Monte Carlo Simulation for Econometricians presents the fundamentals of Monte Carlo
simulation (MCS), pointing to opportunities not often utilized in current practice, especially with
regards to designing their general setup, controlling their accuracy, recognizing their
shortcomings, and presenting their results in a coherent way. The author explores the properties
of classic econometric inference techniques by simulation.

The first three chapters focus on the basic tools of MCS. After treating the basic tools of MCS,
Chapter 4 examines the crucial elements of analyzing the properties of asymptotic test
procedures by MCS. Chapter 5 examines more general aspects of MCS, such as its history,
possibilities to increase its efficiency and effectiveness, and whether synthetic random
exogenous variables should be kept fixed over all the experiments or be treated as genuinely
random and thus redrawn every replication. The simulation techniques discussed in the first
five chapters are often addressed as naive or classic Monte Carlo methods. However, simulation
can also be used not just for assessing the qualities of inference techniques, but also directly for
obtaining inference in practice from empirical data. Various advanced inference techniques have
been developed which incorporate simulation techniques. An early example of this is Monte
Carlo testing, which corresponds to the parametric bootstrap technique. Chapter 6 highlights
such techniques and presents a few examples of (semi-)parametric bootstrap techniques. This
chapter also demonstrates that the bootstrap is not an alternative to MCS but just another
practical inference technique, which uses simulation to produce econometric inference.

Each chapter includes exercises allowing the reader to immerse in performing and interpreting
MCS studies. The material has been used extensively in courses for undergraduate and graduate
students. The various chapters contain illustrations which throw light on what uses can be made
from MCS to discover the finite sample properties of a broad range of alternative econometric
methods with a focus on the rather basic models and techniques.