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“Effective regulatory stringency” and firms’ profitability: the effects of effluent limits and government monitoring

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Abstract

The Porter hypothesis asserts that properly designed environmental regulation motivates firms to innovate, which ultimately improves profitability. Specifically, the Porter hypothesis posits that more stringent environmental regulation, i.e., greater regulatory stringency, leads to greater profitability. In contrast, the conventional “costly regulation” hypothesis posits that greater regulatory stringency weakens profitability mostly by driving up abatement costs. This study empirically tests these two hypotheses. Of course, regulatory stringency is difficult to measure. More important, regulatory stringency as codified in legislated acts and promulgated rules does not necessarily reflect regulatory stringency in practice, which we deem as “effective regulatory stringency”. Measurement of “effective regulatory stringency” is even more challenging. With this challenge in mind, we divide “effective regulatory stringency” into its two constituent components—(1) legal requirements and (2) regulatory scrutiny—the latter representing government efforts to ensure compliance with the legal requirements. For our analysis, we examine legal requirements in the form of facility-specific effluent limits and regulatory scrutiny in the form of government monitoring inspections. For our empirical analysis, we analyze the U.S. Clean Water Act under which the U.S. Environmental Protection Agency imposes numeric wastewater discharge limits on permitted facilities and conducts wastewater-related inspections. As its primary contribution, our study separately examines the effects of legal requirements and regulatory scrutiny on firm-level profitability in order to appreciate the influence of “effective regulatory stringency”.

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Notes

  1. Some studies explore companies’ desires to present a “green” image to consumers (e.g., Arora and Cason 1996) or assess management’s concerns over corporate image more generally (e.g., Downing and Kimball 1982). Other studies explore local community pressure (e.g., Henriques and Sadorsky 1996; Dasgupta et al. 2000). And some studies explore the role of stochastic discharge patterns (Bandyopadhyay and Horowitz 2006) or the possibility of zero marginal abatement costs (McClelland and Horowitz 1999).

  2. As examples, see the 2001 annual reports of four representative chemical firms: Dow Chemical, E.I. Du Pont de Nemours, Rohm & Haas, and Mississippi Chemical.

  3. The statistics cited here represent the most recent pollution abatement costs and expenditures published by the U.S. Census Bureau.

  4. Our study differs from Brunnermeier and Cohen (2003) since the two studies explore two different outcomes, which are both worthy of exploration. While profitability is a broader measure of the influence of regulatory stringency on firms’ performance and, thus, needed to test the full extent of the Porter hypothesis, we acknowledge that our broader measure does not permit a direct connection between regulatory stringency and innovation, which is important for the Porter hypothesis.

  5. We claim that we improve upon Brunnermeier and Cohen (2003) in two additional ways by (1) examining firm-level outcomes rather than sectoral outcomes and (2) providing a conceptual framework to guide our empirical analysis.

  6. Previous empirical studies that examine the effect of discharge limits on wastewater discharges examine exclusively quantity-based limits (e.g., Brännlund et al. 1995) or examine exclusively concentration-based limits (e.g., Bandyopadhyay and Horowitz 2006; Earnhart 2007).

  7. For the classification of each facility, the EPA calculates a major rating with points assigned on the basis of toxic pollution potential, flow type, conventional pollutant load, public health impact, and water quality impact; the EPA classifies any discharger with a point total of 80 or more as a “major facility”. The EPA also classifies any facility generating a “significant” effect on the receiving water body as a “major facility”.

  8. The chemical industry is not necessarily representative of all industrial sectors. Indeed, its unique attributes contribute to our interest in studying it.

  9. The depicted framework draws heavily upon the framework provided by Earnhart (2010) and Gray and Shadbegian (2005), while reflecting upon frameworks provided by Bluffstone (1999), Barla (2007), and Dasgupta et al. (2000).

