Real Business Cycle Theory: A Semiparametric Approach

1.1 Introduction

Two of the hallmarks of both macroeconomics and ¯nance are the concern
with time and with uncertainty. In the ¯rst half of this book, the focus is on
time.
The key to much of economics is an understanding of choices made with
an eye to the future. The consequences of such choices unfold over time,
but it is the view of the future at the time of decision that governs such
choices. Throughout the ¯rst half of this book, we will make the certainty-
equivalence approximation of looking at the decisions agents would make if
all uncertainty vanished and they were certain to face the expected values of
future variables. Using the certainty-equivalence approximation, one proceeds
as if all the agents in a model had perfect foresight.1 As we proceed to study
\perfect-foresight" models, it is important to keep sight of their purpose of
providing a certainty-equivalence approximation to stochastic models.
1In the second half of the book, we will see how far optimal decisions under uncertainty
depart from the certainty equivalence approximation. One simple generalization is that when
only aggregate, economy-wide uncertainty is at issue, the certainty-equivalence approxima-
tion is typically quite a good approximation. The certainty-equivalence approximation is
often not a very good approximation when the idiosyncratic risk faced by heterogeneous
households and ¯rms is at issue. (The law of averages helps to make aggregate uncertainties
much smaller as a percentage of mean values than the risks faced by individual households
and ¯rms.) In any case, the certainty-equivalence approximation is the foundation on which
higher-order approximations will be built.