Irrigation water pressure, supply elasticity and grain production structure based on heterogeneous coefficient Nerlove model

Fig. 2. Average comparison of irrigation water pressure index and simplified irrigation water pressure index of each province in China from 2002 to 2017

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Table 1. Descriptive statistics

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Table 1. Descriptive statistics

变量	符号	平均值	标准差	最小值	最大值	样本量/个
灌溉水压力指数/%	δ	33.92	35.33	3.08	158.59	432
年降水量/mm	rain	957.74	557.97	142.71	2555.80	432
每年≥10 ℃日数/天	tep	231.19	64.11	119.00	363.00	432
有效灌溉面积比例/%	irr	45.80	20.56	13.70	98.64	432
农业劳动力价格/元	lab	2364.44	2010.21	132.01	14886.07	432
第一产业就业人数比例/%	fir	0.43	0.12	0.19	0.81	432
小麦价格/(元/kg)	P₁	1.13	0.51	0.10	3.51	432
水稻价格/(元/kg)	P₂	1.17	0.36	0.10	2.26	432
玉米价格/(元/kg)	P₃	1.03	0.48	0.10	2.42	432
豆类价格/(元/kg)	P₄	2.67	1.45	0.71	7.78	432
薯类价格/(元/kg)	P₅	2.77	1.05	0.65	9.67	432
油料价格/(元/kg)	P₆	2.23	0.71	0.82	5.48	432
蔬菜价格/(元/kg)	P₇	1.40	1.19	0.30	7.77	432
小麦产量/万t	Y₁	414.00	714.63	21.78	3705.20	240
水稻产量/万t	Y₂	1042.85	665.83	110.60	2819.30	304
玉米产量/万t	Y₃	835.69	752.43	100.20	3703.10	336
豆类产量/万t	Y₄	78.09	112.78	9.70	719.00	384
薯类产量/万t	Y₅	131.31	101.41	8.18	531.10	432

Table 2. Sargan test and Arellano-Bond test for Nerlove model
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Table 2. Sargan test and Arellano-Bond test for Nerlove model
小麦水稻玉米豆类薯类
Sargan检验 0.251 0.302 0.363 0.273 0.292
Arellano-Bond检验 AR(1) 0.023 0.003 0.012 0.048 0.036
AR(2) 0.845 0.253 0.671 0.996 0.432

Table 3. Regression results of Nerlove model

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Table 3. Regression results of Nerlove model

变量	小麦	水稻	玉米	豆类	薯类
$\ln δ_{t - 1}$	-0.140^***	-0.316^***	0.221^***	-0.145^**	-0.216^***
	(0.029)	(0.060)	(0.036)	(0.066)	(0.059)
$\ln Y_{t - 1}$	0.555^***	0.603^***	0.608^***	0.604^***	0.718^***
	(0.050)	(0.039)	(0.042)	(0.060)	(0.046)
$\ln P_{1, t - 1}$	0.899^***	-0.030	-0.153	0.066	0.465^***
	(0.188)	(0.080)	(0.110)	(0.208)	(0.152)
$\ln P_{2, t - 1}$	-0.907^***	0.782^**	0.469^***	-0.202	0.076
	(0.200)	(0.098)	(0.123)	(0.221)	(0.103)
$\ln P_{3, t - 1}$	-0.116	0.213^***	0.661^***	-0.301^**	0.268^**
	(0.163)	(0.077)	(0.104)	(0.148)	(0.114)
$\ln P_{4, t - 1}$	0.362^***	0.147^***	0.179^***	0.283^***	-0.097
	(0.129)	(0.055)	(0.052)	(0.101)	(0.106)
$\ln P_{5, t - 1}$	0.037	-0.077	0.062	-0.043	0.181^***
	(0.092)	(0.074)	(0.054)	(0.103)	(0.009)
$\ln P_{6, t - 1}$	-0.011	0.188^***	0.083	-0.102	-0.308^***
	(0.117)	(0.059)	(0.061)	(0.115)	(0.106)
$\ln P_{7, t - 1}$	0.138	0.061	0.040	0.067	-0.432^***
	(0.123)	(0.070)	(0.061)	(0.124)	(0.089)
$\ln rai n_{t}$	-0.341^***	0.074^*	-0.029	-0.029	0.162^***
	(0.077)	(0.045)	(0.054)	(0.086)	(0.069)
$\ln te p_{t}$	1.448^***	-0.366^*	-0.107	0.045	0.631^*
	(0.274)	(0.137)	(0.190)	(0.250)	(0.332)
$\ln ir r_{t}$	0.459^***	0.060^***	-0.034	0.092	-0.443^***
	(0.116)	(0.015)	(0.077)	(0.136)	(0.122)
$\ln la b_{t}$	-0.075^***	-0.020	0.094^***	-0.018	0.188^***
	(0.052)	(0.030)	(0.028)	(0.046)	(0.044)
$\ln fi r_{t}$	-0.049	-0.201^*	-0.085	0.166^**	0.589^***
	(0.255)	(0.104)	(0.131)	(0.207)	(0.204)
$C P_{t}$	-0.224^***	-0.054	0.098^***	0.105	0.242^***
	(0.066)	(0.037)	(0.037)	(0.098)	(0.062)
$W P_{t}$	0.297^***	0.054	-0.074	0.074	-0.312^***
	(0.082)	(0.049)	(0.055)	(0.081)	(0.092)
$R P_{t}$	-0.223^***	0.103^***	0.002	-0.117^*	-0.174^***
	(0.083)	(0.034)	(0.043)	(0.062)	(0.060)
常数项	-5.266^***	5.073^***	2.173^**	1.982	0.608
	(1.531)	(0.854)	(1.008)	(1.420)	(1.568)
观测值	225	285	315	360	405