  10. However, firms may be unable to anticipate fully future permitted discharge limit levels or firms may not be able to respond to even an anticipated limit before the limit becomes legally binding. Specifically, firms may need more time to plan and implement any response to tighter limits. Regardless of the reason, the connection from limit stringency to profitability might involve a lag. To assess this possibility empirically, we estimate profitability using an alternative regressor set that additionally includes a lagged discharge limit structure: 1-quarter lag, 2-quarter lag, 3-quarter lag, and 4-quarter lag. This lag structure follows Lanoie et al. (2008). Estimation results from this alternative specification support our claim that discharge limits affect a firm’s profitability without a lag. Specifically, the lagged limit coefficients do not prove statistically significant when considered jointly using a Wald Test. Moreover, no individual coefficient proves significant.

  11. Even though our choice of government monitoring inspections is consistent with the most relevant previous study, inspections represent only one component of regulatory scrutiny. Certainly, we could explore other measures of the regulatory scrutiny applied by environmental protection agencies to induce compliance with imposed discharge limits. As the most obvious dimension, we could explore the count or monetary value of any sanctions imposed for non-compliance with imposed discharge limits. However, we purposively avoid sanctions for three reasons. First, sanctions are more vulnerable to concerns of endogeneity. Second, by extracting money from firms, sanctions directly lower profits by raising costs in a way that is not related to innovation offsets, which complicates our testing of the Porter hypothesis. Third and most important, sanctions are imposed on a small proportion of permitted facilities, consistent with the reasonably strong prevalence of compliance. In contrast, inspections are conducted at facilities regularly. Therefore, we are able to garner much more variation in our sample data by focusing on inspections.

  12. Online Appendix Table A-1 provides distributions of the pollutant-basis-specific discharge limits.

  13. To construct one alternative measure of legal stringency, we divide each of the monthly discharge limits by the median discharge limit when considering all populated months and facilities. Use of this alternative measure generates estimation results nearly identical to those reported below. In particular, the Model Set C estimates offer identical statistical significance since the means and medians only scale the coefficient magnitudes. To construct a second alternative measure of legal stringency, we divide each of the monthly discharge limits by the mean discharge limit generated by averaging across firms. Use of this second alternative measure generates estimation results highly similar to those displayed below; these alternative results support conclusions identical to those reported below.

  14. We assess whether or not our chosen replacement values are the “best” values. For each pollutant-basis-specific limit, we generate an indicator that takes a value of one when we use a limit replacement; this indicator equals zero otherwise. We include these four indicators as regressors in our econometric analysis. If these indicators prove statistically significant, then our replacement values are not “best”. These indicators never prove significant in our econometric analysis.

  15. This construction involves three issues worthy of discussion. First, this regressor construction imposes the restriction that the influence of each quarter’s count of government monitoring inspections is equal across the four individual quarters. This restriction represents a joint null hypothesis of equal coefficients. We test this hypothesis by incorporating four lagged individual quarter regressors into an alternative specification and implementing a Wald test to assess the joint null hypothesis. The test statistic fails to reject the null hypothesis so use of a composite measure appears statistically appropriate. Second, the regressor makes no distinction between state and federal inspections, consistent with Brunnermeier and Cohen (2003) and most previous studies of wastewater discharges (e.g., Laplante and Rilstone 1996; Helland 1998). Third, several previous studies of wastewater discharges use a similar approach for explaining the influence of inspections on facilities’ chosen discharges (e.g., Earnhart 2004b, 2009; Laplante and Rilstone 1996; Helland 1998).

  16. Since one might expect that the relationship between environmental regulation and profitability depends on ownership structure, we do not claim that our results generalize to privately owned firms.

  17. As an alternative measure, for each firm, we calculate the proportion of facilities inspected at least once over the preceding 4-quarter period. Use of this alternative measure generates highly similar estimation results in general; however, the alternative estimates offer less evidence of a link from monitoring scrutiny to profitability especially when the specification includes an interaction term (Model C).

  18. The online appendix explores the sub-sample of firms without a primary SIC code in the chemical industries.

References

  • Alpay, E., Buccola, S., & Kerkvliet, J. (2002). Productivity growth and environmental regulation in Mexican and U.S. food manufacturing. American Journal of Agricultural Economics, 84(4), 887–901.

    Article  Google Scholar 

  • Ambec, S., & Barla, P. (2002). A theoretical foundation of the Porter hypothesis. Economic Letters, 75(3), 355–360.

