Master’s Programme in Economic History

American Dream Turns to Nightmare: The Decline of the United States Middle Class

By

Jacob Vogel

jacob.vogel.081@student.lu.se

Abstract: The United States middle class has become a major topic of discussion and debate over the past several years, playing an intricate part in economic and political policies today. The reasoning behind this is due to the acknowledgement of the average American household struggling to maintain their standard of living with rising costs of goods and services along with stagnating wages. Unemployment is still relatively high and the economy is continuing to struggle with recovery from the 2008 recession. Starting with the Golden Age for the middle-class households in 1960, the middle class is analyzed over time and ends with the 2010 census. Although the consensus is that the middle-class households are struggling today, the extent of this struggle is not universally agreed upon and open for new research. This paper attempts to expand the discussion on the topic of the United States middle class and what is occurring to the household within this class. Analysis will also be on households living below the poverty line and households in the top 1% of income earners. Based on real household income, cost of education, homeownership, and purchasing a new car will be compared against stagnating wages. Using micro level data, households will be created and variables transformed for an in-depth analysis using basic regressions and statistics in order to capture what is occurring to America’s middle class.

Key words: Middle Class, Top 1%, Education, Poverty, United States, Median Household Income, Inequality, Financial Crisis, Stagnation.

EKHM53Combined Master’s Thesis (30 credits ECTS)August 2017Supervisor: Kirk Scott & Siddartha AradhyaExaminer: Cornelis Jaco ZuijderduijnWord Count: 18,129

Acknowledgements

I would like to thank my family and girlfriend for supporting me throughout this entire process of completing this thesis and the study period here at Lund University. I would like to also thank Kirk Scott and Siddartha Aradhya for the support and guidance as my supervisors. This goal of mine would not have been achievable without their help and constant support.

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Table of Contents1 Introduction.........................................................................................................................4

2 Contributions......................................................................................................................7

3 Contextual Background & Previous Research....................................................................8

3.1 Outline of the United States Middle Class and How to Define it...............................8

3.2 Birth and Transformation of the United States Middle Class...................................11

3.3 Golden Age of the American Middle Class..............................................................12

3.4 The Declining American Economy and Middle Class.............................................15

3.5 Economic Revival and the Information and Computer Technology (ICT) Revolution.............................................................................................................................17

3.6 Beginning of the 21st Century and the 2008 Recession...........................................19

3.7 Current Middle Class Status.....................................................................................21

4 Theory...............................................................................................................................24

4.1 Household Income....................................................................................................24

4.2 Middle Class.............................................................................................................25

4.3 Stagnating Wages…………………………………………………………………..26

5 Data...................................................................................................................................27

5.1 Data Source, Use, and Transformations...................................................................27

5.2 Data Limitations........................................................................................................31

6 Methodology.....................................................................................................................34

6.1 Regression Models………………………………………………………....……….….35

6.2 À Priori Expectations………………………………………….………...………..……36

6.3 Model Tests………………………………………………………………....…….……39

7 Empirical Analysis............................................................................................................40

7.1 Costs Associated with the Middle Class…………………………………....…...……..40

7.2 Poverty, Middle-Class, and Top 1% Status………………………....…………………44 7.3 Regression Tables………………………………………………....…………………...47

8 Discussion & Conclusion..................................................................................................56

9 References.........................................................................................................................60

10 Appendix………………………………………………………………………………...65

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List of TablesTable 1. À Priori Expectations for Model 1 (1960-2010)………………………………..36Table 2. À Priori Expectations for Model 2 (1960-2010).…………………………….....37Table 3. À Priori Expectations for Model 3 (1960-2010)..................................................38Table 4. À Priori Expectations for Model 4 (1960-2010)..................................................38Table 5. Poverty Status (1960-2010)..................................................................................45Table 6. Middle-Class Status (1960-2010).........................................................................45Table 7. Top 1% Status.......................................................................................................46Table 8. Mean and Median Household Income (1960-2010).............................................46Table 9. Relationship Between Race, Age, and Household Income...................................49Table 10. Relationship Between Education Attainment & Household Income..................52Table 11. Relationship Between Gender & Household Income..........................................53Table 12. Relationship Between Education Attainment, Race, Gender, Age, and Household Income.................................................................................................................................54Table 13. Model 1 Test Results...........................................................................................70Table 14. Model 2 Test Results...........................................................................................70Table 15. Model 3 Test Results...........................................................................................70Table 16. Model 4 Test Results...........................................................................................71Table 17. Unadjusted Relationship Between Race, Age, and Household Income..............72Table 18. Unadjusted Relationship Between Education Attainment & Household Income73Table 19. Unadjusted Relationship Between Gender & Household Income.......................74Table 20. Unadjusted Relationship Between Education Attainment, Race, Gender, Age, and Household Income................................................................................................................75

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List of FiguresFigure 1: The Decoupling of Employee Compensation and Productivity (Bureau of Labor

Statistics, 2014).........................................................................................................................11

Figure 2: Distribution of the Labor Force by Sector, 1840-2010 (Minn. Post, 2012)..............14

Figure 3: Distribution of Output Among Sectors, 2010 (Minn. Post, 2012)............................15

Figure 4: Historic CPI Inflation Rates (Worldwide Inflation Data).........................................16

Figure 5: Shares of Adults Living in Middle-Income Households (Pew Research Center).....18

Figure 6: Median Household Income (U.S. Census Bureau)....................................................22

Figure 7: Average Cost of Tuition for All Universities (NCES) .............................................40

Figure 8: Average College Tuition Costs In-State (NCES)......................................................41

Figure 9: Average Price of a New Car (U.S. Department of Energy)......................................42

Figure 10: Median Sale Price of Houses Sold (U.S. Census Bureau)......................................43

Figure 11: Median Home Value (U.S. Census Bureau)...........................................................44

Figure 12: 1960 Real Household Income (IPUMS-USA)........................................................55

Figure 13: 1970 Real Household Income (IPUMS-USA)........................................................55

Figure 14: 1980 Real Household Income (IPUMS-USA)........................................................56

Figure 15: 1990 Real Household Income (IPUMS-USA)........................................................56

Figure 16: 2000 Real Household Income (IPUMS-USA)........................................................57

Figure 17: 2010 Real Household Income (IPUMS-USA)........................................................57

Figure 18: Coefficients of All Races and Income (IPUMS-USA)...........................................58

Figure 19: Coefficients of All Education Categories and Income (IPUMS-USA)...................58

Figure 20: Coefficients of Gender and Income (IPUMS-USA)...............................................59

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1. Introduction

Over the last several years the American middle class has gained interest as a topic of

discussion and has become the focal point in United States political and economic debates

today. The reason behind this is that this class is seen as the fundamental aspect to the United

States’ economy and drives the consumer market and without it, would impact the economy

and society as a whole. Following the ending of World War II in the 1940s and soldiers

returning home, the United States population gained access to education and loans that have

never been seen before in U.S. history. The passing of the G.I. Bill, in which G.I.s. refers to

returning war veterans, allowed for this access and the American middle class was born. The

idea of the middle class is an abstract one and is difficult to agree on a universal way to define

it. Whether it is an ideology or a concrete idea based on income, it is controversial and is

constantly being debated on how to define what the middle class is and which is the best

approach to answer the question of how to define it.

Regardless of the definition, the middle class in the United States was thriving from the 1950s

through the beginning of the 1970s and the U.S. economy was growing just as fast. This

period was known as the Golden Age for the middle class and wages were being equally

compensated for the productivity in the labor market. The average American was

experiencing a higher standard of living that was unprecedented, and the idea of the American

dream was born; family, owning a home and car, economic security, disposable income,

accumulation of wealth, and providing a future for their children through means of care and

education. During the Golden Age, the middle class saw the lowest inequality among the

classes and the United States was booming on almost all levels.

Just like most things in life, all good things must come to an end. The American middle class

was no different and the 1980s brought about negative changes to the lower and middle-class

families. Wages became stagnant, wealth in the U.S. was no longer going to the middle

percentiles of the population, but rather to the top 1% of the population. Drastic tax cuts were

made on the wealthy and big business lost incentive to pay their employees a high wage. The

information and communications technology (ICT) revolution boosted the economy and

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benefited the middle class in the beginning, but this also opened the door to globalization and

the labor force no longer drove wages up, rather competing with cheaper foreign labor drove

wages down.

As wages were stagnating, the prices of goods and services continued to rise, which put a

squeeze on the middle-class members. The standard of living that was once easier to maintain

has now become a struggle and members of the middle class are socially and economically

moving downward to the lower class or below the poverty line. This paper aims to investigate

what is occurring to the United States middle class and attempts to answer the following

questions:

1. Is the United States middle class shrinking and if so, to what extent?

2. What impact do variables such as gender, race, age, and education attainment have on

household income?

3. What has happened to the prices of goods and services associated with the middle

class in relation to middle class wages in the United States from 1960 to 2010?

4. What movement has occurred for middle class members to households below the

poverty line and households in the top 1% of income earnings?

These questions are difficult to answer due to the lack of consensus on what it means to be a

member of the middle class and how to define the class itself. Researchers and authors today

suggest that the middle class is indeed shrinking, but the extent of the shrinking is not

definitive. This paper aims to put figures on what is happening to the middle class and show it

statistically using micro level data and building a dataset that will allow for a thorough

analysis. These numbers will be compared against aggregated data on the prices of goods and

services in order to capture what has happened to the standard of living for the typical

American middle-class household. Multiple regressions will be used to analyze the impact of

the variables listed previously on household income to establish if there is a way for the

struggling middle class family to either maintain its socioeconomic standing or move up from

the lower class. Furthermore, look at the movement of household below the poverty line and

households into the top 1% of earners with the focus on middle class individuals. By doing

this, if the middle class is shrinking, data will suggest where the middle-class members are

going in relation to economic standing from 1960 to 2010.

Performing a quantitative analysis, combined with discussions regarding past research on the

topic, a narrative will be presented on what has occurred to the middle class since 1960.

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Firstly, a literature review will be discussed regarding current and past research on the topic

and the narrative of the birth and decline of the U.S. middle class will be created. Secondly,

the data sources used for this analysis will be presented and further elaborations will be made

concerning the source’s limitations and transformations that were needed to conduct an

analysis over time. Thirdly, economic theory that is relevant to this subject area is described

and applied to this specific study. The fourth section will examine the methodology that was

used for this paper and provide an in-depth look into the models and variables used for

regression analysis. The fifth section will present the results and attempt to show what has

happened to the U.S. middle class and the costs associated with the middle class, such as

home prices, car prices, and tuition costs for both public and private universities, as well as

costs for in-state and out-of-state tuition. Following the results section, a discussion section

will be used to elaborate on the findings presented and the questions mentioned previously in

this section will attempt to be answered. The final section will consist of concluding remarks

and highlight key discussions, as well as findings presented throughout this paper, connecting

everything together that will suggest a narrative of what has occurred to the U.S. middle class

since 1960.

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2. Contributions

This thesis will examine what is happening to the United States middle class in relation to the

household movements into poverty status and into the top 1% of wage earnings in the country

as a whole, using a repeated cross section analysis. The emphasis will be on what variables

impact the socioeconomic standing of households in the U.S. and use raw data, transforming

the data into adjusted figures that can be used to compare and analyze across time.

The primary contribution of this thesis will be the creation of a unique dataset using raw

micro level data to analyze the middle class and attempt to show exact figures that represent

the movement in or out of the middle class. Researchers today use aggregated data and

address the possible reasons for what is happening to the U.S. middle class and approach the

topic using a qualitative analysis whereas this paper will use a quantitative analysis of the

middle class.

Unlike most published work today, this paper will take an objective approach on the middle-

class situation and will not implore policy implications or suggest what can be done to

improve the middle-class situation. Instead, this paper will attempt to provide data on what is

occurring to the middle class since 1960. Even though the U.S. Census Bureau did not start

tracking median household income until 1967, using raw micro level data and creating a

dataset will allow an analysis further back in time than when records were kept for median

household income.

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3. Contextual Background & Previous Research

3.1 Outline of the United States Middle Class and How

to Define it

Current literature regarding the United States’ middle class have opposing views on how to

define it, as well as what is happening to it. There is a universal consensus that it is indeed

shrinking, but narrowing down on a specific cause of the shrinkage is the challenge due to the

plethora of reasons. America’s middle class can be classified as a combination of income

levels along with ideologies such as personal goals, values, and future expectations that an

individual or family hopes to achieve. These values and expectations of an American middle-

class family or an aspiring middle-class family can include owning a home and car, providing

for the welfare of their children, sending their children to college, family vacations, money for

retirement, and economic security (Blank, 2010). Relating to the idea of the American Dream

that was born during the middle of 20th century and the mentality of the middle class in order

to achieve such goals, it is necessary to work hard and save money. The ideologies of the

American middle class are difficult to quantify and will not be analyzed in this paper, but it is

important to address these ideologies due to how people identify themselves in terms of their

socioeconomic status. Whether a family or individual is in fact a member of the United States

middle class, often times this is self-perceived and people that have lower incomes than the

purposed income range will still classify themselves as being part of the middle class. The

same can be said for individuals or families that have higher incomes than the middle-class

range. Regardless of what end of the spectrum families or individuals fit into, they share the

same ideologies and hope for a better future for their children and themselves.

