Skip to main content
SpringerLink
Log in

Changing state interest group systems: replicating and extending the ESA model

  • Original Article
  • Published:
Interest Groups & Advocacy Aims and scope Submit manuscript

Abstract

The ESA model adapted for interest group research by Gray and Lowery (1996) based on population ecology theory has become perhaps the most widely used framework for studying interest groups in the American states. Yet though replication is a hallmark of scientific research, and while it is important to verify a model’s fundamental assumptions before expanding on it, there has been little replication of the energy-stability-area (ESA) model with new, but comparable, data. Using new data on state interest groups from 2006 to 2017, I replicate their early analyses. While some of their findings do not hold up, many do, including the density dependence effect, which I further explore with new variables. I then extend ESA by exploring interactions between its component variables. Finally, I propose a new term for the model, the government’s capacity to support new policies as an influence on group formation and find it is empirically supported.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Notes

  1. The idea is that at lower, and even mid-range, values, GSP should have a positive linear effect, but at higher values, captured by the square of the variable, the effect should be negative. Thus the analysis captures a nonlinear effect for use in a linear model where the effect initially curves up, plateaus, and then starts to curve back down.

  2. Interestingly, Gray and Lowery equate tests of Stability, as measured by the years since statehood, as a test of the hypothesis advanced long ago by Olson (1982), who claimed that interest groups increase in number over time until their demands become so numerous that they effectively paralyze the government. Since Olson’s hypothesis has not received much empirical support (see Unger and van Waarden 1999), I do not define Stability this way.

  3. For information on the Institute, see http://www.followthemoney.org/.

  4. Data and supporting information is at https://thomasholyoke.com/home/peer-reviewed-journal-articles/.

  5. GSP data is at https://www.bea.gov/data/gdp/gdp-state. To prevent vanishingly small coefficients, it is divided by 100, so its mean is 3.16, its standard deviation is 3.92, and it ranges from 0.24 to 28.02.

  6. Ranney Index for 2006 to 2012 is from Carl Klarner at https://dataverse.harvard.edu/dataset.xhtml?persistentId=hdl:1902.1/22519. Later data is from Holbrook and Raja (2018); since there is no new data for 2017, the 2016 data is repeated. Mean is 0.86, standard deviation is 0.09, and it ranges from 0.66 to 0.99 where higher values mean greater party competition and lower values mean single-party dominance.

  7. Total lobbying organizations ranges from 99 to 4,233 with a mean of 1,076 and standard deviation of 816. Since in some models lobbying organizations divided by GSP produced coefficients that were essentially 0, it was then divided by 100, so now mean = 533, S.D. = 299, ranging from 66 to 1,826.

  8. As Gray and Lowery did, I also estimated individual models for each year, but since they do not produce different results, the results are not presented here (but are available on request).

  9. The sectors are agriculture, communication, construction, general business (including manufacturing and retail), education, electronics, energy, entertainment, finance and insurance, health, law, leisure, real estate, social services, and transportation.

  10. These results are available in the online appendix (https://thomasholyoke.com/home/peer-reviewed-journal-articles/).

  11. From the U.S. Census Bureau. Results are in the online appendix (https://thomasholyoke.com/home/peer-reviewed-journal-articles/).

  12. State population is from the Census Bureau. Because population numbers are very large relative to the dependent variable, the coefficients are essentially 0, so I divided it by 1,000,000. Its mean is now 6.17, the standard deviation is 6.78, and it ranges from 0.51 to 39.36.

  13. From annual editions of Fiscal Survey of the States published by the National Association of State Budget Officers. It is divided by population for a per capita measure, and then multiplied by 1,000 to prevent very small coefficients. The mean is 2.61, the standard deviation is 1.70, and it ranges from 0.87 to 28.05.

  14. From the Census Bureau and is divided by state population for a per capita measure. Because this made the measure very small, I multiplied it by 1 billion. The mean is 4028, its standard deviation is 2755, and ranges from 751 to 41,565.

  15. The mean is 417, the standard deviation is 242, and it ranges from 47 to 1293.

  16. Results are in the online appendix.

  17. From Fiscal Survey of the States and standardized to year 2000 dollars. It is divided by population, but then multiplied by 10,000 to make the coefficients readable. Mean is 0.25, standard deviation is 0.17, and it ranges from 0.07 to 2.76.

  18. Data comes from the National Institute for Education Statistics at the U.S. Department of Education. It is divided by population and multiplied by 100. Its mean is 0.60, standard deviation is 0.23, and ranges from 0.22 to 4.35.

