An application of transfer function and econometric procedures to employment impact analysis: Grant County, Oregon Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/k3569693x

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  • This study centered upon two objectives. First, to demonstrate and apply a statistical method, the transfer function, and to test its usefulness in regional economic modeling and regional impact ana1ysis; and second, to obtain a better understanding of the causal relationships among total employment, government employment, lumber and wood products manufacturing employment, and agriculture employment in Grant County, Oregon. The first objective is because of the deficiencies in using economic base, input-output, and regional econometric models in regional impact analysis. The second objective is because of the need for analyzing the direct and induced dynamic impacts of basic industry employment changes in Grant County. Transfer function models are based upon an interative approach to the identification of a statistical model that specifies a dynamic relationship between two or more interrelated time series. In this study, one-input and two-input transfer function models, that specify dynamic relationships among total employment, government employment and lumber and wood products manufacturing employment, are developed. In order to comparatively evaluate the results from the transfer function models, univariate ARIMA and econometric models also are specified and presented for the same employment series. Six types of goodness-of-fit measures are used to examine the forecasting performances of the ARIMA, transfer function, and econometric models. The empirical results suggest considerable confidence in the accuracy of the ARIMA, one-input transfer function, and econometric models. Various hypothetical changes of basic employment in Grant County are simulated in order to estimate the employment multiplier effects for the basic industries. The static and dynamic employment multipliers of three basic industries from the econometric models are also presented and interpreted. The agriculture sector is found to have a higher employment multiplier than the government and lumber and wood products manufacturing sectors. The transfer function models are found to be quite appealing if one is primarily interested in forecasting. However, if the researcher wants to analyze the nature of regional impacts or to explain the "complicated" behavior of an economic system, the input-output model and the regional econometric models appear to be more attractive tools to employ.
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