Public Green Investment and Green Development in China

Linyi Zheng

Introduction

China’s economic growth strategy has changed from rapid expansion to prioritizing high-quality, environmentally sustainable development. However, this transition has highlighted the issue of significant carbon emissions, a result of previous unrefined growth strategies. According to data published by the International Energy Agency (IEA), China’s carbon dioxide emissions amounted to 10.523 billion tons in 2021, accounting for 33% of global emissions and marking the highest emission intensity among leading global economies. To address these critical levels of emissions, China introduced a “dual carbon” goal in 2020, advocating for a consensus on low-carbon transformation and development. However, this shift towards a low-carbon economy requires significant investment. Thus, the deployment of “green public investment” as an economic instrument to mitigate environmental pollution is crucial for sustainable development.

Methodology

The first part specifically investigates the influence of economic performance on the allocation of funds toward green public investment. The second part leverages national-level data to illustrate the effect of public green investment on green development. To measure green development, indicators such as energy utilization efficiency and the performance records of the nation’s most polluting enterprises are used. This approach allows for a comprehensive evaluation of China’s environmental and economic policies in relation to sustainability. By analyzing shifts in energy dynamics, insights are gained into the transition towards renewable energy sources and the enhancement of traditional energy efficiency. Moreover, assessing the performance of the six major polluting industries sheds light on industrial reactions to environmental policies and regulations. Through this dual-focused analysis, areas of progress and prevailing challenges are highlighted, offering a nuanced perspective on China’s sustainable development efforts.

Profits and The Green Public Investment across Provinces

library (here)
library(readxl)
library(ggplot2)
library(readr)
library(countrycode)
library(tidyverse)
library(sf)

library(hchinamap)
library(dplyr)
library(magrittr)
library(readr)
library(here)

dir <- tempdir()
download.file('https://czxb.github.io/br/chinadf.rda', file.path(dir, 'chinadf.rda'))
load(file.path(dir, 'chinadf.rda'))

# Read in your regional profits data
regional_profits2 <- read_csv(here("03_data_processed", "China_pfmc_province_Chinese.csv"))

# Join the map data with your regional profits data
merged_data <- chinadf %>%
  filter(region == "China") %>%
  left_join(regional_profits2, by = c("name" = "indicator"))

# Generate the map without the interactive() condition
hchinamap(name = merged_data$name, value = merged_data$value.y, region = "China",
          title = "Provincial Profits", subtitle = "Data source: EPS database")

regional_economy2 <- here("03_data_processed", "gf_province_Chinese.csv") |> 
  read_csv()

merged_data <- chinadf %>%
  filter(region == "China") %>%
  left_join(regional_economy2, by = c("name" = "indicator"))  

   hchinamap(name = merged_data$name, value = merged_data$value.y, region = "China",
  title = "Green Public Investmen Index", subtitle = "Data source: EPS database")

The first map depicts different provinces shaded according to their profit levels, with the color intensity representing the scale of profits—darker shades imply higher profits. The second map shows the Green Public Investment Index measuring the extent of investment in environmentally sustainable public projects. Based on the visuals alone, one could hypothesize that:

• Provinces with greater economic development have more resources to invest in green initiatives.

• There might be a threshold of economic development above which provinces begin to invest more significantly in green projects.

Public Green Investment and Energy Growth

energy_data <- read_csv(here("03_data_processed", "China_energy.csv")) 
environment_data <-  read_csv(here("03_data_processed", "China_environment.csv"))
performance_data <- read_csv(here("03_data_processed", "China_performance.csv")) 

library(tidyverse)
library(tidyverse)

environment_selected <- environment_data %>%
  filter(indicator == "Total Investment in Environmental Pollution Control (100 million yuan)") %>%
  mutate(dataset = "Investment")