  19. See (Berry et al. 1998). The data is at https://rcfording.com/state-ideology-data/. Since they have not yet estimated 2017 data, I repeat the 2016 data. To produce more meaningful coefficients, the measure is divided by 100. The mean is 0.48, the standard deviation is 0.27, and it ranges from 0.03 to 0.97.

  20. Results are in the online appendix.

  21. Results are in the online appendix.

  22. The coding was done by Holyoke (2019).

  23. The associations dependent variable’s mean is 297, its standard deviation is 170, and it ranges from 38 to 950. For change in citizen / public interest groups, the mean is 0.08, standard deviation is 0.75, and ranges from − 0.93 to 14.58. It is also worth noting that these results are largely the same when simply using a one year lag of the number of citizen and public interest groups.

  24. While research by Kattelman (2015) finds a connection between legislative professionalism and interest group growth, Berkman (2001) came to the opposite conclusion, arguing that there is density dependence here because very professionalized legislatures have little need for interest group information and this depresses group formation.

  25. This comes from annual editions of the Book of the States.

  26. At https://www.aei.org/wp-content/uploads/2017/09/Kallen-WP-Sept-217.pdf.

  27. The eigenvalue of the factor is 2.53. Legislative professionalism loads at 0.64, state employees at 0.75, state revenue at 0.84, Democratic legislators at 0.53, governor’s party at 0.38, governor’s budget powers at 0.24, and state government ideology at 0.61. Its mean is 0.01, standard deviation is 0.98, and it ranges from − 1.48 to 4.98.

References

  • Andserson, S., and P. Habel. 2009. Revisiting adjusted ADA scores for the U.S. Congress, 1947–2007. Political Analysis 17 (Winter): 83–88.

    Article  Google Scholar 

  • Baldassarri, D. 2011. Partisan joiners: Associational membership and political polarization in the United States (1974–2004). Social Science Quarterly 92 (September): 631–655.

    Article  Google Scholar 

  • Balogh, B. 2015. The associational state: American governance in the twentieth century. Philadelphia: University of Pennsylvania Press.

    Book  Google Scholar 

  • Baumgartner, F.R., V. Gray, and D. Lowery. 2009. Federal policy activity and the mobilization of state lobbying organizations. Political Research Quarterly 62 (September): 552–567.

    Article  Google Scholar 

  • Baumgartner, F.R., H.A. Larsen-Price, B.L. Leech, and P. Rutledge. 2011. Congressional and presidential effects on the demand for lobbying. Political Research Quarterly 64 (March): 3–16.

    Article  Google Scholar 

  • Beck, N., and J.N. Katz. 1995. What to do (and not to do) with time-series cross-section data. American Political Science Review 89 (September): 634–647.

    Article  Google Scholar 

  • Berkman, M.B. 2001. Legislative professionalism and the demand for groups: The institutional context of interest population density. Legislative Studies Quarterly 26 (November): 661–679.

    Article  Google Scholar 

  • Berry, W.D., E.J. Ringquist, R.C. Fording, and R.L. Hanson. 1998. Measuring citizen and government ideology in the American states, 1960–1993. American Journal of Political Science. 42 (January): 327–348.

    Article  Google Scholar 

  • Berry, J.M. 1999. The new liberalism: The rising power of citizen groups. Washington, DC: Brookings Institution Press.

    Google Scholar 

  • Brambor, T., W.R. Clark, and M. Golder. 2006. Understanding interaction models: Improving empirical analyses. Political Analysis 14 (Winter): 63–82.

    Article  Google Scholar 

  • Carson, J.L., M.H. Crespin, J.A. Jenkins, and R.J. Vander Wielen. 2004. Shirking in the contemporary Congress: A reappraisal. Political Analysis 12 (Spring): 176–179.

    Article  Google Scholar 

  • Chamberlain, A., A.B. Yanus, and N. Pyeatt. 2019. Revisiting the ESA model: A historical test. Interest Groups & Advocacy 8 (March): 23–43.

    Article  Google Scholar 

  • Chamberlain, A., A.B. Yanus, and N. Pyeatt. 2020. Expanding the energy stability-area model: Density dependence in voluntary associations in the early 20th century. Interest Groups & Advocacy 9 (March): 57–79.

    Article  Google Scholar 

  • Clark, T.S., and D.A. Linzer. 2015. Should I use fixed or random effects? Political Science Research and Methods 3 (2): 399–408.

    Article  Google Scholar 

  • Dusso, A. 2010. Legislation, political context, and interest group behavior. Political Research Quarterly 63 (March): 55–67.

