Factors Influencing Appalachia's Changing Industrial Structure

• Published in: Japanese Journal of Human Geography Vol. 51; no. 4; pp. 410 - 423
• Main Author: KATO, Kazusei
• Format: Journal Article
• Language: English; Japanese
• Published: The Human Geographical Society of Japan 1999
• Subjects: Appalachia; changing industrial structure; low wages; manufacturing; United States
• ISSN: 0018-7216; 1883-4086
• DOI: 10.4200/jjhg1948.51.410

This paper analyzes the changing industrial structure of Appalachia. The analysis is based on time-series data on income, earnings, and employment from the Regional Economic Information System (REIS), plus wages data from the census. First, two Gini coefficients were calculated: one is the Gini coefficient of personal income and the other is the Gini coefficient of net earnings (GNE, income without dividends, interest and rent, and transfer payments). This was done in order to observe the income distribution at the county level in Appalachia. Both were on a downward slope in the 1970s and on an upward slope after the mid-1980s. The difference between them changed markedly after the mid-1980s due to the growth rate in net earnings per capita in nonmetropolitan areas (GRE), which is highly correlated with GNE. Second, the years 1969-96 were divided into two periods, 1969-1985 and 1986-1996, because there was structural change between the Gini coefficients and GRE in 1985. Linear multiple regression models were employed, where the average annual growth rate of private earnings is a dependent variable and the average annual growth rates of industrial employments (AGRE) are independent variables in the subregions (Northern, Central and Southern Appalachia). This estimate showed (1) that AGRE in services, including finance, insurance, and real estate, is significant in all subregions except for Central Appalachia after 1986; (2) that AGRE in manufacturing in 1969-1985 is significant in all subregions, but insignificant for Central Appalachia and the Northern nonmetropolitan areas after 1986; (3) that AGRE in mining is still significant, but AGRE in services is most significant in Northern nonmetropolitan areas after 1986; (4) that AGRE in manufacturing and services is significant in the Southern nonmetropolitan areas after 1986; (5) and that AGRE in wholesale trades is significant in Central Appalachia after 1986. Third, employment in manufacturing has increased in nonmetropolitan Appalachia though it has decreased in the United States overall during the periods 1969-1985 and 1986-1996. Added value per establishment in manufacturing in Appalachia is in excess of the national average because of the employment of many low-wage workers. Consequently, income disparities in Appalachia have increased. Fourth, the only location factor that affects AGRE in manufacturing is the average hourly wage rate. Low wages mean a high growth rate in employment in 1969-1985. Northern Appalachia has lost jobs due to a high hourly wage. Conversely, Southern Appalachia has more jobs in 1969-1985. Though Southern Appalachia has experienced the fastest jobs and earnings growth, nonmetropolitan areas in the region still depend on low productivity manufacturing industries. Central nonmetropolitan areas, particularly Eastern Kentucky, have experienced more than a two percent annual growth in employment, but they have not increased earnings effectively. Using a regression model, the significance of the low wages was minimal after 1986.