percent_data <- energy_data %>%
  filter(grepl("Rate|%|Efficiency", indicator)) %>%
  mutate(indicator = recode(indicator, 
                            `Growth Rate of Energy Production (%)` = "Energy Production Growth Rate",
                            `Growth Rate of GDP (%)` = "GDP Growth Rate")) %>%
  mutate(dataset = "Growth Rate%")

combined_data <- bind_rows(environment_selected, percent_data)

combined_plot <- ggplot(combined_data, aes(x = year, y = value, color = indicator, group = indicator)) +
  geom_line(size = 1) +  
  facet_grid(dataset ~ ., scales = "free_y") +  
  scale_color_brewer(palette = "Set1") +
  labs(
    title = "Comparative Trends in Environmental Investment and Energy Growth Rates",
    x = "Year",
    y = "Value",
    caption = "Source: EPS Energy Database"
  ) +
  theme_minimal() +
  theme(
    plot.title = element_text(size = 10, face = "bold", hjust = 0.5),
    axis.text.x = element_text(angle = 45, hjust = 1),
    strip.text.x = element_text(face = "bold"),
    legend.position = "bottom",
    legend.title = element_blank()
  ) +
  scale_x_continuous(breaks = seq(min(combined_data$year), max(combined_data$year), by = 1))

print(combined_plot)

Despite the annual increase in both the consumption and production of energy, there is a noticeable deceleration in the growth rate, particularly around the year 2016—a period marking a significant transitional phase for China. Concurrently, a gradual increase in energy utilization efficiency reflects a strategic shift towards more sustainable energy practices, as China seeks to balance its economic growth with environmental sustainability. This subtle improvement in energy utilization underscores the effectiveness of a more sustainable energy landscape.

The Most Polluting Industries Performance

performance_selected <- performance_data %>%
  filter(pfmc_name %in% c("Return on Capital (%)", 
                           "Growth of Total Assets (%)"))

library(tidyverse)
library(RColorBrewer) 

ggplot(performance_selected, aes(x = year, y = value, group = pfmc_name, color = pfmc_name)) +
  geom_line() +
  facet_wrap(~indicator, scales = 'free_y') + 
  theme_minimal(base_size = 14) +  # Increase base text size
  scale_color_brewer(palette = "Set2") +
  labs(
    title = "The Most Polluting Industries Performance",
    x = "Year",
    y = "Profitability Ratio (%)",
    color = "indicator"
  ) +
  theme(
    legend.position = "bottom",
    legend.title.align = 0.5,
    strip.text.x = element_text(size = 6,face = "bold"),  # Increase facet label size
    axis.text.x = element_text(angle = 45, hjust = 1, size = 7),  # Adjust x-axis text size and angle
    axis.text.y = element_text(size = 7),  # Adjust y-axis text size
    plot.title = element_text(size = 12, face = "bold", hjust = 0.5),  # Bold and center title
    legend.text = element_text(size = 8)  # Adjust legend text size
  ) +
  guides(color = guide_legend(title.position = "top", title.hjust = 0.5)) 

The asset growth in China’s most polluting industries has been predominantly negative. Based on the rise in public green investment, this change may be attributed to the implementation of stricter environmental policies, which reflect a deliberate reallocation or contraction of resources from high-polluting traditional industries. The Return on Capital (RoC) has been fluctuating significantly from 2010 to 2019. Negative RoC during certain periods may have resulted from significant investments in sustainable practices before any financial gains were realized.

Conclusion

China has been shifting its growth strategy towards green development, which is evident from the systematic increase in green public investment. The aim is to reduce the environmental impact of economic activities. This analysis shows a positive correlation between economic prosperity and the capacity for green investment, with wealthier provinces investing more in sustainable practices. At the same time, a trend towards reduced assets in highly polluting industries suggests that investments are channeled into greener, less environmentally intensive sectors, which indicates a change in economic paradigm where green development and public investment are closely interlinked, propelling a transition to a low-carbon economy. Despite the financial oscillations indicated by the Return on Capital, the broader economic shift reflects a deliberate integration of environmental considerations with growth policies.