    Article  Google Scholar 

  • Fisker, H.M. 2013. Density dependence in corporative systems: Development of the population of Danish patient groups. Interest Groups & Advocacy 2 (June): 119–138.

    Article  Google Scholar 

  • Garlick, A., and J. Cluverius. 2020. Automated estimates of state interest group lobbying populations. Interest Groups & Advocacy 9 (June): 396–409.

    Article  Google Scholar 

  • Gray, V., and D. Lowery. 1993. The diversity of state interest group systems. Political Research Quarterly 46 (March): 81–97.

    Article  Google Scholar 

  • Gray, V., and D. Lowery. 1996. The population ecology of interest representation. Ann Arbor: University of Michigan Press.

    Book  Google Scholar 

  • Gray, V., and D. Lowery. 1997. Life in a niche: Mortality anxiety among organized interests in the American states. Political Research Quarterly 50 (March): 25–47.

    Article  Google Scholar 

  • Halpin, D.R., and G. Jordan. 2009. Interpreting environments: Interest group response to population ecology pressures. British Journal of Political Science 39 (April): 243–265.

    Article  Google Scholar 

  • Hanegraaff, M., J. van der Ploeg, and J. Berkhout. 2020. Standing in a crowded room: Exploring the relationship between interest group system density and access to policymakers. Political Research Quarterly 73 (January): 51–64.

    Article  Google Scholar 

  • Hansen, J.M. 1985. The political economy of group membership. American Political Science Review 79 (March): 79–96.

    Article  Google Scholar 

  • Holbrook, T.M., and R.J. La Raja. 2018. Parties and elections. In Politics in the American states, ed. V. Gray, R.L. Hanson, and T. Kousser, 57–97. Thousand Oaks: Sage.

    Google Scholar 

  • Holyoke, T.T. 2019. Dynamic state interest group systems: A new look with new data. Interest Groups & Advocacy 8 (December): 499–518.

    Article  Google Scholar 

  • Hunter, K.G., L.A. Wilson, and G.G. Brunk. 1991. Societal complexity and interest-group lobbying in the American states. Journal of Politics 53 (May): 488–503.

    Article  Google Scholar 

  • Johnson, J.B., R.A. Joslyn, and H.T. Reynolds. 2001. Political science research methods, 4th ed. Washington, DC: Congressional Quarterly Press.

    Google Scholar 

  • Kashin, K., G. King, and S. Soneji. 2015. Explaining systematic bias and nontransparency in U.S. Social Security Administration forecasts. Political Analysis 23 (Summer): 336–362.

    Article  Google Scholar 

  • Kattelman, K.T. 2015. Legislative professionalism and group concentration: The ESA model revisited. Interest Groups & Advocacy 4 (June): 165–184.

    Article  Google Scholar 

  • King, D.C., and J.L. Walker. 1992. The provision of benefits by interest groups in the United States. Journal of Politics 54 (May): 394–426.

    Article  Google Scholar 

  • Klüver, H., and E. Zeidler. 2019. Explaining interest group density across economic sectors: Evidence from Germany. Political Studies 67 (2): 459–478.

    Article  Google Scholar 

  • Leavitt, F. 2001. Evaluating scientific research. Upper Saddle: Prentice Hall.

    Google Scholar 

  • Loomis, B.A. 2015. Beyond metaphor: Populations and groups, interests, and lobbyists. In The population ecology of interest communities, ed. David Lowery, Darren Halpin, and Virginia Gray, 249–262. London: Palgrave-Macmillan.

    Google Scholar 

  • Lowery, D., and V. Gray. 1993. The density of state interest group systems. Journal of Politics 55 (February): 191–206.

    Article  Google Scholar 

  • Lowery, D., and V. Gray. 1995. The population ecology of Gucci Gulch, or the natural regulation of interest group numbers in the American states. American Journal of Political Science 39 (February): 1–29.

    Article  Google Scholar 

  • Lowery, D., and V. Gray. 2007. Interest organization communities: Their assembly and consequences. In Interest group politics, 7th ed., ed. Allan Cigler and Burdett Loomis, 130–154. Washington, DC: Congressional Quarterly Press.

    Google Scholar 

  • Lowery, D., V. Gray, J. Anderson, and A.J. Newmark. 2004. Collective action and the mobilization of institutions. Journal of Politics 66 (August): 684–705.

    Article  Google Scholar 

  • Lowery, D., V. Gray, and J. Cluverius. 2015. Temporal change in the density of state interest communities, 1980 to 2007. State Politics & Policy Quarterly 15 (May): 263–286.