Since ideologies of the United States middle class is difficult to quantify for analysis, then

how is the middle class defined? Current research suggests that the American middle class is

defined using median income for a four-member household. As the number of household

members increase or decrease, the median household income is adjusted using a method

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established by Mollie Orshansky and using poverty rates in the United States (Pressman,

2015). One method posits that middle-class households in the United States are defined by

those that have incomes between 67 and 200 percent of the national median household

income. For example, in 2010, the median household income was $53,507.00 (U.S Census

Bureau). In order to be classified as American middle-class for that year, a four-person

household would have to have a combined income in the range of $35,849.69 to $107,014.00.

This method for defining the middle class appears to be the most accepted in current research

but there is not a universally agreed upon definition by social scientists. Instead, other

approaches are offered but tend to have flaws in relation to the poverty line or adjusting for

household size. The classification of the American middle class was virtually nonexistent

until the ending of World War, which causes issues with defining this class. Similarly, it

wasn’t until recently that the shrinking of the United States middle class has become a serious

concern (Pressman, 2015). The following section will discuss alternative methods for defining

the middle class and put forth why the method described above is preferred by current

researchers on the topic.

Various researchers investigate the different approaches used in defining the United States

middle class and the shortcomings that are associated with it in which there are an abundance,

but only the most popular are discussed:

Income received by the middle three income quintiles (Robert Solow). Once the upper

and lower quintiles are removed, the middle 60% of individuals remain in which

represents the middle class.

Education attainment (Robert Putnam, Charles Murray). Class is defined by the

highest education level attained by a household member. College educated represents

upper class, high school educated represents lower class and some college education

represents middle class.

Accumulation of Wealth (Thomas Piketty). Middle class has wealth holdings between

the top 10% of the wealth distribution and median household wealth.

Median income (Paul Taylor). Middle Class are those with incomes between 75% and

150% of adjusted median income.

Household income (Robert Reich). Middle class households making 50% higher and

lower than the median.

Median household income (Mollie Orshansky). Middle class defined as households

with incomes that fall between 67 and 200 percent of the National median.

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Listed above are the most prevalent methods for attempting to define the middle class in

America, since there is not a universal method in doing so. The method used for analysis in

this paper is the median household income proposed by Mollie Orshansky. Unlike the other

methods, using median household income allows for analysis over time with adjustments for

inflation, showing change in the percentage of households that fall within the middle-class

range, rather than having the size of the middle class remain the same over time, and puts the

lower range for categorizing the middle class well above the poverty line. Using median

household income allows for analysis on the composition of the middle class and what

percentage of households fall into the middle class using Orshansky’s definition. Wealth

accumulation appears to be a good measure because economic security is a key factor in being

a member of the middle class and being able to maintain the same standard of living during

short term economic stress as well as retirement, but falls short in terms of annual income,

which is the preferred method for defining the middle class. An example could be someone

recently graduating from a university. Like most college graduates, this person enters the

professional world with minimal to no assets or acquired wealth, if anything carries debt

(Pressman, 2015). Yet, this individual could get a job making $50,000 or more in which

would categorize him/her as middle class. Since this person has not acquired wealth, then he

or she would be categorized as lower class.

Flaws that arise when using the method by Robert Solow, income received by the middle

three quintiles, is that the size of the middle class will remain the same since 60% of the

population will always be 60% of the population. This method attempts to show how much

money goes to households in the middle of the distribution, but not the size of the group in the

middle of the distribution, or in other words, cannot seeing shrinkage or expansion (Pressman,

2015). This is a key flaw since this paper aims to analyze the shrinking of the middle class in

America and what percentage of household fall into the middle-class range since 1960. Using

median income, method discussed by Paul Taylor and used by Pew Research Center, similar

analysis can be made using this method as with using median household income. Similarly, to

other researchers on this topic, the issue arises with what range of percentages to use to

categorize the middle class. Using the range of 75% to 150% would put the lower range too

high over the poverty line and would put more individuals outside of the middle-class range.

This could lead to more individuals falling into lower class or moving up to upper class

without the accurate income for that group categorization. These flaws, or shortcoming, that

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arise when using methods other than the one purposed by Mollie Orshansky, using median

household income, would affect the research question and aim of this paper. For this reason,

Orshansky’s method and definition of the middle class will be used for analysis in this paper.

With the middle class being defined, the birth of the American middle class, the Golden Age

period, and its current situation needs to be addressed.

3.2 Birth and Transformation of the United States Middle

Class

Most research suggests that the American middle class was created after the second World

War. Economist Thomas Piketty suggests that the American middle class was created due to

two things: the destruction of European inherited wealth during the Second World War and

higher taxes on the rich (Hartmann, 2014). By taxing the rich, wealth and income were

brought from the top down and allowed working people to rise from lower class to middle

class. High taxes on the rich incentivize them to provide higher wages and benefits because

it’s better to invest in human capital compared to losing it to taxes. From the birth and rise of

the middle class, the tax rates on the rich fluctuated from 74% to 91% (Hartmann, 2014).

These high tax rates remained this high until the 1980s and President Ronald Reagan took

office. Another key moment began when President Franklin D. Roosevelt signed the

Servicemen’s Readjustment Act of 1944, or better known as the G.I. Bill, into a law and

provided a wide range of benefits to returning American soldiers. These benefits included free

college tuition and vocational training, living expenses while pursuing an education, low-

interest loan guarantee for homes and/or businesses, and unemployment pay (U.S Department

of Veterans Affairs). Prior to the passing of this bill, becoming a homeowner or pursuing a

college education was not an easily achievable dream for the average American. An educated

population provides benefits on both the micro and macro level, leading to massive

contributions to economic growth from formal education (Lebergott, 1966). The G.I Bill laid

the framework for an educated workforce and gave rise to the stereotypical American

lifestyle; a home in the suburbs, car in the driveway, white picket fence, barbeques, and

children playing in the yard.

As a result of the G.I Bill, residential construction took off and resulted in a jump from

114,000 new homes built in 1944 to 1.7 million new homes in 1950 (Suddath, 2009). This

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gave rise to the American suburban neighborhood in which American middle-class families

strive to own and belong to. The Federal Aid Highway Act of 1956, signed by President

Dwight D. Eisenhower, led to the creation of the modern-day highway system that is

established in the United States and connected the suburban neighborhood to cities across the

country. Since the cost of living is lower in the suburbs compared to the city, this provided the

opportunity for workers to still work in the city but own a home and live outside the city

limits. In the brief span from 1944 to 1952, the Veterans Affairs (VA), backed roughly 2.4

million home loans to the World War veterans. Similarly, 7.8 million of the 16 million World

War II veterans had participated in a training or an education program by 1956. Out of all the

benefits offered to returning soldiers from the G.I Bill, few collected the unemployment pay

in which less than 20 percent of funds set aside for this were used (U.S Department of

Veterans Affairs). By the middle of the 20th century, the American middle class was born.

3.3 Golden Age of the American Middle Class

From the beginning of the 1950s and up to the mid-1970s, all aspects of the American

economy were booming and is referred to as the Golden Age for the middle-class. During

these two decades following World War II, wages were rising along with increased

productivity output by workers, which epitomizes the idea of the hard-working American

middle class. Productivity and wages were rising at such similar rate in that a worker was

almost twice as productive in 1973 as a worker in 1948 and the wages were almost twice as

much (Blank, 2010). This trend diverged and the compensation per hour began to stagnate by

the 1980s and has experienced slow growth since. On the other hand, real output per hour has

continued to rise with a small period of stagnation during the 1980s (Figure 1).

Figure 1. Employee Compensation and Output Per Hour (1947-2012).

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Source: Bureau of Labor Statistics

Increasing wages and productivity during this Golden Age period for the middle class led to

the economic growth by an average of 3.9% a year from 1948-1973. One of the more

important aspects to the economic gains during this time was that the bottom 90% of families

reaped 68% of the gains (Blank, 2010). Members of the American middle class were

experiencing what we know today as the American dream and were able to take part in higher

education, acquiring wealth, buying a car and home, and having economic security. During

the 1960s, when President Johnson took the presidency after Kennedy was assassinated,

Federal government spending dramatically increased and new programs and initiatives were

implemented to provide benefits to the population in what was termed a “war on poverty.”

Such programs introduced include food stamps in assisting the poor and Medicare in which

provided health care for the elderly (Conte, 2001). Benefits were also gained for the

workforce through the success of labor unions during the 1960s and 1970s that fought for fair

wages, safe working condition, benefits, pensions, and long-term contracts. This period of

time experienced improved social benefits along with increased wages, which led to a higher

standard of living for the American middle class.

Post-war economic prosperity in the United States can be attributed to the transition from

agriculture to manufacturing/industry to the service sector (Figure 2).

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Figure 2. Distribution of the Labor Force by Sector (1840-2010).

Source: Bureau of Economic Analysis, NBER

During this time, introduced was big business and conglomerates, which can be seen in

today’s capitalist society. An example of this is when the International Telephone and

Telegraph Company bought out Avis Rent-a-Car, Continental Banking, Hartford Fire

Insurance, and several other companies during the 1950s (U.S. Department of State). This

directly impacted the agricultural sector, which was the backbone to the U.S. economy during

the 19th century, resulting in smaller farms failing to compete with big business farms. Late

1940s and early 1950s saw these farmers and returning soldiers entering the manufacturing

sector. The manufacturing sector was not the only part of the economy that was booming, but

so was the service sector. Most researchers suggest that industry was the primary sector in the

United States during the first half of the 20th century in terms of employment share and

output, but one author, Louis D. Johnston, has an opposing view. He suggests that the

distribution of the labor force by sector transitioned from agriculture to services, with industry

never surpassing services. In terms of the distribution of output among sectors (Figure 3),

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industry did surpass services during the late 1890s but started falling behind again during the

early 1900s (Johnston, 2012).

Figure 3. Distribution of Output Among Sectors (1840-2010).

Source: Bureau of Economic Analysis

This furthers the discussion regarding how the service sector is the key contributor to the U.S.

economy today, but serves as a contributor on the debate of when the United States initially

moved away from the industry sector.

3.4 The Declining American Economy and Middle Class

By the end of the 1950s the majority of workers held white-collar jobs rather than blue-collar

jobs, but both job types encompass the careers of the American middle class. Economic

prosperity and the overall health of the U.S. middle class was not able to maintain this success

through the 1970s and 1980s. The beginning of the 1970s marked a period in which the

United States would begin to see economic decline or stagnation in various aspects. Shortly

following WWII, there was a dollar shortage but as the decade proceeded it transformed into a

dollar oversupply, which is referred to as the dollar crisis during the early 1970s. The Bretton

Woods system is centered on gold and when the U.S suspended the exchange of U.S dollars

15

for gold in 1971, this led to the collapse of this system (Dezhao, 2006). As a result, rather than

using the gold standard, other countries began the implementation of the floating exchange

rate system. This began a period of increasing globalization and increased foreign competition

from countries such as Japan and Germany, along with spiraling inflation from the Arab oil

embargo from 1973 to 1974 in which crude oil prices quadrupled, high unemployment,

increased federal budget deficits, and stagnant consumer demand (Selgin, 2012). Interest rates

rose drastically during the 1970s (Figure 4) and impacted markets such as for cars and the

housing market directly impacting the middle class or aspiring middle class members in

America. Inflation rose so much that the 1970s can be categorized as the Great Inflation in

which inflation rates reached a historical high and is considered the greatest failure of

American macroeconomic policy in the postwar period (Bryan, 2013). Policies in place

during this decade sent spending in such excess that the economy could not produce with its

ordinary productive capacity and resulted in the need for more resources to compensate.

Although labeled as a failure to most economists, out of that failure came transformations in

monetary policies that central banks use around the world today.

Figure 4. Historic CPI Inflation Rates (1957-2015).

Source: Worldwide Inflation Data

Inflation was not the only detrimental aspect affecting the middle class, but also during the

1960s and 1970s the unemployment rate was rising at unacceptable levels. In 1964, inflation

was at 1% and unemployment was at 5%. In 1974, ten years later, inflation was over 12% and

unemployment above 7%. By the beginning of the 1980s, inflation was near 14.5% and

unemployment was over 7.5% (Bryan, 2013). Members of the middle and lower class were

the ones most impacted during this time as they were the groups losing jobs, while dealing

with increasing prices on goods and services. This falls in line with what current researchers

suggest in terms of the middle class beginning to decline during the 1970s. A more optimistic

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researcher, Chen Dezhao, suggests that rather than an economic decline during this period, it

was in fact a period of slowdown. Dezhao puts forth that the U.S. economy had not declined

but instead was still growing but just at a slower rate. American growth was overshadowed by

the faster growing and increasingly competitive economies of Western Germany and Japan

(Dezhao, 2006). As the 1970s came to an end, some of the issue, such as stagnating wages,

still remained during the early 1980s but reforms brought about hope for the economy and

middle-class households during the 1980s and 1990s.

