An Input-Output Econometric Model

model of the type used to forecast the effects on an industry of changes in the national economy is described. The components representing input data and the type of output from such a model are discussed. This paper is intended as a tutorial discussion of an advanced application in data processing. Input-output models are used to forecast various effects that can occur to an industry as it interacts with other industries under changing conditions in the general economy. The conceptual framework for such models was established many years ago by such economic theoreticians as Quesnay (1758) and Leon Walras (1877) and, more recently, Leontief. As is readily apparent , these interindustry interactions are not only complex but numerous. Therefore, the practical use of these concepts has largely awaited the advent of the computer. In this paper, an input-output model developed for IBM is described to show what parameters are used in such models and what type of results are expected. The purpose of the IBM input-output (1l0) model is to forecast the industrial implications of changes in the overall national economy. Given forecasts of such broad components of the Gross National Product (GNP) as personal consumption expenditures , investment, exports, imports, etc., the I/O model makes predictions of output originating in different industries. The G N P components are forecast by an Annual Macro Eco-nometric Model developed by IBM'S Economic Research Department .' The Annual Model consists of a set of simultaneous equations which represent the interrelationships among different aggregate (macro) economic variables. From a set of assumptions about policy variables such as government expenditures, personal income tax rates, treasury bill rates, etc., the system of equations can be solved for such economic aggregates as GNP, personal consumption expenditures, investment expenditures, imports, etc. The Annual Model is thus suitable for forecasting SARMA IBM SYST J