The Impact of Digital Economy Empowerment on Green Total Factor Productivity in Forestry
Abstract
:1. Introduction
2. Research Hypothesis
2.1. Digital Economy and Green Total Factor Productivity in Forestry
2.2. Digital Economy and Green Innovation
2.3. Digital Economy, Green Technology Innovation and Green Total Factor Productivity in Forestry
2.4. Spatial Spillovers of the Digital Economy and Green Total Factor Productivity in Forestry
3. Research Design and Data Sources
3.1. Econometric Model
3.1.1. Basic Model
3.1.2. Intermediary Effect Model
3.1.3. Spatial Econometric Model
3.2. Variable Selection
3.2.1. Explained Variable
3.2.2. Core Explanatory Variables
3.2.3. Mediating Variable
3.2.4. Control Variables
3.3. Data Sources
4. Empirical Results
4.1. Basic Model Analysis of the Impact of the Digital Economy on Forestry GTFP
4.2. Modeling the Intermediary Effects of Adding Green Innovation
4.3. Robustness Test of the Basic Model
4.3.1. Instrumental Variable Method
4.3.2. Excluding Municipalities
4.4. Time Trend Analysis of the Impact of the Digital Economy on Forestry GTFP
4.5. Heterogeneity Test of the Impact of the Digital Economy on Forestry GTFP
4.5.1. By Geographical Location
4.5.2. By the Hu Huanyong Line
4.5.3. By Level of Economic Development
4.5.4. Quantile Regression
4.6. Spatial Spillover Effect of the Impact of the Digital Economy on Forestry GTFP
4.6.1. Spatial Correlation Test
4.6.2. Regression Results of the Dynamic Spatial Durbin Model
5. Discussion and Conclusions
5.1. Discussion
5.2. Conclusions
5.3. Policy Recommendations
5.4. Shortcomings and Outlook
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Indicator Type | Indicator | Definition |
---|---|---|
Forestry inputs | Labor input | Number of employees in the forestry system at the end of the year (people) |
Land input | Forest area (millionha) | |
Capital input | Completed investment in forestry-fixed assets (RMB million) | |
Energy input | Total regional energy consumption × gross regional forestry product/gross regional product (million tons of standard coal) | |
Forestry desired outputs | Economic output | Forestry industry GDP (billion CYN) |
Ecological output | Area afforested in the year (thousands of ha) | |
Forestry undesired outputs | Forestry wastewater emissions | Regional industrial COD emissions × regional forestry output/regional gross industrial product (million tons) |
Forestry waste gas emissions | Regional industrial SO2 emissions × regional forestry output/regional industrial GDP (million tons) | |
Forestry solid waste generation | Regional industrial solid waste generation × regional forestry output value/regional gross industrial product (million tons) |
Variable Type | Variable | Mean | Standard Deviation | Min | Max |
---|---|---|---|---|---|
Dependent variable | GTFP | 0.549 | 0.312 | 0.095 | 1.428 |
Core independent variable | TDE | 0.123 | 0.086 | 0.041 | 0.563 |
STDE | 0.022 | 0.043 | 0.002 | 0.317 | |
Mediating variable | GRE | 0.089 | 0.198 | 0.001 | 1.271 |
Control variables | IS | 0.096 | 0.058 | 0.015 | 0.296 |
TEC | 0.003 | 0.002 | 0.001 | 0.014 | |
EDU | 0.034 | 0.015 | 0.013 | 0.089 | |
POLL | 0.08 | 0.074 | 0.002 | 0.435 | |
IN | 10.294 | 0.257 | 9.781 | 11.004 |
Variable | (1) | (2) | (3) | (4) |
---|---|---|---|---|
FE | FE | FE | FE | |
GTFP | GTFP | GRE | GTFP | |
TDE | 1.091 *** | 1.169 *** | −0.403 *** | 1.242 *** |
(3.40) | (3.71) | (−2.82) | (3.94) | |
STDE | −1.400 ** | −1.704 *** | 1.519 *** | −1.979 *** |
(−2.35) | (−2.90) | (5.71) | (−3.35) | |
IS | 0.361 | −0.723 *** | 0.492 * | |
(1.26) | (−5.54) | (1.70) | ||
TEC | 15.046 *** | 18.855 *** | 11.635 *** | |
(4.25) | (11.75) | (3.17) | ||
EDU | −1.514 * | −0.804 * | −1.369 | |
(−1.67) | (−1.96) | (−1.52) | ||
POLL | −0.547 *** | 0.053 | −0.557 *** | |
(−5.33) | (1.14) | (−5.43) | ||
