价格支持政策改革背景下中国玉米市场空间关联

doi:10.11821/dlxb202110017

Abstract

Abstract:

Market spatial correlation is one of the key indicators that reflect the operation efficiency of corn markets. The implementation and reform of corn price support policy in China plays an important role in changing the spatial correlation of corn markets. Employing market price data at province level, this study first analyzed the change of corn market spatial correlations under the price support policy reform. Then, social network analysis was applied to describe the network characteristics of corn market spatial correlations, and quadratic assignment procedure (QAP) analysis was used to investigate key factors that affected the spatial correlation. The results indicated that, (1) overall, the spatial correlation of China's corn markets was relatively high, and there was an upward trend in recent years. The implementation of temporary corn storage policy exerted insignificant effect on this upward trend, but it led to a decrease in the spatial correlation between markets in policy-affected provinces and those in non-policy affected provinces. (2) The spatial correlation of corn markets presented a multi-threaded and complex network structure, which was closely related and stable as a whole. Provinces with large corn consumption in the central and eastern regions were at the center of the spatial correlation network and played as the central actor in the network. However, provinces in the western region and provinces implementing corn support policy had little effect on the spatial correlation network of corn markets, indicating their marginal and disadvantaged role in the network. (3) Geographical proximity, market distance, market power, information transmission effect and the implementation of temporary storage policy were the key factors that affected the spatial correlation of corn markets. Furthermore, the role of market power and information transmission effect in determining the spatial correlation has become increasingly important.

Key words: price support policy, spatial correlation, social network analysis method (SNA), quadratic assignment procedure (QAP), corn, China

DING Cunzhen. Spatial correlation of corn markets under the background of price support policy reform in China[J].Acta Geographica Sinica, 2021, 76(10): 2585-2604.

Figures/Tables 13

Fig. 1

Tab. 1

Characteristics of spatial correlation network for corn markets

指标		公式	含义
整体网络	网络密度	$D = L N × N - 1$ （8）	反映玉米市场空间关联网络的紧密程度,网络密度越大,省际玉米市场之间的联系就越紧密。
	网络关联度	$C = 1 - V N N - 1 2$ （9）	反映玉米市场空间关联网络的稳健性和脆弱性,关联度越高,网络越稳定。
	网络等级度	$H = 1 - K max K$ （10）	反映玉米市场空间关联网络的等级结构,等级越高,越多省份在玉米市场关联网络中处于从属和边缘地位。
	网络效率	$E = 1 - M max M$ （11）	反映玉米市场空间关联网络的效率,效率越低,玉米市场空间关联网络越稳定。
个体网络	度数中心度	$De = n N - 1$ （12）	反映一个地区在玉米市场空间关联网络中的影响力,中心度越大,市场影响力越大。
	中间中心度	$C b i = 2 ∑ j N ∑ k N b jk i N 2 - 3 N + 2$ （13）	反映一个地区在玉米空间关联网络中的“中介”或“桥梁”作用。
	接近中心度	$C e i = ∑ j N d ij N - 1$ （14）	反映一个地区在玉米空间关联网络中的“中介”或“桥梁”作用。