3.5 Economic Revival and the Information and Computer

Technology (ICT) Revolution

Shortly after the recessions during the beginning of the 1980s, the United States economy

began to recover and inflation rates began to drop and stabilize below 5% through the mid to

late 1980s. Ronald Reagan became the 40th President of the U.S. and held office from 1981 to

1989. He implemented new economic policies that would impact the middle class to this date

and has been coined “Reaganomics.” These policies were based on the supply side economics

in that a greater supply of services and manufactured goods are the most direct path to

economic growth and wanted to initiate tax cuts to encourage investments and consumer

spending (U.S. Department of State). The issue with these new policies is that it favored the

individuals or households that fall into the upper income levels. The ideology behind this was

that if the rich received tax relief, then they will invest and spend more. In terms of economic

growth during this period, the U.S. saw growth in gross national product (GNP), gross

domestic product (GDP), low inflation rates, and the creation of millions of jobs. Current

literature discusses the impact of Reagan’s tax cuts on the middle class and what impact his

Presidency had on the economy. The optimist side suggests that real economic growth

occurred, which averaged 3.2% during his presidency compared to the prior and following

Presidencies, median family income grew by $4,000, unemployment and interest rates fell,

and the focus on building the information highway sparked investments in information

technology and new hi-tech industries (Niskanen, 1996). Although the ICT revolution did not

take hold until the Clinton administration during the 1990s, Reagan was the one that

encouraged the initial investment into that sector.

17

During the 1980s, there were two significant tax reforms that were adopted in which favored

the wealthy over the remaining population. The first tax reform, Economic Recovery Act of

1981, lowered the income tax on the wealthy from 70% to 50% and lowered the income tax

on the middle class from 14% to 11%. The second reform, Tax Reform of 1986, further

lowered the taxes on the wealthy to 28% but raised the taxes on the middle class to 15%

(Feulner, 2015). More pessimistic researchers suggest that Reagan’s Presidency was a

temporary relief to economic crisis and would hurt the middle class in decades to come. The

1980s were a time of recovery from a recession but new policies resulted in the idea of the

rich-getting-richer and the average American did not benefit from these changes. By the late

1980s, middle class incomes were barely higher than what they were during the 1970s and the

poverty rate rose (Krugman, 2008). Even though the economy was growing as a whole, the

middle class was beginning to shrink and moving down a tier into the working class or lower

middle class (Figure 5). The creation of the top 1% occurred during this decade and this group

has continued to grow through the decades. As the 1980s came to an end, the U.S. economy

was growing but would experience another recession in the early 1990s, then experience the

benefits from the ICT revolution during the mid to late 90s.

Figure 5. Share of Adults Living in Middle-Income Households.

Source: Pew Research Center

Bill Clinton took office as the 42nd President, serving two terms from 1993 to 2001 and

continued Reagan’s economic plan of stimulating and restoring the economy by investing in

18

and developing information technology. The 1990s were a time of prosperity for most people

in the United States, saw stable economic growth and high productivity growth through the

decade. The U.S. was coming off a victory in the Persian Gulf War and the Cold War,

resulting in the fall of the Soviet Union in 1991. From 1992 to 1999, the U.S. GDP grew by

an average of 4% a year and roughly 1.7 million new jobs were created a year on average,

resulting in unemployment rates dropping from 8% to 4%. Also during this time, median

household incomes grew by 10% and stock values quadrupled (Andersen, 2015). Success on

Wall Street during this time, termed the Dot-Com bubble, was unparalleled compared to the

past and would eventually bust in 2000. Movies, TV shows, musicians/bands, books, and

other aspects of the U.S. middle class that are enjoyed became easily accessible due to

technological advancements and this country was ready to embrace the future and was excited

for it.

When analyzing the 1990s, some authors suggest that even though the economy was growing,

it was actually the weakest growth since 1945 but was considered the longest economic

expansion in history. Due to its compound effect over time, overall economic health improved

and suggests why the 1990s were some of the best time for the American economy

(Weinberg, 2002). If such economic progress was being made, then what was occurring to the

middle class during this decade? Incomes were rising the fastest at the top income tier but the

typical worker’s wage was above inflation, which allows for maintaining or achieving that

middle class standing. The 21st century brought about a different pattern than in the past in

that the productivity growth was rising, but the wages were not. After wages are adjusted for

inflation, the typical worker has only seen a 1% increase since 2000 (The Economist, 2006).

Stagnation in wages combined with rising costs of goods and services have caused a squeeze

on the middle class and inequality during the 2000s began to raise serious concerns.

3.6 Beginning of the 21st Century and the 2008

Recession

Prior to the Great Recession in 2008, the United States’ economy was growing, yet the same

could not be said for the middle-class individuals and/or families. According to economist

Jared Bernstein, worker’s productivity in the U.S. grew by 18% in the 2000s, which is

19

roughly 2.5% growth per year. Between 2000 to 2007, Bernstein suggests real median income

for middle income families dropped by $2,000 (Goldman, 2008). This falls in line with what

other researchers and authors have suggested in relation to the increase in productivity yet

workers are not being equally compensated for their work. Of course, not all researchers agree

with these numbers and suggest that other aspect need to be accounted for, such as

increasingly better retirement plans and health care plans, bonuses and other benefits that

workers receive. Leading up to 2008, unemployment was an issue due to the lack of new job

creations and could not keep up with the growing U.S. population. With lack of job creation

combined with stagnating wages for the average worker, the country experienced increasing

inequality among the different classes. In a book by economist Heidi Schierholz, she puts

forward that 90% of the growth in U.S. worker’s income went to the top 10% highest earners

from 1989 to 2007. Income for the top 1% during that time grew 204% and the top 0.1%

income grew by 425% during this period (Schierholz, 1988). These numbers are staggering

when investigating what is happening to the middle class in America, as well as the

exponential growth that the top 1% of earners are experiencing. These numbers fall in line

with the expression that the rich keep getting richer, while the rest of the population stagnates

or regresses.

When the 2008 recession hit, things certainly did not get better for the members of the middle

and lower class and are struggling to recover today. This recession and the housing bubble

bursting in 2007 can be traced back to the 1990s where the housing market experienced

investments that were high risk and high reward. Over a ten-year span, U.S. housing stocks

increased 13.3% and national homeowner rate was 66.2% in 2000 compared to 64.2% in 1990

(U.S. Department of Housing). When 2001 hit, a minor recession occurred and resulted in

easy loans provided by the Federal Reserve and more investments were shifted from the

financial sector into the housing market. These loans were high risk for individuals receiving

the loan, while the banks were removed from the risks. As these subprime loans began to go

into default in mid 2007, interest rates increased dramatically. In order to preserve the banks

and the United States economy, the Federal Reserve provided the largest bail out in U.S.

history, coming to a total of 700 billion dollars. This directly impacted the middle-class

families and by 2009, there were over 3 million foreclosure filings, unemployment rose above

10% and this recession was the worst since the early 1980s (DeGrace, 2011). These economic

events impacted the middle class because they were the ones whom lost their homes and jobs.

20

Even though most of the effects from the housing bubble bust were wearing off by 2009, the

effects were still felt within the middle and lower class.

With these factors coming into play and leading up to the 2008 Great Recession, it has caused

the middle class to lose its purchasing power, wages have decreased, people dependent on

government assistance had increased greatly, and the middle class is not expected to bounce

back to prerecession standards, 2007, until 2019 (Snyder, 2014). Although it is only a

projection, the middle class appears to be stagnating and that can be attributed to employment

rates, or lack thereof. When the recession peaked in 2008, the share of the United States

population that was employed dropped drastically and in 2014, there were 1.4 million fewer

full-time jobs than in 2008 and those that lost their jobs are still struggling to find

employment (Snyder, 2014). The events of the Great Recession have squeezed the members

of the middle class of their standard of living, as well as their wealth that they had

accumulated over the years leading up to 2008. This has moved families downward on the

socioeconomic ladder and unsure if they will move their way back up.

3.7 Current Middle-Class Status

The middle class is shrinking or as some authors say, squeezed, which focuses on the incomes

of families and the costs that are associated with being a middle-class member. According to

the Center for American Progress, middle-class wages are stagnating (Figure 6), the middle

class share of national income has fallen and the cost of being in the middle class-maintaining

a middle-class standard of living-is rising at a fast rate (Erikson, 2014). Within this standard

of living falls the costs for higher education, transportation, housing, child care, health care

and retirement. If costs for these necessities are rising yet incomes are stagnating, then it

creates a serious issue for covering these costs in respect to middle class families.

21

Figure 6. Median Household Income.

1967

1969

1971

1973

1975

1977

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

2009 $-

$10,000.00 $20,000.00 $30,000.00 $40,000.00 $50,000.00 $60,000.00 $70,000.00

Median household income, inflation adjusted (1967-2010)

Year

Inco

me

Source: U.S. Census Bureau

Another reason posited for the shrinking of the middle class is attributed to globalization and

the impact it has had on policies as well as the middle class. Middle class American jobs are

now outsourced to countries abroad and the American labor force is competing against

foreign labor forces that will work for lower wages. Prior to globalization, the domestic labor

force drove wages up due to competition as skills and productivity rose. Globalization has

resulted in wages decreasing and the domestic workforce is competing against foreign

workers that will perform the same task for less. Similarly, American organizations and

corporations have shifted their interest from national to international and policies in the

United States tend to favor these large organizations (Kuhl, 2012). Such policies put a

stranglehold on the American middle class and new checks and balances need to be

introduced in both the economic and political systems in order to reverse this trend and

promote a stronger middle class. Since the early 1990s, the top 1% has continued to grow and

the United States has experienced a growing income inequality gap. The top 1%, in terms of

wealth, holds more wealth than the bottom 90% and more than half of the nation’s income

growth has been capture by the 1% (Beltz, 2012). In today’s politics and economics, this very

issue is the centerpiece of discussion. Many researchers, such as Piketty and Saez, suggest

that the focus needs to shift back to the middle class and increase the shares of income growth

to the middle class. This is important because according to one researcher, the American

middle class has gained little economic growth over the last 30 years (Burkhauser, 2012).

This raises concerns considering the middle class consumes the most goods and services, yet

are experiencing stagnation in wages and lack of mobility between classes. For lower income

22

families or individuals, it is difficult to move up the social ladder. For middle class members,

it is increasingly more difficult to move up income groups yet becoming easier to move down

an income group. If adjustments are not made on the political and economic level, then the

middle class will continue to be impacted and more members of this class will be squeezed

out of it.

Wages are not the only way to examine the middle class but rather look at accumulation of

wealth in middle class members. Current economic shocks such as the housing crisis and the

recession in 2008 led to middle class members needing to tap into investments and other

assets, such as savings, to maintain the standard of living during tough times. As a result,

these savings have turned into spending. When looking at median wealth, assets minus debt,

the middle class has experienced a decrease in median wealth by 28% from 2001 to 2013

(Pew Research Center). Accumulation of wealth is an important aspect to the middle class and

this number shows that these members are unable to save and have either tapped into their

assets or used them all up. This is when individuals move down economically towards the

lower middle class, or working class, and living paycheck to paycheck.

Within current literature, the debate revolves around the shrinking of the American middle

class, but the discussion is centered around to what extent has the middle-class shrunk. As

addressed, some researchers suggest the middle class has seen a significant decrease in the

percentage of individuals or families that fall within the middle class since the 1970s, while

others suggest it has shrunk but not at such a high rate. This paper aims to investigate the

shrinking of the United States middle class and to what extent is this happening.

23

4. Theory

Income is an essential aspect when analyzing the U.S. middle class due to its function in

defining what the middle class is, provides insight into living standards in America, and what

is happening in the domestic economic environment. Regardless of what range of percentage

is used when framing the middle class in terms of income, any discussion of the middle class

starts with those at the very middle of the income distribution (Elwell, 2014). It is up to the

researcher to define the parameters of the range for median household income in order to

analyze the middle class.

4.1 Household Income

Household income, more specifically income, is a good gauge for economic performance

within a country and gives insight to what the standard of living is. If the median income for

individuals within a population is high enough to account for living expenses, possesses the

ability to save and have disposable income, then that country would be seen as having a high

standard of living. Income is a small measure and proxy for standard of living and the most

common way to measure standard of living is by GDP per capita (Brewer, 2012). When

looking at the United States and the middle class, income appears to be the best proxy for

analyzing the standard of living and investigating how it has increased or decreased over time.