    Article  Google Scholar 

  • Ambec, S., & Barla, P. (2006). Can environmental regulations be good for business? An assessment of the Porter hypothesis. Energy Studies Review, 14(2), 42–62.

    Article  Google Scholar 

  • Ambec, S., & Lanoie, P. (2008). Does it pay to be green? A systematic overview. Academy of Management Perspectives, 22(4), 45–62.

    Article  Google Scholar 

  • Arimura, T., Hibiki, A., & Johnstone, N. (2007). An empirical study of environmental R&D: What encourages facilities to be environmentally-innovative? In N. Johnstone (Ed.), Corporate behaviour and environmental policy (pp. 142–173). Cheltanham: Edward Elgar.

    Google Scholar 

  • Arora, S., & Cason, T. (1996). Why do firms volunteer to exceed environmental regulations? Understanding participation in EPA’s 33/50 program. Land Economics, 72(4), 413–432.

    Article  Google Scholar 

  • Bandyopadhyay, S., & Horowitz, J. (2006). Do plants over-comply with water pollution regulations? The role of discharge variability. B.E. Journal of Economic Analysis and Policy, 6(1), 1–32.

    Google Scholar 

  • Barbera, A. J., & McConnell, V. D. (1990). The impact of environmental regulations on industry productivity: Direct and indirect effects. Journal of Environmental Economics and Management, 18(1), 50–65.

    Article  Google Scholar 

  • Barla, P. (2007). ISO 14001 certification and environmental performance in Quebec’s pulp and paper industry. Journal of Environmental Economics and Management, 53, 291–306.

    Article  Google Scholar 

  • Becker, R., & Henderson, V. (2000). Effects of air quality regulations on polluting industries. Journal of Political Economy, 108(2), 379–421.

    Article  Google Scholar 

  • Berman, E., & Bui, L. (2001a). Environmental regulation and productivity: Evidence from oil refineries. Review of Economics and Statistics, 83(3), 498–510.

    Article  Google Scholar 

  • Berman, E., & Bui, L. T. M. (2001b). Environmental regulation and labor demand: Evidence from the South Coast Air Basin. Journal of Public Economics, 79(2), 265–295.

    Article  Google Scholar 

  • Bluffstone, R. (1999). Are the costs of pollution abatement lower in Central and Eastern Europe? Evidence from Lithuania. Environment and Development Economics, 44, 449–470.

    Article  Google Scholar 

  • Brännlund, R., Färe, R., & Grosskopf, S. (1995). Environmental regulation and profitability: An application to Swedish pulp and paper mills. Environmental and Resource Economics, 6(1), 23–36.

    Article  Google Scholar 

  • Brunnermeier, S. B., & Cohen, M. A. (2003). Determinants of environmental innovation in US manufacturing industries. Journal of Environmental Economics and Management, 45, 278–293.

    Article  Google Scholar 

  • Burtraw, D. (2000). Innovation under the tradable sulfur dioxide emission permits program in the U.S. Electricity Sector. Discussion Paper 00-38, Resources for the Future, Washington, DC.

  • Capon, N., Farley, J. U., & Hoenig, S. (1990). Determinants of financial performance: A meta-analysis. Management Science, 36(10), 1143–1159.

    Article  Google Scholar 

  • Carrión-Flores, C., & Innes, R. (2010). Environmental innovation and environmental performance. Journal of Environmental Economics and Management, 59, 27–42.

    Article  Google Scholar 

  • Dasgupta, S., Hettige, H., & Wheeler, D. (2000). What improves environmental compliance? Evidence from Mexican industry. Journal of Environmental Economics and Management, 39, 39–66.

    Article  Google Scholar 

  • Dean, T. J., Brown, R. L., & Stango, V. (2000). Environmental regulation as a barrier to the formation of small manufacturing establishments: A longitudinal examination. Journal of Environmental Economics and Management, 40(1), 56–75.

    Article  Google Scholar 

  • Deily, M., & Gray, W. (1991). Enforcement of pollution regulation in a declining industry. Journal of Environmental Economics and Management, 21, 260–274.

    Article  Google Scholar 

  • Downing, P., & Kimball, J. (1982). Enforcing pollution control laws in the United States. Policy Studies Journal, 11(1), 15–22.

