Effect of Financialization on Income Inequality in United States: 1975-2010
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This research scrutinizes the relationship between financialization and income inequality in United States. The latest period of financialization which started after 1973 crisis is going to be examined in this research. The level of contribution from financialization to income inequality tried to be explained by an econometric model. The metrics used for this research are GDP share of financial industry, GDP share of stocks traded and GDP share of domestic credits provided for financialization; income share percentage of lowest and highest twenty percent and gini index for income inequality. Both financialization and income inequality will be examined separately and econometric model will be created with the metrics from that examination. The metrics going to be used for the econometric model is gini index for income inequalization as dependent variable, GDP share of stocks traded and GDP share of domestic credits provided for financialization as independent variable. The econometric model is valid and it can be said that financialization contributes on the increase of income inequality from the work in this research.
Keywords: Financialization, Income Inequality, Income Distribution, United States.
This research scrutinizes the relationship between financialization and income inequality in United States. United States picked for this research because of the fact that United States has the largest economy and financial firms in the world. The metrics for financialization are going to be GDP share of US Financial Industry, domestic credit provided by financial sector in United States (% of GDP) and total value of traded stocks (% of GDP). Metrics for income inequality are going to be Gini Index and income shares by quantiles in United States. Python (Programming Language) is going to be used for data visualization and Gretl (Statistical Software) is going to be used for the econometric model analysis in this research. The data source for this research is going to be World Bank Open Data Platform. This research focuses on the years between 1975 and 2010 which is defined as the fourth period of financialization by Fasianos, Apostolos & Guevara, Diego & Pierros, Christos (2016:2). They identify phases of financialization: 1900s to 1933 (early financialization); 1933 to 1940 (transitory phase); 1945 to 1973 (definancialization); 1970s to 2010 (complex financialization).
The 1973 crisis, also known as the 1973 oil crisis or the Arab oil embargo, was a global economic crisis caused by countries' decisions to ban oil exports. As Akins (1973) stated, Arabia produces oil for countries that helped Israel during the Yom Kippur War. The embargo has led to a significant increase in oil prices, negatively impacting the global economy, as many countries rely heavily on oil imports. The crisis had a number of economic and political consequences, including stagnant inflation (a combination of high inflation and poor economic growth) in many countries, the collapse of fixed exchange rates, and the collapse of fixed exchange rates. and the erosion of the dominant position of the United States as the dominant economy. power. Strong and political power. It also leads to a change in the balance of power between oil producing countries and oil consuming countries, in which the former has a greater influence over the latter. Overall, the 1973 crisis had a significant impact on the global economy and geopolitical landscape, and it continues to be studied and analyzed by economists and policymakers today. After the 1973 crisis, the phase of complex financialization began, which will be the phase of financialization that will be studied in this study. The complex financialization stage differs from the others in several ways. During the complex financialization phase, there are weak inflation targets, high household debt, and predominance of the financial sector. In addition, this final stage includes an increase in the value of internal income inequality.
The statement accepted as the best description for the financialization is the one from Epstein (2005:1), which is “the increasing importance of financial markets, financial motives, financial institutions, and financial elites in the operation of the economy and its governing institutions, both at the national and international level.”. This definition is the general accepted explanation for financialization. There will be three financialization figures in the following pages; GDP share of US Financial Industry, stocks traded value (% of GDP) and domestic credit provided by financial sector (% of GDP). GDP share of US Financial Industry is showed in the following figure by. In the preparation process of this figure addition of wages and profits of US financial sector as a share of GDP taken for the years between 1900-2012 by Philippon.
The figure of GDP share of US financial industry starts around twenty percent of GDP in year 1860 and it starts with a decrease. After that GDP share of US financial industry constantly increased for the time period where World War II starts. It can be seen clearly in the figure, the only phase that GDP share of US financial industry declined is the phase of before and during World War II. Before and after that phase, GDP share of the US financial industry at like all times increased. After World War II it started to increase from the value around 30% of GDP and in the period between 1945 and 1973 which is also named as definancialization GDP share of United States financial industry increased to the value around fifty percent of GDP which means there were an increase about twenty percent of GDP. After that it can be seen that increasing speed of the financial industry rised up after 1970s which is the period that this research will focus on. In that period the increasing speed of the percentage of GDP share of US financial industry increased. In complex financialization period, GDP share of US financial industry increased from around fourty percent of the GDP to eighty percent of the GDP. In the complex financialization period GDP share of US financial industry increased two times more than the definancialization period. Following figure shows the traded stocks value in terms of percentage of GDP in United States.
