Learning from Neighbors: The Spatial Spillover Effect of Crisis Learning on Local Government
Abstract
:1. Introduction
2. Literature Review
3. Theoretical Background and Research Hypothesis
3.1. Theoretical Background
3.2. Research Hypothesis
3.2.1. Major Accidents and the Crisis Learning Effects of Local Governments
3.2.2. The Moderating Effect of Political Pressure
4. Research Design
4.1. Sample Selection and Data Sources
4.2. Variable Definitions
4.3. Identification Strategies
5. Results
5.1. Descriptive Statistics
5.2. Major Accidents and Crisis Learning Effect of Local Government
5.3. Robustness Check
5.4. Moderating Effect of Political Pressure
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Variables | Name | Specific Codes | Data Sources | |
---|---|---|---|---|
Dependent Variables | Crisis Learning Effect | Yrate | The death rate of 100 million yuan of GDP of safety Accidents | China Work Safety Yearbook, Provincial Emergency Management Departments, and the Statistical Bulletin of National Economic and Social Development |
LnYdeath | Log (the number of safety accident death) | |||
Independent Variables | Frequency of Major Accidents | LnMajornum | Log (the number of major accidents) If a major accident occurred before June, it is summarized in the number of major accidents in the current year; after June, it is summarized in the following year. | CSMAR Database |
The Number of Fatalities in Major Accidents | LnMajordea | Log (the number of fatalities in major accidents) | ||
Moderating Variables | Political Pressure | Lnpure | Log (the number of policy documents in the field of production safety) | North University Fabulous |
Control Variables | Level of Economic Development | Lnpgdp | Log (per capita GDP) | China Statistical Yearbook |
Financial Revenue | Lninc | Log (local fiscal revenue) | ||
Financial Expenditure | Lnexp | Log (local financial expenditure) | ||
Industrial Structure | Lnindu | Log (percentage of secondary industry) | ||
Fixed Investment | LnAsset | Log (total social fixed asset investment in the mining sector) | ||
Per Capita Wage | Lnwage | Log (the average wage of urban unit workers on duty) | ||
Technical Equipment Rate | Lnequ | Log (the technical equipment rate of enterprises in the construction industry) | ||
Public Safety Expenditure | Lnsafety | Log (local financial public safety expenditure) |
Year | Geographical Adjacency Matrix (W1) | Geographical Distance Matrix (W2) | Economic Geography Matrix (W3) |
---|---|---|---|
2006 | 0.479 *** | 0.319 *** | 0.260 *** |
2007 | 0.482 *** | 0.314 *** | 0.281 *** |
2008 | 0.488 *** | 0.301 *** | 0.249 *** |
2009 | 0.511 *** | 0.334 *** | 0.210 *** |
2010 | 0.526 *** | 0.344 *** | 0.198 *** |
2011 | 0.545 *** | 0.362 *** | 0.177 * |
2012 | 0.536 *** | 0.354 *** | 0.158 * |
2013 | 0.215 ** | 0.301 *** | 0.073 * |
2014 | 0.064 | 0.107 * | 0.191 *** |
2015 | 0.003 | 0.03 | 0.116 * |
2016 | 0.182 * | 0.177 ** | 0.148 ** |
2017 | 0.125 * | 0.190 ** | 0.098 * |
Variable | Obs | Mean | SD | Min | Max |
---|---|---|---|---|---|
Yrate | 360 | 0.2263 | 0.2152 | 0.0000 | 1.2274 |
LnYdeath | 360 | 7.5214 | 0.7665 | 3.1359 | 9.1963 |
LnMajornum | 360 | −0.7714 | 2.5395 | −4.6052 | 2.6398 |
LnMajordea | 360 | 1.1512 | 3.8075 | −4.6052 | 6.3457 |
Lnpure | 360 | 3.7450 | 1.1409 | −4.6052 | 5.8750 |
Lnpgdp | 360 | 10.4487 | 0.5912 | 8.7491 | 11.7675 |
Lninc | 360 | 7.0887 | 1.0099 | 3.7436 | 9.3344 |
Lnexp | 360 | 7.8237 | 0.7933 | 5.1622 | 9.6183 |
Lnindu | 360 | 3.8176 | 0.2124 | 2.9450 | 4.0828 |
LnAsset | 360 | 5.0357 | 1.6489 | −2.4079 | 7.4396 |
lnwage | 360 | 10.6209 | 0.4552 | 9.6544 | 11.8130 |
Lnequ | 360 | 9.3322 | 0.4208 | 6.5903 | 10.4600 |
Lnsafety | 360 | 5.0540 | 0.7403 | 2.6899 | 7.1017 |
Variables | Non-Spatial OLS | Non-Spatial Plain Panel (FE) | Space Durbin Model | ||
---|---|---|---|---|---|
Model 1 | Model 2 | Adjacency Matrix | Geographical Matrix | Economic Matrix | |
Model 3 | Model 4 | Model 5 | |||
LnMajornum | −0.0014 (0.0026) | −0.0013 (0.0020) | 0.0101 * (0.0049) | 0.0136 * (0.0053) | 0.0093 (0.0056) |
