Abstract
There are two basic ingredients to an economic impact analysis: an estimate of the exogenous or differential stimulus that serves as the direct impact, and a model of the regional economy that will produce estimates of the indirect effects.1 Perhaps due to increased demand for economic impact statements by various levels of government there has been a fairly dramatic increase in modeling efforts in recent years. Methodological innovations resulting from these research efforts have produced an almost infinite variety of models that resist categorization. Economic base multipliers are estimated with econometric techniques,2 input-output models are treated as econometric models,3 and hybrid models are constructed that may combine elements of economic base, econometric, and input-output models.4 There are aggregate and disaggregate models of all types so that even the level of aggregation cannot serve as an alternative classifying variable.5
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Notes
See, for example, Hildebrand and Mace (1950), Mathur and Rosen (1974), and Park (1970).
S. Gerking (1976).
Treyz, Friedlander, and Stevens (1978), Chalmers (1978).
See D. Garnick (1969) and Tiebout (1962) for examples of disaggregated economic base models, Bell (1967) and Glickman (1971) for examples of aggregated econometric models.
The economic base model has a considerable history starting with Robert Haig (1926). For a rather complete bibliography of the early work on the economic base model, see Isard (1960), pp. 227–231.
See Charles M. Tiebout (1962) for a more detailed description of these models.
See Weiss and Gooding (1968) and Hildebrand and Mace (1950).
If firm A sells a product to firm B,the output price of firm B includes the price of firm A so that counting sales leads to the double counting of A values.
The description to follow uses employment as the unit of measurement. Any of the other variables mentioned previously could have been used with the same difficulties noted above.
See Pindyck and Rubinfeld (1976).
See for example, Henry Fishkind (1977) and Norman Glickman (1974).
The notation presented here is from Glickman (1977).
For the importance of error analysis, see Fishkind (1977).
Autocorrelation occurs when the error terms in a regression equation are not independent over time. If a large error in year t — 1 influences the size of the error in year t, then biased estimates of sample variances will result.
When multicollinearity is present it is difficult to separate the independent influence of the explanatory variables in determining the variable of interest.
For a complete description of the sampling problem, see Gerking and Fleeter (1978).
In fact, if all firms in A had identical production functions, we would only need to sample one firm.
See R. Billings (1969).
For some comparisons, see R. Webster et al. (1976).
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© 1980 Martinus Nijhoff Publishing, Boston
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Pleeter, S. (1980). Methodologies of Economic Impact Analysis: An Overview. In: Pleeter, S. (eds) Economic Impact Analysis: Methodology and Applications. Studies in Applied Regional Science, vol 19. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-7405-3_2
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DOI: https://doi.org/10.1007/978-94-011-7405-3_2
Publisher Name: Springer, Dordrecht
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