Using GDP per capita can be deceiving as it gives insight to economic performance, can

suggest whether a country is developed or developing, and can be traced historically to see

changes (Jahan, 2001). The issue with using GDP per capita is that is shows how the country

as a whole is performing rather than certain people or classes within that society.

With focus on the middle class, the idea is not to measure how the economy as a whole is

doing. Although it is an important analyze how the economy is doing, as it does directly

impact the middle class, it is not critical in this examination. On the other hand, analyzing the

U.S. middle class income is a critical aspect to understanding how the class is performing.

24

Through readings and research, median household income is the most efficient way to study

and analyze the middle class. The only flaw with using household income was discussed in

the earlier sections and that is what range to use when determining the parameters of the

middle class for the upper and lower bound. This paper will use household income, more

specifically median household income, as a measure for the U.S. middle class and a proxy for

the change in the standard of living over time. The real median household income is adjusted

for inflation using the consumer price index (CPI) in order to make the data comparable

across the scope of this study, 1960 to 2010.

4.2 Middle Class

The middle class itself is a theory of its own. This is because there is not a universal definition

for the U.S. middle class and is constantly being debated on how to approach the question.

Some researchers suggest that it is up to the individual to self-identify to a specific class due

to personal beliefs or ambitions. Since that is an abstract idea, it becomes difficult to quantify

and solid results cannot be gathered from using that approach. One the other hand, income is

preferred since that can be applied to everyone in the United States and it is a fair way to

categorize the population. Whether an individual perceives themselves as middle class by

goals and views or by income, the theory is still open to interpretation. It is up to the author or

researcher to define how they will approach defining the middle class and who falls into that

class.

Within this theory of the middle class, this paper takes on the fixed percentage of median

income approach in which a certain percentage is used to encapsulate which households fall

into the middle class (Horrigan & Haugen, 1988). As discussed in early sections, the range in

attempt to define the middle class is 67 to 200 percent of the median household income.

Regardless of the approach taken to attempt to define the theory of the middle class, it is

arbitrary and determined by the researchers themselves.

25

4.3 Stagnating Wages

Stagnation in wages has been a focal point in research and discussion when analyzing the

United States middle class and can be explained by conventional economic theory. This

theory predicts that within a globalized economy, such as the United States economy,

interactions with low-wage countries will negatively impact domestic wages for less educated

workers and see an increase in profit and wages for the high-income earners (Mishel, 2015).

With increasing labor competition around the world and an increase in imports over the past

several decades, middle class earners are the ones most impacted by this shift, while the top

earners reap the rewards. This theory ties into the idea that wages in the United States are and

have been stagnating for several decades. This is an important aspect when analyzing the

middle class since inflation has risen the prices of goods and services, which this particular

class enjoys. With less disposable income and increasing prices, stagnation in wages are a

driving force behind this squeeze on the U.S. middle class. This paper will attempt to prove

this theory and attempt to show that wages are indeed stagnant and having a negative effect

on the U.S. middle class.

26

5. Data

5.1 Data Source, Use, and Transformations

Data used in this paper is a mixture of macro and micro level data. The primary data is on the

individual level with the macro data used as a compliment to the micro level data used and aid

in filling in the gaps. The dataset used in this examination was created using data from

IPUMS-USA, which is an integrated public use microdata series that the University of

Minnesota has gathered and made accessible to the public. IPUMS-USA uses decennial

census data that provides a plethora of variables and sample sizes for analysis, along with the

ability to control sample sizes, which was valuable since this paper investigates the American

middle class on a national level and this allowed for a manageable sample size. Many

adjustments were needed to the variables used in analysis because IPUMS-USA provides raw

data that is unadjusted, so cannot be used to compare across time. The total number of

observations used within this analysis is from IPUMS-USA is 150,018.

The second primary source for data used in analysis is from the United States Census Bureau.

The information accessible though this source is macro level data used to investigate prices of

goods and services, along with information regarding the whole United States population

rather than a specific sample size. The Census Bureau provided the figures for what the

poverty line was for each decade and needed adjustments as well to be comparable over the

time of analysis. Also, provided by the U.S. Census Bureau, were the figures for the median

household income from 1967-2010 in which can be used to compare against findings in the

IPUM-USA dataset. Furthermore, the U.S. Census Bureau provided data for median home

values, which were adjusted to 2000 dollars and the time frame is from 1940 to 2000.

Another database used within this paper is the National Center for Education Statistics

(NCES) in which provides data regarding college tuition cost for in-state and average tuition

costs for all universities, along with the costs for public and private universities. The figures

27

are given in current U.S. dollars and already adjusted for inflation. Also, calculated into

tuition costs are room and board rates charged for full-time students. The time covered by this

database is from 1964 to 2006.

The next dataset used for analysis is for car prices in the United States over time and compiled

by the U.S. Department of Energy. The numbers are given in 2013 constant U.S. dollars and

are presented as the average price of a car, rather than the median price. The figures exclude

the prices for pickup trucks, vans, and/or sport utility vehicles (SUVs). The available data is

from 1913 to 2013, but only the years used specified within this paper will be used.

The last dataset used for analysis is provided by the Federal Reserve Bank of St. Louis

(FRED) and the figures available for the median sale’s price of houses sold for the United

States were used. This data is in U.S. dollars, but is not seasonally adjusted. Data provided is

quarterly, and all figures for each quarter of each year was used within this analysis.

With the data sources presented and defined in relation to how they are used later in the

analysis, the variables used in this study need to be defined and how they were transformed to

make new variables along with the ability to analyze the middle class since 1960.

As discussed in previous sections, the method for the analysis of the middle class is using

median household income, which is the dependent variable. The explanatory variables consist

of: gender, age, race, and education attainment. The independent variable is real median

household income that was transformed from household income by applying the CPI for each

decade to the IPUM-USA data. Gender is described as being either male or female, in which

required no transformation for analysis. When running regressions, males are held as the

constant and females being the group that has its income compared to.

The ages for individuals provided by IPUMS-USA was transformed using a range of ages in

order to include only working age individuals. This was necessary to exclude individuals from

the dataset that were either too young to work, or retired when the census was taken. If these

individuals were included in the analysis, the results would be skewed and would not

accurately represent the results that current and past research posits. The working age defined

in this analysis is between the ages of 25 and 65. The reasoning behind this age bracket is

based on individuals that would most likely being working full-time by then, and retired by

age 65. Before the age of 25, majority of high school and college students would either have

28

no income or a low income as working and studying full-time is not common. It’s

acknowledged that this age bracket excludes those that do not attend college and enter the

workforce, but that was overlooked to get more accurate results. Within the dataset, an age

flag variable was created in STATA and the individual was marked with a 1 if they were in

the working age group and a 0 if too young or too old. Another transformation to the age

variables was creating age categories, which allowed for an analysis and comparison between

various ages. The following age groups are defined and denoted as: (1) 25-29, (2) 30-34, (3)

35-40, (4) 41-44, (5) 45-50, (6) 51-54, (7) 55-60, and (8) 61 & older. During the regression

testing, the control age variable within the formula was set for greater than and equal to thirty-

five years old and less than and equal to forty years old.

The race variable is another one that required some transformations and there are two separate

race identifiers provided by IPUMS-USA. First being a broader category of race, including

White, Black, Asian and/or Pacific Islander, American Indian/Alaska Native, and other

race/non-Hispanic. The second identifier of race is more specific and expands on the previous

races mentioned. The detailed race identifier consists of American Indian, Alaskan Native,

American Indian/Alaskan Native, Asian and Pacific Islanders, Filipino, Chinese, Japanese,

Korean, Hawaiian, Asian Indian, Asian, and other race/Hispanic. Some limitations within the

race data consists of available data for each race for each decade. Prior to 1970, Korean and

Pacific Islander were not available as options on the census. Prior to 1980, Hispanic, Asian

Indian, and Asian were not options on the census. By 1980, all the data for the race identifiers

used for this analysis were available and provided enough data to perform testing. There were

some transformations required when working with race but not too much since they were

provided by IPUMS-USA and are predefined. Due to the large number of race identifiers,

some races were combined to examine them more accurately. One transformation was to

combine American Indian (AI) and Alaskan Native (AN) into American Indian/Alaskan

Native. It wasn’t until 1990 that the census separated the two races so the two races were

combined into American Indian/Alaskan Native to be more consistent over time. Similarly,

the same was done for the race identifier Hawaiian, Pacific Islander (PI) and Asian and

Pacific Islander. Since these locations are geographically similar, in the Pacific, these races

were grouped together within this analysis and are all represented in the race identifier Pacific

Islander.

29

The next explanatory variable is educational attainment and covers all levels of schooling,

from no education to 5+ years of college. IPUMS-USA provides two separate education

variables, one that is broader and groups into multiples grades, while the other education

variable is more descriptive and has the exact schooling level achieved. Using the descriptive

education variable, an education category was made within STATA that confined the

observations to six categories: first being no schooling (1), second is some primary schooling

(2), third is some high school (3), four is high school diploma (4), five is some college (5),

and six is college degree or higher (6). This allows for easier groupings in analysis and much

more organized than what the raw data provided. By creating education categories, a base

education level could be used as a control variable when running the analysis on the effects of

education on the other variables. Within the analysis, a high school diploma (category four)

was used as the control category in the regression models in order to analyze the value of a

high school degree over time, along with the value of being college educated.

The income variable was the one that required the most transformations and several new

variables were created out of these transformations. IPUMS-USA provided unadjusted, pre-

tax income for each family member in a household, which is provided by a serial number and

personal number. Once the households were created for all the observations, this was done by

combining serial numbers, the total income for that household was able to be calculated.

Using the consumer price index (CPI) provided by IPUMS-USA for each decade of study,

this created the adjusted real household income for individuals and/or families. This also put

the real household income into current 1990 prices in which allowed for analysis across the

decades. Furthermore, the real household income was transformed into natural log form,

which was used during the regression analysis for easier interpretation, as well as accounting

for outliers within the sample. Within STATA, the median household income was calculated

for each decade. Using the methodology put forward by Mollie Orshansky, the lower bound

for real household income was created using 67% of the median household income. Same

goes for the upper bound, using 200% of the median household income to calculate it for each

decade. With the lower and upper bounds calculated, STATA was then used to create the

middle-class variable and the families or individuals that fell within this range were given a 1

and those that did not were labeled as a 0.

The next step was finding which families or individuals fell below the poverty line and which

ones belonged to the top 1% for each decade. The poverty line figures were provided by the

30

U.S. Census Bureau and were adjusted for inflation by using the CPI for each decade

provided by IPUMS-USA for comparison across time. If the real household income was

below the poverty line, then that household was labeled with a 1 to identify their poverty

status. If the household income was above the threshold, then it was labeled with a 0. The last

step was creating the minimum household income in order to be categorized as a member of

the top 1%. Within STATA, the top 1% was calculated from the real household income

variable. If the household income was equal to or above the threshold, then it was given a 1. If

the household income was less than the threshold, then it was given a 0. After all these

variables and categories were created within STATA, the dataset used in this analysis was

complete and ready to use for regressions and analysis of the households below the poverty

line, within the middle class, and the ones in the top 1%.

The final transformation that was performed is related to the regression tables and results. The

adjusted numbers from the regression tests are presented below within the paper, while the

unadjusted tables and numbers are presented in the appendix, but these numbers are used in

the results section. Prior to adjusting the results from the regression analysis, the numbers are

the expected change in log of Y, real household income, with respect to a one-unit increase in

X, race, gender, age, and education attainment, holding all other variables constant. In order

to get the correct value from the regression results, the inverse of logarithm function is used,

which is how calculating the exponentiated regression coefficients is done. By transforming

the results this way, this allows for an interpretation of what is happening to the outcome

variable itself, real household income, for a one-unit increase is the X-values (Bruin, 2016).

Rather than using the arithmetic mean, exponentiating the coefficients results in using the

geometric mean and provides a more reliable result than the coefficients produced by the

standard OLS regression output.

5.2 Data Limitations

With the data sources and their purpose defined, the limitations found when performing

analysis need to be discussed. The first limitation is the availability of data for each variable,

which became apparent quickly. The United States is a young country compared to the likes

of the rest of the world and the data collection reflects that. Median household income was not

31

recorded until 1967 by the U.S. Census Bureau and that is why individual data was used to

create median household income that could be used for analysis further back in time. The

starting period for analysis is 1960 due to the unreliable data, or lacking data, that was

available prior to 1950, the period of World War II and soldiers returning home. With the G.I.

Bill providing benefits to returning soldiers, males were either going to school to receive an

education or training, or starting businesses in which would categorize them outside of the

middle-class due to lack of income. In terms of women, the majority still have not entered the

workforce and remained within the domestic role. Even though IPUMS-USA offers an

abundance of variables, the ones chosen were the only ones available for the years of this

study, which would have an expected relationship with household income. These are the

reasons why the analysis started with the 1960 census rather than earlier.