Table 4. Regression results of heterogeneous coefficient Nerlove model

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Table 4. Regression results of heterogeneous coefficient Nerlove model

变量(自然对数形式)	小麦	水稻	玉米	豆类	薯类
以灌溉水压力指数回归的结果
$\ln P_{k, t - 1} \times \ln δ_{t - 1}$	-0.254^*	0.199^**	0.169^***	-0.308^***	-0.157^*
	(0.145)	(0.089)	(0.071)	(0.118)	(0.091)
$\ln P_{k, t - 1}$	1.665^***	0.557^*	0.645	1.678^***	1.159^*
	(0.476)	(0.283)	(0.611)	(0.253)	(0.326)
$\ln δ_{t - 1}$	0.268^***	-0.089	0.248^***	0.161	-0.009
	(0.010)	(0.057)	(0.039	(0.135)	(0.110)
$\ln Y_{t - 1}$	0.541^***	0.417^***	0.495^***	0.618^***	0.509^***
	(0.051)	(0.043)	(0.043)	(0.061)	(0.060)
以简化灌溉水压力指数回归的结果
$\ln P_{k, t - 1} \times \ln δ_{t - 1}^{'}$	-0.337^**	0.508^***	0.305^*	-0.213^*	0.367^***
	(0.154)	(0.122)	(0.091)	(0.113)	(0.158)
$\ln P_{k, t - 1}$	1.944^***	-0.640^***	0.228	1.263^***	-0.380
	(0.449)	(0.180)	(0.057)	(0.265)	(0.410)
$\ln δ_{t - 1}^{'}$	0.079	-0.078	-0.066	-0.323^**	-0.507^***
	(0.087)	(0.063)	(0.058)	(0.133)	(0.179)
$\ln Y_{t - 1}$	0.591^***	0.750^***	0.700^***	0.533^***	0.367^**
	(0.043)	(0.039)	(0.040)	(0.050)	(0.157)

Table 5. Spatio-temporal changes of irrigation water pressure index and long-term supply elasticity of grain in main grain-producing areas of China

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Table 5. Spatio-temporal changes of irrigation water pressure index and long-term supply elasticity of grain in main grain-producing areas of China

		灌溉水压力指数平均值/%	长期供给弹性
		灌溉水压力指数平均值/%	小麦	水稻	玉米	豆类	薯类
不同年份	2003年	28.773	1.768	2.102	2.889	1.684	1.286
	2008年	33.288	1.688	2.152	2.959	1.566	1.240
	2013年	36.314	1.640	2.182	3.000	1.496	1.212
	2017年	36.026	1.644	2.179	2.996	1.503	1.214
南方粮食主产区	江苏	13.491	2.188	1.844	2.529	2.295	1.528
	安徽	6.094	2.627	1.572	2.151	2.935	1.783
	湖北	8.993	2.412	1.705	2.336	2.622	1.658
	湖南	25.598	—	2.062	—	1.778	1.324
	江西	24.896	—	2.053	—	—	1.333
	四川	13.542	2.185	1.845	2.531	2.292	1.527
	平均值	15.436	2.353	1.847	2.387	2.384	1.526
北方粮食主产区	河北	147.866	0.863	—	3.669	0.364	0.763
	山东	61.755	1.346	2.363	3.253	1.068	1.042
	河南	70.360	1.274	2.407	3.315	0.963	1.000
	内蒙古	28.555	1.773	—	2.886	1.690	1.289
	黑龙江	9.758	2.367	1.733	2.374	2.556	1.632
	辽宁	75.453	1.235	2.431	3.348	0.907	0.978
	吉林	46.442	1.503	2.266	3.117	1.298	1.133
	平均值	62.884	1.480	2.240	3.137	1.264	1.120

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Xin YANG, Yue-ying MU. Irrigation water pressure, supply elasticity and grain production structure based on heterogeneous coefficient Nerlove model[J]. Journal of Natural Resources, 2020, 35(3): 728

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