Abstract
The primary objective of this paper is to examine the influence of natural amenities on student migration decisions using institution-level data from the National Center for Education Statistics’ Integrated Postsecondary Education Data System. We surpass the scope of previous studies focused on natural amenities, which rely on a limited selection of state-level measures, by matching interpolated weather station- and county-level climate data to each post-secondary institution. Results suggest that students consider natural amenities in their migration to college decision and, in a number of cases, preferences for natural amenities vary based on origin state amenity conditions. Nonetheless, migration decisions are dominated by origin state educational opportunities and by proximity of the student’s origin state to the state of college attendance.
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Notes
This parameter (18.3 %) considers first-time students originating from the USA who graduated from high school in the year preceding the Fall 2012 semester and who matriculated to a Title IV-participating, academic, undergraduate degree-granting, ‘brick-and-mortar’ institution. Among such first-time students regardless of recency of high school graduation, 15.6 % are migrants.
Clark and Hunter (1992) consider the following natural amenity measures: percentage of available sunshine, January–July temperature differential, number of cooling degree days per year, coastal proximity, and percentage of land devoted to state parks. Their sample is limited to white males.
Institutions provide annual data to IPEDS for most other variables.
2012 was the most recent year for which ‘final release data’ were available for all variables of interest at the time of analysis.
These eight indicators are based on the National Center for Education Statistics’ urban-centric locale codes, which are available on IPEDS for each university. Urban-centric locale subcategories distinguished by differences in population only (‘large,’ ‘midsize,’ and ‘small’ cities and suburbs) have been merged into single categories.
The Pagan-Hall general test statistic is 854.94 (p value = 0.00).
In some cases, multiple Carnegie classifications have been combined into a single institution type, and types with less than 50 schools with data for all variables are excluded from the analysis. Research and doctorate-granting universities (combination of research universities [‘very high’ and ‘high’ research activity] and doctoral/research universities); master’s colleges and universities (‘larger,’ ‘medium,’ and ‘smaller’ programs); and baccalaureate colleges (‘arts & sciences’ and ‘diverse fields,’ and baccalaureate/associates colleges) remain in the reduced sample.
Migrants originating from the District of Columbia are additionally excluded. Due to insufficient institutional data availability, DC’s public universities are not included in the reduced sample, meaning that in-sample enrollment-weighted mean public tuition of the origin ‘state’ cannot be computed for students originating from the District.
University spots per college-goers and student out-migrant percentage have a statistically significant (p value \(<0.05\)) Pearson’s correlation coefficient of \(-\)0.37.
Latitude and longitude coordinates of institutions are provided by IPEDS.
The Natural Amenities Scale uses data from the U.S. Department of Health and Human Services’ Area Resources tape and the U.S. Department of the Interior’s 1970 National Atlas of the USA. The data span the period 1941–1970.
Variance inflation factors for natural amenity terms in each specification do not exceed 10, the ‘rule of thumb’ (Gujarati 2003, p. 362) threshold for high collinearity.
These measures are warm winter, winter sun, temperate summer, low summer humidity, topographic variation, and water area.
July relative humidity and annual precipitation have a statistically significant (p value \(<0.05\)) Pearson’s correlation coefficient of 0.61.
Year round Pell Grants were still in place during Summer 2011.
Introduction of squared terms to each specification produces the following significant effects: natural amenity rank (\(-\)); July relative humidity (+), percentage water area (\(-\)); precipitation (+), precipitation days (\(-\)). Linear measures of precipitation and precipitation days at the destination become significant when squared terms are introduced, and the linear July relative humidity term becomes insignificant.
