Journal Article Presentation:Shocks and Valuation in the Rental Housing Market

Alm, James and Follain, James “Shocks and Valuation in the Rental Housing Market,” Journal of Urban Economics, 36 (September 1994): 117-142.

Presented by Cynthia S. Blasses

November 25, 2002

Introduction and Objectives

• Theoretical paper exploring impact of major shocks in the rental housing market

• Develops a structural dynamic model of simultaneous equations– demand– supply– construction– asset price

A Perfect Foresight Model

• Formulation of expectations

• Equations link price with future expected rents

• Manipulating the equations-– Future values are eliminated using only current &

lagged values of rent & price

• Pt represents the present value of actual future path of rents

Model Equations

Rt = a0 + a1Kt + a2Yt (Demand)Parameters a0 , a2 > 0 , Parameter a1 < 0

Kt = (1-d)Kt-1+ Ct (Supply)

Ct = α(Pt - P*) (Construction)

ttt Rrd

rPrP

1)1( (Price)

The Solution

• To solve this system of linear simultaneous difference equations, Alm and Follain develop a second-order difference equation

E = Rt + D1Rt-1 + D2Rt-2

Where it is assumed that

Yt = Yt-1 = Yt-2 = YT

• Where the particular solution represents a steady state value for rent

• And the characteristic roots (b1, b2) determine the dynamic behavior of rent over time.

ttt bFbF

DD

ER )()(

)1( 221121

Adjustment Paths

• The adjustment path of rent depends on b1 & b2

• The path oscillates over timeD1>0, D2<0

• Convergence to steady-state requires b1 & b2 to be less than one in absolute value

• Speed of adjustment is affected by many factors– in general, the smaller the characteristic roots, the faster the market converges

to equilibrium

Concluding Recommendations• Additional structure

– Demand & construction equations derived from intertemporal utility and profit maximization

• Alternative expectations models should be explored– Specifically, a Rational Expectations Model

• Actual estimation of one or more of the equations presented– Econometric estimations of model parameters