Write a five-page paper covering a federal social welfare problem policy approach on Housing Choice Voucher In addition to our course readings, you will need to review the lite

Instructions Write a five-page paper covering a federal social welfare problem policy approach on Housing Choice Voucher In addition to our course readings, you will need to review the literature on the social issues or problems you select in order to respond to some of the requirements below. Include the following in your submission:

Introduction Provide an introduction that identifies and succinctly summarizes the policy.

Body of Paper ● Analyze a current federal policy's effectiveness with respect to the chosen

issue or problem. ● Synthesize historic and current public opinion in response to the federal

policy. ● Describe what is working and for whom with the current policy. ● Analyze the current policy’s impact on family structure and family life. ● Discuss the flaws in the existing policy, including some reasons why it does

or does not work.

Conclusion Provide a succinct conclusion that highlights the key points of your discussion.

Additional Requirements ● References: Include a minimum of seven peer-reviewed journal articles.

Only one can be older than five years. (Please see attached the list of peer-reviewed journal articles to be used)

● Length of paper: Approximately five pages, not including cover and references.

● Communication: Communicate in a manner that is scholarly, professional, and respectful of the diversity, dignity, and integrity of others, consistent with expectations for members of the human services profession. Written communication should be free of errors that detract from the overall message.

● APA style and format: Use appropriate APA style and formatting for citations and references.

The Effect of the Earned Income Tax Credit on Housing and Living Arrangements

Natasha Pilkauskas1 & Katherine Michelmore2

Published online: 17 June 2019 # Population Association of America 2019

Abstract As rents have risen and wages have not kept pace, housing affordability in the United States has declined over the last 15 years, impacting the housing and living arrange- ments of low-income families. Housing subsidies improve the housing situations of low-income families, but less than one in four eligible families receive a voucher. In this article, we analyze whether one of the largest anti-poverty programs in the United States—the Earned Income Tax Credit (EITC)—affects the housing (eviction, home- lessness, and affordability) and living arrangements (doubling up, number of people in the household, and crowding) of low-income families. Using the Current Population Survey, the American Community Survey/decennial census, and the Fragile Families and Child Wellbeing Study, we employ a parameterized difference-in-differences strategy to examine whether policy-induced expansions to the EITC affect the housing and living arrangements of single mothers. Results suggest that a $1,000 increase in the EITC improves housing by reducing housing cost burdens, but it has no effect on eviction or homelessness. Increases in the EITC also reduce doubling up (living with additional, nonnuclear family adults)—in particular, doubling up in someone else’s home—and reduce three-generation/multigenerational coresidence, suggesting that mothers have a preference to live independently. We find weak evidence for a reduction in overall household size, yet the EITC does reduce household crowding. Although the EITC is not an explicit housing policy, expansions to the EITC are generally linked with improved housing outcomes for single mothers and their children.

Demography (2019) 56:1303–1326 https://doi.org/10.1007/s13524-019-00791-5

Electronic supplementary material The online version of this article (https://doi.org/10.1007/s13524-019- 00791-5) contains supplementary material, which is available to authorized users.

* Natasha Pilkauskas [email protected]

Katherine Michelmore [email protected]

1 Gerald R. Ford School of Public Policy, University of Michigan, 735 S. State Street, Ann Arbor, MI 48109, USA

2 Maxwell School of Citizenship and Public Affairs, Syracuse University, 426 Eggers Hall, Syracuse, NY 13244, USA

Keywords EITC . Housing . Living arrangements . Doubling up . Household instability

Introduction

Stable housing is crucial to the physical, emotional, and economic well-being of individ- uals and families (e.g., Bratt 2002; Leventhal and Newman 2010). Housing affordability in the United States has declined over the last few decades, impacting the housing and living arrangements of low-income families (Desmond 2016; Joint Center for Housing Studies (JCHS) 2017). Housing subsidies for low-income renters, such as housing choice vouchers, are effective at improving housing outcomes (e.g., Ellen 2017), but only 24 % of the 19 million eligible households receive assistance, and wait lists for housing assistance are frequently two to three years long (Leopold et al. 2015). Understanding how other poverty-related public policies, such as the Earned Income Tax Credit (EITC), might affect the housing and living arrangements of low-income families with children is of vital importance. By understanding whether the EITC affects housing outcomes, such as homelessness, affordability, and living arrangements, we can consider whether expan- sions to the EITC might improve the housing of low-income families.

