Frontiers in Business, Economics and Management ISSN: 2766-824X | Vol. 9, No. 3, 2023 59 Economic Recession and Full‐Time College Enrollment Haijinyue Li AAA School, Zhuhai, 519000, China Abstract: Using macro data for the United States from 1970-2019, this paper develops a simple linear regression model and by using OLS methods, we conclude that the economic recession reduces full-time college enrollment by 14.1% and that the economic recession has a significantly higher impact on female than male. In this paper, we also replace the independent variable with the overall enrollment in tertiary education, and by the same method, we obtain the same conclusion that the economic recession reduces the enrollment in tertiary education by about 10.87%. Keywords: Economic recession, Enrollment, OLS methods. 1. Introduction The economic downturn has had a profound impact on both the supply and demand for higher education. According to Long (2014), the economic recession has caused many educational institutions to experience cuts in multiple sources of revenue, including charitable giving, endowment proceeds, and government grants, all of which may cause tuition to rise. In terms of demand for higher education, the economic downturn has affected household incomes and unemployment rates, and people may not be able to afford high tuition because of the decline in their incomes, so college admissions will decline in response to the economic recession. There is also a view that the economic recession has caused unemployment to rise and earnings from work to fall, which reduces the opportunity cost of college, so people will choose to attend college. This paper will use the National Center for Education Statistics (NCES), combined with data obtained from FRED on the recession, to explore whether the recession affects changes in college enrollments or enrollment rates. The results of this paper show that the economic recession reduces full-time college enrollment by 14.1%, and that the economic recession has a significantly higher impact on female than on male. This paper proceeds as follows. In Section 2, we will summarize the literature that previously studied this issue. In Section 3, we provide the sources of the relevant data as well as a description of the data. In Section 4, we create a model using a simple OLS regression to analyze whether the economic recession affects the number of college students enrolled and their enrollment rates. In Section 5, the results are given. In Section 6, we provide the conclusions of this study. In Section 7, we point out the shortcomings of our study and future research plans. 2. Literature Review As we mentioned earlier, economic crises can affect demand for higher education in two different ways, but much of the prior literature has generally concluded that economic crises boost student enrollment in higher education. Fry (2010) empirically analyzes data from the U.S. Department of Education and finds that enrollment in four-year colleges, community colleges, and trade schools increases during economic recessions, and that these increases Long (2014) reaches the same conclusion, and his analysis shows that part- time enrollment increased and full-time enrollment decreased during the recession, and that the increase in enrollment was concentrated among people of color. However, Wright & VΓ‘squez-Colina (2013) argue that from 1979 to 2009, higher education enrollment in the U.S. was not affected by the recession. Li & Bichsel (2019) analyze U.S. enrollment data from 2004 to 2018 and find that from 2009 to 2011, public school student enrollment rates have increased significantly, and changes in private school enrollment rates have remained relatively stable. 3. Data Description The dependent variable in this paper is full-time college enrollment (Data is from NCES, available at https://nces.ed.gov/programs/digest/d20/tables/dt20_303.70. asp), and we also log the dependent variables in order to eliminate the effect of heteroskedasticity and to examine how the economic recession affects the rate of change in enrollment. The core independent variable is the economic recession, and Long (2004) analysis indicates that college enrollment tends to increase with unemployment rates, so this paper will also include unemployment as an independent variable. Another independent variable is the U.S. GDP (Unemployment rate and GDP both from FRED database). Considering that the dependent variable in much of the literature is enrollment rate, this paper also includes overall enrollment rate (Enrollment data from UNESCO at: https://datatopics.worldbank.org/education/) in higher education as another dependent variable. See Table 1 for specific information on these data. In order to be able to observe more visually whether there is a causal relationship between the data, we made a scatter plot of the number of enrollments per year, where the vertical line indicates the year in which the main economic recession was experienced. By looking at this we can see that there is a significant drop in enrollment after the economic recession (or the year after it occurs), suggesting that there is some negative relationship between the economic recession and college enrollment. 