Probability Models for
Economic Decisions, Second Edition

A book by Roger B. Myerson and Eduardo Zambrano
MIT Press (2019).

This book uses Simtools.xlam, a free add-in for simulation and decision analysis in Microsoft Excel. You can download the add-in, together with detailed installation instructions at the following link:

Available here are the spreadsheets that appear as figures in each chapter of the book, as well as sample text from two chapters.
After you have installed the simtools.xlam add-in, you can make these xlsx spreadsheets work by using Edit-Links (in the Data tab, under 'connections') to change the source of all "simtools.xla" references to your local installed version of simtools.xlam (See Section 1.0 of Chapter 1 if you need more help with this).

  1. Introduction to probability models and simulation in spreadsheets. [draft text] [chapter1.xlsx] (Independence, conditional probabilities, basic techniques of simulation in spreadsheets.)
  2. Discrete random variables. [draft text] [chapter2.xlsx] (Expected value and standard deviation from probabilities, simulation from inverse cumulative, law of large numbers, 95% confidence intervals for expected values from sample data, the expected value criterion for optimal decisions, value at risk, expected shortfall, cumulative risk profiles.)
  3. Utility theory with constant risk tolerance. [chapter3.xlsx] (Utility functions, certainty equivalent, constant risk tolerance, limitations of expected utility theory.)
  4. Continuous random variables. [chapter4.xlsx] (Normal distribution, central limit theorem, Lognormal distribution for growth rates, the EXP and LN functions, fitting Generalized-lognormals for subjectively assessed quartiles, the time diversification fallacy.)
  5. Correlation and Multivariate Normal random variables. [chapter5.xlsx] (Covariance and correlation, using CORAND to simulate Multivariate Normals, linear combinations of random variables, portfolio analysis, political forecasting.)
  6. Conditional expectation. [chapter6.xlsx] (Expected posterior law, introduction to regression, prediction intervals.)
  7. Optimization of decision variables. [chapter7.xlsx] (Analysis of decision variables in simulation models, strategic value of information, use and limitations of Solver, newsvendor problems, revenue management, bidding problems, winner's curse.)
  8. Risk sharing and finance. [chapter8.xlsx] (Optimal risk sharing among investors with constant risk tolerances, moral-hazard incentive constraints, asset pricing with constant risk-tolerant investors, credit rationing.)
  9. Dynamic models of growth. [chapter9.xlsx] (Net present value, forecasting models, Brownian motion, introduction to real options, log-optimal investment strategies, some mathematics of gambling, risk aversion on growth rates.)
  10. Dynamic models of arrivals. [chapter10.xlsx] (Exponential arrival and queuing models, the transmission of information and disease, project length models.)
  11. Model risk. [chapter11.xlsx] (Implementation errors, interpretation errors, data errors, model specification errors, mitigating model risk, the precautionary principle.)

Preface and Table of Contents.

Listing at

Simtools.xlam is available with documentation at