Adoption of Fertilizer-Reduction and Efficiency-Increasing Technologies in China: The Role of Information Acquisition Ability
Abstract
:1. Introduction
2. Theoretical Analysis
3. Data and Methods
3.1. Data
3.2. Model Set
3.2.1. Regression Model
3.2.2. Mechanism Testing Model
3.3. Variable Definitions and Choices
3.4. Descriptive Statistics
4. Results
4.1. Results of the IRT Model
4.1.1. Results of the IRT Model Parameter Estimation
4.1.2. Results of IAA Measurement
4.2. Impacts of IAA on Decisions to Adopt FREITs
4.3. Robustness Testing
4.4. Mechanism Testing
5. Discussion
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Data Availability Statement
Conflicts of Interest
Appendix A
Combinations of Information Channel | IAA | Proportion of Farmers (%) | Combinations of Information Channel | IAA | Proportion of Farmers (%) |
---|---|---|---|---|---|
NP | −1.101 | 1.301 | AE+DB+AC+SH+NP | 0.215 | 0.186 |
None | −0.882 | 7.249 | GD | 0.331 | 2.416 |
AC+NP | −0.832 | 0.929 | AE+DB+AC+SH | 0.357 | 0.558 |
SH+NP | −0.830 | 5.019 | GD+SH+NP | 0.367 | 0.372 |
AC | −0.636 | 0.929 | GD+AC | 0.507 | 1.115 |
SH | −0.634 | 20.260 | GD+SH | 0.509 | 7.063 |
AC+SH+NP | −0.589 | 3.160 | GD+AC+SH+NP | 0.543 | 0.558 |
AE+NP | −0.498 | 0.743 | GD+AC+SH | 0.689 | 5.948 |
DB | −0.480 | 0.186 | AE+GD | 0.765 | 1.301 |
AC+SH | −0.412 | 5.576 | AE+GD+SH+NP | 0.803 | 1.115 |
AE | −0.327 | 2.230 | DB+GD+SH | 0.819 | 0.743 |
AE+SH+NP | −0.286 | 0.558 | DB+GD+AC+SH+NP | 0.856 | 0.186 |
DB+SH | −0.269 | 0.929 | AE+GD+AC | 0.958 | 0.929 |
DB+AC+SH+NP | −0.231 | 0.186 | AE+GD+SH | 0.959 | 9.665 |
AE+AC | −0.130 | 0.743 | AE+GD+AC+SH+NP | 0.998 | 0.558 |
AE+SH | −0.129 | 5.390 | DB+GD+AC+SH | 1.015 | 0.558 |
DB+AC+SH | −0.076 | 0.186 | AE+DB+GD+SH+NP | 1.142 | 0.558 |
AE+DB+SH+NP | 0.036 | 0.186 | AE+GD+AC+SH | 1.167 | 5.019 |
AE+AC+SH | 0.057 | 2.788 | AE+DB+GD+SH | 1.320 | 0.743 |
AE+DB+SH | 0.181 | 0.186 | AE+DB+GD+AC+SH+NP | 1.365 | 0.743 |
GD+NP | 0.189 | 0.558 | AE+DB+GD+AC+SH | 1.560 | 0.372 |
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Variable | Definition | Mean | Std. Dev. | Min. | Max. | |
---|---|---|---|---|---|---|
Dependent Variables | STFFT | Adoption of STFFT (1 = adopter, 0 = otherwise) | 0.125 | 0.330 | 0 | 1 |
OFRT | Adoption of OFRT (1 = adopter, 0 = otherwise) | 0.260 | 0.439 | 0 | 1 | |
Independent Variable | IAA | Parameters measured by the IRT model | 0.002 | 0.723 | −1.101 | 1.560 |
Mechanism Variables | Technical Training | Whether farmers participated in formal training in FREITs (1 = yes, 0 = no) | 0.571 | 0.495 | 0 | 1 |
Cognitive Level | Cognitive level for FREITs (1 = very low, 2 = low, 3 = moderate, 4 = high, 5 = very high) | 3.294 | 0.966 | 1 | 5 | |
Instrument Variable | Cooperatives | Number of cooperatives in villages | 0.217 | 0.521 | 0 | 3 |
Control Variables | Scale | Cropland area (hectares) | 5.507 | 11.897 | 0.133 | 193.43 |
Plots | Number of arable plots (blocks) | 3.191 | 4.749 | 1 | 70 | |
Cropping System | 1 = rice–crayfish coculture system, 0 = rice-only system | 0.699 | 0.459 | 0 | 1 | |
Village Cadre | Village cadre in the household (1 = yes, 0 = no) | 0.230 | 0.422 | 0 | 1 | |