60 Table 1. Variable Descriptions Variable Obs Mean Std. Dev. Min Max Description economicrecession 48 .229 .425 0 1 Dummy variable, =1 if economic recession total enrollment 48 14539312 2713724.1 7368644 18082427 The number of people enroll in colleges both as full-time and part- time students fulltime total 48 8914926 1777626.5 5280064 11457040 The number of people enroll in colleges as full-time students parttime total 48 5624323.1 978313.67 2088580 6712128 The number of people enroll in colleges as part-time students fulltime female 48 4828385.9 1115341.6 2183693 6338065 The number of females enroll in colleges as full-time students parttime female 48 3292500.5 618490.93 935249 3959689 The number of females enroll in colleges as part-time students fulltime male 48 4086602.6 676008.42 3096371 5118975 The number of males enroll in colleges as full-time students parttime male 48 2331843.4 367343.42 1153331 2752439 The number of males enroll in colleges as part-time students unemploymentrates 48 4.671 2.564 0 8.6 Unemployment rates gdp 48 9.01 6.754 0 21.433 U.S. GDP ln fulltime total 48 15.982 .211 15.479 16.254 The log form of fulltime total ln fulltime female 48 15.36 .258 14.597 15.662 The log form of fulltime female ln fulltime male 48 15.209 .169 14.946 15.448 The log form of fulltime male enrollment rate 37 76.715 12.566 47.323 96.322 Gross tertiary enrollment rate Figure 1. Trend in full-time college enrollment 4. Model Selection and Empirical Analysis The data in this paper consider only the United States, so our model uses mainly OLS regression, and the expression of the model is as follows. πΈπ‘›π‘Ÿπ‘œπ‘™π‘™π‘šπ‘’π‘›π‘‘ 𝛽 𝛽 π‘’π‘π‘œπ‘›π‘œπ‘šπ‘–π‘π‘Ÿπ‘’π‘π‘’π‘ π‘ π‘–π‘œπ‘› 𝛽 𝐺𝐷𝑃 𝛽 π‘’π‘›π‘’π‘šπ‘π‘™π‘œπ‘¦π‘šπ‘’π‘›π‘‘π‘Ÿπ‘Žπ‘‘π‘’π‘  πΈπ‘›π‘Ÿπ‘œπ‘™π‘™π‘šπ‘’π‘›π‘‘ denotes full-time college enrollment in period 𝑑 (we also consider the logarithm of full-time college enrollment and the college enrollment rate). π‘’π‘π‘œπ‘›π‘œπ‘šπ‘–π‘π‘Ÿπ‘’π‘π‘’π‘ π‘ π‘–π‘œπ‘› is a dummy variable that equals 1 if there is an economic recession in period 𝑑 and 0 otherwise. 𝐺𝐷𝑃 and π‘’π‘›π‘’π‘šπ‘π‘™π‘œπ‘¦π‘šπ‘’π‘›π‘‘π‘Ÿπ‘Žπ‘‘π‘’π‘  denote the GDP and unemployment rate in the United States in period 𝑑. In this paper, we want to investigate whether the economic recession affects the number of enrollments. Using the previous graph, we predict that the coefficient of 𝛽 is negative. Economic growth leads to higher income, so we predict that 𝛽 is positive. As mentioned earlier, Long (2004) argues that college enrollment tends to increase with unemployment rate, so we predict 𝛽 to be negative. In addition, we also predict that the economic recession affects males and females differently, so we also make a gender distinction in this paper. 5. Results The results are shown in Table 2. Table 2. Regression Results (the number of enrollment) (1) (2) (3) (4) (5) (6) (7) (8) (9) Fulltime_total Fulltime_total Fulltime_total Fulltime_female Fulltime_female Fulltime_female Fulltime_male Fulltime_male Fulltime_male EconomicRecession -1116947.3* 151956.8 30734.4 -782997.9** 3236.2 -61525.3 -334030.4 148720.6 92259.7 (594687.6) (249119.4) (196771.4) (369557.0) (151909.4) (129065.3) (229437.1) (110594.8) (84331.2) GDP 298048.0*** 297486.5*** 186536.7*** 186236.7*** 111511.3*** 111249.7*** (19842.4) (15547.0) (12099.6) (10197.5) (8808.9) (6663.0) UnemploymentRates 318532.5*** 170171.9*** 148360.6*** (65508.3) (42967.8) (28075.2) Constant 9170893.1*** 5232806.2*** 3442070.9*** 5007822.9*** 2551050.4*** 1594373.2*** 4163151.2*** 2681755.8*** 1847697.7*** (284685.0) (269335.6) (424451.4) (176912.0) (164237.0) (278404.0) (109834.6) (119569.6) (181908.9) Observations 48 39 39 48 39 39 48 39 39 R2 0.071 0.867 0.921 0.089 0.875 0.914 0.044 0.819 0.899 Adjusted R2 0.051 0.860 0.914 0.069 0.868 0.906 0.023 0.809 0.891 Standard errors in parentheses * p < 0.10, ** p < 0.05, *** p < 0.01 Using the table above we find that the economic recession reduces college enrollment when GDP and unemployment are not included, and this coefficient is significant at the 10% level of significance. Columns (4) and (7) show that the economic recession affects females significantly more than males. The sign of the coefficient on GDP is consistent with our prediction, but the sign of the coefficient on unemployment is in the opposite direction of our prediction. 