Tab. 1

Tab. 2

Correlation matrix of China's corn market from 2001 to 2018

	北京		天津		河北		山西		内蒙古		辽宁		吉林	黑龙江		上海		江苏		浙江		安徽		福建		江西		山东		河南
北京	9.537		3.744		4.331		3.260		1.564		1.960		2.086	1.782		4.316		4.273		3.945		3.672		3.616		3.229		5.314		4.209
天津	3.041		9.254		4.986		3.510		2.045		2.329		1.755	2.031		4.735		4.126		4.418		3.392		4.032		3.357		5.294		4.545
河北	2.934		3.996		6.969		3.704		1.887		2.452		1.776	2.061		4.810		4.307		4.974		3.855		4.840		4.121		6.339		4.878
山西	2.431		3.777		4.245		7.780		1.810		1.688		1.257	1.488		4.892		4.455		4.488		4.324		4.190		3.862		5.650		5.370
内蒙古	2.324		3.356		3.837		4.061		9.209		3.659		2.731	3.473		3.866		3.223		3.436		3.043		3.741		3.065		3.348		3.230
辽宁	2.045		3.508		4.302		2.863		3.518		10.292		4.605	4.799		3.528		2.717		4.113		2.901		4.794		2.937		3.299		3.296
吉林	2.289		3.117		3.374		2.695		3.612		6.499		12.527	7.450		3.307		2.996		3.516		3.096		3.076		2.508		2.888		2.656
黑龙江	2.637		3.406		4.125		2.344		3.179		6.042		5.416	11.551		3.604		3.264		4.402		3.080		4.471		2.706		3.118		2.504
上海	2.508		3.140		4.514		3.814		2.063		1.683		1.287	1.947		7.719		5.453		4.861		3.527		5.838		4.367		5.936		4.422
江苏	3.229		3.043		3.865		3.958		1.630		1.440		1.187	1.503		5.746		8.638		5.751		4.721		4.493		3.942		7.253		5.549
浙江	2.626		2.971		4.144		3.096		2.121		2.360		1.255	2.123		5.393		5.111		7.884		4.097		5.749		4.650		6.279		4.114
安徽	2.990		3.817		4.127		4.503		1.842		2.076		1.873	1.823		3.931		4.988		4.533		8.433		3.863		3.702		5.278		5.385
福建	2.814		2.997		4.628		2.981		2.036		2.481		1.326	2.341		5.944		5.118		5.500		3.456		8.259		4.286		5.886		4.149
江西	2.557		2.729		3.806		3.777		1.525		1.643		1.214	1.798		4.438		4.572		5.777		4.188		5.109		8.227		5.210		4.113
山东	3.232		3.626		5.190		3.723		1.629		1.528		1.095	1.457		5.333		6.090		5.734		4.139		4.565		4.104		9.063		5.672
河南	3.021		3.399		4.821		4.465		1.555		1.516		1.524	1.379		5.072		5.430		5.179		4.847		4.083		3.743		7.190		7.909
湖北	2.545		2.660		3.924		4.067		1.626		1.688		1.254	1.636		4.780		4.564		5.283		4.450		4.339		4.348		6.075		4.849
湖南	2.580		2.373		4.047		3.701		1.950		1.581		1.194	1.886		4.884		4.847		5.371		4.407		5.446		5.226		5.408		3.969
广东	2.732		2.482		4.118		3.453		1.637		2.216		1.135	1.585		4.954		4.076		5.761		3.872		6.269		5.430		4.943		3.578
广西	2.590		2.222		3.894		3.141		1.762		1.980		1.251	1.368		4.421		3.748		4.612		3.567		5.027		4.642		4.888		3.759
海南	2.645		2.613		3.570		3.093		2.427		2.737		2.043	2.177		4.022		3.953		4.762		3.773		5.397		4.804		4.117		3.473
重庆	2.855		2.785		3.378		3.711		1.859		2.127		1.428	1.515		3.513		3.298		3.468		3.876		3.497		3.668		4.079		3.322
四川	3.073		2.997		4.041		3.077		2.405		2.423		1.778	1.821		3.388		2.987		3.154		2.975		3.879		3.990		3.797		3.775
贵州	1.827		1.910		2.680		3.630		1.928		2.153		1.806	1.936		3.759		2.845		3.012		3.776		3.303		2.798		3.833		3.093
云南	2.277		2.304		2.420		2.446		1.903		2.339		2.205	2.243		2.892		2.640		2.737		3.213		3.326		3.425		2.527		2.777
陕西	2.416		3.139		3.960		4.197		1.687		1.666		1.378	1.485		4.016		4.069		4.168		3.077		3.548		4.027		5.363		4.890
甘肃	2.235		2.762		3.739		3.580		2.237		2.043		1.563	2.060		3.572		2.918		3.897		3.070		3.417		4.135		4.402		3.947
青海	2.961		3.119		3.244		3.240		2.570		2.559		2.375	2.270		3.444		3.470		4.011		2.962		3.546		3.509		3.615		3.007
宁夏	2.670		2.761		3.573		3.489		2.431		2.737		1.768	2.440		3.606		3.538		4.065		2.661		3.810		3.143		4.292		3.813
新疆	2.691		3.119		4.257		2.762		2.787		2.105		2.645	2.497		3.644		3.236		2.562		2.975		3.103		2.708		3.644		3.108
To	76.777		87.874		115.138		100.346		61.229		69.710		54.208	64.373		123.807		116.312		127.490		104.992		124.368		110.432		139.264		115.451
Total	86.313		97.128		122.108		108.126		70.439		80.003		66.736	75.924		131.526		124.950		135.374		113.425		132.627		118.659		148.327		123.360
