = 1000)
plot(irf_oil)
Key Findings
-0.42
Oil-Reserves Correlation
+0.38
Oil-Inflation Correlation
Primary Results
1. Foreign Exchange Reserve Impact
- Negative Correlation: 10% increase in oil prices associated with 4.2% decline in reserves after 6 months
- Transmission Mechanism: Higher import costs → increased dollar demand → reserve depletion
- Asymmetric Effects: Reserve losses during price spikes exceed gains during price drops
- Threshold Effect: Impact intensifies when oil exceeds $80/barrel
2. Inflationary Pressure
- Positive Correlation: 10% oil price increase leads to 3.8% higher inflation after 8 months
- Pass-Through Channels: Transportation costs → production costs → consumer prices
- Persistent Effects: Inflation remains elevated for 18-24 months post-shock
- Broader Impact: Oil shocks affect food prices (agricultural inputs) and non-tradables
3. Moderating Factors
Identified variables that cushion oil shock impacts:
- Remittance Inflows: Higher remittances partially offset reserve losses (elasticity: 0.28)
- Exchange Rate Flexibility: NPR/USD adjustments help absorb 15-20% of shock
- Tourism Receipts: Foreign exchange from tourism provides buffer
Policy Implications
- Reserve Management: Maintain higher reserve buffer (6+ months import cover) given oil vulnerability
- Energy Diversification: Accelerate hydroelectric development to reduce oil dependence
- Hedging Strategies: Consider commodity hedging mechanisms for oil imports
- Inflation Management: Monetary policy should anticipate 6-8 month lag in oil price transmission
- Remittance Facilitation: Policies supporting remittance inflows enhance resilience
Research Process
Phase 1: Literature Review (Weeks 1-2)
- Reviewed 40+ academic papers on oil price shocks and macroeconomic impacts
- Studied VAR methodology and time series econometrics
- Examined prior research on developing economy vulnerabilities
- Identified gaps in Nepal-specific literature
Phase 2: Data Collection & Cleaning (Weeks 3-4)
- Compiled data from World Bank, IMF, Nepal Rastra Bank, and EIA databases
- Standardized different data frequencies and formats
- Handled missing values through interpolation and imputation
- Created comprehensive dataset spanning 516 months
Phase 3: Econometric Analysis (Weeks 5-8)
- Tested for stationarity using ADF and PP tests
- Selected optimal VAR lag length through information criteria
- Estimated VAR(4) model and conducted diagnostic tests
- Performed Granger causality and impulse response analysis
- Conducted robustness checks across different specifications
Phase 4: Writing & Revision (Weeks 9-11)
- Drafted research paper following academic journal format
- Created figures and tables visualizing key results
- Incorporated feedback from graduate mentor (University of Pittsburgh)
- Refined argumentation and policy recommendations
Phase 5: Presentation (Week 12)
- Prepared 15-minute conference-style presentation
- Created visual slides highlighting key findings
- Practiced delivery and Q&A responses
- Presented to audience of 200+ scholars via Zoom
Collaboration & Mentorship
Graduate Mentor
Worked closely with PhD candidate from University of Pittsburgh's Economics Department:
- Weekly one-on-one meetings discussing progress and challenges
- Guidance on econometric methodology and model specification
- Feedback on research design and empirical strategy
- Coaching on academic writing and presentation skills
Peer Collaboration
- Participated in cohort workshops with fellow research scholars
- Received peer feedback during draft presentations
- Engaged in intellectual discussions across disciplines
- Built network with talented undergraduate researchers globally
Skills Developed
Technical Skills
VAR Modeling
Time Series Analysis
Granger Causality
R Programming
Data Visualization
Statistical Testing
Research Skills
- Independent research design and execution
- Academic literature review and synthesis
- Econometric methodology selection and application
- Research paper writing in academic style
- Peer review incorporation and revision
Communication Skills
- Conference-style presentation to academic audience
- Responding to technical questions under pressure
- Explaining complex econometric results to diverse audiences
- Creating compelling visual narratives with data
Achievements
Research Grant
Individual Research Grant: $3,000
Awarded to top 5% of scholars based on research quality, presentation performance, and potential for future impact.
Publication Status
SSRN Working Paper (2025): Paper uploaded to Social Science Research Network, making research publicly accessible to academic and policy communities.
Conference Presentation
Successfully presented research findings to international audience of 200+ scholars, receiving positive feedback from faculty reviewers and peers.
Impact & Future Directions
Academic Impact
- Contributes to limited literature on Nepal's macroeconomic vulnerabilities
- Provides empirical evidence for energy policy discussions
- Demonstrates application of advanced econometric methods to developing economy context
Policy Relevance
- Informs foreign exchange reserve management strategies
- Supports energy diversification policy arguments
- Provides quantitative basis for inflation forecasting
Future Research Extensions
- Expand analysis to include other commodity prices (food, metals)
- Investigate non-linear effects during extreme price movements
- Conduct comparative analysis across South Asian nations
- Examine impact of renewable energy adoption on oil vulnerability
Program Experience
Structure
- 12-week intensive summer research program
- Remote/virtual format enabling global participation
- Weekly mentor meetings and cohort workshops
- Culminating symposium with presentations to scholars
What Made It Valuable
- Graduate-Level Mentorship: Guidance from PhD candidate elevated research quality
- Academic Rigor: Held to standards of publishable research
- Intellectual Community: Engaged with brilliant peers across disciplines
- Professional Development: Learned academic research workflow and presentation skills
- Recognition: Top performer status validates research capabilities
Personal Growth
- Gained confidence in independent research abilities
- Developed resilience through challenging econometric problems
- Enhanced time management juggling research with other commitments
- Built self-motivation and discipline in remote work environment
- Strengthened commitment to pursuing research-oriented career path
Interested in My Research?
I'm passionate about using rigorous quantitative methods to address real-world economic challenges in developing countries. Whether you're a potential employer, graduate program, or research collaborator, I'd love to discuss my work and explore opportunities to contribute to impactful economic research.
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