References
Abreu M, Faggian A, Comunian R, McCann P (2012) Life is short, art is long: the persistent wage gap between Bohemian and non-Bohemian graduates. Ann Reg Sci 49:305–321. doi:10.1007/s00168-010-0422-4
Adkisson RV, Peach JT (2008) Non-resident enrollment and non-resident tuition at land grant colleges and universities. Educ Econ 16:75–88. doi:10.1080/09645290701563156
Alm J, Winters JV (2009) Distance and intrastate college student migration. Econ Educ Rev 28:728–738. doi:10.1016/j.econedurev.2009.06.008
Baryla EA, Dotterweich D (2001) Student migration: Do significant factors vary by region? Educ Econ 9:269–280. doi:10.1080/09645290110086135
Benson ED, Hansen JA, Schwartz AL, Smersh GT (1998) Pricing residential amenities: the value of a view. J Real Estate Financ Econ 16:55–73. doi:10.1023/a:1007785315925
Busch O, Weigert B (2008) Where have all the graduates gone? Internal cross-state migration of graduates in Germany 1984–2004. Ann Reg Sci 44:559–572. doi:10.1007/s00168-008-0274-3
Campbell R, Siegel BN (1967) The demand for higher education in the United States, 1919–1964. Am Econ Rev 57:482–494
Clark DE, Hunter WJ (1992) The impact of economic opportunity, amenities, and fiscal factors on age-specific migration rates. J Reg Sci 32:349–365. doi:10.1111/j.1467-9787.1992.tb00191.x
Cooke TJ, Boyle P (2011) The migration of high school graduates to college. Educ Eval Policy Anal 33:202–213. doi:10.3102/0162373711399092
Dotterweich D, Baryla EA (2005) Non-resident tuition and enrollment in higher education: implications for tuition pricing. Educ Econ 13:375–385. doi:10.1080/09645290500251631
Dotterweich D, Baryla EA, Rochelle CF (2011) Nonresident enrollment at religious and secular colleges. Christ High Educ 10:1–9. doi:10.1080/15363750903526936
Dwenger N, Storck J, Wrohlich K (2009) Do tuition fees affect the mobility of university applicants? Evidence from a natural experiment. Econ Educ Rev 31:155–167. doi:10.2139/ssrn.1496362
Faggian A, Franklin RS (2014) Human capital redistribution in the USA: the migration of the college-bound. Spat Econ Anal 9:376–395. doi:10.1080/17421772.2014.961536
Faggian A, McCann P (2009) Human capital, graduate migration and innovation in British regions. Camb J Econ 33:317–333. doi:10.1093/cje/ben042
Faggian A, McCann P, Sheppard S (2006) An analysis of ethnic differences in UK graduate migration behaviour. Ann Reg Sci 40:461–471. doi:10.1007/s00168-006-0061-y
Faggian A, McCann P, Sheppard S (2007) Human capital, higher education and graduate migration: an analysis of Scottish and Welsh students. Urban Stud 44:2511–2528. doi:10.1080/00420980701667177
Glaeser EL, Maré DC (2001) Cities and skills. J Labor Econ 19:316–342. doi:10.1086/319563
Gottlieb PD (2003) Economy versus lifestyle in the inter-metropolitan migration of the young: a preliminary look at the 2000 census. Int J Econ Dev 5
Graves PE (1979) A life-cycle empirical analysis of migration and climate, by race. J Urban Econ 6:135–147. doi:10.1016/0094-1190(79)90001-9
Graves PE (1980) Migration and climate. J Reg Sci 20:227–237. doi:10.1111/j.1467-9787.1980.tb00641.x
Gujarati DN (2003) Multicollinearity: What happens if the regressors are correlated? In: Sutton L, Bright A (eds) Basic econometrics, 4th edn. McGraw-Hill Higher Education, West Point, pp 335–386
Hansen SB, Ban C, Huggins L (2003) Explaining the “brain drain” from older industrial cities: the Pittsburgh region. Econ Dev Q 17:132–147. doi:10.1177/0891242403252377
Hsing Y, Mixon FG (1996) A regional study of net migration rates of college students. Rev Reg Stud 26:197–209
Kodrzycki Y (2001) Migration of recent college graduates: evidence from the national longitudinal survey of youth. New Engl Econ Rev 13–34
