城镇化发展如何影响非正规就业？

doi:10.3969/j.issn.1004-9479.2022.06.2020551

摘要/Abstract

摘要：

城镇化是城镇非正规经济发展的载体，是影响非正规就业的重要因素之一。采用2006—2017年省际面板数据，并利用邻接矩阵和地理距离矩阵构建空间杜宾（SDM）模型，实证分析了城镇化发展对非正规就业的影响及作用机制。研究发现：城镇化发展会通过直接效应和空间溢出效应两种作用传导机制对非正规就业产生显著的促进作用。其中，直接效应主要通过集聚效应、空间效应、投资效应三种途径来直接促进本地区的非正规就业，同时邻近地区之间的城镇化发展存在协同效应，这使得地区城镇化发展对非正规就业有显著的正向空间溢出效应，而且相比于边界相邻地区，地理距离相近地区的正向溢出效应更强。而且，各省份的政府竞争在城镇化发展对非正规就业的空间溢出效应中具有完全中介作用，是产生正向空间溢出效应的重要因素。

关键词: 城镇化, 非正规就业, 影响机制, 空间溢出效应, 空间杜宾模型

Abstract:

Urbanization is the carrier of urban informal economy development and one of the important factors affecting informal employment. This paper adopts the inter-provincial panel data from 2006 to 2017, and uses the adjacent-matrix and geographical distance matrix to construct the Spatial Durbin Model (SDM), and empirically analyzes the impact of urbanization development on informal employment and its mechanism. It is found that urbanization can significantly promote informal employment through direct effect and spatial spillover effect. Among them, the direct effect mainly through agglomeration effect, space effect and investment effect to directly promote the informal employment in the region. At the same time, the urbanization development of synergies between neighborhood, which makes the regional urbanization development of informal employment has a significant positive spillover effects. Compared with the border region, the spillover effect of geographically close regions is stronger. Further research shows that government competition between provinces plays a strong mediating role in the spatial spillover effect of urbanization development on informal employment and is an important factor that produces such spatial spillover effect.

Key words: urbanization, informal employment, influence mechanism, space spillover effect, spatial Durbin model

马林靖, 李培速, 伍亚红. 城镇化发展如何影响非正规就业？[J]. 世界地理研究, 2022, 31(6): 1273-1284.

Linjing MA, Peisu LI, Yahong WU. How does urbanization affect informal employment?[J]. World Regional Studies, 2022, 31(6): 1273-1284.

图/表 8

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符号	样本量	均值	标准差	最小值	最大值
inf	360	0.443	0.095	0.196	0.694
urb	360	0.483	0.132	0.206	0.854
educ	360	0.145	0.097	0.030	0.574
rgdp	360	10.807	3.066	-2.500	19.200
une	360	3.487	0.652	1.210	5.100
gap	360	2.850	0.543	1.845	4.593

符号	样本量	均值	标准差	最小值	最大值
inf	360	0.443	0.095	0.196	0.694
urb	360	0.483	0.132	0.206	0.854
educ	360	0.145	0.097	0.030	0.574
rgdp	360	10.807	3.066	-2.500	19.200
une	360	3.487	0.652	1.210	5.100
gap	360	2.850	0.543	1.845	4.593

邻接矩阵（W1）			距离矩阵（W2）
检验	统计量	概率值	检验	统计量	概率值
Moran's I	0.450	0.0000	Moran's I	0.413	0.0000
LM-lag	57.074	0.0000	LM-lag	80.951	0.0000
R-LM-lag	33.861	0.0000	R-LM-lag	31.270	0.0000
LM-err	36.963	0.0000	LM-err	57.745	0.0000
R-LM-err	13.750	0.0000	R-LM-err	8.064	0.0005
Hausman	66.380	0.0000	Hausman	23.230	0.0000
LR-lag	26.850	0.0001	LR-lag	14.170	0.0146
LR-err	26.190	0.0001	LR-err	15.220	0.0095

邻接矩阵（W1）			距离矩阵（W2）
检验	统计量	概率值	检验	统计量	概率值
Moran's I	0.450	0.0000	Moran's I	0.413	0.0000
LM-lag	57.074	0.0000	LM-lag	80.951	0.0000
R-LM-lag	33.861	0.0000	R-LM-lag	31.270	0.0000
LM-err	36.963	0.0000	LM-err	57.745	0.0000
R-LM-err	13.750	0.0000	R-LM-err	8.064	0.0005
Hausman	66.380	0.0000	Hausman	23.230	0.0000
LR-lag	26.850	0.0001	LR-lag	14.170	0.0146
LR-err	26.190	0.0001	LR-err	15.220	0.0095

var	SDM(W1)			SDM(W2)
var	（1）	（2）	（3）	（4）	（5）	（6）
urb	0.3448^***(3.49)	0.2306^***(3.07)	0.0802(0.79)	0.2450^**(2.43)	0.1953^***(3.19)	0.1336(1.35)
educ	0.3531^***(3.04)	-0.2287^**(-0.26)	0.2320^**(2.01)	0.2661^**(2.16)	-0.0909(-1.12)	0.1767^*(1.44)
rgdp	0.0031^**(2.12)	0.0057^***(2.61)	0.0021(1.42)	0.0022(1.47)	0.0060^***(3.02)	0.0011(0.76)
gap	-0.0067(-0.41)	-0.0190(-1.51)	-0.0261(-1.59)	-0.0148(-0.92)	-0.0546^***(-4.50)	-0.0307^*(-1.86)
une	0.0271^***(3.20)	-0.0061(-0.94)	0.0314^***(3.77)	0.0284^***(3.33)	-0.0045(-0.77)	0.0299^***(3.48)
Wurb*	0.1330(0.95)	0.2822^**(2.57)	-0.3692^**(-2.35)	0.7023^***(3.10)	0.3234^*(1.67)	-0.0112(-0.04)
Weduc*	-0.1080(-1.38)	-0.7668^***(-4.90)	-0.6937^***(-2.75)	-0.1009(-0.57)	-0.9992^***(-5.02)	-0.3864(-1.50)
Wrgdp*	-0.0076^*** (-3.92)	-0.0094^** (-2.50)	-0.0081^*** (-3.25)	-0.0089^*** (-3.92)	-0.0144^*** (-3.02 )	-0.0101^*** (-2.66)
Wgap*	0.0383(1.48)	0.0482^**(2.55)	-.0136(-0.44)	0.1377^***(4.41)	0.1194^***(4.18)	0.0477(1.21)
Wune*	-0.0230(-1.38)	-0.0178(-1.19)	0.0024(0.13)	-0.0649^***(-3.21)	-0.0701^***(-4.11)	-0.0308(-1.19)
rho	0.3169^***(5.26)	0.1517^**(2.15)	0.0479(0.66)	0.2040^***(2.66)	0.1476^*(1.80)	-0.1827^*(-1.81)
Sigma²	0.0014^*** (13.29)	0.0050^*** (13.37)	0.0013^*** (13.41)	.0015^***(13.38)	0.0042^***(13.39)	0.0013^***(13.37)
Fe-s	Y	N	Y	Y	N	Y
Fe-t	N	Y	Y	N	Y	Y
R²	0.6219	0.3250	0.2439	0.6390	0.4553	0.3289
Log-L	655.0006	441.8924	681.7517	654.9594	469.9277	676.6068