Journal of Real Estate Finance and Economics, 15: 3, 283±307 (1997)
# 1997 Kluwer Academic Publishers
Economic Risk Factors and Commercial Real
DAVID C. LING
Department of Finance, Insurance and Real Estate, Graduate School of Business Administration,
University of Florida, Gainesville, FL 32611-7160
A great deal of research has focused on the links between stock and bond market returns and macroeconomic
events such as ¯uctuations in interest rates, in¯ation rates, and industrial production. Although the comovements
of real estate and other asset prices suggests that these same systematic risk factors are likely to be priced in real
estate markets, no study has formally addressed this issue. This study identi®es the growth rate in real per capita
consumption, the real T-bill rate, the term structure of interest rates, and unexpected in¯ation as fundamental
drivers or ``state variables'' that systematically affect real estate returns. The ®nding of a consistently signi®cant
risk premium on consumption has important rami®cations for the vast literature that has examined the (risk-
adjusted) performance of real estate, for it suggests that prior ®ndings of signi®cant abnormal returns (either
positive or negative) that have ignored consumption are potentially biased by an omitted variables problem. The
results also have important implications for dynamic asset allocation strategies that involve the predictability of
real estate returns using economic data.
Key Words: real estate returns, asset pricing, economic risk factors, risk premiums, multibeta asset pricing
model, systematic risk
Theoretical and empirical work linking the macroeconomy to real estate returns is
extremely limited and focused primarily on the question of whether real estate returns are
``sensitive'' to various economic events or factors, especially unanticipated in¯ation.
These sensitivities are estimated by regressing ex post real estate returns on a prespeci®ed
set of explanatory variables (e.g., Gyourko and Linneman, 1988; Liu and Mei, 1992; and
Park, Mullineaux, and Chew, 1990). Sensitivity (or risk ``exposure'') is measured by each
variable's beta coef®cient.
Statistical signi®cance of a coef®cient in these ex post return regressions indicates
exposure, but it does not tell us whether a risk factor is ``priced'' ex ante (i.e., bears a
premium) or whether the factor's in¯uence changes over time. Financial theory suggests
that a factor will be priced ex ante only if the factor has a ``systematic'' in¯uence on asset
returns, in which case there is a marketwide price of risk measured in the form of an
increment to the expected return (a risk premium) per unit of beta.
This can be seen in the
CAPM (one factor) framework, which posits that an ex ante risk premium is paid to a
particular asset in proportion to the beta coef®cient (or ``loading'') on the market portfolio.
Empirically, considerable evidence indicates that state variables such as the slope of the