Net	-13.687		-2.872		22.108		8.126		-29.561		-19.997		-33.264	-24.076		31.526		24.950		35.374		13.425		32.627		18.659		48.327		23.360
		湖北		湖南		广东		广西		海南		重庆			四川		贵州		云南	陕西	甘肃		青海		宁夏		新疆		From
北京		3.770		3.322		3.937		3.100		2.543		2.791			3.073		1.667		2.347	3.247	1.974		1.830		3.129		2.431		90.463
天津		4.254		3.184		3.431		2.413		2.007		3.109			2.337		2.168		2.083	3.995	2.197		1.914		2.263		1.794		90.746
河北		4.107		3.829		4.039		2.784		2.655		2.265			2.212		1.728		1.619	3.283	1.915		1.413		2.052		2.194		93.031
山西		4.639		3.284		3.518		2.612		3.047		2.340			1.839		2.062		2.270	4.106	2.360		1.637		2.513		2.066		92.220
内蒙古		3.332		2.887		3.564		2.656		2.819		2.576			3.001		1.760		2.383	3.291	3.247		2.762		3.446		2.674		90.791
辽宁		3.048		2.271		3.623		3.198		3.183		2.111			2.518		1.764		2.714	2.431	2.049		2.512		2.993		2.069		89.708
吉林		2.216		2.338		2.414		2.310		2.322		1.828			2.319		3.347		2.972	1.859	2.208		3.188		2.441		2.630		87.473
黑龙江		2.690		2.727		3.635		2.335		2.810		1.500			2.509		3.044		2.030	1.980	2.048		2.179		2.948		1.718		88.449
上海		4.850		4.105		4.812		2.948		2.892		1.913			2.289		1.637		1.610	2.814	1.592		1.546		2.038		1.875		92.281
江苏		4.587		3.727		3.873		2.763		2.185		1.934			1.996		1.387		1.854	3.164	1.410		1.459		1.834		1.877		91.362
浙江		4.046		4.620		4.980		3.366		2.905		1.993			2.079		1.225		1.717	2.580	1.462		1.528		2.006		1.521		92.116
安徽		4.176		3.114		4.118		3.083		2.306		2.199			1.950		1.989		2.568	3.314	1.678		1.802		2.056		2.483		91.567
福建		3.800		4.330		5.487		3.398		3.294		1.550			2.058		1.205		1.563	2.562	1.411		1.408		2.375		1.356		91.741
江西		4.211		4.907		5.067		3.743		4.057		2.245			2.473		1.451		1.802	2.657	1.926		1.328		1.788		1.661		91.773
山东		4.722		3.964		3.704		2.919		2.189		2.108			1.931		1.398		1.589	2.983	1.474		1.245		1.914		1.679		90.937
河南		4.493		3.622		3.342		2.627		2.540		1.912			2.516		1.422		1.562	3.675	1.569		1.502		2.103		1.983		92.091
湖北		6.858		3.846		4.036		3.646		2.903		2.314			2.740		1.827		2.160	3.516	1.961		1.886		2.451		1.769		93.142
湖南		4.074		7.049		5.148		4.174		3.291		2.305			2.534		1.492		1.591	2.477	1.904		1.543		1.998		1.552		92.951
广东		4.122		4.598		8.398		3.531		3.674		2.103			2.521		1.359		1.777	3.198	1.673		1.291		2.081		1.435		91.602
广西		4.255		5.328		4.751		9.489		3.543		2.295			2.619		2.163		2.035	2.441	2.325		1.456		2.223		2.204		90.511
海南		3.474		3.857		5.159		3.712		8.815		1.919			2.426		1.777		2.735	2.933	1.661		1.859		2.126		1.942		91.185
重庆		4.179		3.676		4.175		4.458		2.741		8.849			3.874		3.067		3.982	3.576	2.416		2.121		2.509		1.995		91.151
四川		4.283		3.203		4.569		3.803		3.257		4.164			9.389		2.069		2.736	3.181	2.547		2.488		2.119		2.633		90.611
贵州		4.704		4.179		3.310		4.556		2.039		3.020			2.758		12.227		5.266	3.128	3.732		2.098		2.612		2.085		87.773
云南		3.137		2.862		4.109		4.197		2.947		3.374			2.741		5.623		15.304	3.063	3.494		1.984		3.103		2.387		84.696
陕西		4.877		2.881		3.930		2.464		3.159		2.782			2.295		2.270		3.091	10.189	2.492		1.509		2.852		2.123		89.811
甘肃		4.565		2.964		3.547		3.656		2.977		3.106			3.013		2.906		3.218	3.640	8.762		1.779		4.189		2.102		91.238
青海		3.322		3.247		3.377		2.867		2.723		2.723			3.407		2.730		2.299	2.390	3.301		13.111		2.506		2.092		86.889
宁夏		3.886		3.160		3.407		3.156		2.970		2.576			2.634		2.651		3.329	3.813	3.570		2.038		9.639		2.374		90.361
新疆		3.849		2.874		2.958		2.476		2.694		2.399			2.763		3.183		3.201	3.980	3.007		2.291		2.333		14.150		85.850
To		115.666		102.903		116.020		92.948		82.672		69.452			73.424		62.374		70.104	89.277	64.601		53.596		71.004		58.705		2714.519
Total		122.524		109.953		124.419		102.437		91.487		78.301			82.814		74.600		85.407	99.466	73.363		66.708		80.643		72.855		TCI
Net		22.524		9.953		24.419		2.437		-8.513		-21.699			--17.186		-25.400		-14.593	-0.534	-26.637		-33.292		-19.357		-27.145		90.484%

