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A simple model of particular socio-economic and technical environment proves useful in forecasting and planning. The specific application forecasts air traffic at King Abdulaziz International Airport (KAIA) in Jeddah, Saudi Arabia, through a number of explanatory variables.The purpose of the model is to explain and forecast the change in growth rates of passenger flow through the airport. The dynamics of passenger flow are linked to the dynamics of the oil-based economy of Saudi Arabia and the global economic and business environment.

This paper is concerned with some computational aspects of Fisher's simultaneous‐equation estimator in its modified version [15] and with the alternative of using this computational scheme as the first stage of the two‐stage instrumental variables (2 SIV) estimator [1, p. 11]. The main disadvantage of the above estimation process arises out of the repeated investigation of a given set of instruments to determine how significantly some of their combinations contribute to R̄2. A short‐cut procedure that eliminates this computational inconvenience is suggested in this paper. The new method treats the problem within the framework of operations research, i.e., by isolating the optimum combination through the shortest way possible. The resulting step‐wise algorithm leads to the optimum combination of the given instrumental variables in, at most, n steps, where n is the number of instruments. The results of the application of this procedure to the estimation of the Ontario Econometric Model [9] are discussed, tested and compared with other methods of estimation.

ABSTRACT. Several forecasting methods for a target (or response) variable Y is considered. Of these, even simple explanatory-variable-based forecast, let alone multiple explanatory-variable-based causal-chain forecasting models, should provide superior, to most "expert" judgment and various extrapolation-based, time series analyzing methods of Box-Jenkins type and other "black box" related forecasts.Steps in the development of the relevant theoretical apparatus for judging the quality of data base which, in turn, affects the qualities of individual forecasting methods are described in the text to prove the point.All the investigated forecasting methodologies have been tested for accuracy and compared with actual data for the forecast period. The data series chosen for the experiment is the annual series "Total International Passengers" at the Jeddah King Abdulaziz International Airport (KAIA) for the years 1975-1987 of which 1975-1981 is considered "historical" data and, based on this interval, forecasts were made for the years 1982 -1987. The Problem of Forecasting Socio-Economic PhenomenaA useful term in the understanding of how the process of forecasting relates to what we observe and how it serves, as a means of reporting these observations, is "data credibility" that has to do with our ability to measure and/or sometimes even quantify the socioeconomic data (Shackle, 1968, Morgenstern, 1963, and Alem and Karasek, 1989.

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