Manufacturing's Impact on Household Income and the Middle Class

The manufacturing industry provides a key foundational base for our nation’s economic health and stability. Each state, to one degree or another, relies on manufacturing to help sustain and promote economic growth and prosperity within their local businesses, labor force and general population.

In the past 13 years, the percentage of input from the manufacturing sector into a state’s economy has changed. The change, while undeniable, engendered fear surrounding the ability of future wage earners to achieve equal financial success in other industries. Indiana has sought to maintain a strong manufacturing base with the belief that manufacturing maintained workers’ salaries at a high level and promoted the well-being of the state’s middle class. This article examines this claim and analyzes the impact of manufacturing upon a state’s household income.

Methodology

A model was constructed examining data from 1997 through 2010 for each state. Household income data and state population statistics were obtained from the U.S. Census Bureau. The income data were converted based on a BLS measure of statewide cost of living to make them comparable across states. State gross domestic product (GDP) statistics were obtained from the Bureau of Economic Analysis (BEA). Included variables were overall state GDP growth (from the prior year) and state manufacturing GDP as a percent of total GDP. State binaries were included for regional and state specific influence, and a fixed effects model was employed to account for inflation and time variant influences. The model was run with lagged dependent variables to account for autoregressive tendencies. In the autoregressive models, some of the dependent variable influences were likely included in the autoregressive term, thus diminishing their impact in those models. Despite this, the results were statistically significant. View regression results.

Results

After accounting for cost of living, Indiana maintained no statistically significant bias in household income, implying that Indiana provides the same opportunity for an adjusted income equal to other states. The other results are summarized in Table 1.

Table 1: Regression Results

Notes: Level of statistical significance set at 15 percent. Incomes adjusted with a cost of living factor.
Source: Indiana Department of Workforce Development

GDP growth is a positive indicator of median household income. As the economy improves in the state, the salaries of its citizens improve. Population is shown to negatively influence median household income. While the magnitude of the effect is small, larger states are shown to have a negative impact on the income level of its citizens. As indicated by the lagged variables, the household income in one year is a positive indicator of income in future periods.

Finally, the percent of GDP derived from manufacturing is positively correlated with household income. While the relative magnitude is small, manufacturing (relative to other economic sectors) is shown to increase state incomes. For every 1 percentage point increase in manufacturing’s contribution to Indiana’s economy, yearly median household incomes increase by nearly $89.

This study is limited as it covers only a few years of data. Under such conditions, it would be premature to indicate a causal relationship. Further study and development of the model would benefit all researchers.

Timothy E. Zimmer, Ph.D.
Manager, Research and Analysis Division of the Indiana Department of Workforce Development

Debra A. Guzman
Economic Analyst, Indiana Department of Workforce Development