The paper specifies a disequilibrium model for the aggregate
labor market consisting of demand and supply functions for labor,
an adjustment equation for wages as well as for prices, a
transactions equation and, finally, an equation that relates
measured unemployment to vacancies and to excess demand. The
model has a more sophisticated treatment of dynamics than earlier
disequilibrium models, and uses measured unemployment as an
endogenous variable. Two of the error terms are assumed to be
serially correlated and the coefficients are estimated by maximum
likelihood. The parameter estimates and the goodness—of—fit are
satisfactory and the model's implications for the behavior of
several important variables are sensible. Excess demand
estimates computed in various ways are reasonable. The model is
used to estimate the natural rate of unemployment as well as a
short run Phillips curve. Finally, the stability properties of
the model are analyzed by considering the eigenvalues of the
system; they are found to have moduli less than one.

The paper examines seven methods of numerical integration, including
both special purpose algorithms designed for the multivariate normal density
and general algorithms such as Gauss—Legendre and Newton—Cotes methods.
With the aid of some five functions, the accuracy of these methods and their
computational cost are compared in matched experiments on an IBM 370/3081
Model K and a 2-pipe CYBER 205. The effect of vectorised computation is
also examined.

A common feature to most aggregative studies of the labor market is a marginal productivity expression in which the quantity of labor appears on
the left hand side of the equation, and the right hand side includes the real
wage and output. A number of researchers have cautioned that if the output
variable is treated as exogenous, serious econometric difficulties may
result. However, the assumption that output is exogenous has not been
tested. In this paper, we estimate an equilibrium model of the labor market,
and use it to test the assumption of output exogeneity. We find that the
assumption that output is exogenous cannot be rejected by the data.