The figure shows that stocks traded ratio over the GDP in years between 1975 and 2010 increases with the years, especially after 1995. After 1995 the percentage increases to more than one hundred percent which shows the traded stocks has more value than the GDP in United States. The graph starts around ten percent level in year 1975 and constantly increases to the years between 1985 and 1990. After a decline, there were a huge increase speed increase after 1995 which can be explained by the The Financial Services Modernization Act of 1999, which means the deregulation of the Financial Industry in United States. Stocks traded (% of GDP) almost doubled the GDP in the year 2000 and after a decline it kept increasing unless the year 2009. The reason this feature is selected for this research is show the attention to the financial assets in United States in our complex financialization period. Following figure shows the domestic credit provided by financial sector in terms of percentage of GDP in United States.
The figure shows that domestic credit provided from financial sector ratio over the GDP in years between 1975 and 2010 increases with the years, especially after 1995. It can be seen clearly that credits provided doubled in terms of percentage of GDP in the year 1998. Domestic credit provided by financial sector (% of GDP) value started around one hundred twenty percent in the year 1975 and it is constantly increased. We can say credits and banks role increased in the domestic production from this information. After 1995 domestic credit provided by financial sector were more than two times of GDP which can also be explained with The Financial Services Modernization Act of 1999. From these three data we can say that impact of financial assets and financial sector resources increased in complex financialization phase.
By the GDP share of US financial industry it can be clearly seen that the portion of financial industry increased in serious amount which we also refer that as financialization. By the stocks traded ratio over the GDP it can be clearly seen that the interest for the financial assets increased in serious amount which means there were an increase in the financial investment. By the domestic credit provided by financial sector ratio over the GDP it can be clearly seen that the credits which financial sector provides has increased importance over time. These three different data figures intersect in a field, that is the financialization.
One of the main reasons why the figures starts to increase rapidly after 1995 is the The Financial Services Modernization Act of 1999 for Akhigbe and Whyte (2001). The Financial Services Modernization Act of 1999, also known as the Gramm Leach Bliley Act, is a United States federal law that has dramatically changed the regulation of financial services companies. The Gramm Leach Bliley Act was enacted in response to the changing landscape of the financial services industry, which is becoming increasingly integrated and interconnected. The law removed many of the regulatory barriers that had previously separated different types of financial institutions, such as banks, insurance companies and securities companies. The Gramm Leach Bliley Act allows financial institutions to enter new areas of business, such as insurance and securities, and allows the creation of financial holding companies that can hold both banking and non-banking subsidiaries. The act also established new regulatory agencies, including the Office of the Comptroller of the Currency and the Office of Thrift Supervision, to regulate certain types of financial institutions. One of the main goals of the GLBA is to increase competition in the financial services industry by enabling companies to offer a wider range of products and services to consumers. However, the Gramm Leach Bliley Act also includes provisions to protect consumer privacy, such as requiring financial institutions to tell customers about their information-sharing practices. and get your consent before sharing certain types of personal information with third parties. Overall, the Financial Services Modernization Act of 1999 has had a significant impact on the financial services industry in the United States, enabling the establishment of more diversified and integrated financial businesses, and enhancing competition in the market. The law also emerged as one of the main reasons for the 2008 crisis as it allowed banks to engage in hedge fund trading with derivatives. Banks then require more collateral to support selling these derivatives profitably.