Tab. 2

Fig. 2

Fig. 3

Tab. 3

Fig. 4

Tab. 4

Tab. 5

Tab. 6

Fig. 5

Tab. 7

Tab. 8

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序列		临储前	临储期	补贴期
To	内蒙古	3.6499	1.5745	1.2454
	辽宁	2.9899	1.9732	2.4172
	吉林	2.0623	1.8667	1.2086
	黑龙江	2.4139	2.1409	1.7972
From	内蒙古	2.8356	3.0609	3.1822
	辽宁	2.9434	2.9787	3.0879
	吉林	3.0207	2.8483	2.9736
	黑龙江	2.9293	2.9761	2.8914
Net	内蒙古	0.8143	-1.4864	-1.9368
	辽宁	0.0465	-1.0056	-0.6707
	吉林	-0.9584	-0.9816	-1.7650
	黑龙江	-0.5154	-0.8353	-1.0943

经济板块	接受关系				板块成员数	期望内部比例	实际内部比例	接受外板块数	板块属性
经济板块	板块一	板块二	板块三	板块四	板块成员数	期望内部比例	实际内部比例	接受外板块数	板块属性
板块一	17	4	2	0	9	0.276	0.739	102	净受益板块
板块二	0	11	0	0	4	0.103	1	36	主受益板块
板块三	66	24	102	53	11	0.345	0.416	47	净溢出板块
板块四	36	8	45	30	6	0.172	0.252	53	经纪人板块

	板块一	板块二	板块三	板块四	板块一	板块二	板块三	板块四
板块一	0.236	0.111	0.020	0.000	0	0	0	0
板块二	0.000	0.917	0.000	0.000	0	1	0	0
板块三	0.667	0.545	0.927	0.803	1	1	1	1
板块四	0.667	0.333	0.682	1.000	1	0	1	1

