Interactive Solow‑Romer Growth Simulator (Shiny, R)
Modeling Long-Run Economic Dynamics
Shiny
R
Economics
Visualization
Table of Contents
Eduardo engineered an interactive Solow‑Romer growth simulator that lets users test how savings, depreciation, population growth, R&D effort, and productivity shocks shape capital deepening and long‑run output. The app supports four independent experiment tabs plus a counterfactual, turning the classic model into a powerful classroom and policy sandbox.
Key engineering achievements
| Focus | Highlights |
|---|---|
| Modular stack | simulate_solow() (~200 LOC) computes Δk, TFP, factor returns, logs, and auxiliary flows period‑by‑period, then feeds tidy results to the UI. |
| Dynamic experiments | Reusable helpers build four DT tables with add/delete buttons, Excel upload, and reactive storage—analysts can batch‑load hundreds of parameter overrides without touching code. |
| Endogenous shock layer | A second helper lets users overwrite core state variables (A, L, k, K, Y, Δk) for one‑off regime‑switch scenarios. |
| Data integration | Reads multi‑sheet World Bank workbooks, filters any country‑year window, converts the average savings rate into a slider, and re‑simulates instantly. |
Visual analytics & UX
- Ten high‑resolution ggplot dashboards—capital (K), output (Y), efficiency units (k), Δk/k, MPL, MPK, and log‑scales.
- Visibility toggles add counterfactual, 2nd‑, 3rd‑, and 4th‑scenario lines without clutter.
- One‑click downloads: ZIP of all PNGs and CSV of results.
- Custom bslib theme, responsive widths, and intelligent point‑thinning keep plots crisp for horizons up to 150 periods.
Economic rigor
- Implements the Solow steady‑state (k^*) with R&D spill‑ins ((z)) and iterates growth with full accumulation dynamics.
- Calculates MPL and MPK from the Cobb‑Douglas form, plus logs and percent changes—demonstrating clear command of calculus‑driven macro metrics.
Software craftsmanship
- Version‑tagged comments (
v2.3,v4.1, etc.) track evolution.
- Defensive input validation, informative modals, and namespaced modules prevent UI clashes.
- Codebase is deployment‑ready for shinyapps.io or RStudio Connect.
Technologies showcased
| Domain | Evidence |
|---|---|
| Advanced R | functional helpers, vectorized math, tidy data |
| Shiny | dynamic tabsets, DT tables, file I/O, downloads |
| Data viz | ggplot2 with consistent theming and legend control |
| Macro growth theory | Solow‑Romer mechanics, marginal analysis |
| Data integration | Excel ingestion via rio, reactive UI updates |
Employer takeaway
Eduardo translates complex growth theory into an elegant, data‑driven web tool—showcasing deep economics knowledge, production‑level R/Shiny skills, and clean software design.