SLnMajornum | 0.0014 *** (0.0003) | 0.0011 *** (0.0003) | 0.0026 * (0.0012) | 0.0035 ** (0.0013) | 0.0018 (0.0014) |
Lnpgdp | −0.1550 *** (0.0196) | −0.395 *** (0.0604) | −0.356 *** (0.0482) | −0.350 *** (0.0559) | −0.381 *** (0.0543) |
Lninc | 0.0158 (0.0231) | 0.192 ** (0.0699) | 0.144 ** (0.0535) | 0.216 *** (0.0587) | 0.194 ** (0.064) |
Lnexp | −0.116 *** (0.0286) | −0.450 *** (0.0884) | −0.186 ** (0.0671) | −0.333 *** (0.0784) | −0.272 *** (0.0788) |
Lnindu | −0.0148 (0.0274) | 0.0103 (0.0827) | −0.0367 (0.0609) | 0.0394 (0.0746) | 0.1 (0.0745) |
LnAsset | −0.0108 * (0.0043) | −0.0004 (0.0081) | 0.0123 * (0.0062) | 0.00626 (0.0068) | 0.00891 (0.0072) |
lnwage | −0.104 *** (0.025) | −0.173 * (0.0816) | 0.0308 (0.0495) | 0.0154 (0.0697) | 0.0519 (0.078) |
Lnequ | 0.0498 *** (0.0142) | 0.0488 *** (0.0156) | 0.0168 0.0119) | 0.0227 0.0134) | 0.0423 ** 0.0138) |
Lnsafety | 0.0194 * (0.0084) | 0.0292 (0.0187) | 0.0467 *** (0.0136) | 0.0562 *** (0.0152) | 0.0580 *** (0.0147) |
w.Yrate | 0.619 *** (0.0495) | 0.445 *** (0.0765) | 0.254 ** (0.089) | ||
w.LnMajornum | −0.0167 * (0.0084) | −0.0275 * (0.0137) | 0.0074 * (0.0157) | ||
Regional Effect | None | Control | Control | Control | Control |
Time Effect | None | Control | Control | Control | Control |
Log-L | 511.5879 | 488.1484 | 480.8593 |
Variables | Substitution of Explanatory Variables | Substitution of Explanatory Variables | Replacement Estimation Model | |
---|---|---|---|---|
Model 6 | Model 7 | Model 8 | Model 9 | |
LnMajornum | 0.0182 *** (0.0051) | 0.0273 ** (0.0128) | 0.0273 (0.0228) | |
SLnMajornum | 0.0046 *** (0.0013) | 0.0074 *** (0.0017) | 0.0073 ** (0.0034) | |
LnMajordea | −0.0004 (0.0011) | |||
SLnMajordea | 0.0011 *** (0.0002) | |||
w.Yrate | 0.265 ** (0.0871) | 0.231 ** (0.0891) | ||
w.LnMajornum | 0.0321 (0.0149) | |||
w.LnMajordea | −0.0056 (0.0028) | |||
Control variables | Control | Control | Control | Control |
Regional effects | Control | Control | Control | Control |
Time effect | Control | Control | Control | Control |
Log-L | 524.6133 | 514.8987 | −29.4363 | −49.6805 |
Variables | Non-Spatial OLS | Non-Spatial General Panel Model (FE) | Space Durbin Model | ||
---|---|---|---|---|---|
Model 10 | Model 11 | Adjacency Matrix | Geographical Matrix | Economic Matrix | |
Model 12 | Model 13 | Model 14 | |||
LnMajornum | 0.126 *** (0.0215) | 0.0928 *** (0.0174) | 0.0502 *** (0.0144) | 0.0740 *** (0.0141) | 0.0835 *** (0.0147) |
SLnMajornum | 0.0290 *** (0.0057) | 0.0204 *** (0.0046) | 0.0113 ** (0.004) | 0.0164 *** (0.0037) | 0.0185 *** (0.0038) |
LnMajornum × Lnpure | 0.0074 (0.0077) | −0.0217 *** (0.0046) | −0.0109 ** (0.0038) | −0.0155 *** (0.0037) | −0.0204 *** (0.0038) |
SLnMajornum × Lnpure | −0.0075 *** (0.0015) | −0.0048 *** (0.0012) | −0.0024 * (0.0011) | −0.0034 *** (0.001) | −0.0046 *** (0.001) |
Lnpure | 0.0074 (0.0077) | 0.0116 (0.0067) | 0.0071 (0.0067) | 0.0049 (0.0056) | 0.0141 * (0.0056) |
w. Yrate | 0.369 *** (0.0655) | 0.244 ** (0.089) | −0.0121 (0.1024) | ||
w.LnMajornum | −0.0272 (0.0341) | −0.102 (0.053) | −0.0159 (0.0472) | ||
w.SLnMajornum | −0.0155 (0.0091) | −0.0317 * (0.0131) | −0.00733 (0.0125) | ||
w.Lnpure | −0.0453 *** (0.0134) | −0.0291 (0.016) | −0.0466 ** (0.0172) | ||
Control variables | Control | Control | Control | Control | Control |
Regional effects | None | Control | Control | Control | Control |
Time effect | None | Control | Control | Control | Control |
Log-L | 557.4930 | 527.9089 | 526.3293 |
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Tang, Y.; Wang, Y. Learning from Neighbors: The Spatial Spillover Effect of Crisis Learning on Local Government. Sustainability 2022, 14, 7731. https://doi.org/10.3390/su14137731
Tang Y, Wang Y. Learning from Neighbors: The Spatial Spillover Effect of Crisis Learning on Local Government. Sustainability. 2022; 14(13):7731. https://doi.org/10.3390/su14137731
Chicago/Turabian StyleTang, Yun, and Ying Wang. 2022. "Learning from Neighbors: The Spatial Spillover Effect of Crisis Learning on Local Government" Sustainability 14, no. 13: 7731. https://doi.org/10.3390/su14137731