The EITC may affect the housing of low-income families in a number of ways. First, as one of the largest cash transfer programs in the United States, it provides low-income families with cash that can be used on housing: an average of more than $3,000 for families with children (Center for Budget and Policy Priorities 2018). Second, the EITC has been shown to increase employment and long-term earnings (e.g., Dahl et al. 2009), which in turn may increase income, thus affecting housing and living arrangements. Last, the EITC is distributed as a lump sum payment, which may provide households with cash needed for a security deposit or the ability to prepay a few months of rent. Despite the EITC’s potential to positively impact housing and living arrangements, no quantitative research to date has examined this link.

Exploiting federal, state, and family size variation in the generosity of the EITC over the last three decades, we examine the effect of the EITC on housing outcomes and the living arrangements of single mothers. We use data from three sources—the Current Population Survey, the American Community Survey/decennial census, and the Fragile Families and Child Wellbeing Study—to examine a variety of housing outcomes, employ different methodological approaches, and address data limitations in each data set. Using a parameterized difference-in-differences approach—similar to a traditional difference-in-differences analysis but allowing us to exploit variation in the many EITC policy changes over time—we study a number of housing and living arrangement outcomes that have been linked in prior research with the health and well-being of families. Specifically, we study whether expansions to the EITC affect homelessness and eviction; cost burden (share of earnings paid on rent/mortgage); and living arrangements, including doubling-up (living with additional nonnuclear family adults), multigenerational households (coresident grandparent, parent, and child), household size, being named on the lease or mortgage, and household crowding. We focus our analysis on single mothers, the primary recipients of the EITC (Tax Policy Center 2006), who are most likely to experience poor housing outcomes (JCHS 2017) and whose children may be particularly vulnerable to any detrimental impacts of housing instability (e.g., Ziol-Guest and McKenna 2014). Overall, this study broadens our

1304 N. Pilkauskas, K. Michelmore

understanding of how the EITC affects the housing and living arrangements of low- income families, informing future policy proposals to further expand the credit.

Background

The Earned Income Tax Credit

The EITC began in 1975 as a temporary credit (made permanent in 1978) for low- income parents, intended to offset payroll tax contributions. The credit is fully refund- able, which means that households with no tax liability can still receive the credit in the form of an income tax refund. The benefit schedule has a trapezoidal structure, with benefits phasing in up to a threshold, remaining constant over some values of income (plateau), and then phasing out for earnings beyond a second threshold. Over the last few decades, there have been several expansions to the federal credit, including increases to the phase-in rate and expanded benefits for families with two or more children. In 2009, a benefit for three or more children was introduced. Between 1975 and 2016, the maximum federal EITC grew from $1,700 to $6,300 (2016 dollars).

In addition to the federal EITC, 26 states and the District of Columbia had their own EITCs as of 2016 (see Table A1, online appendix, for more detail). States with EITCs can be found in all regions of the country and across the political spectrum. Several large-population states have EITCs (e.g., New York, California, and Illinois), whereas other large-population states do not (e.g., Texas, Florida, and Pennsylvania). Most state EITCs are structured as fixed percentages of the federal benefit, supplementing the credit for residents filing taxes in those states. Benefit generosity currently ranges from 3.5 % up to 43 % of the federal credit, and most state credits are refundable. States vary in when they implemented EITCs, with the earliest states implementing EITCs in the mid-1980s and the most recent states implementing policies in 2017. Several states changed the generosity of their benefits over time, most becoming more generous; however, some have also decreased generosity.

The year that a state enacted an EITC and the generosity of state EITC benefits are sources of between-state variation. Within-state variation in EITC benefits arises as states implement, expand, and reduce their programs over time. Additionally, any federal changes to the EITC also impact states that have their own EITCs, creating an additional source of between and within state variation over time. We use this federal and state variation over time to examine whether the EITC is linked to housing and living arrangements.

Why Might the EITC Affect Housing Outcomes and Living Arrangements?

We expect the EITC to affect housing and living arrangements because it increases disposable income, increases labor supply and earnings, and provides families with a lump sum payment that might be used for housing. This increased income leads to three specific hypotheses related to how the EITC might influence housing and living arrangements:

Hypothesis 1: The EITC will likely reduce homelessness and eviction/ foreclosures.

