Add news post: Gorman aggregation lecture (December 2025) (#180)

* Add news post: Gorman aggregation lecture (December 2025)

* Update _posts/2025-12-28-gorman-aggregation-lecture.md

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

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Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

Author: mmcky

_posts/2025-12-28-gorman-aggregation-lecture.md

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+---
+layout: post
+title: "New Lecture: Gorman Aggregation with Heterogeneous Households"
+author: QuantEcon
+excerpt: A new lecture on Gorman aggregation has been added to the Advanced Quantitative Economics series, exploring conditions under which heterogeneous household economies can be represented by a single representative agent.
+---
+
+We're pleased to announce a new lecture on [Advanced Quantitative Economics with Python](https://python-advanced.quantecon.org/): **[Gorman Aggregation with Heterogeneous Households](https://python-advanced.quantecon.org/gorman_aggregation.html)**.
+
+## About the Lecture
+
+This lecture explores one of the fundamental questions in macroeconomic theory: under what conditions can an economy with diverse households be analyzed as if there were a single representative consumer?
+
+Key topics covered include:
+
+- **Gorman aggregation conditions**: When household demand can be aggregated regardless of income distribution
+- **Linear Engel curves**: The role of quasi-homothetic preferences in enabling aggregation
+- **Practical implications**: Understanding when representative agent models are appropriate approximations
+
+## Why This Matters
+
+Representative agent models are ubiquitous in macroeconomics, but their validity depends on specific conditions that aren't always met. This lecture provides the theoretical foundations for understanding:
+
+- When aggregation is justified
+- What heterogeneity matters for aggregate outcomes
+- How to think about distributional effects in macro models
+
+The lecture includes computational examples and exercises to reinforce the theoretical concepts.
+
+## Contributors
+
+This lecture was developed by Humphrey Yang and Thomas Sargent.