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Effect of Income Level on Academic Success

Introduction
I’ve read and analyzed several studies that argue whether or not family income level directly affects academic success. And there still stands a discrepancy on whether or not there is a direct negative correlation between the two. One lingering inconsistency and gaps in previous literature is what unit of analysis should be observed to signify Academic success. Many different studies have utilized different units to display their respective stances on the relationship between family income and Academic success. This issue was brought to my attention in particular because I, myself came up in a low-income/ poverty level family, yet I am now in my fourth year here at The University of Texas at Austin, and on to track to graduate due to academic success throughout the years.
The dependent variable of interest is academic success as I am looking at how students’ academic success levels correlate and are affected by other variables. I will signify the dependent variable of academic success with the college attendance rates by city as this will show how many individuals go on to attend college as that can be referred to a signal of academic success. The independent variable of interest is Family Income. I will signify low family income percentage by the child poverty rate as that will represent the percentage of individuals whose household income lies less than $23,624. The purpose of this study is to investigate the effect of family income on student achievement. The hypothesis for this research is about students who have higher families income are having better education than those who have lower income. The research question of this study is “ Is there a relationship between income level (child poverty rate) and student achievement (college attendance)?” The unit of analysis in my research is going to be the percentage of students that make it to college.
Literature Review
The most recent piece of literature I reviewed, released in 2017, was written by Han Lv titled “ The effects of family income on children’s education: An empirical analysis of CHNS data”. This study analyzed the relationship between family income and concluded that Family income has significant impacts on children’s educational level, which is assumed to be elevated with the increasing income. A financially well-off family is able to give more, especially educational resources. The study stated ,“For lower-income families, parents are bustle around for life and expect little from their kids, and moreover they may put subsistence before children’s learning.” This also means those who yearn for the improvement of their life by studying hard are naive as the bar is raising and the income gap is widening. On that account, governments should provide more fair education opportunities and subsidies in order to cut down the inequality of intergenerational transmission. (Lv, Han. (2017)).
The second most recent piece of literature I reviewed ,released in 2011, was written by Laura D. Lissington titled “This study analyzed the relationship between income level and percentile among students in assessments from the ECLS database poverty significantly affects the resources available to students. Due to this lack of resources, many students struggle to reach the same academic achievement levels of students not living in poverty. The factors affecting student achievement include income, source of income, and the mother’s education level. The study stated, “Although many poor students score below average on assessment measures, instructional techniques and strategies implemented at the classroom, school, district, and government levels can help close the achievement gap by providing students with necessary assistance in order to achieve high performance in academics. “(Tissington, D. Laura (2011)).
The third most recent piece of literature I reviewed, released in 2009, was written by Kazim Celik titled “ The relationship between the students’ academic achievement and their socioeconomic level: cross regional comparison”. This study analyzed the relationship between family household income and achievement scores in math reading and science across various regions. The study concluded that Several of the studies state that many of the variables related with family affect students’ academic achievement. In general, the results of the study also support those studies. However, familial variables show differences in their effects on different academic achievement fields. Generally, familial variables have the highest effect on math and the least effect on reading academic achievement of 15-year-old students. The study stated ,”When a cross regional comparison is made, familial variables have the most meaningful effect on mathematics achievement of 15-year-old students living in Aegean region and the least meaningful effect on mathematics achievement of 15-year-old students living in South East Anatolian region. Familial variables do not have a meaningful effect on academic achievement of 15-year-old students in East Anatolian region”. And so, as regional developmental level decreases, effects of familial variables on academic achievement decrease, too. In East Anatolian and South Anatolian regions, the education levels and annual average income levels of the families are low, at the same time, mathematics, reading and science achievement levels of 15-year-old students living in those regions are also low. All in all, it came to the conclusion that regional affiliations didn’t alter the fact that the variable of family income did have an effect on student achievement.
