Growth in the Postbellum Economy: The Comparison of Two Sectors

One aspect of the postbellum economy that has interested scholars is agricultural productivity growth. Any outside observer (non-economist) interested in the labor component to the Civil War struggle (liberation of slaves-agricultural workers in the South) would concern themselves naturally with whether the War’s outcome resulted in an increase in agricultural productivity across the nation as a whole. Two sectors (number of agricultural workers versus number of non-agricultural workers) of the economy can be analyzed to aid in determining whether agricultural output had risen. The historiography of the topic must also include the efforts of economists as it is a question relevant to economic history.

Prior to 1966, the consensus amongst scholars was that agricultural productivity increased throughout the 19th Century steadily. Marvin Towne and Wayne Rasmussen (1960) published findings on gross farm product that corroborated this. However, Stanley Lebergott published data in 1966 that caused a debate concerning this and his figures suggested agricultural productivity growth was actually slower after the Civil War compared to before. Now it appeared postbellum productivity was not as previously thought and was surprisingly lower than before the War. Yet, Thomas Weiss in 1993 questioned the Lebergott data and was found to be accurate.

The method used to analyze agricultural output is simply the number of workers in the agricultural sector. This is designated by the United States Census Bureau, and these tables can be examined for the postbellum period. In this blog, the study’s purpose is to compare the increase or decrease of agricultural workers to nonagricultural workers and show that both sectors grew thus there was more productivity in both. The statistics show that in the postbellum period, agricultural output (measured by number of workers gainfully employed in that sector) grew. Concomitantly, other sectors (or industries) had an increase in the number of workers. This analysis is not meant to show findings that indicate the agricultural output of the nation was higher after the War than before as Weiss concluded. It is merely meant to compare two sectors of the postbellum economy to each other concerning growth.

The Census bureau changed the form used after 1910 to allocate the number of farm workers. These figures gleaned from that data can be applied to the data from earlier years that may not have included specific breakdowns on the census form of laborers who may have been farm workers. Statistical techniques can be used, such as logistic regression analysis, to determine to what degree certain characteristics may have affected the data after 1910. This can be applied to the postbellum period where the data is lacking, and it sheds insight on the gaps of knowledge that affect the data (how many “laborers” on the old census form were farm workers).

According to Freedman, in Statistical Models and Shoe Leather, regression modeling can be suspect. He does not believe regression can provide answers in a causal argument. In this journal article, he believed, correlation is not the same as causation. A proper kind of theory or empirical validation is necessary, or conclusions cannot be trusted using linear or multilinear models of regression when applying these statistical tools to a causal argument. This study in this blog, is not engaging in speculation of causation. It is merely trying to compare two sectors of the postbellum economy concerning the growth of those sectors using data of numbers of workers.

According to Weiss in 1880 there were 8,302,000 agricultural workers and then in 1900 there were 10,496,000. In nonagricultural work, according to the same researcher, there were 9,088,000 workers in 1880 and 18,574,000 in 1900. These figures clearly indicate that in the last two decades of the 19th Century there was growth in both sectors of the economy.

Alfred Chandler wrote “Organizational Capabilities and the Economic History of the Industrial Enterprise,” which appeared in the Journal of Economic Perspectives (1992). He suggests the modern business entity first appeared in the 1880s. This was an era he describes as the Second Industrial Revolution. Modern transportation and communication networks (railroads, telegraph, steamships, cable systems) revolutionized deliveries of goods and services. Examining the labor statistics for this study we notice the significant growth in both sectors of the economy that were compared (agricultural and nonagricultural). Applying Chandler’s depiction of that highly significant time period economically, it gives a good backdrop to envision how the growth rates measured by the numbers of workers looked the way they did.

Comparisons in economic history can be done using statistical data in a variety of ways. Data can be less reliable the further back researchers go in history due to unreliable archival results. New methods of compiling data surface as we see here when Weiss’ results contradicted Lebergott’s and the two researchers had different opinions on agricultural growth before and after the U.S. Civil War. Comparisons of data can be a valuable tool that aids historians trying to write narratives about the past. This comparison study using the numbers of workers in two different sectors of the economy shows how the American economy grew in the postbellum period. One tentative conclusion that can be made is that many ex-slaves may have remained in agricultural roles, and they may have stayed in that sector if and when they migrated to the North after the struggle.