Two-Region Armington Trade Model with GAMSPy

This repository contains a concise implementation of a 2-Region Armington Trade Model solved as a Mixed Complementarity Problem (MCP) using the GAMSPy framework and the PATH solver.

---

📖 Model Overview

The model simulates trade flows between two regions (e.g., R1 and R2) based on the Armington assumption, where goods are differentiated by their place of origin.

Key Features:

• Market Structure: Perfect competition.
• Preferences: Constant Elasticity of Substitution (CES) utility.
• Trade Costs: "Iceberg" transport costs ($\tau \ge 1$).
• Solver: Solved as an MCP (Mixed Complementarity Problem) to handle equilibrium conditions and lower bounds robustly.

The notebook includes detailed equations for:

1. Bilateral Prices with Iceberg Costs.
2. CES Price Indices.
3. Iso-elastic Demand Functions.
4. Market Clearing Conditions.

---

📂 Repository Structure

• Prototype of Trade model.ipynb: The main Jupyter Notebook containing the math model, code, and visualization logic.
• output_csv/: Directory where simulation results are saved.
• requirements.txt: List of Python dependencies.

---

🧪 Scenarios

The model currently implements two distinct scenarios for comparison:

1. Baseline Scenario

• Symmetric World: Identical demand elasticities and production capabilities for both regions.
• Constant Friction: Trade costs remain low and constant over time.
• Purpose: Validates the model logic (results should be symmetric).

2. China-EU Counterfactual (Asymmetric)

• Demand Shock: Region 2 (representing EU) has different demand elasticities compared to R1 (China).
• Rising Costs: Trade costs from R1 to R2 increase over time (simulating tariffs or shipping disruptions).
• Supply Constraint: R2 has a capped supply capacity.
• Purpose: Analyzes how trade shares and price indices react to structural shocks.

---

🚀 Getting Started

Prerequisites

Ensure you have Python installed. It is recommended to use a virtual environment.

Installation

1. Clone the repository:

   git clone https://github.com/YOUR_USERNAME/simple-armington-gamspy.git
   cd simple-armington-gamspy

2. Install dependencies:

   pip install -r requirements.txt

   Note: The gamspy package includes a community license that allows solving small-sized models (like this one) for free without a separate GAMS license.

Running the Model

Open the Jupyter Notebook:

jupyter notebook "Prototype of Trade model.ipynb"