The fourth most recent (least recent) and final piece of literature I reviewed, released in 2008, was written by Lance Lochner titled “The Impact of Family Income on Child Achievement; Evidence from the Earned Income Tax Credit”. This study analyzed the relationship between family income and scholastic achievement in math and reading standardized scores. The study concluded that the IV results indicate that current income has significant effects on a child’s math and reading test scores. The study stated, “The baseline estimates imply that a $1,000 increase in income raises contemporaneous math and reading test scores by 6% of a standard deviation. Over the entire sample period (1987–1999), the median EITC payment for eligible two-child families increased by $1,670 (in year 2000$), implying an average test score increase of 10% of a standard deviation for this group” . This was one of the more strong correlations compared to the other studies as this one displayed the greatest degree of impact between the variables. (Lochner, Lance. (2008).)
Of the literatures reviewed, they weren’t all able to come to an exact agreeing result as some suggest that the family income has greater affects than shown in alternative studies as the studies all analyzed different units of analysis. Some studies suggest a moderate effect while other studies I reviewed suggested significant effects. So moving forward my study I will conduct will fight to erase some of those discrepancies and confirm or reestablish the true effects of family income on student achievement and to what degree. I will do so by looking at a different signal for income level by looking at child poverty rates and a different signal for academic success being college attendance rates.
Empirical Model
Linear regression is used to estimate the relationship between city College attendance rates and city child poverty rates. In this paper we estimate the following regression model:
College Attendance = ? ?
1ChildPoverty. ?2%SingleParents ?3Race ?
In the model above, College attendance measures the proportion of the population that moved forward to College after graduation. Child Poverty measures the proportion of the population that had a household income of less than 23,624 dollars as a child.
The “%SingleParents” variable Measures the amount of children with single parents. The Race coefficient measures the proportion of the city population that is either black, Asian, or other as it is broken up into three dummy variables.
This study uses publicly available state-level data. The data source for College Attendance is based on the data from the 2000 Decennial Census. The data is available at https://www.brookings.edu/wpcontent/uploads/2018/03/es_20180314_looneyincarceration_final.pdf.
The dependent variable of interest is academic success as I am looking at how students’ academic success levels correlate and are affected by other variables. I will signify the dependent variable of academic success with the college attendance rates by city as this will show how many individuals go on to attend college as that can be referred to a signal of academic success. The independent variable of interest is Family Income. I will signify low family income percentage by the child poverty rate as that will represent the percentage of individuals who’s household income lies less than $23,624.
TABLE 1
City
College attendance
ChildPoverty Rate
%single Parents
% Black
%Asian
%Other Race
Waco, Texas
24.0%
35.0%
12.0%
34.0%
0.0%
22.0%
Dallas,Texas
19.0%
47.0%
27.0%
85.0%
0.0%
8.0%
Tulsa, Oklahoma
29.0%
41.0%
10.0%
80.0%
0.0%
9.0%
Orlando, Florida
24.0%
42.0%
10.0%
79.0%
0.0%
6.0%
Syracuse, New York
32.0%
32.0%
12.0%
50.0%
2.0%
6.0%
La jolla, California
85.0%
8.6%
20.0%
1.0%
11.0%
5.0%
Winfield, Illinois
65.0%
50.0%
10.0%
3.0%
3.0%
3.0%
Portland Oregon
81.0%
1.9%
16.0%
1.0%
3.0%
5.0%
Mineapolis, Minnesota
82.0%
2.8%
12.0%
2.0%
5.0%
2.0%
Apline, Utah
76.0%
3.1%
7.0%
0.0%
0.0%
2.0%
Wyckoff, New Jersey
71.0%
1.2%
8.0%
0.0%
4.0%
1.0%
Moraga, California
86.0%
3.5%
13.0%
1.0%
13.0%
5.0%
Medfield, Massachusetts
78.0%
1.3%
10.0%
1.0%
2.0%
1.0%
Grossse Ile, Michigan
70.0%
2.2%
11.0%
0.0%
3.0%
2.0%
Alamo, California
85.0%
4.1%
9.0%
0.0%
6.0%
3.0%
Rye, New York
82.0%
2.2%
10.0%
1.0%
6.0%
2.0%
Princeton Junction, New Jersey
86.0%
2.6%
7.0%
3.0%
24.0%
2.0%
Jericho, New York
89.0%
4.8%
6.0%
1%
10.0%
1.0%
Mill Valey, California
78.0%
4.1%
20.0%
1%
5.0%
4.0%
Summit,New Jersey
75.0%
3.9%
12.0%
4%
5.0%
3.0%
Logmeadow, Massachussets
78.0%
0.3%
11.0%
1%
3.0%
1.0%
Northborugh,
Massachussets
69.0%
2.2%
16.0%
1%
5.0%
1.0%
Winnetka, Illinois
88.0%
1.8%
10.0%
0%
3.0%
2.0%
Englewood, Colorado
87.0%
2.0%
16.0%
2%
5.0%
3.0%
Brimingham, Michigan
85.0%
2.7%
18.0%
1%
2.0%
1.0%

