Panel Paper: Organizational Cheating in Environmental Policy Implementation: A High-Powered Incentive System and Anticorruption Efforts in China

Saturday, November 4, 2017
Columbian (Hyatt Regency Chicago)

*Names in bold indicate Presenter

Jiaqi Liang, University of Illinois, Chicago, Laura Langbein, American University and Michaela Buenemann, New Mexico State University

High-powered monetary and promotion incentives are often regarded as key to successful public sector performance. Despite evidence showing the positive effects of outcome-based performance management on government’s achievement, opportunistic behavior of policy implementers and organizational cheating are also well documented. Organizational cheating often involves the misreporting of performance related data, or actions that result in favorable reports for the manager but unfavorable outcomes for the beneficiary.

Research has yet to evaluate the possible relation between high-powered performance incentives and corruption. Specifically, generous rewards for reports of desired outcomes provide a motivation for opportunistic behavior by public officials regarding both the production of outputs likely to produce desired outcomes and their measurement. In the environmental domain, the construction of pollution mitigation facilities is intended to reduce emissions of pollutants. However, infrastructure projects are potential sources of economic rents for public bureaucrats in autocracies, where they have monopolistic control over licenses, permits, and some budgets. Empirical evidence has shown that even in a highly-centralized political system such as that in China, high-powered performance-based incentives for public officials cannot consistently control outcomes that are contingent on cooperation at the subnational level. While high-powered performance incentives in environmental governance can increase the demand for investment in pollution-abatement facilities, it may also raise the central government’s levels of tolerance for subnational political corruption. One possible result of corruption is facilities’ inferior quality and their failure in pollution abatement.

This study examines if performance management and anticorruption efforts in China account for the misreport of pollution emissions, and weaken the link between pollution abatement facility construction and emissions. We use a panel design with data from 2005-2010 on China’s 30 provinces (excluding Tibet). The dependent variables are satellite and official reports of emissions of sulfur dioxide (SO2). We measure policy actions to build infrastructure intended to reduce the growth of SO2 emissions in year (t) in three ways: (1) the number of desulfurization facilities constructed in year (t-1); (2) the amount of industrial SO2 removed per desulfurization facility, representing their capacity; and (3) annual expenditures for operating waste air treatment facilities, representing willingness to pay for infrastructure. The first focal policy variable is the implementation of the high-powered performance-based incentive system, measured with a dichotomous variable indicating adoption of the Eleventh Five-Year Plan. The second is the government’s anticorruption efforts, measured by the number of annually registered cases for corruption investigation. We use interaction terms to assess whether the effect of construction and effectiveness of infrastructure depends on the dynamics between performance management and anticorruption efforts. We control for likely confounding variables, including provincial bureaucrats’ career motivation (i.e., age of provincial governors, the provinces’ chance of representation in the Politburo, and actual provincial Politburo presence); share of governmental spending on education and health, and on social security and welfare; and disposable income per capita, tax revenues, coal consumption, pollution-intensive industry fixed assets, population, and geographical area. We use fixed and random effects estimators, and lagged dependent variable estimators, to check the robustness of our results.