    Google Scholar 

  • Dufour, C., Lanoie, P., & Patry, M. (1998). Regulation and productivity. Journal of Productivity Analysis, 9(3), 233–247.

    Article  Google Scholar 

  • Earnhart, D. (2004a). Regulatory factors shaping environmental performance at publicly-owned treatment plants. Journal of Environmental Economics and Management, 48(1), 655–681.

    Article  Google Scholar 

  • Earnhart, D. (2004b). Panel data analysis of regulatory factors shaping environmental performance. Review of Economics and Statistics, 86(1), 391–401.

    Article  Google Scholar 

  • Earnhart, D. (2004c). The effects of community characteristics on polluter compliance levels. Land Economics, 80(3), 408–432.

    Article  Google Scholar 

  • Earnhart, D. (2007). Effects of permitted effluent limits on environmental compliance levels. Ecological Economics, 61(1), 178–193.

    Article  Google Scholar 

  • Earnhart, D. (2009). The influence of facility characteristics and permit conditions on the effects of environmental regulatory deterrence. Journal of Regulatory Economics, 36(3), 247–273.

    Article  Google Scholar 

  • Earnhart, D. (2010). The effects of financial status on corporate environmental performance: Liquidity, solvency, and ‘Bottomline Success’. University of Kansas working paper.

  • Earnhart, D., & Segerson, K. (2012). The influence of financial status on the effectiveness of environmental enforcement. Journal of Public Economics, 96, 670–684.

    Article  Google Scholar 

  • EPA. (1990). A Primer on the Office of Water Enforcement and Permits and Its Programs. Office of Water, Environmental Protection Agency, Washington, DC.

  • EPA. (1997). Chemical Industry National Environmental Baseline Report 1990-1994, Office of Enforcement and Compliance Assurance, Environmental Protection Agency, EPA 305-R-96-002, October 1997.

  • EPA. (1999). EPA/CMA Root Cause Analysis Pilot Project: An Industry Survey, Environmental Protection Agency, EPA-305-R-99-001, May 1999.

  • Gabel, H. L., & Sinclair-Desgagné, B. (2002). The firm, its procedures, and winwin environmental regulations. In A. Rose, H. Folmer, H. L. Gabel, & S. Gerking (Eds.), Frontiers of environmental economics. Cheltenham: Edward Elgar.

    Google Scholar 

  • Gollop, F. M., & Roberts, M. J. (1983). Environmental regulations and productivity growth: The case of fossil-fueled electric power generation. Journal of Political Economy, 91(4), 654–674.

    Article  Google Scholar 

  • Gray, W. (1987). The cost of regulation: OSHA, EPA, and the productivity slowdown. American Economic Review, 77(5), 998–1006.

    Google Scholar 

  • Gray, W. B., & Deily, M. E. (1996). Compliance and enforcement: Air pollution regulation in the U.S. steel industry. Journal of Environmental Economics and Management, 31, 96–111.

    Article  Google Scholar 

  • Gray, W. B., & Shadbegian, R. J. (1998). Environmental regulation investment timing and technological choice. Journal of Industrial Economics, 46(2), 235–256.

    Article  Google Scholar 

  • Gray, W. B., & Shadbegian, R. J. (2003). Plant vintage, technology, and environmental regulation. Journal of Environmental Economics and Management, 46(3), 384–402.

    Article  Google Scholar 

  • Gray, W. B., & Shadbegian, R. J. (2005). When and why do plants comply? Paper mills in the 1980s. Law and Policy, 27(2), 238–261.

    Article  Google Scholar 

  • Greenstone, M. (2002). The impacts of environmental regulations on industrial activity: Evidence from the 1970 and 1977 Clean Air Act amendments and the Census of Manufactures. Journal of Political Economy, 110(6), 1175–1219.

    Article  Google Scholar 

  • Hazilla, M., & Kopp, R. J. (1990). Social cost of environmental quality regulations: A general equilibrium analysis. Journal of Political Economy, 98(4), 853–873.

    Article  Google Scholar 

  • Helland, E. (1998). The enforcement of pollution control laws: Inspections, violations, and self-reporting. Review of Economics and Statistics, 80, 141–153.

