# The impact of economic growth target management on urban green land utilization efficiency

## TL;DR

This study examines how economic growth targets affect urban green land use efficiency in China and suggests using flexible targets to improve sustainability.

## Contribution

The paper identifies the differential impacts of economic growth target types and their spatial spillover effects on urban green land utilization efficiency.

## Key findings

- Local economic growth targets and their hard constraints negatively affect urban green land use efficiency, while soft constraints improve it.
- Green technology innovation and industrial structure upgrading are key transmission channels for these effects.
- Environmental regulation intensity moderates the relationship between economic growth targets and green land use efficiency.

## Abstract

Improving urban green land utilization efficiency (UGLUE) is the key to promoting green and sustainable development in China. Clarifying the impact of economic growth target management (EGTM) on UGLUE and its mechanism of action is of great significance to improving UGLUE. Selecting 273 cities in China from 2010 to 2021 as the research sample, this paper uses panel data model, and spatial Durbin model (SDM) to empirically examine the impact, transmission mechanism and spatial spillover effect of EGTM (including economic growth target values, hard constraints and soft constraints of economic growth targets) on UGLUE. In addition, this paper uses panel threshold model to verify the threshold role of environmental regulation in the relationship between EGTM and UGLUE. The research found that: (1) Local economic growth target value and its hard constraints have a negative impact on UGLUE, while soft constraints are conducive to improving UGLUE. (2) Green technology innovation and industrial structure upgrading are the main transmission channels. (3) As the intensity of environmental regulation increases, the negative impact of economic growth target value and its hard constraints on UGLUE weakens, while the positive impact of its soft constraints on UGLUE strengthens. (4) The economic growth target value and its hard constraints of surrounding areas can reduce the UGLUE in the region, while its soft constraints can improve the UGLUE in the region. (5) Economic growth targets have the greatest negative impact on UGLUE in the central region and resource-based cities. In the future, the importance of GDP growth rate in official performance evaluations should be reduced. More flexible “soft constraints” should be used to set economic growth targets.