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Price mimicking under cost-of-service regulation: the Swedish water sector

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Abstract

This study provides an empirical test of price mimicking among publicly owned water utilities. Using a fixed effects spatial Durbin model with data from Swedish municipalities during 2002–2012, I estimate the elasticity of the own relative to neighbors’ average price to 0.14. This behavior can be explained in terms of an informal yardstick competition: when consumers use neighboring municipalities’ prices as benchmarks for costs or as behaviorally based reference prices, policy makers will face the risk of consumer complaints and reduced voter support if deviating too much from neighboring municipalities’ prices. Further, I find some evidence that price mimicking is more pronounced in municipalities where voter support for the ruling coalition is weak.

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Notes

  1. For a more thorough review of these models, see Brueckner (2003), and Revelli (2005).

  2. As discussed in the introduction, these markets are not subject to a c-o-s regulation. Still, it should be noted that in none of these markets utilities are completely free to set their own prices. The Austrian utilities are not allowed to set prices that exceed twice the total cost of production. However, Klien (2015) notes that “...price setting appears very ad-hoc and discretionary...” (p. 6) and that “...the Austrian water sector...is characterized by the absence of a regulator...” (p. 6) Similarly, the Swedish market for district heating is in theory regulated by a specific district heating law. But this regulation does not cover price setting per se, so the market may be characterized as unregulated, as argued by Konkurrensverket (2013).

  3. In total there are 290 municipalities. Huddinge municipality has been excluded due to missing data on water prices, and Knivsta municipality has been excluded since it was formed in 2003 (Knivsta was earlier a part of Uppsala municipality).

  4. Moran’s I is a measure of spatial autocorrelation, see Moran (1950) for a technical discussion.

  5. The models are estimated using Stata’s xsmle command, which is described by Belotti and Mortari (2013). Coordinates of the municipal offices have been obtained using Stata’s geocode command, which is described by Ozimek and Miles (2012).

  6. The estimator has been implemented using Stata’s spreg command, which is described in detail by Drukker et al. (2013).

  7. Since the SAR model is nested within the Durbin model, the first procedure is to test the null hypothesis \({\hat{\gamma }}=0\), i.e., that all coefficients on the spatially lagged independent variables in the Durbin model are zero. The p value is 0.035, so the null hypothesis is rejected. Further, even if the Mixed model provides no statistically significant results on the presence of autocorrelation, Wald tests indicate that there is a stronger case for spatial dependence in the dependent variable than in the error term: Since the mixed model nests both the SAR and the SEM models, the procedure is to first test the restriction \(\hat{\rho }=0\), which yields a p value of 0.16. When instead testing the restriction \(\hat{\lambda }=0\) the p value is 0.97.

  8. Testing the null hypothesis \({{\hat{\upgamma }}}=0\) yields a p value of 0.24, so there is a relatively high probability that the SAR model is appropriate.

References

  • Allers, M. A., Maarten, A., & Paul Elhorst, J. (2005). Tax mimicking and yardstick competition among local governments in the Netherlands. International Tax and Public Finance, 12(4), 493–513.

    Article  Google Scholar 

  • Anselin, L. (1980). Estimation methods for spatial autoregressive structures. Ph.D. Dissertation, Regional Science Dissertation and Monograph Series nr 8. Ithaca: Cornell University.

  • Azomahou, T., & Lahatte, A. (2000). On the inconsistency of the ordinary least squares estimator for spatial autoregressive processes. Working papers of BETA 2000-12.

  • Belotti, F., Hughes, G., & Mortari, A. P. (2013). XSMLE-A command to estimate spatial panel models in Stata. In German Stata user group meetings 2013 09, Stata Users Group.

  • Besley, T., & Case, A. (1995). Incumbent behavior: Vote-seeking, tax-setting, and yardstick competition. American Economic Review, 85(1), 25–45.

    Google Scholar 

  • Brueckner, J. K. (2003). Strategic interaction among governments: An overview of empirical studies. International Regional Science Review, 26(2), 175–188.

    Article  Google Scholar 

  • Drukker, D. M., Prucha, I., & Raciborski, R. (2013). Maximum likelihood and generalized spatial two-stage least-squares estimators for a spatial-autoregressive model with spatial-autoregressive disturbances. Stata Journal, 13(2), 221–241.

    Google Scholar 

  • Francese, M., Piacenza, M., Romanelli, M., & Turati, G. (2014). Understanding inappropriateness in health spending: The role of regional policies and institutions in caesarean deliveries. Regional Science and Urban Economics, 49, 262–277.

    Article  Google Scholar 

  • Geys, B. (2006). Looking across borders: A test of spatial policy interdependence using local government efficiency ratings. Journal of Urban Economics, 60(3), 443–462.