Variable Obs Mean Std. Dev. Min Max

Collegeatt~e 25 .6896 .2307683 .19 .89
ChildPover~e 25 .12092 .1703643 .003 .5
sSinglePar~s 25 .1252 .0486587 .06 .27
Black 25 .1408 .2785217 0 .85

Asian 25 .048 .0524404 0 .24
OtherRace 25 .04 .0436845 .01 .2
Table 1 above summarizes the previous dataset that shows a wide variety of college attendance rates. Attendance rates range from 19 percent to 89 percent with a mean of 68.96 percent. The dataset is a random sample taken through random survey. Child poverty rates range from .3 percent to 50 percent of the city population. The unit of analysis is percentage points. The percentage points of single parents in given cities range from 6 percent to 27percent.
Empirical Results
The regression results in Table 2 below display that child poverty is an important determinant of College attendance rates. Higher rates of child poverty lead to lower rates of college attendance. When the rate of child poverty increases by 1 percent, college attendance decreases by 26.6 percent.
TABLE 2
Source SS df MS Number of obs = 25
F(5, 19) = 50.53
Model 1.1886962 5 .237739239 Prob > F = 0.0000
Residual .089399804 19 .004705253 R-squared = 0.9301
Adj R-squared = 0.9116
Total 1.278096 24 .053254 Root MSE = .06859

Collegeatte~e Coef. Std. Err. t P>t [95% Conf. Interval]

ChildPovert~e -.2659421 .1525416 -1.74 0.097 -.5852152 .053331
sSinglePare~s .2313353 .2993839 0.77 0.449 -.3952824 .857953
Black -.4802612 .0905258 -5.31 0.000 -.6697339 -.2907885
Asian .6866067 .2950486 2.33 0.031 .0690629 1.30415
OtherRace -1.212924 .4026774 -3.01 0.007 -2.055737 -.3701106
_cons .7759752 .0454262 17.08 0.000 .680897 .8710533
Other important determinants of obesity rates includes race. For instance you can compare the fact that Black has a coefficient of -.48 as to where Asian has a coefficient of .69. This displays that race has a negative correlation when it comes to black people yet when it comes to Asian people there is a positive correlation.
Conclusions and Policy Implications
Empirical results show that the rate of child poverty in a given city is an important determinant of college attendance rates for that city. Therefor reducing rates of child poverty needs to be an important focus for our country.
Moving forward this study is significant because it can better display the negative impacts of low income/ high poverty levels on students and how it can lead to a higher chance of lack of success in academics. This can then ensure that governments should act as a designer for the entire process of educational system and the policy of fair education, to ensure the equitable distribution of educational resources in particular. Relevant authorities are supposed to further develop the urban-rural educational industry in local area, so that the rural and underdeveloped regions are able to enjoy high-quality teaching resources. Our government needs to and should step in to address this policy in order to help lower income students overcome the given setbacks coming from a low income background. With this knowledge we can put forth policies to help our lower income level citizens succeed academically, attend college, and achieve great things.
References
Lv, Han. (2017). “The effects of family income on children’s education: An empirical analysis of CHNS data”. Research on Modern Higher Education. 4. 49-54. 10.24104/rmhe/2017.04.02002.
Tissington, D. Laura (2011). “The effects of poverty on academic achievement.”
University of West Florida, Educational Research and Reviews Vol. 6.
Celik, Kazim. (2009). “The relationship between the students’ academic achievement and their socioeconomic level: cross regional comparison”. Pamukkale University, World Conference on Educational Sciences.
Lochner, Lance. (2008).” The Impact of Family Income on Child Achievement; Evidence from the Earned Income Tax Credit”. National Bureau of Economic Research, NBER Working Paper Series.
Decennial census (2000). “Family income and disadvantage in childhood”. Economics Studies at Brookings.

