Beyond Bricks and Mortar: Drivers of India's Economic Growth

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Create a stunning, high-impact research defence PowerPoint (30-mark level, premium academic design) based on this dissertation: Title: Beyond Bricks and Mortar — Education Expenditure, Capital Investment and the Drivers of India's Economic Growth (1991–2023) Author: Mahdiya Tasneem Institution: St. Xavier's College, Kolkata Design Theme: - Dark academic + modern minimal (black, deep blue, gold accents) - Clean graphs, bold headings, strong visual hierarchy - Suitable for viva/defence with examiners - Use subtle animations and emphasis on key results Structure (expand to ~14–16 slides): 1. Title slide (premium, elegant) 2. Research motivation (why this matters for India) 3. Literature review (Mallick & Dash 2015) 4. Research gap & contribution (highlight novelty strongly) 5. Data & variables (visual icons + clean layout) 6. Methodology flow (ADF → Johansen → VAR) 7. Unit root results (simple, visual) 8. Cointegration result (rank = 0 explained visually) 9. VAR model overview 10. Key regression results (GDP equation focus) 11. System equations insights (UNEMP, EDU, GCF) 12. Diagnostics (clean credibility slide) 13. Granger causality (highlight 4 key findings boldly) 14. IRF insights (visual storytelling) 15. FEVD results (big numbers, impact) 16. Conclusion & policy implications (exam-ready) 17. Thank you + viva questions Special emphasis: - Highlight: Jobless growth (GDP → UNEMP) - Highlight: GCF → EDU (novel finding) - Highlight: Education is long-run only Make it visually stunning, professional, and worthy of top marks. Use minimal text per slide and strong visual storytelling. Return a downloadable PPT and PDF.

Research defence analyzing education expenditure, capital investment, and unemployment's role in India's GDP growth (1991–2023). Employs VAR models, Granger causality, IRFs, and FEVD to reveal physical capital's short-run dominance, education's long跑

April 17, 202617 slides

Slide 1 of 17

Slide 1 - Research Defence

Beyond Bricks and Mortar

Education Expenditure, Capital Investment, and the Drivers of India's Economic Growth (1991–2023) | Mahdiya Tasneem, St. Xavier's College, Kolkata

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Photo by Tom Parkes on Unsplash

Slide 2 of 17

Slide 2 - Research Motivation

Shift from protectionist policies to LPG reforms (1991)
Critical need to identify sustainable growth drivers
Addressing the paradox: High GDP vs. persistent structural issues
Evaluating the efficacy of public investment in education vs. physical capital

Slide 3 of 17

Slide 3 - Literature Review

Mallick & Dash (2015): Analyzed linkages between public expenditure and growth in India
Established the role of infrastructure and fiscal policies in long-run development
Foundations for understanding structural transformations in transition economies
Acknowledged the need for updated analysis incorporating recent post-liberalization data

Slide 4 of 17

Slide 4 - Research Gap & Contribution

Extended temporal scope (up to 2023) to capture post-pandemic dynamics
Novel investigation: Direct causality from Gross Capital Formation (GCF) to Education Expenditure
Explicit focus on 'Jobless Growth' dynamics within the VAR framework
Empirical verification of education as a long-run growth driver exclusively

Slide 5 of 17

Slide 5 - Data & Variables

📈 Growth Indicator Real GDP (Constant Prices)

🏗️ Physical Capital Gross Capital Formation (% of GDP)

🎓 Human Capital Public Expenditure on Education (% of GDP)

👥 Labour Market Unemployment Rate (LFPR adjusted)

Slide 6 of 17

Slide 6 - Methodology Flow

Phase 1	Phase 2	Phase 3	Phase 4
Stationarity Check	Integration Analysis	Model Estimation	Diagnostic & Impact Analysis
Augmented Dickey-Fuller (ADF)	Johansen Cointegration Test	Vector Autoregression (VAR)	Granger, IRF, FEVD

Slide 7 of 17

Slide 7 - Unit Root Results

100%: Level Test
Stable: First Difference

Slide 8 of 17

Slide 8 - Cointegration Analysis

Trace Statistic and Max-Eigenvalue Test utilized
Null hypothesis: Rank=0 (No cointegration) failed to be rejected
Implication: Lack of long-run equilibrium vector among chosen variables
Conclusion: VAR model in first differences is the statistically robust specification

Slide 9 of 17

Slide 9 - VAR Model Overview

Framework: Unrestricted VAR model in first differences
Variables: d(GDP), d(GCF), d(EDU), d(UNEMP)
Lag Length Selection: Based on AIC/SC criteria to minimize information loss
Focus on short-run dynamic linkages between variables

Slide 10 of 17

Slide 10 - Key Regression Results (GDP Equation)

GDP growth positively influenced by lagged GCF (Physical Capital)
Education Expenditure shows negligible short-run impact on GDP
Evidence of Jobless Growth: GDP growth coefficients positively associated with UNEMP changes
Model R-squared indicates robust explanatory power for the period

Slide 11 of 17

Slide 11 - System Equations Insights

GCF → EDU: Statistically significant positive feedback loop identified
UNEMP: Relatively insensitive to short-run shocks in EDU spending
EDU: Confirmed as a long-run determinant rather than a short-run policy lever
Capital formation remains the dominant driver of short-term industrial expansion

Slide 12 of 17

Slide 12 - Diagnostics & Credibility

Stability Condition: All roots reside within the unit circle (Stable VAR)
Serial Correlation: Breusch-Godfrey test indicates no evidence of autocorrelation
Heteroskedasticity: White test confirms residual constant variance
Normality: Residuals demonstrate multivariate normality (Jarque-Bera)

Slide 13 of 17