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The Analysis of Two Linear Regression Models that Demonstrate the Relationship Between History and Modern Development Using the Transatlantic Slave Trade in West Africa

Sydney Taylor

INTRODUCTION

The development of a nation is determined by the strength of its social systems. Successful countries throughout the world have developed because of their strong political, economic and social systems. During the sixteenth century, British colonizers invaded West Africa in search of resources and economic opportunities. Millions of Africans were violently stolen from their homes and shipped across the Atlantic Ocean, towards the Americas. This was known as the transatlantic slave trade.

Colonizers and missionaries brought new ideologies and social practices. Europeans instituted schools, churches and plantations that greatly benefitted their economies. These institutions were created to influence the communities in West Africa, so people would adapt to a “westernized” way of life. The transatlantic slave trade earned millions of dollars for nations abroad because of the demand for slave labor and goods. As the world was benefitting from West Africa’s resources, the region struggled to protect itself from violence and systematic shifts in society. Nations including Nigeria, Ghana and Liberia are among the few countries in West Africa that have taken centuries to formulate strong social structures. Today, 64 million people can neither read nor write, making up nearly 40 percent of the total adult population in West Africa. These rates are the highest in the world, proving that historical events may have a strong influence on modern human development.

In order to understand the relationship between history and human development, this paper will focus on two different uses of a linear regression (OLS) model. This model evaluates numerous factors to determine a correlation between two separate scenarios. The first version mentioned in this paper is by Nonso Obikili. Obikili conducted a research study that analyzes the relationship between slavery and modern literacy rates in West Africa. In his regression model, he uses multiple factors including agriculture, population density and gender to describe a negative correlation between slavery and education. Edoardo Teso uses a different linear regression model to understand the Transatlantic slave trade and the Indian Ocean slave trade impact on gender roles within the West African workplace.

The broad central research question of this paper is “did the transatlantic slave trade have the power to impact modern human development in West Africa?” Both linear regression models will provide information about the importance of human development in West Africa.

INQUIRY TYPE

This research will use an explanatory inquiry, which focuses on the causes and effects within a problem or situation. In particular, this paper will focus on the influences the transatlantic slave trade has had on modern West Africa. Explaining history’s relationship with the current society can help researchers further understand human development. It is important to analyze this relationship because it can improve West Africa and other regions throughout the world that are still struggling to develop. How can we move development forward if developing countries are unable to move on from their pasts? Will West Africa ever be able to fully recover from the transatlantic slave trade and fully develop their complex social systems like education and labor?

Obikili and Teso use the same linear regression model with two separate purposes. Obikili focuses on the Transatlantic slave trade’s impact on education, while Teso focuses on its impact on gender roles. Both uses of data explain the aftermaths of the horrific and inhumane enslavement of African people, which has extended into modern society. Currently, the world has entered into the 2020, nearly two centuries after the slave trade was deemed illegal. The fact that West Africa still struggles today shows the impact of the slave trade. It is important to study and interpret the causes and effects of modern human development issues that may have been caused by the “tentacles” of enslavement throughout West Africa.

MODEL #1

The first geospatial model is Nonso Obikili’s explanation of slave intensity’s impact on modern literacy rates. His linear regression model calculates different factors that may have an influence on the relationship between literacy and slavery during the post-colonial era. These factors include employment in agriculture, Christian missionaries, historic distance from the coast, historic population density and malaria ecology index.

• Slave intensity = slave exports / earliest population of ethnic groups reported

Using the equation above, he found that areas with higher intensities of slavery had negative correlations with low education/literacy rates. This data can be found on Table 9 within his research.

The data above is divided into four separate groups. Obikili does this to prevent any western bias on literacy rates. Column 1 focuses on standard literacy; these refer to a person’s ability to read and write in English only. Column 2 uses extended rates which consists of Arabic, a dominant language spoken throughout Western Africa. Columns 3 and 4 use both standard and extended literacy rates. All groups show a negative correlation between slave intensity and literacy during the post-colonial era.