What Is City College of San Francisco Doing to Assist Women with Body Image Issues?

What is city college of San Francisco doing to assist women with body image issues and how does it impact their chances of success?
The pressure from the media and magazines for women to be thin is overreaching. Women pay the price for focusing on their magazines filled with thin and half hungry women. With body image negatively impacting women and their success, institutions like City college of San Francisco helps students by providing services according to their individual needs.
Body image plays a vital role on how one sees themselves and how development influences certain thoughts about oneself. ResearchGate defines it as, “a merging of one’s outer appearance with perceptions derived from personal and cultural factors; body image is a multidimensional construct that is influenced by biological, psychologic, and social factors.” An individual sees themselves through many facets, how you feel and conduct yourself maybe from culture and or biology. It is not just one influence, environmental and biology plays a role. We must also include psychological factors of how a person thinks about themselves and social factors of how individuals interact with each other.
Women with body image issues were sometimes told as a child or an adolescent by parents that they need to lose weight when they didn’t need to and according to ResearchGate it may lead to body dissatisfaction. To better understand what it is The National Eating Disorders Collaboration defines it as, “When a person has negative thoughts and feelings about his or her own body, body dissatisfaction can develop.” Body image issues goes deeper than what we see, it can occur overtime and it can be influenced by parents and love ones. Parents aren’t perfect and the media may have an effect on them and in turn they may encourage their kids to lose weight. As a result it encourages the adults to try to become thin and in doing so they are enforcing an already unhealthy message that may signal to their kids that they aren’t loved and or appreciated in their own skin.
Magazines play an important role on how women sees themselves, because they want to imitate those ultra-thin women that they see and that is not helping women with body image issues because it is somewhat unrealistic look. Women purchase magazines to see what is in style or in fashion for the season and the magazines may seem innocent but is not always so, that perfect ideal can get obsessive for some girls. Additionally according to Chapman, “When women do not naturally fit the standard or do not constantly strive to fit the standard, they are considered to have failed themselves, and most often, are told that they should be ashamed.” The media has presented the ideal woman who is perfect in every way in her appearance but the ideal look isn’t achievable yet vulnerable women and teens are attached to these fables of this perpetuated lie. Women and girls are then feeling rejected for not having that ideal look that they are striving for but it’s not attainable because everyone is made differently.
How we think about our bodies is important and it directly affects our daily activities whether we know it or not, hence having a healthy mind is very vital to our day to day survival. A woman with body issues may find it difficult to dress herself because of her lack of confidence in her appearance and as a result she may spend hours just looking in the mirror to find faults. Another issue is that she may be meticulous about what to wear, she would nitpick about what dress seems perfect to everyone else but not to her and she may feel less confident than other women. For example, a woman with body issues may spent most of her morning getting dress and finding it difficult to find something to wear but in her eyes nothing is perfect. Women with body issues has these daily problems due to the fact that they cannot make a decision because of how they view themselves.
It is especially challenging for women with body issues in a competitive environment such as a college or university because it is difficult for women suffering with negative thoughts of their own perceptions of themselves to integrate into a social environment of the classroom and this exposure can lead to them being ridiculed or feeling insecure. For example, a woman who has body image issues may feel less confident in her appearance than her peers and she may become withdrawn especially when socializing or interacting in a classroom setting or even going to the school’s restroom because of the mirrors or the presence of other schoolmates. She may also have difficulties eating in public because she may have developed an eating disorder, which The National Eating Disorders Collaboration states that it may occur because of, “overvaluing body image in defining ones self-worth…” Women who has the need to be accepted no matter what and defining their self-worth through magazines can be dangerous. Especially when they are being described as fat and are seeing themselves with flaws that are not there or emphasizing on slight imperfections. This is where schools and other educational institutions need to shine because they are enrolling women who may have body image issues who need the help.
Institutions such as the City College of San Francisco has facilitated the need for students with body image issues according to theirTitle IV-E Training Topics section of their website, under their subsection of Psychological, Social,

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