    Article  Google Scholar 

  • Haraldsson, M. (2013). Särredovisning inom VA-branschen (Vol. 2013-21). Svenskt Vatten Utveckling.

  • Holmström, B. (1982). Moral hazard in teams. Bell Journal of Economics, 13(2), 324–340.

    Article  Google Scholar 

  • Kelejian, H. H., & Ingmar, R. P. (1998). A generalized spatial two-stage least squares procedure for estimating a spatial autoregressive model with autoregressive disturbances. The Journal of Real Estate Finance and Economics, 17(1), 99–121.

    Article  Google Scholar 

  • Klien, M. (2015). The political side of public utilities: How opportunistic behaviour and yardstick competition shape water prices in Austria. Papers in Regional Science, 94(4), 869–890.

    Article  Google Scholar 

  • Konkurrensverket. (2013). Inför prisregleringen av fjärrvärme - vilka lärdomar kan dras från ekonomisk teori och empiri? Report 2013:1

  • Laffont, J.-J., & Tirole, J. (1993). A theory of incentives in procurement and regulation (1st ed., Vol. 1). Cambridge: The MIT Press.

  • LeSage, J. P., & Pace, R. K. (2009). Introduction to spatial econometrics statistics: A series of textbooks and monographs. Boca Raton: CRC Press LLC.

    Book  Google Scholar 

  • Mizutani, F., & Urakami, T. (2001). Identifying network density and scale economies for Japanese water supply organizations. Papers in Regional Science, 80(2), 211–230.

    Article  Google Scholar 

  • Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23.

    Article  Google Scholar 

  • Nauges, C., & Berg, C. (2008). Economies of density, scale and scope in the water supply and sewerage sector: A study of four developing and transition economies. Journal of Regulatory Economics, 34(2), 144–163.

    Article  Google Scholar 

  • Ozimek, A., & Miles, D. (2012). GEOCODE: Stata module to geocode data. Statistical Software Components, Boston College Department of Economics.

  • Revelli, F. (2005). On spatial public finance empirics. International Tax and Public Finance, 12(4), 475–492.

    Article  Google Scholar 

  • Revelli, F. (2006). Performance rating and yardstick competition in social service provision. Journal of Public Economics, 90(3), 459–475.

    Article  Google Scholar 

  • Revelli, F., & Tovmo, P. (2007). Revealed yardstick competition: Local government efficiency patterns in Norway. Journal of Urban Economics, 62(1), 121–134.

    Article  Google Scholar 

  • SCS. (2013). Water and Sewage Act, Swedish Code of Statutes 2006:412.

  • Shleifer, A. (1985). A theory of yardstick competition. RAND Journal of Economics, 16(3), 319–327.

    Article  Google Scholar 

  • Söderberg, M., & Tanaka, M. (2012). Spatial price homogeneity as a mechanism to reduce the threat of regulatory intervention in locally monopolistic sectors. Working Papers hal-00659458, HAL.

  • Solé-Ollé, A. (2003). Electoral accountability and tax mimicking: The effects of electoral margins, coalition government, and ideology. European Journal of Political Economy, 19(4), 685–713.

    Article  Google Scholar 

  • Statistics-Sweden. (2013). Official records of Swedish statistics, Statistics Sweden. www.scb.se.

  • SWSST. (2013). Official legal records. http://www.domstol.se/Ladda-ner--bestall/Domar-beslut-och-handlingar/Statens-va-namnds-avgoranden/Avgoranden-enligt-1970-ars-va-lag/-27---Tillamplig-va-taxa-A-och-uppskov-med-betalning-B/. Accessed March 21, 2017.

  • Thaler, R. (1985). Mental accounting and consumer choice. Marketing Science, 4(3), 199–214.

    Article  Google Scholar 

  • Tiebout, C. M. (1956). A pure theory of local expenditures. Journal of Political Economy, 64, 416.

    Article  Google Scholar 

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Acknowledgements

I would like to thank Richard Friberg, Pär Holmberg, two anonymous referees, and participants at the 2014 ENTER-Jamboree for valuable comments. Financial support from the Jan Wallander and Tom Hedelius Foundation (Grant nr H13-0467) and the Swedish Competition Authority is greatly appreciated.

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Correspondence to Erik Lundin.

Appendix A

Appendix A

See Fig. 3, Table 6.

Fig. 3
figure 3

Density plot of the water price. Note: This figure depicts a kernel density plot of the water price for the whole sample, i.e., a total of 3168 observations for 288 municipalities during 2002–2012. The unit of measurement is the total cost (fixed plus variable cost) in SEK for a typical stand-alone house consuming 150 \(\mathrm{m}^{3}\) per year

Table 6 Detailed description of the variables

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Lundin, E. Price mimicking under cost-of-service regulation: the Swedish water sector. J Regul Econ 52, 313–332 (2017). https://doi.org/10.1007/s11149-017-9345-7

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