A Nationally‐linked Regional Econometric Model*

Crow, Robert Thomas

doi:10.1111/j.1467-9787.1973.tb00394.x

Cited by 34 publications

(9 citation statements)

References 12 publications

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“…p is a constant where a refers to the sector type. The relationships in ( 4 ) are similar in principle to the gravity or potential concepts of Stewart [20] and Zipf [22].3…”

Section: Construction Of the County Interaction Variablementioning

confidence: 94%

A Multiregional Econometric Forecasting System: A Model for the Delaware Valley*

Ballard

Glickman

1977

Journal of Regional Science

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“…p is a constant where a refers to the sector type. The relationships in ( 4 ) are similar in principle to the gravity or potential concepts of Stewart [20] and Zipf [22].3…”

Section: Construction Of the County Interaction Variablementioning

confidence: 94%

A Multiregional Econometric Forecasting System: A Model for the Delaware Valley*

Ballard

Glickman

1977

Journal of Regional Science

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“…Early regional econometric models, such as those by Bell (1967), Glickman (1971), and Crow (1973), used the simplest, most aggregate export-base approach to determine regional manufacturing activity. In these models, total regional manufacturing output [or in the case of Bell (1967), total export-oriented output] is related directly to national output (gross national product).…”

Section: Previous Studiesmentioning

confidence: 99%

A Supply‐side Model of Texas Manufacturing Growth

Plaut

1984

Journal of Regional Science

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INTRODUCTIONIn most regional econometric models, regional manufacturing activity as measured by output, income, or employment is driven largely by national activity through an explicit demand-side, export-base framework. Although a demandoriented model may be useful for forecasting short-term fluctuations in manufacturing activity in slow-growing, highly industrialized regions of the North and East, it is less suited for forecasting long-term manufacturing growth in fast-growing, relatively underindustrialized regions of the South and West. In order to forecast long-term manufacturing growth in fast-growing regions, a supply-side approach is needed, in which the growth in regional manufacturing capacity is explicitly modeled.This paper reports on an attempt to implement a supply-side model of regional manufacturing growth for the state of Texas. The theoretical structure of the model follows the approach suggested by Engle (1974) and Crow (1979). Manufacturing investment is explicitly modeled and the growth in manufacturing capacity is the major determinant of the long-term growth in Texas manufacturing man-hours and output. The model is estimated on annual data for 15 industries over the period 1958-1978. The Texas manufacturing model has been embedded into an overall economic-demographic forecasting model for the state-the Texas Economic-Demographic Forecasting Model (TEDFM). The major use of TEDFM is to produce consistent, long-term forecasts of Texas economic and population growth.The organization of the remainder of this paper is as follows. Section 2 outlines the history of modeling manufacturing activity in regional econometric models and documents the need for a supply-side approach. Section 3 details the theoretical structure of the Texas manufacturing model, and Section 4 presents the results of the estimation of the investment, man-hours, and output equations. Results of an in-sample simulation of the manufacturing submodel (as part of TEDFM) are given in Section 5, and Section 6 summarizes the major results of this study and discusses their implications for future work on modeling regional manufacturing activity.

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“…Indeed, the variability in total personal income at quarterly rates arises principally from farm income, as visually evidenced in Figure 1. The correlation 2Examples are the models of Bell [2], Crow [5] and Moody and Puffer [9]. Other models such as those of Adams, Brooking and Glickman [1], Glickman [7] and L'Esperance, Nestel and Fromme [8], contain specific equations relevant to estimating regional governmental revenues.…”

Section: Tax Revenue Forecasting Schemamentioning

confidence: 99%

State tax revenues-new methods of forecasting

Barnard

Dent

1979

Ann Reg Sci

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This paper presents an econometric schema for tax revenue forecasting for regions which are apparently insensitive to national business cycle phenomena.ARIMA methods and simulation procedures for forecasting exogenous income components are linked to standard regression tax forecasting equations for individual income, sales, and use taxes. The procedure is exemplified by the case for Iowa. Forecast accuracy suggests the worth of this approach.

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A Nationally‐linked Regional Econometric Model*

Cited by 34 publications

References 12 publications

A Multiregional Econometric Forecasting System: A Model for the Delaware Valley*

A Multiregional Econometric Forecasting System: A Model for the Delaware Valley*

A Supply‐side Model of Texas Manufacturing Growth

State tax revenues-new methods of forecasting

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