IN | 0.391 *** | 0.040 | 0.384 *** | |
(4.95) | (1.12) | (4.87) | ||
GRE | 0.181 *** | |||
(3.34) | ||||
_cons | 0.447 *** | −3.562 *** | −0.268 | −3.513 *** |
(15.63) | (−4.43) | (−0.73) | (−4.38) | |
N | 1939 | 1939 | 1939 | 1939 |
R2 | 0.761 | 0.773 | 0.885 | 0.774 |
Variable | (1) | (2) |
---|---|---|
GTFP | GTFP | |
TDE | 15.382 * | 1.114 *** |
(8.505) | (0.322) | |
STDE | −41.9148 ** | −1.426 ** |
(20.739) | (0.614) | |
Control variables | Yes | Yes |
_cons | 0.614 | −3.595 *** |
(2.6) | (0.803) | |
N | 1939 | 1911 |
R2 | 0.774 |
Variable | GTFP |
---|---|
DE | 0.812 ** |
(2.46) | |
STDE | −1.764 *** |
(−2.83) | |
TDE2014 | 0.521 *** |
(3.16) | |
TDE2015 | 0.395 ** |
(2.43) | |
TDE2016 | 0.219 |
(1.34) | |
TDE2017 | 0.300 * |
(1.82) | |
TDE2018 | 0.324 * |
(1.95) | |
TDE2019 | 0.521 *** |
(3.16) | |
cons | −3.848 *** |
(−4.77) | |
Control variables | Yes |
_cons | −3.848 *** |
(−4.77) | |
N | 1939 |
R2 | 0.774 |
Variables | (1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) |
---|---|---|---|---|---|---|---|---|
GTFP | GTFP | GTFP | GTFP | GTFP | GTFP | GTFP | GTFP | |
TDE | 1.271 ** | 0.035 | 2.480 *** | 0.886 *** | 4.644 *** | 2.725 *** | −0.821 | 2.046 *** |
(2.37) | (0.06) | (4.87) | (2.63) | (5.37) | (3.93) | (−1.10) | (3.44) | |
STDE | −1.978 ** | 0.779 | −4.262 *** | −1.150 * | −8.941 *** | −5.560 *** | 2.796 | −2.807 *** |
(−2.33) | (0.58) | (−3.56) | (−1.87) | (−5.14) | (−2.84) | (1.35) | (−2.93) | |
Control variables | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
_cons | −5.239 *** | −3.115 ** | −2.997 *** | −3.323 *** | −8.851 *** | −2.575 ** | −1.231 | −5.685 *** |
(−3.16) | (−2.38) | (−2.77) | (−3.87) | (−3.78) | (−2.47) | (−0.78) | (−3.48) | |
N | 693 | 700 | 546 | 1771 | 168 | 531 | 598 | 762 |
R2 | 0.781 | 0.801 | 0.876 | 0.811 | 0.843 | 0.862 | 0.838 | 0.774 |
Variables | (1) | (2) | (3) |
---|---|---|---|
0.25 | 0.50 | 0.75 | |
TDE | −1.156 ** | 0.674 | −0.235 * |
(0.018) | (0.252) | (0.088) | |
STDE | 1.922 ** | 0.611 | −0.939 *** |
(0.044) | (0.663) | (0.000) | |
Control variables | Yes | Yes | Yes |
Year | TDE | GTFP | ||
---|---|---|---|---|
I | p-Value | I | p-Value | |
2013 | 0.467 | 0.000 | 0.691 | 0.000 |
2014 | 0.461 | 0.000 | 0.790 | 0.000 |
2015 | 0.419 | 0.000 | 0.790 | 0.000 |
2016 | 0.395 | 0.000 | 0.728 | 0.000 |
2017 | 0.402 | 0.000 | 0.784 | 0.000 |
2018 | 0.347 | 0.000 | 0.809 | 0.000 |
2019 | 0.300 | 0.000 | 0.792 | 0.000 |
(1) | (2) | (3) | |
---|---|---|---|
Direct Effect | Indirect Effect | Total Effect | |
TDE | 0.599 *** | 2.920 * | 3.518 * |
(2.78) | (1.74) | (1.92) | |
STDE | −1.108 ** | −1.207 | −2.315 |
(−2.54) | (−0.33) | (−0.57) | |
IS | −0.741 ** | 0.324 | −0.416 |
(−2.56) | (0.30) | (−0.40) | |
TEC | 5.579 ** | 35.789 ** | 41.368 ** |
(2.49) | (2.06) | (2.20) | |
EDU | −1.056 * | −8.060 * | −9.116 * |
(−1.83) | (−1.83) | (−1.91) | |
POLL | −0.283 *** | −1.909 *** | −2.192 *** |
(−4.48) | (−4.61) | (−4.79) | |
IN | 0.373 *** | 0.259 ** | 0.632 *** |
(10.42) | (2.29) | (5.50) | |
Spatial rho | 0.850 *** | ||
(72.45) | |||
sigma2_e | 0.005 *** | ||
(29.79) | |||
N | 1939 | 1939 | 1939 |
R2 | 0.510 | 0.510 | 0.510 |
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Chen, H.; Ma, Z.; Xiao, H.; Li, J.; Chen, W. The Impact of Digital Economy Empowerment on Green Total Factor Productivity in Forestry. Forests 2023, 14, 1729. https://doi.org/10.3390/f14091729
Chen H, Ma Z, Xiao H, Li J, Chen W. The Impact of Digital Economy Empowerment on Green Total Factor Productivity in Forestry. Forests. 2023; 14(9):1729. https://doi.org/10.3390/f14091729
Chicago/Turabian StyleChen, Hanting, Zhuoya Ma, Hui Xiao, Jing Li, and Wenhui Chen. 2023. "The Impact of Digital Economy Empowerment on Green Total Factor Productivity in Forestry" Forests 14, no. 9: 1729. https://doi.org/10.3390/f14091729