The Effect of the EITC on Housing and Living Arrangements 1305

Research has found that income transfers reduce homelessness/eviction (e.g., Evans et al. 2016); thus, we expect an increase in the EITC to have a similar effect. However, it is also possible that the EITC will not affect homelessness or eviction given that individuals can receive the EITC only if they are employed, and research has shown the EITC does little to assist those at the very bottom of the income distribution (below 50 % of the poverty line; Hoynes and Patel 2018). If mothers who are homeless or evicted are unemployed or have very low incomes, then expansions to the EITC may do little to reduce these severe forms of housing instability.

Hypothesis 2: The EITC should reduce the share of mothers who are cost- burdened.

The increased income from the EITC should reduce the share of mothers who report paying more than 30 % (or 50 %) of their earnings on rent/mortgage. However, if receipt of the EITC leads mothers to move into more expensive housing (say, in a better neighborhood) or move others out of their homes, then their cost burden may be unchanged or even worsen.

Hypothesis 3: Increased income from the EITC is likely to lead mothers to reduce shared living arrangements, decreasing household size and crowding.

Increased income from Social Security expansions reduced shared living arrange- ments (Carlson et al. 2012; Engelhardt et al. 2005), and mothers have reported that living in someone else’s home is challenging because it conflicts with their ideals and identities (Harvey 2017). Thus, on average, we expect that the EITC will reduce shared living arrangements, especially doubling up in someone else’s home, which in turn will reduce household size and crowding. However, it is also possible that the increased income from the EITC will increase doubling up among single mothers if they end up supporting other economically disadvantaged friends and family (low-income mothers are typically embedded in homophilous networks; Smith et al. 2014).

Prior Research

Although no quantitative research has examined if the EITC is linked to housing and living arrangements, a number of studies have explored links between these outcomes and income-related policies.1 Qualitative research has suggested that low-income families rely heavily on the EITC as a means of improving housing outcomes, such as paying for security deposits or rent (Halpern-Meekin et al. 2015). A related experimental study found that individuals who were at risk of losing their homes and received cash assistance were 76 % less likely to enter a shelter compared with those who applied for aid after the funds were depleted (Evans et al. 2016). Studies of the effect of the EITC on living arrangements have examined its impact on marriage, finding small negative effects (Dickert-Conlin and Houser 2002; Herbst 2011;

1 One study modeled how the inclusion of the EITC in income reduces housing cost burdens (Stegman, Davis, and Quercia 2004).

1306 N. Pilkauskas, K. Michelmore

Michelmore 2018), but they have not analyzed other living arrangements. Related research on the effects of Temporary Assistance for Needy Families (TANF) has found mixed results on living arrangements (Bitler et al. 2006). In contrast, research on Social Security expansions has generally found that increases in income result in more elderly living independently (e.g., Engelhardt et al. 2005).

An extensive literature has examined the effect of housing support policies (public housing and housing choice vouchers) on housing stability and other outcomes. Although functionally different from the EITC (in-kind, different eligibility require- ments), both public housing and housing vouchers reduce housing costs, thus increas- ing household income to spend on other items (e.g., Jacob and Ludwig 2012; Mills et al. 2006). In general, vouchers have been linked with reduced homelessness (Gubits et al. 2016) and crowding (Carlson et al. 2012), with mixed evidence on housing quality and neighborhoods (for a review, see Ellen 2017). One study found that voucher receipt was linked with fewer adults living in the household (Carlson et al. 2012). Related evidence from a randomized housing-mobility program (Moving to Opportu- nity) found that moving to higher-income neighborhoods improved mental and phys- ical health and subjective well-being (e.g., Clampet-Lundquist and Massey 2008; Katz et al. 2001; Kling, Liebman, and Katz 2007) and mixed evidence for child well-being (e.g., Chetty et al. 2016; Ludwig et al. 2013). Last, research has found that living in a housing project is associated with less crowding and improved school outcomes (Currie and Yelowitz 2000) but also no effects on children (Jacob 2004). In sum, the literature generally suggests that subsidized housing is linked with improved housing and individual outcomes, with some exceptions.