61 Nevertheless, we found that the coefficients we obtained were too large, so we also did a logarithmic treatment in this paper to obtain the results in Table 3. We find that the results in Table 3 are not very different from those in Table 2, but the coefficients are all much smaller, because by taking the logarithmic form, the meaning of the coefficients changes to the percentage effect of the economic recession on the number of enrollments. Table 3. Regression results (log the number of enrollment) (1) (2) (3) (4) (5) (6) (7) (8) (9) ln_fulltime_ total ln_fulltime_ total ln_fulltime_ total ln_fulltime_f emale ln_fulltime_f emale ln_fulltime_f emale ln_fulltime_ male ln_fulltime_ male ln_fulltime_ male EconomicRece ssion -0.141* 0.00999 -0.00227 -0.198** -0.0215 -0.0334 -0.0838 0.0387 0.0259 (0.0704) (0.0283) (0.0239) (0.0846) (0.0370) (0.0344) (0.0575) (0.0262) (0.0206) GDP 0.0356*** 0.0355*** 0.0426*** 0.0426*** 0.0282*** 0.0281*** (0.00225) (0.00189) (0.00295) (0.00271) (0.00208) (0.00163) Unemployment Rates 0.0322*** 0.0312*** 0.0335*** (0.00795) (0.0114) (0.00687) Constant 16.01*** 15.55*** 15.36*** 15.41*** 14.85*** 14.67*** 15.23*** 14.85*** 14.67*** (0.0337) (0.0306) (0.0515) (0.0405) (0.0400) (0.0741) (0.0275) (0.0283) (0.0445) Observations 48 39 39 48 39 39 48 39 39 R2 0.080 0.879 0.918 0.107 0.863 0.887 0.044 0.838 0.904 Adjusted R2 0.060 0.872 0.910 0.087 0.855 0.877 0.023 0.829 0.895 Standard errors in parentheses * p < 0.10, ** p < 0.05, *** p < 0.01 In addition to this, this paper also includes enrollment rate, (The disadvantage of doing this is that we cannot observe the difference between males and females.) which has been used in many papers, as a dependent variable, and by doing the same, we obtain the regression results in Table 4. The results in Table 4 also confirm our prediction that the economic recession reduces college enrollment. Table 4. Regression Results (enrollment rate) (1) (2) (3) enrollment rate enrollment rate enrollment rate EconomicRecession -10.87** -2.817 -2.801 (4.345) (2.426) (1.985) GDP 1.875*** 1.958*** (0.194) (0.160) UnemploymentRates 2.763*** (0.655) Constant 79.65*** 57.06*** 40.40*** (2.259) (2.622) (4.494) Observations 37 37 37 R2 0.152 0.773 0.853 Adjusted R2 0.127 0.760 0.839 Standard errors in parentheses * p < 0.10, ** p < 0.05, *** p < 0.01 6. Conclusion In this paper, we have developed a simple OLS regression model using econometric methods to obtain our findings using U.S. data from 1970 to 2019. We argue that the presence of an economic recession reduces full-time college enrollment by 14.1%; or by 10.87% in gross enrollment rate. 7. Limitations and Future Research This conclusion is different from previous literature (Fry, 20010; Long, 2014; Li & Bichsel 2019) and we believe that there are several main reasons for its existence. First, the model in this paper is too rudimentary and has the problem of omitted variables. Second, the data in this paper are macro- level data, and such data do not take into account the heterogeneity of individuals bringing about bias in individual choices. This is demonstrated by the fact that this paper focuses only on overall admissions, but there are disparities in enrollment by race. Fry (2010) found through his data that from 2007 to 2008, freshman enrollment at postsecondary institutions increased by 15% for Hispanics, 8% for Blacks, 6% for Asians, and 3% for Whites. In addition, our data are for the entire United States, but there are differences in economic development as well as college admissions policies from state to state, and this difference likely influenced the results we wanted. The plan for future research in this paper is that we can use individual-level data to differentiate between individuals of different races, as well as to analyze whether the economic recession affects college admissions using panel models, taking into account their state of residence. References [1] Barr, Andrew, and Sarah Turner. "Out of work and into school: Labor market policies and college enrollment during the Great Recession." Journal of Public Economics 124 (2015): 63-73. [2] Fry, Richard. "Minorities and the recession-era college enrollment boom." Washington, DC: Pew Research Center Social and Demographic Trends Project (2010). [3] Long, Bridget Terry. "How have college decisions changed over time? An application of the conditional logistic choice model." Journal of econometrics 121.1-2 (2004): 271-296. [4] Long, Bridget Terry. "7. The Financial Recession and College Enrollment: How Have Students and Their Families 62 Responded?". How the Financial Recession and Great Recession Affected Higher Education, edited by Jeffrey R. Brown and Caroline M. Hoxby, Chicago: University of Chicago Press, 2014, pp. 209-234. [5] Li, Jingyun, Jasper McChesney, and Jacqueline Bichsel. "Impact of the Economic Recession on Student Enrollment and Faculty Composition in US Higher Education: 2003-2018. A CUPA-HR Research Report." College and University Professional Association for Human Resources (2019). [6] Wright, Dianne A., Gianna Ramdin, and MarΓ­a D. VΓ‘squez- Colina. "The Effects of Four Decades of Recession on Higher Education Enrollments in the United States." Universal Journal of Educational Research 1.3 (2013): 154-164.