    Article  Google Scholar 

  • Henriques, I., & Sadorsky, P. (1996). The determinants of an environmentally responsive firm: An empirical approach. Journal of Environmental Economics and Management, 30, 381–395.

    Article  Google Scholar 

  • Innes, R., & Sam, A. (2008). Voluntary pollution reductions and the enforcement of environmental law: An empirical study of the 33/50 program. Journal of Law and Economics, 51, 271–296.

    Article  Google Scholar 

  • Jaffe, A. B., & Palmer, K. (1997). Environmental regulation and innovation: A panel data study. Review of Economics and Statistics, 79(4), 610–619.

    Article  Google Scholar 

  • Jaffe, A. B., Peterson, S. R., Portney, P. R., & Stavins, R. N. (1995). Environmental regulation and the competitiveness of U.S. manufacturing: What does the evidence tell us? Journal of Economic Literature, 33(1), 132–163.

    Google Scholar 

  • Jaffe, A. B., Newell, R., & Stavins, R. N. (2005). A tale of two market failures: Technology and environmental policy. Ecological Economics, 54(2–3), 164–174.

    Article  Google Scholar 

  • Johnstone, N., & Labonne, J. (2009). Why do manufacturing facilities introduce environmental management systems? Improving and/or signaling performance. Ecological Economics, 68(3), 719–730.

    Article  Google Scholar 

  • Jorgenson, D. W., & Wilcoxen, P. J. (1990). Environmental regulation and U.S. economic growth. Rand Journal of Economics, 21(2), 314–340.

    Article  Google Scholar 

  • Khanna, M., & Damon, L. A. (1999). EPA’s voluntary 33/50 program: Impact on toxic releases and economic performance of firms. Journal of Environmental Economics and Management, 37(1), 1–25.

    Article  Google Scholar 

  • King, A. (1999). Retrieving and transferring embodied data: Implications for management of interdependence within organizations. Management Science, 45(7), 918–935.

    Article  Google Scholar 

  • King, A. (2000). Organizational response to environmental regulation: Punctuated change or autogenesis? Business Strategy and the Environment, 4(9), 224–238.

    Article  Google Scholar 

  • Konar, S., & Cohen, M. A. (2001). Does the market value environmental performance? Review of Economics and Statistics, 83(2), 281–289.

    Article  Google Scholar 

  • Lanoie, P., Patry, M., & Lajeunesse, R. (2008). Environmental regulation and productivity: Testing the Porter hypothesis. Journal of Productivity Analysis, 30(2), 121–128.

    Article  Google Scholar 

  • Lanoie, P., Laurent-Lucchetti, J., Johnstone, N., & Ambec, S. (2011). Environmental policy, innovation and performance: New insights on the Porter hypothesis. Journal of Economics and Management Strategy, 20(3), 803–842.

    Article  Google Scholar 

  • Laplante, B., & Rilstone, P. (1996). Environmental inspections and emissions of the pulp and paper industry in Quebec. Journal of Environmental Economics and Management, 31(1), 19–36.

    Article  Google Scholar 

  • Levinson, A. (1996). Environmental regulations and manufacturers’ location choices: evidence from the census of manufactures. Journal of Public Economics, 62(1–2), 5–29.

    Article  Google Scholar 

  • List, J. A., Millimet, D., Fredricksson, P., & McHone, W. (2003). Effects of environmental regulations on manufacturing plant births: Evidence from a propensity score matching estimator. Review of Economics and Statistics, 85(4), 944–952.

    Article  Google Scholar 

  • Managi, S., Opaluch, J. J., Jin, D., & Grigalunas, T. A. (2005). Environmental regulations and technological change in the offshore oil and gas industry. Land Economics, 81(2), 303–319.

    Article  Google Scholar 

  • McClelland, J., & Horowitz, J. (1999). The costs of water pollution regulation in the pulp and paper industry. Land Economics, 75(2), 220–232.

    Article  Google Scholar 

  • McConnell, V. D., & Schwab, R. M. (1990). The impact of environmental regulation on industry location decisions: The motor vehicle industry. Land Economics, 66(1), 67–81.

    Article  Google Scholar 

  • Mohr, R. (2002). Technical change, external economies, and the Porter hypothesis. Journal of Environmental Economics and Management, 43(1), 158–168.