Although no research has examined the effect of the EITC on housing outcomes, many studies have investigated its effect on related outcomes. Research has shown that the EITC increases the labor supply of single mothers (e.g., Meyer and Rosenbaum 2001), increases earnings (Dahl et al. 2009), lifts families out of poverty (Hoynes and Patel 2018), increases household savings (Jones and Michelmore 2018), reduces child neglect (Berger et al. 2017), and improves children’s education outcomes (Bastian and Michelmore 2018; Dahl and Lochner 2012). Together, this literature suggests that the EITC reduces economic uncertainty and reduces poverty, which in turn may affect housing and household well-being.

Method

Data

Data for our analyses come from three primary sources: the Current Population Survey (CPS) March Supplement, the American Community Survey (ACS)/decennial census, and the Fragile Families and Child Wellbeing Study (FFCWS). We discuss each source in turn.

Current Population Survey

The CPS is a nationally representative household survey conducted annually in March, gathering household income and employment information based on the prior calendar year. Each year the survey collects data from approximately 60,000 households. We use the

The Effect of the EITC on Housing and Living Arrangements 1307

1990–2016 surveys, reflecting the tax years 1989 to 2015. This period captures the effect of the numerous federal expansions to the EITC in the early 1990s and the introduction of many of the state EITCs, which largely occurred after welfare reform in 1996.

We limit our sample to single mothers who are identified as the respondent and who have at least one child under the age of 19 residing in the household (n = 137,595). Although pointers help us link parents and children, we must restrict our sample to respondents to accurately ascertain other relationships in the household: for example, we cannot reliably identify multigenerational households where the mother or grand- parent is not the respondent. In Table A2 in the online appendix, we show results for nonrespondents for housing outcomes. We focus on single mothers because they represent the majority of EITC recipients and federal dollars spent (Tax Policy Center 2006). Following prior research (e.g., Hoynes and Patel 2018), we further limit the sample to women aged 19–45 who have less than a college degree (n = 99,409). College-educated single mothers have far lower rates of EITC eligibility than women with less education, so they are less affected by the EITC. We also exclude women living in public housing given that public housing often places restrictions on who may coreside.2 Our final analytic sample includes 85,089 single mothers.

Respondents in the CPS are required to be the owner or the renter who is named on the lease or mortgage. As a result, when we restrict our sample to respondents to obtain accurate living arrangements, we create a sample that is somewhat more advantaged relative to those who are nonrespondents (e.g., respondents are more like to be employed than nonrespondents). To address this issue, and to examine whether the findings are robust to other data sources and methods, we supplement our CPS analysis with two additional data sets.3

ACS/Decennial Census

We also incorporate data from the 2000–2016 ACS and the 1990 decennial census (Ruggles et al. 2018).4 Although the ACS uses a household roster that also requires that we restrict to the respondent to get accurate household relationships, unlike the CPS, there is no preference for the renter/owner of note; any adult who will live (or has lived) in the household for two months or more can fill out the ACS. Thus, respondents are more likely to include both householders and subfamilies. Further, the ACS allows us to investigate how the EITC affects household crowding and cost burden, measures not available in the CPS. The ACS, however, did not exist in the 1990s, so we are unable to fully evaluate the effects of the mid-1990s federal EITC expansions using the ACS. Additional information on the ACS/census and differences between the CPS and ACS are available in the online appendix. After we make the same sample restrictions as for the CPS (except excluding public housing recipients because this information is not available), our ACS/census analytic sample includes 757,877 single mothers.

2 We include women who receive housing vouchers because they do not face the same restrictions as women in public housing. We find no evidence that the EITC affects the likelihood of living in public housing or having a housing voucher (results available upon request). 3 We also run analyses in the Survey of Income and Program Participation (SIPP; see Table A7 in the online appendix) but do not include them here due to data limitations. 4 In a supplemental analysis, we restricted the CPS to the same years used in the ACS, and findings (available upon request) were similar to those presented here.

1308 N. Pilkauskas, K. Michelmore

FFCWS

Because there may be concerns that the EITC changes the population of single mothers over time, we further supplement our analyses with panel data from the FFCWS, a longitudinal birth cohort study covering tax years 1998–2016.5

Mothers were interviewed at the birth of the child and at ages 1, 3, 5, 9, and 15 years old. The FFCWS oversampled nonmarital births, making it ideal for studying single mothers but also rendering it a more disadvantaged sample than the ACS or CPS. Because the FFCWS follows the same individuals over time, we conduct an individual fixed-effects analysis. This allows us to observe within-person changes in outcomes of interest as a function of EITC generosity, which also varies within person over time because of federal and state policy changes. After sample restrictions, the analytic sample includes 9,930 person- observations.

