EasyEcon

Economics made easy — interactive models that accelerate your learning.

EasyEcon spans macroeconomics, microeconomics, and econometrics. Fast native TypeScript/SVG diagrams provide indexable front doors, while Python/Marimo notebooks retain equation-heavy depth inside an editorial Astro shell.

Browse models How it works

Interactive models published as static web apps.

Core tracks now span theory, policy, and empirical identification.

Advanced additions now extend the library beyond the original growth and price-theory core.

Model library

Browse the growing library by category.

View all models

Growth, business cycles, and open economy

Macroeconomics

From Solow and Ramsey to business-cycle dynamics, overlapping generations, endogenous growth, and open-economy adjustment.

10 published models

Price theory to strategic interaction

Microeconomics

From partial-equilibrium price theory into consumer choice, firm behaviour, and game theory.

11 published models

Regression, identification, and simulated evidence

Econometrics

Regression and causal identification through deterministic simulations, native diagrams, and full notebooks.

6 published models

Two complementary lanes

Fast native diagrams up front, full notebooks when the model needs depth.

Closed-form and high-traffic models lead with server-rendered TypeScript/SVG diagrams that load immediately and remain readable by search engines. Hybrid pages keep the full Marimo notebook available when learners want more equations, controls, or computational detail.

The econometrics track now moves from simple OLS through omitted-variable bias, difference-in-differences, regression discontinuity, and instrumental variables. Its deterministic simulations keep the data-generating process visible and teachable.

Econometrics models

Explore regression and causal-inference models.

Econometrics Regression Intermediate EasyEcon / Marimo

Upper-undergraduate econometrics

Simple OLS Regression

Adjust the true intercept, slope, noise, and sample size to relate realised estimates to fit, slope estimation error, and an approximate 95% slope interval.

Fitted line, residuals, precision, and known truth Open model

Econometrics Causal inference Advanced EasyEcon / Marimo

Upper-undergraduate econometrics

Omitted Variable Bias

Change confounding strength and the omitted variable's effect to compare the true coefficient, the naive regression, and the fully controlled benchmark.

Bias direction, confounding strength, and benchmark truth Open model

Econometrics Panel data Advanced EasyEcon / Marimo

Upper-undergraduate econometrics

Difference-in-Differences

Adjust treatment effects, group gaps, noise, and trend violations to see exactly when the DiD estimate matches the truth and when it drifts.

Parallel trends, group means, and treatment-effect decomposition Open model

Econometrics Causal inference Advanced EasyEcon / Marimo

Upper-undergraduate econometrics

Instrumental Variables

See when IV improves on OLS, when weak instruments make the estimate unstable, and how exclusion violations undermine the design.

Endogeneity, relevance, exclusion, and weak instruments Open model

Econometrics Causal inference Intermediate Native JS

Intermediate causal inference

Regression Discontinuity and the Cutoff Jump

See how a discontinuity identifies a causal effect: fit a line each side of the cutoff and read the vertical jump between them, then watch the bandwidth trade bias against noise.

The cutoff, the local-linear fits, and the jump that estimates the treatment effect Open model

Econometrics Time series Intermediate Native JS

Intermediate econometrics

The AR(1) Process: Persistence, Mean Reversion, and the Unit Root

Drag the persistence parameter through one and watch a stationary, mean-reverting series become a random walk and then explosive — while the sample ACF tracks the theoretical geometric decay φᵏ.

The simulated path, the ACF, and the phase change at φ = 1 Open model