Another limitation that arose while researching and performing analysis is sample size. Due to

the size of the United States population, every person or household was not able to be

included. While selecting variables and sample sizes, 1% of the total population for each

decade, was used to make the data easier to work with. This sample size seems reasonable to

attempt to draw conclusions regarding what is happening to the middle class, lower class, and

top 1% of the population in the United States over time. The sample size of 1% was also

reasonable because it is a random sample generated by IPUMS-USA. The data regarding the

poverty line in the United States is incomplete due to the figures available for different size

families. For example, the figure for poverty line for family size seven or more people were

categorized together from 1959 to 1980. After that, figures become available for individual

family sizes of seven, eight, and nine or more people. Due to this, the poverty line for

households with four members are used in this analysis and the data was available for the time

frame of study, 1960 to 2010.

A second limitation that can be categorized within sample size is the inability to track a single

household over the entire time period of focus. IPUMS-USA generates random households in

which each household is given a specific I.D. number. With the selected sample size for each

census year, there is no guarantee that the same household I.D. will be provided. As a result,

the data does not allow tracking and analyzing individual households for each census year and

tracking household’s movements among different classes over time. Instead, using

randomized household data from IPUMS-USA, a snapshot of the middle-class in each decade

is used in an attempt to explain what is happening to the U.S. middle-class.

32

Similarly, to the median household income available for the United States, data for college

tuition costs and home prices does not cover the full-time period of this analysis, but are very

close to covering every decade. For college tuition costs, the data used within this analysis

was available beginning in 1964 until 2006. Working with housing price data, the figures

available covers 1963 to 2010. Regarding the data available for housing costs, two graphs are

presented due to a major limitation in one of them. One graph provides the median sales price

of a home, which is not seasonally adjust so difficult to draw conclusion when comparing

prices over time. To compensate for that, the U.S. Census Bureau offers the median home

values that are adjusted to 2000 dollars. The limitation with using this source is that the last

decade available is the year 2000. With this study spanning up to the year 2010, this data is

short a decade. But, trends will still be capable of being analyzed and these limitations are

accounted for.

The overarching limitation within this study is in regard to the way different databases

adjusted their data in terms of dollars. Without having the raw, unadjusted data available, the

transformation of the all the data is difficult to achieve. This limitation’s importance is

diminished as the data used for college tuition, car price, and housing price are aggregated and

serve as supplementary figures to the findings from using the IPUMS-USA database.

Although there are several limitations when it comes to performing the analysis from the

databases discussed previously, they still need to be acknowledged and addressed.

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6. Methodology

Within this study, the use of a basic ordinary least squares (OLS) model will be used to

analyze the impact that each explanatory variable; education attainment, race, age, and sex,

independently has on the dependent variable, real household income. In other words, what

impact do these variables have on middle-class status. One motivation for using the OLS

model is that this analysis is not causal, rather looking at associations and the way

associations develop over time, which may give indications of more causal relationships. But,

the important aspect to remember is that the relationships are only associations. The OLS

model is used for estimating the unknown parameters in a linear regression model and the

goal is to minimize the differences between the observations in the dataset and the responses

predicted by the linear approximation of the data (Benoit 2010). These reasons are the

motivation for the OLS models selected for this analysis.

Within these models, log household income was used rather than real household income. As a

result, a log linear model, or a log level regression, was used as well for this analysis. Both

bivariate and multivariate regression analysis will be performed and analyzed throughout this

paper. For each model, a regression analysis is performed for each decade in order to examine

how incomes have changed over time based on the various explanatory variables. The alpha

term is the constant, or interception, and will show where the y-axis is crossed by the

regression line. The beta term will show the slope of the regression line and is referred to as

the coefficient (Benoit, 2010). The residual, or error term, will attempt to show the errors

within the OLS model used in this analysis and it’s capturing the influence of everything

unobserved or unmeasured which is affecting the dependent variable, real household income

(Helgertz 2017). Each regression will be run separately within STATA and the outcomes will

be discussed in the following results section.

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6.1 Regression Models

The first regression model used within this analysis, listed below, is a multivariate regression

and examines the impact that race has on household income, controlling for age, for each

decade. The model specifies the base age category as 3, which is 35 to 40 years old, and an

age parameter is set for ages older than twenty-four and younger than sixty-six. The added

age parameter is included in all the regression models to exclude those that are in college or

retired, but not dropping them from the database. The race identifier, White, is held constant

and is the race that the others are compared to.

ln hhinci=β0+β1 Racesingd i+ β2 ib (3 ) . agecati+ε i

The second regression model, a multivariate regression, examines the impact that education

attainment has on household income and again, controlling for age. This model uses the base

education category 4, which is obtaining a high school diploma. Similarly, to the previous

model discussed, the age category 3, 35-40 years old, serves as the reference category. Using

the high school diploma education category as a constant aid in analyzing the value of various

educational levels over time and what levels of education have gained or lost its value.

ln hhinci=β0+β1 ib (4 ) . educati+β2ib (3 ) . agecat i+εi

The third regression model, a bivariate regression, investigates the impact that gender has on

income. Males are held constant and the females are the comparing sex. Again, age is

controlled for but the age category was dropped within this model to solei capture the effects

of all gender, regardless of age, on household income.

ln hhinci=β0+β1 Genderi+εi

The last model, a multivariate regression, contains all four of the variables used within this

study and analyzes the effects that education attainment, race, gender, and age have on

household income. Within this model, the base age category was removed and only the age

variable was used. Instead, age squared was added into the model in order to counter the

potential issue of a non-linear relationship between age and the independent variable,

household income. Up until a certain age, using 55 as an example, income usually rises until

it peaks, then will begin to decrease. To account for this negative figure, age squared is used

35

to counter this issue and provide a positive number. This model continues to use the base

category of a high school diploma as the reference, and the same can be said for the race and

gender variable, whereas white ethnicity and males are held constant.

ln hhinci=β0+β1 ib (4 ) . educati+β2 Racesingd i+β3 Genderi+β4 c .age¿c . age¿i+εi

6.2 À Priori Expectations

With the models defined and how they will be used within this analysis, à priori expectations

need to be discussed in order to present the expected value of the coefficients for each

variable, whether it will carry a positive or negative coefficient. The first set of expectations

are shown below (Table 1) for each decade and for the first model presented earlier in this

section. From 1960 to 1980, the expected coefficients for all the various race categories are

expected to be negative. After that, the expected signs for Asian decent categories were

switched to positive, as they tend to have economic success in the U.S. later in time. For the

age categories that were previously defined, the expected value for anything lower than the

constant, age 35-40 years old, is expected to be negative over time during this study.

36

But, the three age groups above the constant, 41 to 54 years old, the expected sign is positive

as wages tend to increase with age up until a certain point. Once the age categories that

encompass 55 years and older are reached, the sign is predicted to be negative.

The next set of à priori expectations are shown below (Table 2) for the second model and

considers the expected signs for the relationship between education attainment, age, and

income. Through the decades, a negative relationship is expected with any education level

lower than a high school diploma. Any education higher than a high school diploma is

expected to have a positive relationship with income. Aforementioned with the first model,

any age categories below the constant is expected to have a negative relationship with income.

The age groups containing the ages of 41 to 54 years old are expected to have a positive

relationship with income. Then, any age groups that are 55 years and older are expected to

have a negative relationship.

The third model (Table 3) and its à priori expectations are looking at the impact that gender

has on income. With males held constant, females are expected to have a negative coefficient

spanning the entire time period of this study. As past and current research suggest, women

typically earn less than men do. This is the reasoning behind the expected negative

coefficients for females over time.

37

The final set of à priori expectations are for the fourth model (Table 4) and looks at the

impacts that education attainment, race, gender, and age have on income. Interchangeable

with the expected signs discussed in the previous three models, the education categories, race

categories, and gender are expected to carry the same positive or negative relationship. The

addition of the age variable is expected to possess a positive relationship with income since

age tends to be a factor when analyzing income.

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6.3 Model Tests

The models used for analysis have now been defined and discussed, along with the expected

coefficient signs for each variable. The next task is to discuss the model tests used and what

the results were from the two tests used (appendix). The first model test used was the

variation inflation factor (VIF) test. This was performed in order to test for multicollinearity

and the VIF test runs simultaneous models, where each X is predicted by remaining X

variables (Helgertz 2017). If a high VIF figure is present, then there will be an issue with

multicollinearity, whereas if a value of one is calculated, then this is an indication of no

collinearity. The general rule of thumb is that if the VIF statistic reported is below five, then

the absence of multicollinearity is indicated. The second model tests used is the Breusch-

Pagan test and is ran for checking for heteroskedasticity, which can occur when the error is

linked to one or more of the variables in the model (Helgertz, 2017). If heteroskedasticity is

present, that can impact the standard errors and negatively impact the statistical inferences

that can be drawn from the results produced by the models used for regression. Both model

tests were performed for each of the four models formerly discussed, for each decade within

the period of study (1960-2010).

Following the model tests performed, several results need to be addressed. Within all four of

the models tested (appendix) it can be suggested that all VIF values calculated are low enough

to state that multicollinearity is not present within the regression analysis. As a result, the

OLS estimators will potentially not be subject to enlarged covariance and assures that the

standard errors will not experience increased statistical sensitivity within the model’s

application (Gujarati and Porter, 2009). Based off these findings, it is suggested that there is

an indication of no collinearity.

After performing the Breusch-Pagan test for heteroskedasticity (refer to appendix), it becomes

apparent that this is an issue within the models used for this analysis. Theory suggests that if

p<0.05, then the null hypothesis can be rejected and heteroskedasticity is present. For all four

models tested, the P value is lower than 0.05 and this suggests that heteroskedastic errors are

observed and the error terms do not have constant variance (Williams, 2015). These model

tests performed also resulted in high chi-squared values in which this also signals that

heteroskedasticity is present.

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7. Empirical Analysis

7.1 Costs Associated with the Middle Class

The outline of this research has been presented and discussed, which leads into presenting the

results from the regression analysis and data found regarding the prices of college tuition,

prices of cars, and prices for homes. Within this section, the results will be presented but a full

discussion will be applied in the following section, relating the results back to the original

research questions and the information presented in the literature review section. To

commence this section, the cost of a college education will be addressed first. Figure 7 and

figure 8 attempts to show how the cost of tuition has risen over time since 1964.

Figure 7. Average Cost of Tuition for All Universities (1964-2006), Current Dollars.

Source: National Center for Education Statistics

40

The data used for figure 7 encompasses the tuition costs for both public and private

universities, excluding the aspect if the university is in-state or out-of-state. Based on U.S.

standards, the results are to be expected regarding the differences in price for public and

private universities, as private universities have a higher tuition cost associated with them.

The import aspect of this figure is the steady increase in tuition costs for both types of

universities over time. Graphically, the data suggests that the average tuition costs in the

United States have risen and appears they will continue to increase in the future. Calculating

the percent change in average tuition cost from the data, from 1970 to 1980, the percent

change is 83.59% for all public universities. For the time period from 1980 to 1990, the

percent change for all public universities is 105.96% increase in cost. Lastly, from 1990 to

2000, the percent change is calculated at a 66.91% increase in cost. Similarly, figure 8 also

attempts to show the change it tuition costs, but this is limited to in-state tuition costs. With

in-state tuition being much cheaper, individuals tend to attend college in which state they

reside in.

Figure 8. Average Cost for In-State Tuition (1964-2006), Current Dollars.

Source: National Center for Education Statistics

41

A similar picture is represented and the graph suggests that the cost of tuition has risen over

time for in-state universities. Since a college education is a key factor in socioeconomic

mobility in the United States, the rising cost to achieve such a goal is becoming more

expensive and more difficult to reach. Calculating the percent change in average in-state

tuition cost from the data, from 1970 to 1980, the percent change is 91% for in-state public

universities. For the time period from 1980 to 1990, the percent change for in-state public

universities tuition is a 136% increase in cost. Lastly, from 1990 to 2000, the percent change

is calculated at an 84.26% increase in cost. Figures and percent change in costs were used for

public universities, as those are the predominate schools that individuals attend. As the two

figures suggest, tuition costs for private universities have grown at a faster rate.

The next cost that is typically associated with the U.S. middle class is the price of a new car.

Data used to create figure 9 (below) does not express such a drastic price increase as college

tuition did. Unless individuals reside in cities that provide sufficient means of public

transportation, a car is necessary in order to get to work. For this reason, the prices of cars

needed to be investigated and the following figures were found.

Figure 9. Average Price of a New Car (1960-2010), Constant 2013 Dollars.

