Emerging economies face challenges in improving urban wastewater treatment efficiency (UWTE) due to limited public budgets. While expanding wastewater treatment infrastructure (WTI) is crucial due to industrial agglomeration and population growth, budgetary constraints necessitate efficiency improvements. UWTE, the amount of wastewater purified per unit cost, is vital for environmental quality, public health, and achieving sustainable development goals. Government regulation alone often proves insufficient, hindered by bureaucratic complexities and ineffective oversight of wastewater treatment facilities. While state-owned enterprises offer a solution, they often struggle in fiscally constrained cities. Private entities, focused on profit maximization, can improve efficiency, but may compromise public value and regulatory oversight. Public-private partnerships (PPPs), aiming for a balanced risk and benefit sharing, offer a potential solution. This study assesses the impact of PPPs on UWTE, exploring the optimal mechanisms (return, procurement, and operation) and the role of demonstration projects. The research questions are: (1) Does the adoption of PPPs enhance UWTE?; (2) What PPP mechanisms are most effective?; (3) Does participation in demonstration projects improve UWTE?; (4) What are the policy implications for emerging economies?

Existing literature uses various methods—descriptive case analysis, performance assessment tools, process management systems, the analytical hierarchy process, observational studies, and fuzzy set qualitative comparative analysis—to examine the efficiency of PPPs in public services. While some studies confirmed high wastewater treatment capacity under PPPs, the impact on city-level UWTE remained unexplored. Previous research highlighted the importance of institutionalization and technological advantages in improving water utility service efficiency. This study addresses the gap by systematically analyzing the impact of PPPs at the city level on UWTE.

This study used data from 1303 urban wastewater treatment PPP projects in 283 Chinese prefecture-level cities from 2014 to 2019. The UWTE was measured using data envelopment analysis (DEA) based on the BCC model, considering the length of the urban wastewater network and daily treatment capacity as inputs, and the total amount of wastewater treated as output. The DEA results provided the dependent variable for subsequent analysis. To examine the causal relationship between PPPs and UWTE, a DEA-Tobit regression model was employed. Three measures of PPP development were used: presence/absence of projects, number of projects, and investment amount. Control variables included population density, urbanization rate, GDP per capita, industrialization rate, openness, and green innovations. Two-stage least squares (2SLS) instrumental variable regression was used to address endogeneity concerns. Instrumental variables included waste treatment PPP development (presence/absence and number of projects) and the average number of wastewater treatment PPP projects in neighboring cities within the same province. Robustness checks were conducted using alternative instrumental variables (average investment in neighboring cities and the province itself). Heterogeneity analysis examined the impacts of PPPs across different economic development levels (East, Central, West), marketization levels (high/low), and precipitation levels (high/low).

The study found that cities implementing PPPs for WTI had significantly higher average UWTE (0.651) compared to those without (0.619). Tobit regression results consistently showed a positive and significant relationship between PPP adoption and UWTE, regardless of whether the PPP development was measured by the presence/absence, number, or investment amount of projects. Each additional PPP project, on average, increased UWTE by 0.011 units. Control variable analysis revealed positive relationships between UWTE and GDP per capita, green innovations, and negative relationships with industrialization and openness, as expected. Instrumental variable regression addressed endogeneity, confirming the causal link between PPPs and UWTE. Robustness checks, using different measures of PPP development and instrumental variables, consistently supported the findings. Further analysis of institutional mechanisms showed that feasibility gap subsidies, competitive procurement, and privatized operation significantly improved UWTE. While demonstration projects also had a positive effect, non-demonstration projects showed a stronger impact. Heterogeneity analysis revealed that the impact of PPPs on UWTE was stronger in the western region (relatively lower economic development) and regions with less precipitation, highlighting the potential for PPPs to address disparities in public service provision.

The findings support the hypothesis that PPPs positively impact UWTE. The study's rigorous methodology, including the use of DEA, Tobit regression, and instrumental variable techniques, strengthens the causal interpretation of the results. The positive impact of PPPs is likely due to the increased capital investment, efficient management, and advanced technologies brought by private sector participation. The findings are consistent with previous research on PPPs' positive effects on infrastructure efficiency. The results highlight the importance of appropriate risk-sharing mechanisms (feasibility gap subsidies), competitive procurement, privatized operation, and leveraging the incentive effect of demonstration projects to improve UWTE. The heterogeneity analysis suggests that PPPs can be particularly effective in regions with less developed economies or less precipitation, helping to address regional disparities in public services.

This study demonstrates the significant positive impact of PPPs on UWTE in Chinese cities, particularly when specific institutional mechanisms are in place. Future research could expand the scope geographically, to include other emerging economies, and investigate the mechanisms through which PPPs affect UWTE at the enterprise level, examining the spillover effects to non-PPP firms. The study emphasizes the importance of careful consideration of risk allocation, procurement methods, operational models, and the strategic use of demonstration projects when implementing PPPs in the wastewater treatment sector.

This study's limitations include the use of data up to 2019, before changes in China's PPP regulations. The study focused on city-level impacts, lacking enterprise-level data to assess the spillover effects of PPPs on non-participating firms. Further research is needed to determine the generalizability of the findings to other emerging economies.