Although each data set has advantages and disadvantages, together they help us gain a better understanding of the impact of the EITC on housing and living arrangements of single mothers. Table 1 presents descriptive statistics on the three samples. Despite some sampling and methodological differences between the CPS and ACS, demo- graphic characteristics of the women in the two samples are quite similar. Mothers in the FFCWS, however, are younger, less educated, and comprise more racial minorities compared with mothers in the ACS and CPS. These differences are expected given the differences in sampling frameworks.

Measures

Homelessness and Eviction

We examine homelessness and eviction because studies have found that both are associated with a wide range of negative outcomes, including worse health (e.g., Burgard et al. 2012), job loss (Desmond and Gershenson 2016), and behavior problems in children (Labella et al. 2019). In the CPS, mothers who reported moving because of eviction or foreclosure in the last year are considered to have experienced foreclosure/eviction. In the FFCWS, we create binary indicators for eviction and homelessness if mothers report experiencing either in the last year.

Cost Burden

High housing costs are linked with housing instability (JCHS 2017). High cost burdens can affect neighborhood choice and other household expenditures that might be detrimental to children (Bratt 2002; JCHS 2017). Thus, we examine mother’s cost burden, or her housing affordability, using data from the ACS. We construct a measure of moderate cost burden (paying 30 % or more of pretax earnings on rent/mortgage)

5 Additional details on the data and method, 15 sample states, sample restrictions, balance, and migration tests are available in the online appendix. The FFCWS has been used in previous research to examine the effect of EITC expansions on maltreatment (Berger et al. 2017).

The Effect of the EITC on Housing and Living Arrangements 1309

and a measure of severe cost burden (paying 50 % or more of pretax earnings on rent/mortgage).

Living Arrangements

We examine living arrangements, or changes in household composition (sometimes referred to as household instability; Desmond and Perkins 2016), because the composition of the household can affect family well-being. First we study doubling up, an indicator that the mother is living with a grandparent, parent/in-law, sibling, aunt/uncle, nonrelated adult, or niece/nephew over the age of 18. Following previous research (Mykyta and Macartney 2012; Pilkauskas et al. 2014), we do not consider a mother to be doubled up if she lives with any child under the age of 18 or a cohabiting partner (married mothers are excluded from our study). Although cohabitation may be a form of doubling up, the underlying motivation for living with a partner is likely quite different than living with other

Table 1 Sample descriptive statistics: CPS, ACS, and FFCWS

CPS ACS FFCWS

Maternal Characteristics

Age 33.62 33.78 29.65

(6.82) (6.83) (7.34)

Number of children 1.78 1.79 2.02

(0.78) (0.78) (0.82)

Race/Ethnicity

Non-Hispanic white 0.51 0.51 0.14

Non-Hispanic black 0.23 0.27 0.57

Hispanic 0.20 0.19 0.26

Other race/ethnicity 0.05 0.03 0.03

Education

Less than high school 0.20 0.16 0.44

High school diploma 0.40 0.48 0.30

Some college 0.41 0.36 0.26

Earned Income Tax Credit (EITC)

Average simulated EITC (in $1,000s, 2011 dollars) 1.54 1.62 1.87

(0.59) (0.60) (0.51)

Eligible for the EITC 0.58 0.65 0.69

EITC credit (in $1,000s, 2011 dollars) 1.44 1.44 1.67

(1.67) (1.66) (1.75)

Number of Observations 85,089 757,977 9,946

Notes: Standard deviations are shown in parentheses. The sample is restricted to single mothers with less than a college degree and with at least one coresident child under the age of 19. The CPS and ACS are also restricted to mothers aged 19–45.

Sources: Current Population Survey (CPS) 1990–2016. Census 1990/American Community Survey (ACS) 2000–2016. Fragile Families and Child Wellbeing Study (FFCWS) 1998–2016.

1310 N. Pilkauskas, K. Michelmore

relatives and nonrelatives.6 We study doubling up because it is a common pre- cursor to homelessness, it is often precipitated by a crisis that affects housing (e.g., Wright et al. 1998), and about 65 % of the children identified as homeless by school districts are living in doubled-up households (National Center for Homeless Education 2011). However, doubling up may also represent a form of social support or preference (e.g., Edin and Lein 1997; Stack 1975): families that can move in with others may avoid more extreme forms of housing instability, such as homelessness, and may save significant amounts of money on rent (Pilkauskas et al. 2014). Doubling up is assessed in all three data sets.

