浙江农业学报 ›› 2023, Vol. 35 ›› Issue (2): 455-467.DOI: 10.3969/j.issn.1004-1524.2023.02.23
收稿日期:
2020-04-15
出版日期:
2023-02-25
发布日期:
2023-03-14
作者简介:
王萍萍(1989—),女,山东烟台人,博士,助理研究员,研究方向为农业经济和数字农业。E-mail:wppprivate@126.com
Received:
2020-04-15
Online:
2023-02-25
Published:
2023-03-14
摘要:
土地产权的明晰界定对于农业生产率增长具有重要意义,中国新一轮渐进式的土地确权改革为探究两者的关系提供了一个良好的外生自然实验。使用中国家庭金融调查(CHFS)2013年和2015年两轮追踪面板数据,利用村庄间的土地确权进度差异构造多时点双重差分(Staggered DID)模型,检验土地确权对农业生产率的影响及其作用机制。研究发现,土地确权显著提高了农户的农业生产率,在修正样本选择性偏差、处理内生性问题、替换生产率测度指标等一系列稳健性检验后,该结果依然显著成立。进一步分析发现,土地确权对农业生产率的影响在不同土地规模、不同地区和不同生产率水平的农户之间存在异质性,对于土地规模较大、东部地区,以及农业生产率较高的农户,由确权导致的生产率增长效应显著更大。机制检验表明,土地确权的生产率增长效应主要是通过促进农户间土地流转和增加农业生产性投资实现的,而通过提高信贷可获得性促进农业生产率的机制尚未发挥作用。
中图分类号:
王萍萍. 土地确权对农业生产率的影响——基于中国家庭金融调查(CHFS)的双重差分研究[J]. 浙江农业学报, 2023, 35(2): 455-467.
WANG Pingping. How does land titling affect agricultural productivity: a differences-in-differences study based on China Household Finance Survey (CHFS) data[J]. Acta Agriculturae Zhejiangensis, 2023, 35(2): 455-467.
变量符号 Variable symbol | 平均值 Mean | 标准差 Standard deviation |
---|---|---|
E | 6.930 | 1.346 |
T | 0.132 | 0.222 |
X1 | 0.528 | 0.152 |
X2 | 3.688 | 0.295 |
13.687 | 2.188 | |
X3 | 0.700 | 0.229 |
X4 | 0.713 | 0.272 |
X5 | 0.084 | 0.278 |
X6 | 0.140 | 0.347 |
表1 变量描述统计结果
Table 1 Descriptive statistics of variables
变量符号 Variable symbol | 平均值 Mean | 标准差 Standard deviation |
---|---|---|
E | 6.930 | 1.346 |
T | 0.132 | 0.222 |
X1 | 0.528 | 0.152 |
X2 | 3.688 | 0.295 |
13.687 | 2.188 | |
X3 | 0.700 | 0.229 |
X4 | 0.713 | 0.272 |
X5 | 0.084 | 0.278 |
X6 | 0.140 | 0.347 |
变量 Variable | 2013 | 2015 | ||
---|---|---|---|---|
未确权户 Household without land titling | 确权户 Household with land titling | 未确权户 Household without land titling | 确权户 Household with land titling | |
E | 6.898 | 6.844 | 6.948 | 7.063 |
X1 | 0.532 | 0.525 | 0.528 | 0.524 |
X2 | 3.670 | 3.692** | 3.697 | 3.724** |
X3 | 0.699 | 0.722** | 0.693 | 0.714** |
X4 | 0.726 | 0.725 | 0.699 | 0.703 |
X5 | 0.036 | 0.036 | 0.126 | 0.141 |
X6 | 0.226 | 0.218 | 0.061 | 0.053 |
表2 确权户与未确权户的差异比较
Table 2 Comparison of households without land titling and households with land titling
变量 Variable | 2013 | 2015 | ||
---|---|---|---|---|
未确权户 Household without land titling | 确权户 Household with land titling | 未确权户 Household without land titling | 确权户 Household with land titling | |
E | 6.898 | 6.844 | 6.948 | 7.063 |
X1 | 0.532 | 0.525 | 0.528 | 0.524 |
X2 | 3.670 | 3.692** | 3.697 | 3.724** |
X3 | 0.699 | 0.722** | 0.693 | 0.714** |
X4 | 0.726 | 0.725 | 0.699 | 0.703 |
X5 | 0.036 | 0.036 | 0.126 | 0.141 |
X6 | 0.226 | 0.218 | 0.061 | 0.053 |
指标 Index | 模型1 Model 1 | 模型2 Model 2 | 模型3 Model 3 |
---|---|---|---|
T | 0.683*** (0.249) | 0.691*** (0.249) | 0.618*** (0.236) |
R2 | 0.318 | 0.323 | 0.692 |
n | 4753 | 4753 | 2912 |
表3 基准回归结果
Table 3 Benchmark regression results
指标 Index | 模型1 Model 1 | 模型2 Model 2 | 模型3 Model 3 |
---|---|---|---|
T | 0.683*** (0.249) | 0.691*** (0.249) | 0.618*** (0.236) |
R2 | 0.318 | 0.323 | 0.692 |
n | 4753 | 4753 | 2912 |
指标 Index | PSM+DID | 模型6 Model 6 | ||
---|---|---|---|---|
模型4 Model 4 | 模型5 Model 5 | 一阶段 Stage 1 | 二阶段 Stage 2 | |
T | 0.526** (0.251) | 0.526** (0.252) | — | 0.573** (0.235) |
C1×P | — | — | -4.631*** (0.206) | — |
R2 | 0.319 | 0.322 | 0.010 | 0.010 |