    Article  Google Scholar 

  • Nagle, D. (2008). U.S. Environmental Protection Agency, Water Permits Division, Private conversation on May 10, 2008.

  • Nelson, R., Tietenberg, T., & Donihue, M. (1993). Differential environmental regulation: Effects on electric utility capital turnover and emissions. Review of Economics and Statistics, 75(2), 368–373.

    Article  Google Scholar 

  • Palmer, K. L., Oates, W. E., & Portney, P. R. (1995). Tightening environmental standards: The benefit-cost or the no-cost paradigm? Journal of Economic Perspectives, 9(4), 119–132.

    Article  Google Scholar 

  • Perez-Quiros, G., & Timmerman, A. (2000). Firm size and cyclical variations in stock returns. Journal of Finance, 55(3), 1229–1262.

    Article  Google Scholar 

  • Popp, D. (2010). Exploring links between innovation and diffusion: Adoption of NOX control technologies at U.S. coal-fired power plants. Environmental and Resource Economics, 45(3), 319–352.

    Article  Google Scholar 

  • Porter, M. (1990). Effect of environmental regulation on firm outcomes. Harvard Business Review, 40, 1–20.

    Google Scholar 

  • Porter, M., & van der Linde, C. (1995). Toward a new conception of the environment-competitiveness relationship. The Journal of Economic Perspectives, 9(4), 97–118.

    Article  Google Scholar 

  • Rassier, D., & Earnhart, D. (2010a). The effect of clean water regulation on profitability: Testing the Porter hypothesis. Land Economics, 86(2), 329–344.

    Article  Google Scholar 

  • Rassier, D., & Earnhart, D. (2010b). Does the Porter Hypothesis explain expected future financial performance? The effect of clean water regulation on chemical manufacturing firms. Environmental and Resource Economics, 45(3), 353–377.

    Article  Google Scholar 

  • Research Insight 7.9\(^{\copyright }\)  (1993–2003) Standard and Poor’s of The McGraw-Hill Companies, Inc.

  • Russo, M. V., & Fouts, P. A. (1997). A resource-based perspective on corporate environmental performance and profitability. The Academy of Management Journal, 40(3), 534–559.

    Article  Google Scholar 

  • Sah, R. (1991). Social osmosis and patterns of crime. Journal of Political Economy, 99(6), 1272–1295.

    Article  Google Scholar 

  • Simpson, D., & Bradford, R. L. (1996). Taxing variable cost: Environmental regulation as industrial policy. J. of Environmental Economics and Management, 30(3), 282–300.

    Article  Google Scholar 

  • Wasserman, C. (1984). Improving the efficiency and effectiveness of compliance monitoring and enforcement of environmental policies, United States: A National Review,” OECD.

  • Xepapadeas, A., & de Zeeuw, A. (1999). Environmental policy and competitiveness: The Porter hypothesis and the composition of capital. Journal of Environmental Economics and Management, 37(2), 165–182.

    Article  Google Scholar 

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Acknowledgments

This manuscript was partially developed under a STAR Research Assistance Agreement No. R-82882801-0 awarded by the U.S. Environmental Protection Agency. It has not been formally reviewed by the EPA.

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The views expressed in this document are solely those of the authors. The EPA does not endorse any products or commercial services mentioned in this manuscript. Moreover, this manuscript and the analysis herein were developed prior to and independent of the author’s employment with the Bureau of Economic Analysis (BEA). The views expressed in this manuscript are solely those of the authors and not necessarily those of the U.S. Department of Commerce or BEA.

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  1. Department of Economics, University of Kansas, 436 Snow Hall, 1460 Jayhawk Blvd, Lawrence, KS, 66045, USA

    Dietrich Earnhart

  2. U.S. Department of Commerce, Bureau of Economic Analysis, Washington, DC, USA

    Dylan G. Rassier

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  1. Dietrich Earnhart
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Earnhart, D., Rassier, D.G. “Effective regulatory stringency” and firms’ profitability: the effects of effluent limits and government monitoring. J Regul Econ 50, 111–145 (2016). https://doi.org/10.1007/s11149-016-9304-8

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