Source: U.S. Department of Energy

After calculating the percent change in car price over the entire time period, 1960-2010, the

average price of a new car has risen by 20.2%. These figures attempt to confirm that the

42

average price of a new car has indeed increased over time, but the extent of the increase is not

as substantial as for other goods associated with the middle class.

The last cost that is typically associated with the U.S. middle class that needs to be addressed

is the cost of housing. Within this cost, two separate datasets are used and one provided data

for median sales price of houses sold for the U.S. (figure 10) from 1963 to 2010, while the

other supplied data for median home values (figure 11) from 1940 to 2000. Comparing the

results with figure 10, a steady growth in the sales price of homes can be observed. The only

major drop was at the end of 2007 and into 2009, in which can be connected to the 2008

recession. As observable in the graph below, there is not a period of stagnation in the sales

price, which raises concerns when comparing this rising cost with stagnating wages in the U.S

(figure 6).

Figure 10. Median Sale Price of Houses Sold (1963-2010), Not Seasonally Adjusted.

Source: U.S. Census Bureau

Data gathered to construct figure 11 (below) was limited but still serves as a supplementary

source on the topic of housing prices. The dataset provided the data that spans over five of the

six decades used for this analysis, but still captures the idea that housing prices have increased

compared to wages in the United States. Home values in the U.S. have continued to rise since

1960 and the largest spike appears to occur between 1970 and 1980. While between the other

decades, an increase was observed but not to the extent witnessed in this decade.

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Figure 11. Median Home Value (1960-2000), Adjusted to 2000 U.S. Dollars.

Source: U.S. Census Bureau

From 1970 to 1980, the median home value grew by 43.03% compared to the growth in home

value that occurred from 1960 to 1970, 1980 to 1990, and 1990 to 2000, respectively. Those

growth rates are 11.43%, 8.24%, and 18.3%. These findings suggest that regardless if the

selling price or the home value is used for analysis, increase in housing cost over time is

posited by the data and graphs.

7.2 Poverty, Middle-Class and Top 1% Status

Focus will now shift to results gathered through the analysis that was conducted within

STATA and look at the movement of households into poverty, out of the middle-class, and

into the top 1% of income earners. The first table presented in this section (table 5) expresses

the number of households within the dataset that are categorized as living in poverty, adjusted

by the CPI and poverty line provided by the U.S. Census Bureau. The table provides the total

number of households within the observed decade, along with the total number and

44

percentage of households that considered outside and inside the poverty bracket. Poverty

status is denoted as a 1, while above the poverty line is donated as a 0.

Table 5. Poverty Status (1960-2010).

Census Year 0 1 (Poverty) Total1960 10,221 (80.34%) 2,501 (19.66%) 12,722 (100%)1970 9,570 (86.47%) 1,498 (13.53%) 11,068 (100%)1980 8,632 (83.99%) 1,646 (16.01%) 10,278 (100%)1990 8,791 (84.25%) 1,643 (15.75%) 10,435 (100%)2000 9,121 (86.52%) 1,421 (13.48%) 10,542 (100%)2010 8,756 (84.58%) 1,597 (15.43%) 10,353 (100%)

Source: Authors Calculations (2017)

The data posits that there have not been large fluctuations when it comes to analyzing the

movement of households in and out of poverty. The largest shift occurs between 1960 and

1970, but based on conversations in earlier sections, this is to be expected. Based on previous

research, these numbers are well represented and the numbers are not misrepresentative of

what is occurring within the impoverished class. The fluctuations appear to relate to the

findings for the status of middle class (table 6), such as when the percentage of households in

poverty decrease, the percentage of households in the middle class rise. On the contrary, when

percentage of households in poverty increase, percentage of households in the middle class

decreases.

Table 6. Middle-Class Status (1960-2010).

Census Year 0 1 (Middle Class) Total1960 4,898 (38.50%) 7,824 (61.50%) 12,722 (100%)1970 4,115 (37.18%) 6,953 (62.82%) 11,068 (100%)1980 4,328 (42.11%) 5,950 (57.89%) 10,278 (100%)1990 4,995 (47.87%) 5,440 (52.13%) 10,435 (100%)2000 5,113 (48.50%) 5,429 (51.50%) 10,542 (100%)2010 5,472 (52.85%) 4,881 (47.15%) 10,353 (100%)

Source: Authors Calculations (2017)

Figures found within the analysis are reasonable since most movement of households in the

United States occur either moving up or down one class. Since this analysis only has three

defined classes, rather than including upper-middle and lower-middle class, it is easier to

move into poverty or into the middle-class rather than moving from middle class to top 1%.

45

By excluding the lower-middle and upper-middle status, shortcomings in the results from the

analysis arise but they were left out intentionally in order to perform a simpler analysis of the

middle-class and to group the middle-class as one, rather than three separate divisions.

Based on these figures, the data suggests that the middle class has shrunk since 1960 and for

the most recent year, 2010, less than half of the households within the sample fall into the

predefined middle class. Outside of its peak, referred to earlier as the Golden Age for the

middle-class, the middle class has continued to diminish. This leads into the final income

category that was used in this analysis, the top 1% of income earners in the United States

(table 7).

Table 7. Top 1% Status (1960-2010).

Census Year 0 1 (Top 1%) Total1960 12,552 (98.66%) 170 (1.34%) 12,722 (100%)1970 10,924 (98.70%) 144 (1.30%) 11,068 (100%)1980 10,138 (98.64%) 140 (1.36%) 10,278 (100%)1990 10,303 (98.74%) 132 (1.26%) 10,435 (100%)2000 10,384 (98.50%) 158 (1.50%) 10,542 (100%)2010 10,223 (98.74%) 130 (1.26%) 10,353 (100%)

Source: Authors Calculations (2017)

Although the figures for calculating the top 1% of households in terms of income will be

consistent since by definition, it’s limited to 1% of the population, it is still interesting to see

the number of households that are included in this elite class. Conclusion are difficult to be

drawn from this table, as the relationship between movement among this class and the

middle-class don’t interact like poverty and the middle-class status did. Regardless, the data is

relevant since economic classes are being discussed and analyzed in this paper. The last table

used in this section provides the median and mean household income (table 8) that was

generated from the dataset.

Table 8. Mean and Median Household Income (1960-2010).

Census Year Median Mean1960 30,628.75 33,704.381970 41,087.00 45,779.321980 44,052.53 48,184.441990 42,873.60 50,471.16

46

2000 45,000.00 56,645.142010 43,586.20 56,587.55

Source: Authors Calculations (2017)

Rather than relying on median household income data from other researchers or aggregated

data, this table allows comparisons to findings with this specific dataset and what other

researchers have found. Although the figures are not the same as what was presented in

previous sections, the data still suggests stagnation in median household income as there was

a huge increase from 1960 to 1970, but then fluctuates around similar values for the

remaining decades.

7.3 Regression Tables

The final results to present for this analysis consist of the regression tables for the four

separate models defined previously in the methodology section. The first table (table 9),

investigates the relationship between race, age, and household income, while controlling for

age. Included in the tables for all four models are the coefficients, standard error, and level of

significance for each variable and the number of observations (N), r-squared value, and the F

value for the entire model. This first model uses the race identifier, white, as the reference

category for the race variable and the reference category for age is group 3, 35 to 40 years old.

Observations within this model are totaled at 12,722 for 1960, 11,068 for 1970, 10,278 for

1980, 10,435 for 1990, 10,542 for 2000, and 10,353 for 2010. The r-squared value for each

decade represents what each x variable, race and age, explains the percent of the variation in

Y. For the decades of study listed in order, the r-squared values are 5.8%, 4.7%, 3.5%, 4.2%,

3.7%, and 4.3%. This value is low but only two variables are used in order to explain the

change in household income, which is to be expected.

The first race identifier in the regression table is Black. Over all decades, that race carries a

negative coefficient and the results are statistically significant at the 0.1% level. For each

decade, the figures for the income earned compared to Caucasians is -48%, -33%, -26%, -

29%, -25%, and -36%. The negative coefficient was expected for this race over time, but

these figures suggest a large earning gap between Caucasians and African Americans. The

47

second race identifier in the results is American Indian/Alaskan Native (AI/AN) and are all

negative coefficients and statistically significant at the 0.1% level. Within this analysis, this

race group has the largest earning deficit when compared to whites and results from the other

race identifiers. For each decade, they earn 66%, 71%, 44%, 35%, 35%, and 49% less than

whites. Again, the coefficients were expected to be negative, but not to this extent.

Chinese is the next race identifier analyzed and the coefficients vary year to year. From 1960

to 2010, the coefficients represent an earning difference of -40%, 20%, 15%, -21%, -4%, and

28% when compared to whites. The figure for 1960, 1990, and 2010 are a statistically

significant at the 5%, 10%, and 1%, respectively, while the other figures are not statistically

significant. In earlier decades, a negative coefficient was expected but as time moved on, a

positive one was expected and that is only partially the case suggested by the data. Filipino is

the next race identifier presented and was the most surprising results within this model. For

each decade, Filipinos earned 7%, -7%, 30%, 54%, 45%, and 35% more or less than whites

during this study. Figures for 1990, 2000, and 2010 have a significance level of 0.1% and 1%.

The other decades are not statistically significant. The Japanese race identifier follows and

suggests they earn 9%, 21%, 5%, 5%, -2%, and 44% more or less than whites. Only the

figures for 1970 and 2010 are significant at the 5% level, the rest are not statistically

significant. Based on previous assumptions made in the methodology section, this falls in line

with expectations. Other race, non-Hispanic is the next race in the regression results and carry

negative coefficients until 2000, and the values are -19%, -9%, -31%, -83%, 12%, and 28%

for each decade. Only the figure for 1990 is statistically significant at the 1% level, while the

rest are not significant. The significant value for 1990 is surprising as it is such a large

negative value and difference in income earnings when compared to the reference category.

The next race examined in the analysis is Korean and data for this group is missing for 1960.

For the other decades, the coefficients suggest a 70%, -41%, 8%, -34%, and 20% earnings

than that of whites. Values for 1980 and 2000 are statistically significant at the 1% and 5%

level, respectively. The values fluctuate drastically between decades, but majority are not

significant. Next is Pacific Islanders (PI) and the data is unavailable for 1960 as well. But for

the other decades, the coefficients represent a difference in earnings of 21%, -19%, -44%, 3%,

and -2% when compared to the reference category. Only the value for 1990 is statistically

significant at the 5% level. Other race, Hispanic is the next race identifier and the data is

unavailable for 1960 and 1970. For the remaining decades, the coefficients represent a -24%, -

48

23%, -24%, and -25% income when compared to whites. All figures for this race are

statistically significant at the 0.1% level.

49

Moving forward, the next race identifier is Asian Indian and the data was unavailable for

1960 and 1970. For the remaining decades, the coefficients are -17%, 61%, 13%, 60% and

these suggests that this group makes that percentage more or less than the white category. The

figures for 1990 and 2010 are statistically significant at the 0.1% level. The last race identifier

used for this model is Asian and the data was unavailable for 1960 and 1970. The coefficients

for the remaining decades are -25%, -24%, -19%, and 12% and the values for 1990 and 2000

are significant at the 5% level. This concludes all the values presented for the race identifiers

used in this model and regression.

Still within this model, age categories now need to be presented with their values. The first

age category, 25-29 years old, carries negative coefficients for all decades in the study. For

each, the values are -9%, -4%, -13%, -15%, -12%, and -19%. This suggests that individuals in

that age group earn that percentage less than those in the reference category. Coming out of

college or working with only a high school degree could be explanations for the negative

coefficients. All figures are statistically significant at the 0.1% level except for 1970. The next

age group, 30-34, carries all negative coefficients as well and are -3%, -10%, -4%, -6%, -4%,

and -9%, respectively. The years 1970, 1990, and 2010 are statistically significant at the

0.1%, 10%, and 5%. Still being relatively young, these results are to be expected. Next, is the

age group four, 41-44 years old and carry coefficients for each decade as follows: -1.2%, -

1.1%, 8.5%, 3.3%, 4.8%, and 2.5%. The only value of significance is for the year 1980 and is

significant at the 5% level.

The next age category, 45-50 years old, has coefficients for each decade that consists of -

6.5%, 0.07%, 9.2%, 11%, 13%, and 5%, with 1960, 1980, 1990, and 2000 being statistically

significant at the 5%, 5%, 1%, and 0.1% level, respectively. The following age category, 51-

54 years old, have coefficients of -9.3%, -6.6%, -0.7%, -4.7%, 10%, and 2.9%. These figures

show the percentage of income earned compared to the reference category, white. The values

for 1960, 1970, and 2000 are statistically significant at the 0.1%, 5%, and 5% level for those

three decades. The second to last age group, 55-60 years old, carry all negative coefficients

for each decade. Respectively, for each decade, they are -11%, -19%, -14%, -17%, -5.6%, and

-1.5%. The first four decades are statistically significant at the 0.1% level, but are not

statistically significant for the remaining two decades. Lastly, the age category of 61 years

and older are presented. All figures for each decade possess negative coefficients and are

50

statistically significant at the 0.1% level. The coefficients for each decade are -30%, -39%, -

37%, -38%, -37%, and -29%. The results for the two older age categories fall in line with

expectations and the results were predicted to carry a negative coefficient.