By the end of the 20th century, banks in the United States were generally doing well with steady growth in profits and asset size. The US banking industry has undergone significant changes during this period, including the widespread adoption of new technologies and the consolidation of small banks into larger, regional, or national institutions. During the 1990s and early 2000s, the US banking industry experienced strong economic growth, low interest rates, and relatively stable financial markets. This environment has allowed banks to generate substantial profits through traditional lending practices and to expand into new business lines, such as wealth management and investment banking. Many banks have also pursued aggressive expansion strategies, including mergers and acquisitions, to expand their geographic reach and customer bases. However, the late 2000s saw the emergence of significant challenges for the US banking industry, including the 2008 global financial crisis and the subsequent recession. Many banks have suffered significant losses due to the collapse of the housing market and the slowing economy. As a result, many banks have had to raise capital through asset sales and public offerings, and some have received financial support from the government under the Troubled Asset Relief Program.
Also another point, why the figures starts to increase or decrease rapidly after 2008 is the 2008 crisis. The 2008 financial crisis, also known as the global financial crisis, was a major economic recession that originated in the United States and had far-reaching consequences around the world. It was triggered by the collapse of the US housing market and the subsequent failure of several major financial institutions. The crisis had a significant impact on the financial sector, as many financial institutions invested heavily in the real estate market and suffered significant losses when it collapsed. Many banks and other financial companies have had to be bailed out by governments around the world to prevent their collapse and further destabilize the financial system. The crisis also led to tighter regulations for the financial sector as governments sought to prevent similar crises from occurring in the future. Overall, the financial crisis of 2008 had a significant and lasting impact on the financial sector, leading to a rethink of the sector and a focus on greater stability and good risk management. than. better. It also has broader economic consequences, including high unemployment and slowing economic growth in many countries.
II. Income Inequality
Income inequality refers to the unequal distribution of income and wealth among individuals or households in a society. This happens when some people or households have a significantly higher income or wealth than others. Income inequality can have significant social consequences, as it can lead to social and economic imbalances and create barriers to mobility. Several factors can contribute to increasing income inequality in a society. Differences in education and employment opportunities; people with more education tend to earn more and have better job prospects than those with less education. This can lead to widening the income gap between those with the highest education and those with the least education. Changes in the labor market, a decline in some industries, or an increase in automation can lead to job losses and stagnant wages for some workers, while others could benefit from these changes. This can contribute to income inequality. Public, financial and social policies can increase or decrease income inequality, depending on their design and implementation. For example, progressive taxation, which levies higher taxes on high earners, can help reduce income inequality. Globalization, the globalization of trade, and the movement of capital and labor across borders can lead to income inequality within and between countries. Social attitudes towards wealth and success, norms and values in society can also play a role in income inequality. For example, if there is a strong belief in meritocracy, where individuals are rewarded based on their hard work and talent, this could contribute to income inequality. Overall, income inequality is a complex problem with many causes and requires a multi-pronged approach to address it. Income inequality can have significant social consequences, as it can lead to social and economic imbalances and create barriers to mobility.
In this research, if there is any, the contribution of financialization to the increase of the income inequality is discussed. Income inequality calculations started around 1915 and from that period to today it at like all times increased. However, income inequality increased rapidly between the period that we call as the complex financialization. One of the most common ways to measure income inequality is to compare the share of the top and bottom percentile groups in total income.The following figure shows the income share percentage held by the highest twenty percent in the years between 1990 and 2019.
The income share percentage held by the highest twenty percent data starts with fourty three percent level and increases to fourty seven percent level in years between 1990 and 2019. There is decreases on times like 2008 crisis but it can be said that the total percentage held by the highest twenty percent increases. From this figure it can be said that rich got richer in this period.The following figure shows the income share percentage held by the lowest twenty percent in the years between 1990 and 2019.
The income share percentage held by the lowest twenty percent data starts with five point six percent level and decreases to five percent level in years between 1990 and 2019. There was an decrease in 2008 crisis time for income share percentage held by the highest twenty percent and in that period we can see an increase for the income share percentage held by the lowest twenty percent in that period.
