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Does Eco-labeling of Services Matter? Evidence from Higher Education

  • Daniel C. Hickman und Andrew G. Meyer EMAIL logo
Veröffentlicht/Copyright: 9. Dezember 2016
The B.E. Journal of Economic Analysis & Policy
Aus der Zeitschrift The B.E. Journal of Economic Analysis & Policy Band 16 Heft 4

Abstract:

Eco-labeling of services has become increasingly common, yet little empirical evidence exists concerning its effectiveness. We address this gap in the literature by analyzing a highly visible eco-label, the American College and University Presidents’ Climate Commitment (ACUPCC), in the sector of higher education. We match information about the ACUPCC to the US Department of Education IPEDS database to examine the impact of signing on student applications, admissions, and enrollment. We mainly utilize a difference-in-difference approach to identify the effects of interest but confirm results with an interrupted time series model. We find that signing the ACUPCC increases applications and admitted students by 2.5–3.5 %. However, the evidence regarding enrollment is weaker with only some specifications finding increases of around 1–2 %. Overall, there is considerable heterogeneity across sectors and selectivity of the institutions. These results show that, at the minimum, voluntary and information-based approaches (VIBAs) for services can be effective in generating visibility and influencing less-costly consumer behavior.

Keywords: eco-labeling; information provision; educational economics; higher education; VIBAs

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Appendix: Interrupted Times Series Details

For each signatory IHE, i, define the ACUPCC effective signing year[37] as ki. Normalize by the effective signing year so that

(3)Tˆit=Tit−ki

represents the year relative to the effective signing year. We specify a bandwidth, b, and include all IHEs in the sample that are observed for b years prior to and post signing. Then, for Tˆit≤b, the baseline[38] econometric model is

(4)Yit=α+γi+τ×ITˆit>ki+β1×Tˆit+β2×Tˆit×ITˆit>ki+φt+εit,

where γi are IHE fixed-effects, I(.) represents the indicator function, and φt are year fixed-effects (to account for common changes in the dependent variable over calendar years). For the baseline results, we set b=4; therefore, we include all IHEs with an effective signing year of 2009 or earlier so that each IHE has an equal number of observations prior to and post signing. Thus, τ is the effect of signing on the outcome variable, β1 is the pre-signing slope, and β2 is the change in the slope in the post-signing period relative to the pre-signing period.

Appendix Tables

Table 11:

Summary statistics of DID sampling groups.

Green GuideSignatoriesAll 4-year IHEs
All IHEsSignedNot20072008–2013SignedNot
Applications4,925.48,521.510,354.5*7,652.26,172.6*6,857.83,931.0***
Admissions2,986.35,145.25,408.54,598.13,747.0*4,141.12,392.0***
Enrolled1,072.11,728.32,007.31,537.21,300.01,409.8898.2***
Common application0.2190.3850.3620.360.340.350.15***
In-state tuition16.9917.420.5*16.217.416.917.0
Out-of-state tuition20.723.725.422.722.022.319.9***
HS graduates (1,000s)106.8113.3133.7*113.8101.9107.4106.4
Income per capita (1,000s)43.444.945.045.144.844.942.7***
Undergraduate application Fee53.364.367.961.758.760.149.6***
Average professor salary (1,000’s)94.39109.6118.9***104.2101.8102.989.9***
Private0.610.480.540.470.530.500.66***
Number of IHEs1036208105163189352684

Notes: Statistics come from the 2005–2006 academic year, before the impact of ACUPCC signing takes place. Tuition, income, application fee and professor salary variables measured in constant 2014 dollars. The number of observations is slightly lower for the tuition, application fee, and professor salary variables.

  1. indicates means different at 10 % level,

  2. indicates means different at 5 % level,

  3. indicates means different at 1 % level.

Table 12:

Regression results: levels.

(1)(2)(3)(4)(5)(6)
ApplicationsAdmissionsEnrollment
Signed183.68*186.51*87.6376.8319.50*13.66
(96.10)(101.52)(55.21)(52.50)(11.82)(12.13)
IHE-level controlsNoYesNoYesNoYes
Observations12,35311,21612,35311,21612,35011,214
R-squared0.9880.9870.9840.9870.9890.990

Notes: Table presents regression results from sample of all 4-year IHEs. Standard errors, clustered at IHE level, presented in parentheses. All specifications include IHE fixed effects, IHE-specific linear trends, and year fixed effects. IHE-level controls are common application, HS graduates, income per capita, undergraduate application fee, lagged in-state tuition, lagged out-of-state tuition and lagged professor salary. All monetary variables measured in constant 2014 dollars.

  1. denotes significance at 0.10 level.