The table above also shows an R-squared calculation, the “statistical measure of how close the data are to the fitted regression line.” For groups 1 and 2, these numbers were nearly the same at 65% and 66%. This indicates that there is a high variability of the response data sets. This means that the model presented fits the data at about 65.5%. Although, columns 3 and 4 show a significantly low R-squared percentage. Both columns have a 17% ratio, so this model has a very low variability of the response data.

One of the most interesting and straight-forward graphs in his research focused on the correlation between intensity and each country within West Africa. In a scatterplot, Obikili found a strong negative correlation between slavery and modern literacy rates. Some regions with higher intensities, meaning they were significantly affected by the slave trade and colonization itself, had the lowest education rates throughout West Africa. This graph represents the impact that history has on modern development.

MODEL #2

The second geospatial model is the linear regression model used by Edoardo Teso. His research focuses on the impact the transatlantic slave trade has had on modern gender roles, specifically the work force throughout West Africa. His hypothesis focuses on “the demographic shock to sex ratios- and the accompanying shock to women’s participation in activities outside the domestic sphere – persistently affected cultural beliefs and norms about the appropriate role of women in society” (Teso 7). In addition to the transatlantic slave trade, Teso also collects data from the Indian Ocean trade. His analysis of both slave trades provides more insight on the impact of history on modern society.

In Table 2, Teso shows the results of his linear regression model and the effect of the slave trade on occupations. The data is divided into eight separate working groups: agriculture, high ranking, manual work, clerical, household/domestic and education. The purpose of this specific study was to determine the likelihood of a woman being hired in various workng fields in modern society. Interestingly, “the estimation suggested that the increase in a woman’s probability of being employed can be entirely rationalized by an increase in the likelihood that she has a relatively higher ranking occupation.” According to findings, he discovered that women in regions with higher impacts of the slave trade were more likely to have higher ranking jobs.

Throughout the slave trade, more men were shipped across the Atlantic Ocean and into the New World. As men were taken from their homes, women went into the labor force, replacing the men in many positions thorughout the economy. Teso explains this relationship to be extremely influential to modern society. Not only has the labor force been effected, attitudes towards gender roles have affected the current market significantly. The narrative of female workers shifted, they are now seen as more essential to the African economy than ever before.

DISCUSSION

Both methods have used a linear regression model to explain how history and modern development have a relationship. While both have contrasting results, both documents support that there must be a correlation. In Obikili’s document, he stresses the major impact the transatlantic slave trade had on education itself. But at the conclusion of his essay, he found no perfect explanation of why there is a negative relationship. Regions with high slave intensity have historically lower literacy rates, but these numbers may have been influenced more by cultural values in specific ethnic groups than by the trade itself. In contrast, Teso’s research explained a positive relationship between the transatlantic slave trade and job opportuntities for women. He found that the higher slave intensity within a particular region, the more job opportuntites were available for women in higher rankings. These contrasting conclusions suggest that there is a relationship between history and human development. It may differ according to social systems, educations versus occupations. It is important to understand that there is not always a perfect answer in data science. Although, learning about different studies with contrasting results gives an explanation of the impact that history has on education itself.

SOURCES

[1] Obikili, Nonso. “The Impact of the Slave Trade on Literacy in West Africa: Evidence from the Colonial Era.” Journal of African Economies, vol. 25, no. 1, 2016, pp. 1–27.

[2] Edoardo Teso, The Long-Term Effect of Demographic Shocks on the Evolution of Gender Roles: Evidence from the transatlantic Slave Trade, Journal of the European Economic Association, Volume 17, Issue 2, April 2019, Pages 497–534,

[3] Dakar. “Combating World’s Lowest Literacy Rates.” The New Humanitarian, 2 Dec. 2015, www.thenewhumanitarian.org/news/2009/04/22/combating-worlds-lowest-literacy-rates.