Labor | Number of family agricultural laborers | 2.037 | 0.736 | 1 | 6 | |
Age | Average age of agricultural laborers (years) | 52.090 | 7.622 | 26 | 73 | |
Education | Average education years of agricultural laborers (years) | 7.268 | 2.825 | 0 | 20 | |
Non-farm Income | Non-agricultural income of farm households as a proportion of total household income | 0.220 | 0.256 | 0 | 0.974 | |
Financial Situation | Adequacy of financial resources for agricultural production (1 = adequacy, 0 = inadequacy) | 0.582 | 0.494 | 0 | 1 | |
Knowledge | Knowledge of the hazards of chemical fertilizer application (1 = no knowledge, 2 = less knowledge, 3 = moderate, 4 = more knowledge, 5 = full knowledge) | 3.420 | 1.254 | 1 | 5 | |
Jiangsu | Whether farmers were in Jiangsu Province (1 = yes, 0 = no) | 0.258 | 0.438 | 0 | 1 | |
Response Variables | Agricultural Enterprises (AE) | Whether the farmer obtains information from agricultural enterprises (1 = yes, 0 = no) | 0.346 | 0.476 | 0 | 1 |
Demonstration Bases (DB) | Whether the farmer obtains information from demonstration bases (1 = yes, 0 = no) | 0.065 | 0.247 | 0 | 1 | |
Government Departments (GD) | Whether the farmer obtains information from government departments (1 = yes, 0 = no) | 0.405 | 0.491 | 0 | 1 | |
Agricultural Cooperatives (AC) | Whether the farmer obtains information from agricultural cooperatives (1 = yes, 0 = no) | 0.312 | 0.464 | 0 | 1 | |
Surrounding Households (SH) | Whether the farmer obtains information from surrounding households (1 = yes, 0 = no) | 0.794 | 0.405 | 0 | 1 | |
Network Platforms (NP) | Whether the farmer obtains information from network platforms (1 = yes, 0 = no) | 0.169 | 0.375 | 0 | 1 |
Information Channel | Differentiation Parameter | S.E. | Rank | Difficulty Parameter | S.E. | Rank |
---|---|---|---|---|---|---|
Agricultural Enterprises (AE) | 1.081 *** | 0.283 | 2 | 0.732 *** | 0.169 | 3 |
Demonstration Bases (DB) | 0.758 ** | 0.307 | 3 | 3.838 *** | 1.335 | 1 |
Government Departments (GD) | 2.671 * | 1.447 | 1 | 0.293 *** | 0.073 | 4 |
Agricultural Cooperatives (AC) | 0.448 *** | 0.146 | 5 | 1.848 *** | 0.595 | 2 |
Surrounding Households (SH) | 0.451 ** | 0.178 | 4 | −3.112 *** | 1.157 | 5 |
Network Platforms (NP) | −0.361 ** | 0.176 | 6 | −4.522 ** | 2.115 | 6 |
Variables | Probit | IV-Probit | ||||||
---|---|---|---|---|---|---|---|---|
Model 1 STFFT | Model 2 ORFT | Model 3 STFFT | Model 4 ORFT | |||||
Coef. | S.E. | Coef. | S.E. | Coef. | S.E. | Coef. | S.E. | |
IAA | −0.098 | 0.111 | 0.097 | 0.088 | 1.110 *** | 0.235 | 1.216 *** | 0.212 |
Scale | 0.012 | 0.008 | 0.007 | 0.007 | −0.004 | 0.007 | −0.007 | 0.005 |
Plots | 0.007 | 0.018 | 0.004 | 0.015 | 0.039 *** | 0.014 | 0.038 *** | 0.011 |
Cropping System | −0.447 *** | 0.168 | 0.805 *** | 0.172 | −0.467 *** | 0.136 | 0.297 | 0.238 |
Village Cadre | 0.063 | 0.175 | −0.155 | 0.155 | −0.278 * | 0.159 | −0.410 *** | 0.135 |
Labor | 0.264 *** | 0.093 | −0.043 | 0.094 | 0.020 | 0.098 | −0.164 ** | 0.072 |
Age | 0.022 * | 0.012 | 0.003 | 0.009 | 0.012 | 0.010 | 0.000 | 0.008 |
Education | 0.163 *** | 0.040 | 0.063 ** | 0.027 | 0.056 | 0.046 | −0.003 | 0.030 |