Kyung W (1996) In-migration of college students to the state of New York. J Higher Educ 67:349–358. doi:10.2307/2943848
Luttik J (2000) The value of trees, water and open space as reflected by house prices in the Netherlands. Landsc Urban Plan 48:161–167. doi:10.1016/S0169-2046(00)00039-6
Ma J, Baum S, Pender M, Bell D (2015) Trends in college pricing 2015. College Board. http://trends.collegeboard.org/college-pricing. Accessed 28 Dec 2015
McDuff D (2007) Quality, tuition, and applications to in-state public colleges. Econ Educ Rev 26:433–449. doi:10.1016/j.econedurev.2006.04.003
McHugh R, Morgan JN (1984) The determinants of interstate student migration: a place-to-place analysis. Econ Educ Rev 3:269–278. doi:10.1016/0272-7757(84)90045-1
Mellander C, Florida R, Stolarick K (2011) Here to stay—the effects of community satisfaction on the decision to stay. Spat Econ Anal 6:5–24. doi:10.1080/17421772.2010.540031
Mixon FG (1992) Factors affecting college student migration across states. Int J Manpow 13:25–32. doi:10.1108/eum0000000000900
Mixon FG, Hsing Y (1994a) College student migration and human capital theory: a research note. Educ Econ 2:65–73. doi:10.1080/09645299400000005
Mixon FG, Hsing Y (1994b) The determinants of out-of-state enrollments in higher education: a Tobit analysis. Econ Educ Rev 13:329–335. doi:10.1016/S0272-7757(05)80056-1
Morse RJ, Flanigan S (2010) How we calculate the rankings. In: U.S. News & World Report Best Colleges 2011. U.S. News & World Report LP, Washington, DC, pp 84–87
Partridge MD (2010) The duelling models: NEG vs amenity migration in explaining US engines of growth. Pap Reg Sci 89:513–536. doi:10.1111/j.1435-5957.2010.00315.x
Peters DJ (2000) Understanding natural amenities: Impacts on population and employment in Missouri. Missouri Department of Economic Development. https://www.missourieconomy.org/pdfs/natamenity-aug2000.pdf. Accessed 11 Dec 2015
Rappaport J (2007) Moving to nice weather. Reg Sci Urban Econ 37:375–398. doi:10.1016/j.regsciurbeco.2006.11.004
Rappaport J, Sachs JD (2003) The United States as a coastal nation. J Econ Growth 8:5–46. doi:10.1023/a:1022870216673
Schmidt L, Courant PN (2006) Sometimes close is good enough: the value of nearby environmental amenities. J Reg Sci 46:931–951. doi:10.1111/j.1467-9787.2006.00491.x
Sjaastad LA (1962) The costs and returns of human migration. J Polit Econ 70:80–93. doi:10.1086/258726
Tuckman HP (1970) Determinants of college student migration. South Econ J 37:184–189. doi:10.2307/1056128
Ullis JJ, Knowles PL (1975) A study of the intrastate migration of Washington college freshmen: a further test of the gravity model. Ann Reg Sci 9:112–121. doi:10.1007/BF01284992
US Department of Agriculture, Economic Research Service (2012) Natural amenities scale. http://www.ers.usda.gov/data-products/natural-amenities-scale.aspx. Accessed 15 May 2015
Weiler WC (1996) Factors influencing the matriculation choices of high ability students. Econ Educ Rev 15:23–36. doi:10.1016/0272-7757(95)00023-2
Wilson AG (1967) A statistical theory of spatial distribution models. Transp Res 1:253–269. doi:10.1016/0041-1647(67)90025-1
Zellner A, Theil H (1962) Three-stage least squares: simultaneous estimation of simultaneous equations. Econometrica 30:54–78. doi:10.2307/1911287
Acknowledgments
I wish to graciously acknowledge participants of the 61st Annual North American Meetings of the Regional Science Association International and thank my Ph.D. advisor Alessandra Faggian, in addition to Timothy Wojan, Elizabeth Botkins, Nicholas Irwin, Khushbu Mishra, and Isha Rajbhandari, for comments made on earlier drafts. The paper has also benefited from the constructive suggestions of two anonymous referees, the guest editors of this issue, and the editor of the journal.
