Gary Fromm

The Brookings Model Volume: A Review Article: A Comment

Z VI GRILICHES has written an interesting and provocative article on the first volume on the Brookings model. He does not report on later materials (cf. his footnote 2) that are pertinent to reviewing this continuing research project.1 In some places his own preconceptions and specializations caused some loss of perspective. In a few places too, he obtains seemingly contradictory or implausible results by making extreme assumptions about coefficients or by extrapolating to distant time points, inappropriate for testing a system designed for short-run business cycle analysis. This comment is designed to assure the reader a balanced view. At a general level, Griliches does not indicate the progress in model building associated with the Brookings project. It should be recalled that most of the prior models were small (on the order of 30 equations), had a limited degree of disaggregation of expenditure components and virtually no industry detail, lacked a financial sector, and did not explicitly include government policy parameters.2 The Brookings model has several noteworthy features which advance the state of the art of model building, solution, and simulation. 1. Scale: The model is substantially larger than its predecessors. Estimates of single equations do not necessarily give reasonable complete system results. We have solved a 200 equation condensed version of the model and obtained sensible cyclical and growth path predictions. Future large scale models may give better predictive results; but, at least we have shown that it is feasible to work with systems of several hundred equations. 2. Government Policy Parameters: Rather than simply dealing with variables such as tax yields and required reserves, the model treats the many instruments of government policy action explicitly. That is, tax yields are not controlled by the government but only tax rates. This makes for a more realistic description of the actual structure of the economy; it also permits more sensible simulation of policy changes. 3. Sector and Industry Detail: There is more extensive treatment of several sectors such as housing, financial, agricultural and foreign trade. At the industry level, there are now eight production sectors and an expansion to thirty-three is in progress. For each of these sectors, there are price, wage, employment, hours, investment, and so forth, equations. Such extensive treatment in a macro model has not been attempted previously. 4. Monetary Influences: With the exception of T. C. Lius model, other formulations deemphasized the role of monetary factors.3 And, even in the Liu model, the monetary sector was quite limited. In the Brookings model, the full monetary sector comprises over thirty equations. 5. Input-output: This is the first attempt to integrate an input-output structure into a cyclical model. While input-output is only a limited approximation of the technical structure of the economy, it does permit the translation of GNP component demands into industry gross outputs and industry prices into GNP component prices. As has been shown elsewhere, within the same framework, it is possible to relax the input-output elasticity of substitution assumptions and apply more general CES production functions.4 Yet, an input-output type structure is still required because production from

Financial and Nonfinancial Data for Detailed U.S. Industries

IN THE THEORY UNDERLYING THE MODEL being constructed as part of the SRI/Yale financial flows project, it is posited that consumers and producers allocate their portfolios of assets, liabilities, and net worth in a manner that takes account of relative rates of return, wealth, income streams, prices, and other factors. One consequence of this theory is that expenditure, financial investment, and production decisions are interdependent. Accurate portrayal and estimation of the nature of these decisions require that sectors chosen for analysis be relatively homogeneous in behavioral responses. Otherwise aggregation of sectors could cloud empirical estimates of portfolio and other adjustment parameters as demand, supply, and financial conditions change. Working with detailed industries also permits analysis of sectoral wage, price, and output behavior. These goals have been met by combining detailed input-output sectors with similar technological and demand characteristics into forty-one stage-ofprocess (SOP) industries.l Achieving the goal of needed data availability and consistency is hindered by two difficulties. One is that quarterly balance sheets and income statements, for a full