Non-farm Income | −0.490 | 0.318 | −0.713 *** | 0.271 | −0.422 * | 0.245 | −0.567 ** | 0.234 |
Financial Situation | −0.403 ** | 0.157 | 0.150 | 0.131 | −0.141 | 0.158 | 0.196 * | 0.109 |
Knowledge | 0.066 | 0.065 | −0.058 | 0.051 | 0.084 * | 0.049 | 0.009 | 0.044 |
Jiangsu | −0.265 | 0.213 | 0.629 *** | 0.155 | −0.164 | 0.161 | 0.379 ** | 0.169 |
Constant | −3.840 *** | 0.831 | −1.730 *** | 0.648 | −1.661 | 1.027 | −0.415 | 0.727 |
Results of the first-stage regression | ||||||||
Cooperatives | 0.153 *** | 0.051 | 0.153 *** | 0.051 | ||||
Control Variables | Yes | Yes | ||||||
Log Pseudo Likelihood | −169.044 | −277.428 | −720.110 | −827.43 | ||||
Chi-square | 54.684 *** | 49.176 *** | 193.620 *** | 245.056 *** | ||||
Wald Test of Exogeneity | 7.40 *** | 7.19 *** |
IV-Probit | CMP | ||||
---|---|---|---|---|---|
Model 5 | Model 6 | Model 7 | Model 8 | ||
FREIT | STFFT | ORFT | STFFT | ORFT | |
IAA | 1.197 *** (0.208) | 1.106 *** (0.241) | 1.217 *** (0.211) | ||
Number of Channels | 0.615 *** (0.168) | 0.701 *** (0.152) | |||
Control Variables | Yes | Yes | Yes | Yes | Yes |
Cooperatives | 0.153 *** (0.051) | 0.331 *** (0.089) | 0.331 *** (0.089) | 0.153 *** (0.051) | |
Control Variables | Yes | Yes | Yes | Yes | |
Log Pseudo Likelihood | −870.068 | −971.727 | −1076.555 | −993.822 | |
Chi-square | 222.282 *** | 132.224 *** | 167.872 *** | 189.960 *** | |
Wald Test of Exogeneity | 7.68 *** | 6.40 ** | 6.34 ** | ||
athrho2_1 | −1.094 *** (0.395) | −0.869 ** (0.343) | −0.787 ** (0.312) | ||
atanhrho_12 | 0.797 ** (0.336) | ||||
atanhrho_13 | −1.097 *** (0.413) | ||||
atanhrho_23 | −1.085 *** (0.404) |
Probit | CMP | Oprobit | CMP | |
---|---|---|---|---|
Model 9 Technical Training | Model 10 FREIT | Model 11 Cognitive Level | Model 12 FREIT | |
IAA | 1.244 *** (0.109) | 1.070 *** (0.245) | 0.399 *** (0.068) | 1.154 *** (0.229) |
Technical Training | 0.360 ** (0.139) | |||
Cognitive Level | 0.114 * (0.061) | |||
Control Variables | Yes | Yes | Yes | Yes |
Cooperatives | 0.153 *** (0.051) | 0.153 *** (0.051) | ||
Control Variables | Yes | Yes | ||
Log Pseudo Likelihood | −249.470 | −861.833 | −582.329 | −867.229 |
Chi-square | 170.95 *** | 619.82 *** | 206.01 | 559.68 *** |
atanhrho_12 | −1.103 *** (0.391) | −1.064 *** (0.399) |
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Yang, C.; Huang, W.; Xiao, Y.; Qi, Z.; Li, Y.; Zhang, K. Adoption of Fertilizer-Reduction and Efficiency-Increasing Technologies in China: The Role of Information Acquisition Ability. Agriculture 2024, 14, 1339. https://doi.org/10.3390/agriculture14081339
Yang C, Huang W, Xiao Y, Qi Z, Li Y, Zhang K. Adoption of Fertilizer-Reduction and Efficiency-Increasing Technologies in China: The Role of Information Acquisition Ability. Agriculture. 2024; 14(8):1339. https://doi.org/10.3390/agriculture14081339
Chicago/Turabian StyleYang, Caiyan, Weihong Huang, Yu Xiao, Zhenhong Qi, Yan Li, and Kun Zhang. 2024. "Adoption of Fertilizer-Reduction and Efficiency-Increasing Technologies in China: The Role of Information Acquisition Ability" Agriculture 14, no. 8: 1339. https://doi.org/10.3390/agriculture14081339