一阶段F统计量 | — | — | 507.592 | — |
F statistics in stage 1 | ||||
n | 3 683 | 3 683 | 4 753 | 4 753 |
表4 基于倾向得分匹配(PSM)和工具变量的回归估计结果
Table 4 Regression results based on propensity score matching (PSM) and instrumental variables
指标 Index | PSM+DID | 模型6 Model 6 | ||
---|---|---|---|---|
模型4 Model 4 | 模型5 Model 5 | 一阶段 Stage 1 | 二阶段 Stage 2 | |
T | 0.526** (0.251) | 0.526** (0.252) | — | 0.573** (0.235) |
C1×P | — | — | -4.631*** (0.206) | — |
R2 | 0.319 | 0.322 | 0.010 | 0.010 |
一阶段F统计量 | — | — | 507.592 | — |
F statistics in stage 1 | ||||
n | 3 683 | 3 683 | 4 753 | 4 753 |
指标 Index | 模型7 Model 7 | 模型8 Model 8 | 模型9 Model 9 | 模型10 Model 10 | 模型11 Model 11 |
---|---|---|---|---|---|
T | 0.717*** (0.253) | 0.071*** (0.023) | 0.390** (0.174) | 0.390*** (0.135) | 0.679** (0.265) |
R2 | 0.329 | 0.106 | 0.340 | 0.323 | 0.328 |
n | 5 359 | 5 421 | 5 421 | 4 753 | 4 205 |
表5 稳健性检验结果
Table 5 Results of robustness test
指标 Index | 模型7 Model 7 | 模型8 Model 8 | 模型9 Model 9 | 模型10 Model 10 | 模型11 Model 11 |
---|---|---|---|---|---|
T | 0.717*** (0.253) | 0.071*** (0.023) | 0.390** (0.174) | 0.390*** (0.135) | 0.679** (0.265) |
R2 | 0.329 | 0.106 | 0.340 | 0.323 | 0.328 |
n | 5 359 | 5 421 | 5 421 | 4 753 | 4 205 |
指标 Index | 规模水平Scale | 地区Region | 生产率水平Agricultural productivity | |||||
---|---|---|---|---|---|---|---|---|
小规模 Small-scale | 大规模 Large-scale | 东部 Eastern | 中部 Central | 西部 Western | q25 | q50 | q75 | |
T | 0.717** (0.286) | 1.529*** (0.526) | 1.391*** (0.435) | 0.394 (0.319) | 0.350 (0.494) | 0.337 (0.256) | 0.383 (0.236) | 0.618** (0.310) |
R2 | 0.319 | 0.486 | 0.323 | 0.270 | 0.374 | 0.256 | 0.259 | 0.265 |
n | 4 053 | 622 | 1 359 | 2 084 | 1 309 | 4 753 | 4 753 | 4 753 |
表6 异质性分析结果
Table 6 Heterogeneity analysis results
指标 Index | 规模水平Scale | 地区Region | 生产率水平Agricultural productivity | |||||
---|---|---|---|---|---|---|---|---|
小规模 Small-scale | 大规模 Large-scale | 东部 Eastern | 中部 Central | 西部 Western | q25 | q50 | q75 | |
T | 0.717** (0.286) | 1.529*** (0.526) | 1.391*** (0.435) | 0.394 (0.319) | 0.350 (0.494) | 0.337 (0.256) | 0.383 (0.236) | 0.618** (0.310) |
R2 | 0.319 | 0.486 | 0.323 | 0.270 | 0.374 | 0.256 | 0.259 | 0.265 |
n | 4 053 | 622 | 1 359 | 2 084 | 1 309 | 4 753 | 4 753 | 4 753 |
指标 Index | 机制1 Mechanism 1 | 机制2 Mechanism 2 | 机制3 Mechanism 3 | |||
---|---|---|---|---|---|---|
R | E | I | E | Cr | E | |
T | 0.196** (0.078) | 0.347*** (0.053) | 0.166*** (0.057) | 0.381*** (0.050) | -0.002 (0.058) | 0.691*** (0.250) |
R | — | 0.643*** (0.248) | — | — | — | — |
I | — | — | — | 0.712*** (0.248) | — | — |
Cr | — | — | — | — | — | -0.008 (0.055) |
R2 | 0.245 | 0.333 | 0.311 | 0.337 | 0.323 | 0.323 |
n | 4 745 | 4 745 | 4 753 | 4 753 | 4 753 | 4 753 |
表7 影响机制检验结果
Table 7 Test results of impact mechanism
指标 Index | 机制1 Mechanism 1 | 机制2 Mechanism 2 | 机制3 Mechanism 3 | |||
---|---|---|---|---|---|---|
R | E | I | E | Cr | E | |
T | 0.196** (0.078) | 0.347*** (0.053) | 0.166*** (0.057) | 0.381*** (0.050) | -0.002 (0.058) | 0.691*** (0.250) |
R | — | 0.643*** (0.248) | — | — | — | — |
I | — | — | — | 0.712*** (0.248) | — | — |
Cr | — | — | — | — | — | -0.008 (0.055) |
R2 | 0.245 | 0.333 | 0.311 | 0.337 | 0.323 | 0.323 |
n | 4 745 | 4 745 | 4 753 | 4 753 | 4 753 | 4 753 |
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