Abstract
Gaming, one of the most noticeable “diseases” plaguing performance management, has attracted abundant scholarly attention. Adopting the perspective of methodological individualism, the extant literature, however, has neglected the horizontal strategic interactions among local governments. This study develops a formal game-theoretic model to investigate the bandwagon strategy, a particular type of horizontal gaming strategy, in the context of China’s Energy Conservation and Emission Reduction (ECER) policy and applies spatial econometric methods to empirically confirm the existence of such a bandwagon strategy. Our findings suggest that horizontal gaming strategies should be taken seriously to improve the efficacy of performance management.
Disclosure statement
None.
Acknowledgments
We would like to thank Editor Steven Kelman and two anonymous reviewers for their helpful comments. Any remaining errors are those of the authors.
Notes
1 We use the term “horizontal strategic interactions” to refer to strategic interactions among actors that have no supervisor-subordinate relationship with each other.
2 The competition mechanism was deliberately not discussed by the classical work of DiMaggio and Powell (1983) because they sought to propose alternative explanations of institutional isomorphism that are different from the traditional competition-based ones. Therefore, while competition is a mechanism that contributes to institutional isomorphism, it is actually not derived from the perspective of new institutionalism.
3 More details can be found in the Policy Agenda Program: the website address is http://www.policyagendas.org/.
4 Several provinces have also publicized the detailed sub-items of the ECER expenditure in recent years. According to the author’s calculation, on average, expenditures for energy conservation and pollution abatement, which are directly linked to ECER policy, accounted for approximately 75% of the total ECEP expenditures.
5 Because of the inclusion of the program will randomly omit a year dummy when running regressions with this specification. We performed regressions that remove and found similar results for our key variables.
6 Beijing, Fujian, Guangdong, Hainan, Hebei, Jiangsu, Liaoning, Shandong, Shanghai, Tianjin, and Zhejiang.
7 Chongqing, Gansu, Guangxi, Guizhou, Inner Mongolia, Ningxia, Qinghai, Shaanxi, Sichuan, Tibet, Xinjiang, and Yunnan
8 Anhui, Heilongjiang, Henan, Hubei, Hunan, Jiangxi, Jilin and Shanxi.
9 Observations in the year of 2006 are not included because of the data unavailability of our dependent variables.