    Article  Google Scholar 

  • Lowery, D., V. Gray, J. Wolak, E. Godwin, and W. Kilburn. 2005. Reconsidering the counter mobilization hypothesis: Health policy lobbying in the American states. Political Behavior 27 (June): 99–132.

    Article  Google Scholar 

  • McFarland, A.S. 1984. Common cause. Catham: Catham House Publishers.

  • Messer, A., J. Berkhout, and D. Lowery. 2011. The density of the EU interest system: A test of the ESA model. British Journal of Political Science 41 (January): 161–190.

    Article  Google Scholar 

  • Meyer, D.S., and S. Staggenborg. 1996. Movements, countermovements, and the structure of political opportunity. American Journal of Sociology 101 (May): 1628–1660.

    Article  Google Scholar 

  • Morehouse, S.M. 1981. State politics, parties, and policy. New York: Holt, Rinehart, and Winston.

    Google Scholar 

  • Neulip, J., and R. Crandall. 1993. Reviewer bias against replication research. Journal of Social Behavior and Personality 8 (1): 21–29.

    Google Scholar 

  • Newmark, A.J., and A.J. Nownes. 2017. It’s all relative: Perceptions of interest group influence. Interest Groups & Advocacy 6 (October): 215–230.

    Article  Google Scholar 

  • Nownes, A.J., and D. Lipinski. 2005. The population ecology of interest group death: Gay and lesbian rights interest groups in the United States, 1948–1998. British Journal of Political Science 35 (April): 303–319.

    Article  Google Scholar 

  • Olson, M. 1982. The rise and decline of nations. New Haven: Yale University Press.

    Google Scholar 

  • Rabe-Hesketh, S., and A. Skrondal. 2012. Multilevel and longitudinal modeling using Stata. College Station: Stata Press.

    Google Scholar 

  • Shor, B., and N. McCarty. 2011. The ideological mapping of American legislatures. American Political Science Review 105 (3): 530–551.

    Article  Google Scholar 

  • Squire, P. 2017. A Squire index update. State Politics & Policy Quarterly 17 (4): 361–371.

    Article  Google Scholar 

  • Strickland, J. 2019. A paradox of political reform: Shadow interests in the U.S. states. American Politics Research 47 (July): 887–914.

    Article  Google Scholar 

  • Thomas, C.S., and R.J. Hrebenar. 1992. Changing patterns of interest group activity: A regional perspective. In The politics of interests: Interest groups transformed, ed. Mark P. Petracca, 150–174. Boulder: Westview Press.

    Google Scholar 

  • Thomas, C.S., and R.J. Hrebenar. 2004. Interest groups in the states. In Politics of the American states, 8th ed., ed. Virginia Gray and Russell L. Hanson, 100–128. Washington, DC: Congressional Quarterly Press.

    Google Scholar 

  • Tilly, C. 1978. From mobilization to revolution. Reading: Addison-Wesley.

    Google Scholar 

  • Truman, D.B. 1951. The governmental process. New York: Knopf.

    Google Scholar 

  • Unger, B., and F. van Waarden. 1999. Interest associations and economic growth: A critique of Mancur Olson’s rise and decline of nations. Review of International Political Economy 6 (2): 425–467.

    Article  Google Scholar 

  • Vogel, D. 1989. Fluctuating fortunes: The political power of business in America. New York: Basic Books.

    Google Scholar 

  • Waterhouse, B.C. 2015. Lobbying America: The politics of business from Nixon to NAFTA. Princeton: Princeton University Press.

    Google Scholar 

  • Witko, C., and A.J. Newmark. 2005. Business mobilization and public policy in the US States. Social Science Quarterly 86 (June): 356–367.

    Article  Google Scholar 

  • Zeigler, L.H. 1983. Interest groups in the states. In Politics in the American states, 4th ed., ed. V. Gray, H. Jacob, and K. Vines, 97–132. Boston: Little, Brown.

    Google Scholar 

  • Zeller, B. 1954. American state legislatures, 2nd ed. New York: Thomas Y. Cromwell.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Political Science, California State University, Fresno, 2225 East San Ramon, Fresno, CA, 93740-8029, USA

    Thomas T. Holyoke

Authors
  1. Thomas T. Holyoke
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Thomas T. Holyoke.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Holyoke, T.T. Changing state interest group systems: replicating and extending the ESA model. Int Groups Adv 10, 264–285 (2021). https://doi.org/10.1057/s41309-021-00127-y

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1057/s41309-021-00127-y

Keyword

Search

Navigation