This increase of income share percentage held by the highest twenty percent and decrease of income share percentage held by the lowest twenty percent shows that income inequality increases in United States. Increasing income inequality can lead to a number of negative consequences. When income inequality is high, people may find it difficult to move up the income ladder and improve their socioeconomic status. This can lead to a lack of mobility and a feeling of being trapped in a particular social class. High levels of income inequality can also lead to an increase in the number of people living in poverty. This can have serious consequences for the health and quality of life of these individuals, as well as society as a whole. Income inequality can also prevent low-income people from accessing quality education and health care. This can prolong the cycle of poverty and prevent people from improving their socioeconomic status. In addition, high levels of income inequality are associated with increased crime and social unrest, as people can feel disenfranchised and disconnected from the rest of society. Finally, income inequality can lead to a lack of trust in governments and other institutions, as people may feel that the system is not working in their favor. This can lead to social and political unrest.
III. Econometric Model
In the econometric model, dependent variable is gini index and independent variables are gdp percentage of domestic credits provided by financial sector and gdp percentage of stocks straded value. Gini index as dependent variable represents income inequality. The Gini index is a metric of income inequality which shows if income distributed equally or not. A coefficient measures the variance of income or the distribution of wealth among members of a population. Gdp percentage of domestic credits provided by financial sector and gdp percentage of stocks straded value represents financialization in our model. Gini index takes values between zero percent and a hundred percent, zero represents perfect equality and 100 represents perfect inequality. Following figure shows how gini index changed in United States between 1975 and 2010.
From the figure it can be seen clearly that gini index at like all times increased and it moved from “more equal” to “less equal” in time. Gini index starts around thirty three percent and moves to fourty one percent in time. There is an increase in increasing speed after the year 1995. From this figure it can be said that gini index increased around eight percent in the years between 1975 and 2010. This increase means there is an increase in income inequality. We will try to predict the gini values with our financialization variables like gdp percentage of domestic credits provided by financial sector and gdp percentage of stocks straded value. OLS (Ordinary Least Squares) method is going to be used for the econometric model. In this econometric model, the values of gdp percentage of domestic credits provided by financial sector, gdp percentage of stocks straded value and gini index in years between 1975 and 2010 is going to be used. Following figure is the regression table of the econometric model which is taken by Gretl (Statistical Software) program:
From the regression table taken from the Gretl, it can be said that both of GDP ratio of stocks traded value and GDP ratio of domestic credit provided by financial sector is valid on defining the dependent variable gini index since they both got low p values. R-squared can be defined as “goodness of fit” and R-squared value from the Ordinary Least Squares estimation is 0.91 which means our model defines the dependent variable at the rate of 91%. F value from the model is 222.69 and F critical value for the given degrees of freedom values is 2.49 for the significance level of 90% which means our model is valid, this also can be interpreted from the p value of the model which is 6.91e-20. Since the Durbin-Watson value is closer to the 2 it can be interpreted as there is no autocorrelation. From this regression table it can be said that we have a valid model for defining gini index. The following figure shows the actual gini index values and the ones which are predicted by our model.
From the figure which shows the actual values of gini index and the regression line which is used on predictions, it can be said that prediction (regression line from the Ordinary Least Squares model) is accurate on explaining gini index. The line looks good on predicting the gini values. The intercept starts with around 33 level of gini index. It can be said that around the values of gini index 37 and 40 the econometric model performed better on predicting the gini index.
In this research relationship if there is any between income inequality and financialization examined. The years this research focus on is between 1975 and 2010, which is named as complex financialization by Fasianos, Apostolos & Guevara, Diego & Pierros, Christos (2016:2). From the data that examined and from the econometric model which is created with gini index, domestic credit provided by the financial sector and traded stocks data it can be said that financializaiton contributes on increase of the income inequality. Since income equality is a really broad concept that can be caused because of various factors it is impossible to say income inequality increases because of the financialization. The graphs which are created from the data of world bank open data platform also supports the findings of this research. Increasing income share percentage held by highest 20% and decreasing income share percentage held by lowest 20% shows there is an increase in income inequality which can also be represented with gini index which also increases from 1975 to 2010. The econometric model proves that both of GDP ratio of stocks traded value and GDP ratio of domestic credit provided by financial sector is valid on defining the dependent variable gini index for the time period between 1975 and 2010, which was the main focus of this research.
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