All variables and their coefficients, along with statistical significance, have been discussed for

the first model used in the regression analysis. The next model, investigating the relationship

between education attainment and household income, controlling for age, is presented in table

10, with the results. The base category for education level is a high school diploma and the

other are compared to that. The total number of observation for 1960 is 12,722, for 1970 is

11,068, for 1980 is 10,278, for 1990 is 10,435, for 2000 is 10,542, and for 2010 is 10,353.

The r-squared values for each decade are 7%, 9%, 7.2%, 8.8%, 9.1%, and 11.7%. Compared

to the previous model, these r-squared values are higher and suggest that education attainment

and age explains more variance in the Y value, income, than race and age do.

The first category is no schooling in which carries negative coefficients through the decades

and are -64%, -52%, -49%, -20%, -22%, and -16%. For 1960 to 1980, the values are

statistically significant at the 0.1% level. For 1990 and 2000, the significance level is 5%,

then 10% for 2010. With no schooling, individuals are expected to make this much less than

those with a high school degree and falls in line with expectations and past research. The next

category is some primary and again, carries negative coefficients through all decades and are

all statistically significant at the 0.1% level. For each decade, the coefficients are -36%, -34%,

-35%, -29%, -19%, and -20%. Again, with this low level of education, it is not surprising that

these individuals earn this percentage less than those with a high school diploma. The next

group consists of those with some high school education and possess negative coefficients

and are statistically significant at the 0.1% level for all decades. The coefficients are -13%, -

20%, -26%, -24%, -23%, and -35%.

Some college education is the next group, which carries all positive coefficients for each

decade. They are 3.2%, 16%, 8%, 22%, 23%, and 25%, being statistically significant at the

0.1% level for 1970, 1990, 2000, and 2010. For 1980, the level of significance is 1% while for

1960, the value is not statistically significant. The last education group used for this model,

college degree or higher, possess a positive correlation and is statistically significant at the

0.1% level for all decades. For each decade, the coefficients are 21%, 33%, 32%, 61%, 69%,

and 91%. For the previous two education categories, the values meet the expectations

51

mentioned in previous sections and those with the high level of education and expected to

earn more money than those with a high school diploma. Over time, the value of a high

school diploma has decreased and the value of a college degree has increased.

Within this same model, age categories were again used for analysis. Since majority of the

age categories carry the same sign, positive or negative, for the coefficient, the differences

will be discussed in the following section of the paper.

52

The next model tested (table 11) looks at the relationship between gender and income,

controlling for age. The reference category for this regression is male and the total

observations for each decade are 12,722 (1960), 11,068 (1970), 10,278 (1980), 10,435 (1990),

10,542 (2000), and 10,353 (2010). The r-squared values are extremely low compared to the

first two models, but this is a bivariate regression model and this was expected since it’s just

looking at the effects of gender on income. For females, the coefficients are all negative and

are statistically significant at the 0.1% level. The coefficients for each decade are -8%, -11%,

-10%, -10%, -10%, and -7%. These figures suggest that women earn this percentage less than

males do in terms of income for each decade. Based on knowledge of income gaps between

genders in the United States, these values were expected to be negative.

The last model used in this analysis consists of all the variables defined in the data section of

this paper and examines the relationship between education attainment, race, gender, age, and

household income. The results are posted below in table 12. The total number of observations

for this model are the same as the previous three models. The r-squared value for each decade

within this model is 10.24% (1960), 10.36% (1970), 7.94% (1980), 10.01% (1990), 9.97%

(2000), and 13.2% (2010).

53

54

The r-squared values for this model are higher than the rest, which was the goal since this

model contains all the explanatory variables that were discussed and defined earlier in the

paper. Similarly, to the three models tested previously, majority of the variables carry the

same sign, positive or negative, for the coefficients within the table. The figures are different,

but the trends are the same. As a result, the difference will be analyzed further in the

discussion section that follows. First, the values presented a reoccurring theme that appears

within all the models tested. Those with a college degree or higher earn more than those with

a high school diploma, or an education lower than that. By decade, other races except for

Asian descent, earn less than Caucasians. Spanning all decades, females earn less than males

and age has a positive coefficient in relation to income. Majority of these values fit in with the

expectations that were predicted in the methodology section, which is a positive.

In terms of results gathered through this analysis, a lot can be taken away from this study. A

more in depth discuss will take place next, but one major problem needs to be addressed first.

Considering the issues with heteroskedasticity that were mentioned in previous sections, the

accuracy of these results come into question. Improvements could be made to these models in

an attempt to resolve that issue, but transformations were made to the dataset in order to

combat such issues.

55

8. Discussion and Conclusion

This section will discuss the results found and relate them back to what researchers are

currently saying and have said in the past regarding the United States middle class and the

situation it is in. Relating back to the research questions purposed at the beginning, which this

analysis set out to attempt to answer, has succeeded in the attempt to do so. In relation to if

the U.S. middle class is shrinking and if so, to what extent, the results found within this study

posits that it is indeed shrinking and has been since 1970. Referencing figure 5 that was

mentioned in the background and literature view, the values constructed from the STATA

database are very similar, off by only a couple percentage points. In 1960, 61.50% of

households fell into the predetermined range to be labeled as middle-class members. There

was a small spike in 1970, up to 62.83%, then started decrease each decade until the last value

for 2010 was 47.15% of households that are considered middle class. Researchers have agreed

upon the statement that the U.S. middle class has been struggling and shrinking over the past

couple decades, but this study went back further in time to see to what extent. This paper used

multivariate regression analysis, along with bivariate regression to analyze the United States

middle class since 1960. Aggregated data was also used as supplementary data to support the

findings through the quantitative tests performed within STATA using a custom data base that

was provided as raw data. Transformations were made to the variables used in order to

attempt to create a reliable model that can provide reliable results.

The next question set out to examine the impact that variables such as gender, race, age, and

education attainment have on household income. Based off the findings suggested by the

regression analysis, all variable do indeed impact household income. For gender, females

have constantly made less than males for each decade and in every model, the results were all

statistically significant. With general knowledge and studies performed around the topic of

the gender pay gap, this was to be expected but was useful to see what the exact percentage

was for how much less they made than men through the decades. The same can be said when

looking at the effects that age has on income. The two lower age groups, encompassing ages

25 to 34, earned less for each decade in all the models tested. Excluding the ages 35-40, since

they were held constant and served as the reference categories, the next two age groups were

56

the ones that experienced a positive coefficient and earned more than the reference category.

Those ages are 41 to 50 years old. The last three age groups, 51 years and older, is where the

coefficients change to a negative value and the effect of age on income becomes apparent.

The results presented suggest that age does in fact have an impact on household income.

As for race, the results also suggest that race has an impact on household income. But, to what

extent and for which races were impacted the most. The black race identifier had a negative

coefficient for every decade and for every model ran. Similarly, American Indian/Alaskan

Natives also share the same experience, but possess much larger negative coefficients for each

decade. Race identifiers that include all Asian descent typically maintain a positive coefficient

for the second half of the decades (1990 to 2010), but negative coefficients in the first half of

the decades used in this analysis. Out of all the variables tested within the models presented in

this paper, education attainment appears to be the one that impacts household income the

most. For each education category in both models they were included in, the values were

statistically significant at the 0.1% level. Within both models, no schooling, some primary,

and some high school education, produced negative coefficient that were highly significant

for each decade. The values produced from the regression analysis for the education

categories, some college and college degree or higher, support the idea that higher education

is not only important in terms of income, but also for socioeconomic mobility. The positive

coefficients for college degree or higher are high within both models tested and increase over

time. These findings also suggest that the value of a college education has increased over time

and the difference in earnings between those education levels and a high school diploma are

drastic.

The third question set out to investigate the changes in prices of goods and services that are

associated with the middle class, specifically the price of homes, price of a new car, and

college tuition. The findings within this paper suggest that all of these prices have indeed

increased at a steady rate since 1960. Whereas when referring to figure 6 and median

household income, stagnation is apparent and this creates a strain on the U.S. middle class.

Connecting back to the previous paragraph and the importance of education level in relation

to income, the increasing costs to attend college is making it more difficult to achieve the

American Dream. The housing data provided and used in this analysis also suggests that those

prices have increased steadily since 1960, whereas the average prices of a new car has not

increased too much. The ability to maintain the middle-class status is becoming more difficult

57

over time and the percentage of households within this class posited by the data within this

analysis support that claim. Car and homeownership is also on the rise over the century and

are continuing to rise today. Having the means of transportation is important in the United

States as it is difficult to travel to work and/or school. There is of course the cheaper

alternative of purchasing a used car, as the average prices analyzed in this paper are for new

cars, but more maintenance and less reliability tend to be associated with used cars. In the

long run, that total can add up quickly and surpass the price an individual would pay for a

new car. Becoming a homeowner is another key aspect to the American dream and fitting into

the middle-class standard of living. As discussed in the previous section, the housing market

crashed due to the financial crisis in 2008, but the trend of increasing prices is back and are no

longer low. There are more aspects of the middle-class lifestyle outside of education,

homeownership, and owning a car, but these three are key attributes and assist in achieving

the middle-class status and obtaining the American dream.

The last question was to analyze the movement of household below the poverty line and into

the top 1% of income earners. Household within the data set that are considered to be in

poverty, lines up within current literature surrounding the topic. Other than the large drop

from 1960 to 1970, 19.66% to 13.53% of households in poverty, the figures rest around 13%

to 15%. A relationship between poverty status and middle class can be seen as poverty rates

increase, middle class status decreases. It is an interesting trend and one to be expected since

downward mobility is easier than upward mobility. Movement among the top 1% is difficult

to analyze since by definition, the top 1% of a population is consistent. An interesting aspect

to add to this study, data permitted, would look at the accumulation of wealth among

households in the top 1% rather than movement in or out of the class. That would also show

the effect of wealth accumulation for the middle class and where the economic gains in the

U.S. is going. But, that is just a suggestion for possible research.

In conclusion, the results suggest that the U.S. middle class is indeed shrinking and raises

concerns for the future of the class. The middle-class structure on a national level are

considered the backbone and without it, the economy would struggle as a whole. Only time

will tell what the United States middle class has in store for its future, but one can hope that

things will improve and the middle-class is able to recover from the issues presented within

this study. One thing to mention again refers to the model testing and issues with

58

heteroskedasticity. When that issue appears in model testing, it impacts the accuracy of the

results found and how reliable they are. Even though that issue arose when testing the models,

the results can still be presented and discussed. It is important to remember these shortcoming

within this analysis and needed to be addressed when considering all the results presented

here. This paper has attempted to show the associations between the various variables and

household income, rather than a causal relationship. With the research question discussed and

the results presented, this study has accomplished its task of setting out to attempt to answer

such question using a quantitative analysis. Interesting results were presented and this could

lead to more successful, useful research in the future. As discussed in previous sections, the

main issue is with data availability. The U.S. records do not go back far enough in time to do

a more thorough historical analysis, but with research within that field, more data could

become available for use in future research.

59

9. References

Andersen, K. (2015). The Best Decade Ever? The 1990s, Obviously. The New York Times. Available at http://www.nytimes.com/2015/02/08/opinion/sunday/the-best-decade-ever-the-1990s-obviously.html?_r=0 [Accessed 6 May 2016].

Average Undergraduate Tuition and Fees and Room and Board Rates Charged for Full-Time Students in Degree-Granting Postsecondary Institutions, By Level and Control of Institution: 1963-64 Through 2012-13. Available at http://nces.ed.gov/programs/digest/d13/tables/dt13_330.10.asp [Accessed 8 May 2016].

Beltz, T. (2012). "The Disappearing Middle Class: Implications for Politics and Public Policy". CMC Senior Theses. Paper. Available at 412. http://scholarship.claremont.edu/cmc_theses/412 [Accessed 15 June 2016].

Benoit, K. (2010). Ordinary Least Squares Regression. Quantitative Methods 1. Available at http://www.kenbenoit.net/courses/quant1/Quant1_Week8_OLS.pdf [Accessed 12 August 2016].

Blank, R.M. (2010). Middle Class in America (rep.). Middle Class in America. U.S. Department of Commerce Economics and Statistics Administration. Available at http://www.esa.doc.gov/sites/default/files/middleclassreport.pdf [Accessed 20 July 2016].

Brewer, M. (2012). Measuring Living Standards with Income and Consumption: Evidence from the UK. Institute for Social &Amp; Economic Research, 05, 1–35. Available through https://www.iser.essex.ac.uk/research/publications/working-papers/iser/2012-05.pdf [Accessed 20 July 2016].