变量	相关系数
变量	临储前	临储期	补贴期
临储政策		-0.178^*
补贴政策			-0.194^*
市场邻接	0.258^***	0.348^***	0.341^***
市场距离	0.272^***	-0.440^***	-0.443^***
产区势力	-0.022	0.023	0.001
销区势力	0.116^**	0.149^**	0.174^**
信息效应	0.148^**	0.119^*	0.135^***
市场化程度	-0.098^*	-0.103^*	-0.137^**

阶段	变量	非标准化系数	标准化系数	显著性水平	概率1	概率2
临储前	截距	3.293	0.000	-	-	-
	市场邻接	0.548	0.166	0.000	0.000	1.000
	市场距离	0.000	-0.184	0.010	0.990	0.010
	产区势力	0.000	-0.015	0.390	0.610	0.390
	销区势力	0.000	0.130	0.045	0.045	0.955
	信息效应	0.805	0.147	0.030	0.030	0.970
	市场化程度	-0.015	-0.018	0.365	0.635	0.365
临储期	截距	3.702	0.000	-	-	-
	临储政策	-0.354	-0.079	0.082	0.919	0.082
	市场邻接	1.067	0.189	0.000	0.000	1.000
	市场距离	-0.001	-0.330	0.000	1.000	0.000
	产区势力	-0.001	-0.081	0.220	0.781	0.220
	销区势力	0.001	0.161	0.030	0.030	0.971
	信息效应	1.543	0.170	0.066	0.066	0.935
	市场化程度	0.013	0.009	0.445	0.445	0.555
补贴期	截距	3.781	0.000	-	-	-
	补贴政策	-0.487	-0.102	0.165	0.835	0.165
	市场邻接	1.030	0.172	0.000	0.000	1.000
	市场距离	-0.001	-0.326	0.000	1.000	0.000
	产区势力	0.000	0.068	0.293	0.293	0.708
	销区势力	0.001	0.186	0.015	0.015	0.985
	信息效应	0.787	0.190	0.070	0.070	0.931
	市场化程度	-0.051	-0.034	0.319	0.681	0.319

Spatial correlation of corn markets under the background of price support policy reform in China

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地区	关联省份	点出度	点入度	度数中心度	接近中心度	中间中心度
北京	16	2	16	55.172	69.048	0.045
天津	18	11	14	62.069	72.500	0.575
河北	27	27	14	93.103	93.548	3.698
山西	22	20	14	75.862	80.556	0.824
内蒙古	17	3	16	58.621	70.732	0.886
辽宁	13	3	13	44.828	64.444	0.500
吉林	8	2	8	27.586	58.000	0.290
黑龙江	10	3	10	34.483	60.417	0.164
上海	28	28	13	96.552	96.667	4.118
江苏	23	23	14	79.310	82.857	1.744
浙江	26	26	12	89.655	90.625	2.762
安徽	20	19	13	68.966	76.316	0.736
福建	27	27	13	93.103	93.548	2.915
江西	23	23	14	79.310	82.857	1.145
山东	26	26	14	89.655	90.625	2.361
河南	23	23	14	79.310	82.857	0.985
湖北	26	26	14	89.655	90.625	2.392
湖南	21	20	14	72.414	78.378	0.783
广东	27	27	15	93.103	93.548	2.915
广西	21	14	14	72.414	78.378	1.141
海南	16	8	13	55.172	69.048	0.229
重庆	17	2	17	58.621	70.732	0.347
四川	14	2	14	48.276	67.442	0.144
贵州	14	3	12	48.276	65.909	1.180
云南	12	5	9	41.379	61.702	0.402
陕西	21	16	13	72.414	80.556	1.410
甘肃	17	5	14	58.621	70.732	0.583
青海	14	1	13	48.276	65.909	0.522
宁夏	18	3	16	62.069	72.500	0.493
新疆	8	0	8	27.586	58.000	0.163
平均值	19.100	13.267	13.267	65.862	76.302	1.215

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