Valtice Center for Economic and Statistical Research

Research, models, systems, and games

VCESR builds models, simulations, and games for classrooms, studios, and policy teams.

Illustrative values, not live economic data.

From research to real use

For policy teams. For studios. For classrooms.

Selected work

Built to be explored.

All projects

01 / Economic game

Boom and Bust

The minister’s chair: spend, tax, and answer for the results. Serious macroeconomics, made playable.

Visit Minister's Dilemma
Hermetic Engine

02 / Simulation engine

Hermetic Engine

The shared engine behind our games and models. Scenarios, incentives, and balance, kept consistent.

Inside the engine

03 / Education & research

CNB Game & Modelling Toolkit

A Czech monetary-policy simulator and modelling tools in Python, R, and Excel.

Explore the tools

The practice

Rigorous thinking.
Useful outcomes.

Six fields of work, connected by one standard of evidence.

Consultancy

Straight answers to hard questions, with the workings shown.

Econometric modelling

Forecasts and estimates that stand up to scrutiny, assumptions included.

Game economy design

Currencies, incentives, and progression that stay balanced.

Game development

Playable simulations of systems that are hard to explain.

Education systems

Courses and platforms that teach how economies actually work.

Economic theory education

Theory tied to evidence, taught for retention.

A series, up close

The line, up close.

Illustrative scenario: recovery follows the initial fall, while the dashed counterfactual stays low. Shaded bands show forecast uncertainty.

% 0 1 2 3 4 5 6 '19 '20 '21 '22 '23 '24
Separate illustrative index example; not the rate chart data.
ChapterIndexNote
Shock62Sharp fall in output
Policy response71Stabilisation begins
Recovery104Trend growth resumes
Counterfactual78No recovery without response

Evidence, visualised

Statistics, made visible.

Our point of view

A good model
should be
understood.

About the practice
  1. Start with the question.

    The decision comes first. The method follows.

  2. Show the uncertainty.

    Make assumptions, evidence, and the limits of inference visible.

  3. Make it usable.

    Build for the person working with the result: a policymaker, a player, or a student.

The people behind the work

Two disciplines.
A shared standard.

Economic reasoning and statistical inference, working together.

Meet the team

Let’s make it useful

What are you
trying to understand?

Start a conversation