Second, because doubling up in someone else’s home is a less-stable living arrangement than living in one’s own home (Skobba and Goetz 2015), for the FFCWS, we use data on leases and mortgages from the Years 3–15 surveys to construct two measures: (1) an indicator of doubling up in someone else’s home, and (2) a variable that identifies whether the mother is named on the lease or mortgage.

Third, in all three data sets, we study a particular type of doubled-up house- hold: a multigenerational household, sometimes referred to as a three-generation household. Multigenerational households are defined as those that include a single mother, her child(ren), and at least one of the child’s grandparents.7 We examine these households separately because their prevalence has increased in recent decades (Pilkauskas and Cross 2018), they are particularly common among low-income and single-mother households (Pilkauskas 2012), and multi- generational coresidence is linked with child well-being (e.g., DeLeire and Kalil 2002).

Fourth, we examine the total number of people in the household in the three data sets. In the FFCWS, we also conduct additional analyses separately examin- ing the number of adults in the household and the number of children in the household. This is closely related to our final living arrangement measure, house- hold crowding; crowding is associated with poorer outcomes for children (see, e.g., Evans et al. 1998), including lower graduation rates (Lopoo and London 2016). Using data from the ACS, we define household crowding as more than one person per room (excluding bathrooms).

Earned Income Tax Credit

Our main independent variable of interest is a simulated measure of average EITC generosity at the state–year–family size level. This simulated measure captures policy variation in the EITC at the federal and state level over time while eliminating variation in the EITC due to endogenous family processes, such as job loss, geographic moves, or fertility.

To construct the simulated EITC, we use a nationally representative sample of single mothers from the 1996 Survey of Income and Program Participation

6 Over the period studied, the CPS changed how it identified cohabiting partners. See the online appendix for details.

7 In the ACS and the CPS, we can identify only maternal grandparents. In the FFCWS, we can identify both maternal and paternal multigenerational households.

The Effect of the EITC on Housing and Living Arrangements 1311

(SIPP).8 Using a nationally representative sample of single mothers that is inde- pendent of the sample used in our analysis reduces concerns that our sample is not representative of the population of single mothers. We inflate (deflate) the sample mothers’ earnings using the Consumer Price Index (CPI) in each year between 1989 and 2015. Inflating (deflating) earnings by the CPI rather than observing changes in the income distribution over time reduces concerns that changes to the EITC may affect changes in the national income distribution of single mothers. Using National Bureau of Economic Research’s TAXSIM program (Feenberg and Coutts 1993; www.nber.org/taxsim), we calculate federal taxes for each year between 1989 and 2015. We then determine average state EITC benefits by running the national sample of single mothers through each state’s EITC laws in each year between 1989 and 2015. Calculating state EITCs using the national sample of single mothers (rather than mothers who live in that state) reduces concerns of endogeneity of state demographic characteristics with respect to state EITC benefits.

We then collapse the sample to the state–year–family size level, which produces a data set containing a measure of the average federal and state EITC a single mother can expect to receive given her state, year, and number of children (one, two, or three or more children). We then match this information to our sample of single mothers in each data source. Variation in this measure across individuals will reflect differences in policy generosity only across states, time, and family size, and not potentially endog- enous changes to family income, family size, or geographic location.9

Figure 1 presents a visual depiction of the variation in the simulated EITC over time for all states by number of children that we exploit in our analyses. Panel a shows the EITC for one-child households. The difference in average EITC benefits in states that do not have their own EITCs compared with the most generou

Collepals.com Plagiarism Free Papers

Are you looking for custom essay writing service or even dissertation writing services? Just request for our write my paper service, and we'll match you with the best essay writer in your subject! With an exceptional team of professional academic experts in a wide range of subjects, we can guarantee you an unrivaled quality of custom-written papers.

Get ZERO PLAGIARISM, HUMAN WRITTEN ESSAYS

Why Hire Collepals.com writers to do your paper?

Quality- We are experienced and have access to ample research materials.

We write plagiarism Free Content

Confidential- We never share or sell your personal information to third parties.

Support-Chat with us today! We are always waiting to answer all your questions.