  2. denotes significance at 0.05 level,

  3. denotes significance at 0.01 level,

Table 13:

Interrupted time series falsification tests.

(1)(2)(3)(3)
Application feeLn application feeLn tuition% tenure track
Signed0.475–0.00540–0.00527–0.000495
(0.837)(0.0105)(0.0122)(0.00700)
Observations2,6982,5822,6972,638
R-squared0.3480.3920.210.035
Number of IHEs319313319309

Notes: Table presents result from interrupted time series models, with dependent variable listed. Undergraduate application fee is measured in constant 2014 dollars and tuition is measured in thousands of constant 2014 dollars. Each specification includes linear trend variables. The bandwidth of 4 years in these models means we include IHEs signing in 2009 or earlier. Standard errors, clustered at IHE level, presented in parentheses. Each regression includes year and IHE fixed effects.

* denotes significance at 0.10  level.

** denotes significance at 0.05  level,

*** denotes significance at 0.01 level,

Published Online: 2016-12-9
Published in Print: 2016-10-1

©2016 by De Gruyter

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  2. Voting in Central Banks: Theory versus Stylized Facts
  3. Delinquency Reinforcement and Balance: Is Exposure to Delinquent Peers Always Risky?
  4. Can Polluting Firms Favor Regulation?
  5. Cannabis Control and Crime: Medicinal Use, Depenalization and the War on Drugs
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  7. Can Low-Wage Employment Help People Escape from the No-Pay – Low-Income Trap?
  8. Auctioning Emission Permits with Market Power
  9. Privatization, Unemployment, and Welfare in the Harris-Todaro Model with a Mixed Duopoly
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  11. What Do Regulators Value?
  12. Strategic CSR, Heterogeneous Firms and Credit Constraints
  13. Regulations to Supplement Weak Environmental Liability
  14. Intergenerational Educational Persistence among Daughters: Evidence from India
  15. A Signal of Altruistic Motivation for Foreign Aid
  16. Has Creative Destruction become more Destructive?
  17. Is There a Role for Higher Education Institutions in Improving the Quality of First Employment?
  18. Contribution
  19. The Effects of School Closure Threats on Student Performance: Evidence from a Natural Experiment
  20. School Entry, Compulsory Schooling, and Human Capital Accumulation: Evidence from Michigan
  21. Topics
  22. Overeducation, Overskilling and Mental Well-being
  23. Process and Product Innovation and the Role of the Preference Function
  24. Letter
  25. Does Evasion Invalidate the Welfare Sufficiency of the ETI?
  26. How Lobbying Affects Representation: Results for Majority-Elected Politicians
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https://doi.org/10.1515/bejeap-2016-0050
Schlagwörter für diesen Artikel
eco-labeling; information provision; educational economics; higher education; VIBAs

Artikel in diesem Heft

  1. Research Article
  2. Voting in Central Banks: Theory versus Stylized Facts
  3. Delinquency Reinforcement and Balance: Is Exposure to Delinquent Peers Always Risky?
  4. Can Polluting Firms Favor Regulation?
  5. Cannabis Control and Crime: Medicinal Use, Depenalization and the War on Drugs
  6. Coasean Quality of Regulated Goods
  7. Can Low-Wage Employment Help People Escape from the No-Pay – Low-Income Trap?
  8. Auctioning Emission Permits with Market Power
  9. Privatization, Unemployment, and Welfare in the Harris-Todaro Model with a Mixed Duopoly
  10. Does Eco-labeling of Services Matter? Evidence from Higher Education
  11. What Do Regulators Value?
  12. Strategic CSR, Heterogeneous Firms and Credit Constraints
  13. Regulations to Supplement Weak Environmental Liability
  14. Intergenerational Educational Persistence among Daughters: Evidence from India
  15. A Signal of Altruistic Motivation for Foreign Aid
  16. Has Creative Destruction become more Destructive?
  17. Is There a Role for Higher Education Institutions in Improving the Quality of First Employment?
  18. Contribution
  19. The Effects of School Closure Threats on Student Performance: Evidence from a Natural Experiment
  20. School Entry, Compulsory Schooling, and Human Capital Accumulation: Evidence from Michigan
  21. Topics
  22. Overeducation, Overskilling and Mental Well-being
  23. Process and Product Innovation and the Role of the Preference Function
  24. Letter
  25. Does Evasion Invalidate the Welfare Sufficiency of the ETI?
  26. How Lobbying Affects Representation: Results for Majority-Elected Politicians
  27. Consumers’ Misevaluation and Public Promotion
  28. Meet-the-competition clauses and the strategic disclosure of product quality
  29. Import Competition and Post-displacement Wages in Korea: Whom You Trade with Matters
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