Bruin, J. (2016). Newtest: Command to Compute New Test. UCLA: Statistical Consulting Group. Available at https://stats.idre.ucla.edu/stata/ado/analysis/. [Accessed 7 November 2017].

Bryan, M. (2013). The Great Inflation. Federal Reserve History. Available at http://www.federalreservehistory.org/Period/Essay/13 [Accessed 30 May 2016].

Burkhauser, R., Larrimore, J., & Simon, K. (2012). A “Second Opinion” On the Economic Health of the American Middle Class. National Tax Journal, 65(1), 7–32.

Clark. (2008). “Inside the Middle Class: Bad Times Hit the Good Live,” Pew Research Center, April 9. Available at http://pewsocialstrends.or/assets/pdf/MC-Middle-class-report.pdf [Accessed 13 July 2016].

Conte, C., Karr, A, & Clark, G. (2001). Outline of the U.S. Economy. Washington, D.C.: U.S. Department of State.

60

DeGrace, T. (2011). The Housing Market Crash of 2007 and What Caused the Crash. Available at http://www.stockpickssystem.com/housing-market-crash-2007/ [Accessed 24 June 2016].

Dezhao, C. (2006). The “Decline” of U.S. Economy: A Historical Comparison. China Institute of International Studies, 3. Available at http://www.ciis.org.cn/english/2011-11/18/content_4635120.htm [Accessed 13 June 2016]

Domhoff, W. G. (2013). Wealth, Income, and Power. Available at http://www2.ucsc.edu/whorulesamerica/power/wealth.html [Accessed 28 May 2016].

Elwell, C. K. (2014). The Distribution of Household Income and the Middle Class. Congressional Research Service, 1–7. Available at https://fas.org/sgp/crs/misc/rs20811.pdf [Accessed 15 July 2016].

Erickson, J. (2014). The Middle-Class Squeeze: A Picture of Stagnant Income, Rising Costs, and What We Can Do to Strengthen America's Middle-Class. Center for American Progress, 1–148.

Feulner, E. (2015). Reagan’s Tax-Cutting legacy. Commentary on Taxes, Tax Cuts, Tax Reform, Economy. Available at http://www.heritage.org/research/commentary/2015/7/reagans-tax-cutting-legacy [Accessed 27 July 2016].

Gallman, R. & Weiss, T. (1969). “The Service Industries in the Nineteenth Century.” In Production and Productivity in the Service Industries, ed. Victor R. Fuchs, 287-352. New York: Columbia University Press (for NBER).

Goldman, D. (2008). Work Harder, Take Home Less. CNN Money. Available at http://money.cnn.com/2008/08/27/news/economy/state_of_working_america/index.htm?cnn=yes [Accessed 28 July 2016].

Gujarati, D., Porter, D. (2009). Basic Econometrics. [Online]. 4th Edition. The McGraw-Hill Companies. [Accessed 16 August 2017]. Available from http://www.afriheritage.org/TTT/2%20Basic%20Econometrics%20-%20Gujarati[1].pdf

Hartmann, T. (2014). Reaganomics Killed America’s Middle Class. Salon Media Group. Available at http://www.salon.com/2014/04/19/reaganomics_killed_americas_middle_class_partner/ [Accessed June 18, 2016].

Helgertz, J. (2017). Multicollinearity and Heteroskedasticity. EKHM62 Econometrics. Lund University.

History and Timeline. (2013). Available at http://www.benefits.va.gov/gibill/history.asp [Accessed 16 June 2016].

Horrigan, M. & Haugen, S. (1988). The Declining Middle-Class Thesis: A Sensitivity Analysis. Monthly Labor Review, 3–13. Available at http://www.bls.gov/opub/mlr/1988/05/art1full.pdf [Accessed 14 June 2016].

61

Jahan, S. (2001). Measuring Living Standard and Poverty: Human Development Index as an Alternate Measure. Available through http://www.peri.umass.edu/fileadmin/pdf/gls_conf/glw_jahan.pdf [Accessed 20 July 2016].

Johnston, L. (2012). History Lessons: Understanding the Decline in Manufacturing. Minnesota Post. Available at https://www.minnpost.com/macro-micro-minnesota/2012/02/history-lessons-understanding-decline-manufacturing [Accessed 5 August 2016].

Kendrick, J. (1961). Productivity Trends in the United States. Princeton: Princeton University Press (for NBER).

Krugman, P. (2008). Debunking the Reagan Myth. The New York Times. Available at http://www.nytimes.com/2008/01/21/opinion/21krugman.html [Accessed 28 July 2016].

Kuhl, L. (2012). Maintaining a Nation's Middle Class in the Global Economy. World Future Review, 83–95.

Lebergott, S. (1966). Labor Force and Employment, 1800-1960. Output, Employment, and Productivity in the United States After 1800. Pg. 117-204. Available at http://www.nber.org/chapters/c1567.pdf

Mishel, L. (2015). Causes of Wage Stagnation (rep.). Causes of Wage Stagnation. EPI. Available at http://www.epi.org/publication/causes-of-wage-stagnation/ [Accessed 23 June 2016].

Mishel, L., Josh B., Elise G., and Heidi S. The State of Working America, 12th Edition. A Forthcoming Economic Policy Institute book. Ithaca, N.Y.: Cornell University Press.

Niskanen, W. & Moore, S. (1996). Supply-Side Tax Cuts and the Truth about the Reagan Economic Record. Policy Analysis, 261. Available at http://www.cato.org/publications/policy-analysis/supplyside-tax-cuts-truth-about-reagan-economic-record [Accessed 17 July 2016].

National Center for Education Statistics (2007). Average Undergraduate Tuition and Fees and Room and Board Rates Charged for Full-Time Students in Degree-Granting Institutions, by Type and Control of Institutions: 1964-65 Through 2006-07. Digest of Education Statistics. Available at https://nces.ed.gov/programs/digest/d07/tables/dt07_320.asp

Parsons, J. (2012). Real Estate Charts. Available at http://www.jparsons.net/housingbubble/ [Accessed 14 August 2016].

Pew Research Center Social and Demographic Trends. (2012). The Lost Decade of the Middle Class -Fewer, Poorer, Gloomier. Available at http://www.pewsocialtrends.org/files/2012/08/pewsocial-trends-lost-decade-of-the-middle-class.pdf [Accessed 2 August 2016].

Pressman, S. (2015). Defining and Measuring the Middle Class. American Institute for Economic Research, 1-27. Available at

62

https://www.aier.org/sites/default/files/Files/Documents/Standard/WP007-Middle%20Class.pdf [Accessed 23 June 2016].

Renwick, T. & Short, K. (2014). Examining the Middle Class in the United States Using the Lens of the Supplemental Poverty Measure. U.S Census Bureau, 1–15. Available at https://www.census.gov/hhes/povmeas/publications/other/renwick_short-spm.pdf [Accessed 23 July 2016].

Ruggles, S., Genadek, K., Goeken, R., Grover, J., Sobek, M. (2015). IPUMS-USA. Integrated Public Use Microdata Series: Version 6.0 [Machine-readable database]. University of Minnesota. Available through www.ipums.org [Accessed 24 May 2016].

Selgin, G. (2012). The Rise and Fall of the Gold Standard in the United States. 2012 Free Market Forum. University of Georgia. Available at https://www.hillsdale.edu/wp-content/uploads/2016/02/FMF-2012-The-Rise-and-Fall-of-the-Gold-Standard.pdf. [Accessed 18 October 2017].

Snyder, M. (2014). "Economic Recovery" for the U.S. Middle Class: Significantly Less Purchasing Power than Before the 2008 Financial Crisis. Available at http://www.globalresearch.ca/economic-recovery-for-the-u-s-middle-class-significantly-less-purchasing-power-than-before-the-2008-financial-crisis/5403937 [Accessed 28 July 2016].

Suddath, C. (2009). A Brief History of the American Middle Class. Time Magazine. Available at http://content.time.com/time/nation/article/0,8599,1882147,00.html [Accessed 23 July 2016].

Taylor, P., Taylor and Rich Morin, D’Vera, C. Fry, C., Kachhar, R. (2015). The American Middle Class is Losing Ground. Available at http://www.pewsocialtrends.org/2015/12/09/the-american-middle-class-is-losing-ground/ [Accessed 4 August 2016].

The Post-War Economy 1945-1960. (2012). The Netherlands. Available at http://www.let.rug.nl/usa/outlines/economy-1991/a-historical-perspective-on-the-american-economy/the-post-war-economy-1945-1960.php [Accessed 2 August 2016].

The Rich, the Poor and the Growing Gap Between Them. (2006). The Economist. Available at http://www.economist.com/node/7055911 [Accessed 28 July 2016].

Williams, R. (2015). Heteroskedasticity. Statistics. 30 January, University of Notre Dame.

U.S. Bureau of the Census. (2017). Median Sales Price of Houses Sold for the United States [MSPUS]. Federal Reserve Bank of St. Louis. Available at https://fred.stlouisfed.org/series/MSPUS

U.S. Census Bureau. (2012). Historical Census of Housing Tables. Housing and Household Economic Statistics Division. Available at https://www.census.gov/hhes/www/housing/census/historic/values.html

U.S. Department of Energy. Average Price of a New Car, 1913-2013. Available at cta.ornl.gov/data/tedb34/Spreadsheets/Table10_10.xls

63

U.S. Department of State: The Economy in the 1980s. Available at http://countrystudies.us/united-states/history-137.htm [Accessed 10 August 2016].

U.S. Department of State: The Postwar Economy: 1945-1960. Available at http://countrystudies.us/united-states/history-114.htm [Accessed 18 October 2016].

Webmaster, S. (2016). Comparison of Prices Over 70 Years. Available at http://www.thepeoplehistory.com/70yearsofpricechange.html [Accessed 28 July 2016].

Weinberg, M. (2002). A Short History of American Capitalism. United States. Print.

Williams, G. (2014). “What It Means to Be Middle Class Today -Middle class might be the new poor” U.S. News and World Report. April 24. Available at http://money.usnews.com/money/personalfinance/articles/2014/04/24/what-it-means-to-be-middle-class-today [Accessed 29 July 2016].

Worldwide Inflation Data. (2017). Historic Inflation United States-CPI Inflation. Available at http://www.inflation.eu/inflation-rates/united-states/historic-inflation/cpi-inflation-united-states.aspx

2000 Census Results: Housing Trends 1990-2000. Available at https://www.huduser.gov/periodicals/ushmc/summer2001/summary-2.html [Accessed 14 July 2016].

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10. Appendix

Figure 12. Histogram Showing Income Distribution in 1960.

65

Figure 13. Histogram Showing Income Distribution in 1970.

Figure 14. Histogram Showing Income Distribution in 1980.

66

Figure 15. Histogram Showing Income Distribution in 1990.

Figure 16. Histogram Showing Income Distribution in 2000.

67

Figure 17. Histogram Showing Income Distribution in 2010.

Figure 18. Coefficients of All Races and Income (1960-2010) With Standard Error Bars.

Black

AI/AN (A

meric

an Indian/Alask

an Nativ

e)

Chinese

Filipin

o

Japanese

Other R

ace, n

on-Hisp

anic

Korean

PI (Pacif

ic Isl

ander)

Other R

ace, H

ispanic

Asian In

dianAsia

n

-2

-1.5

-1

-0.5

0

0.5

1

Coefficients of All Races and Income (1960-2010)

1960 1970 1980 1990 2000 2010

68

Figure 19. Coefficients of All Education Categories and Income (1960-2010) With Standard Error Bars.

1960 1970 1980 1990 2000 2010

-1.2

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

Coefficients of All Education Categories and Income (1960-2010)

No Schooling Some Primary Some High School

Some College College Degree or Higher

YEAR

Coef

fici

ent

Figure 20. Coefficients of Gender and Income (1960-2010) With Standard Error Bars.

1960 1970 1980 1990 2000 2010

-0.14

-0.12

-0.1

-0.08

-0.06

-0.04

-0.02

0

Coefficients of Sex (Female) and Income (1960-2010)

YEAR

Coef

fici

ent

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Table 13. Model 1 Test Results: Relationship Between Race, Age, and Income.

Table 14. Model 2 Test Results: Relationship Between Education Attainment, Age, and Income.

Table 15. Model 3 Test Results: Relationship Between Gender and Income.

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Table 16. Model 4 Test Results: Relationship Between Education Attainment, Race, Gender, Age, and Income.

Table 17. Unadjusted Relationship Between Race, Age and Household Income, Controlling for Age.

71

72

Table 18. Unadjusted Relationship Between Education Attainment and Household Income, Controlling for Age.

Table 19. Unadjusted Relationship Between Gender and Household Income, Controlling for Age.

73

Table 20. Unadjusted Relationship Between Education Attainment, Race, Gender, Age, and Household Income, Controlling for Age.

74

75