人口年龄结构变动对碳排放的影响——基于生育率和预期寿命的跨国面板数据

doi:10.18402/resci.2021.10.14

摘要/Abstract

摘要：

在即将进入深度老龄化社会的大背景下,中国完成碳排放目标需要重点关注人口年龄结构变化的影响。归纳世界人口年龄结构对碳排放作用的普遍规律,有助于更好地了解人口年龄结构对碳排放的作用机制。鉴于此,本文选取全球有代表性的55个经济体,从生育率和预期寿命两个维度出发,运用面板数据分析方法,实证研究并对比分析年龄结构对各经济体碳排放的差异化影响和作用路径。研究表明：①生育率和预期寿命对碳排放增长存在着非线性作用,生育率下降促进了碳排放的增长,而预期寿命延长对碳排放具有先减后增的作用;②随着老龄化的加剧,预期寿命在人口年龄结构对碳排放作用中的贡献越来越高;③生育率和预期寿命作用于碳排放的主导路径在发展中国家和发达国家之间存在着差异,前者以规模变化路径为主,而后者由效率技术变化路径主导。本文结论丰富了人口年龄结构对碳排放影响机制的研究,也为探索中国老龄化背景下碳减排路径提供政策上的启示。

关键词: 年龄结构, 人口老龄化, 生育率, 预期寿命, 碳排放, 非线性关系, 面板数据分析

Abstract:

In the context of an emerging deeply aged society, China needs to focus on the impact of demographic change on achieving carbon emissions goals. In fact, to summarize the universal rules of the effect of world’s population age structure on carbon emission can help to better understand the mechanism of population age structure to carbon emission. Thus, based on the panel data of 55 representative global economies, this study empirically and comparatively examines the differential impact of age structure on carbon emissions growth of economies as well as its mechanism from the perspective of fertility rate and life expectancy by using panel data analysis method. The results show that both fertility rate and life expectancy have nonlinear effect on carbon emissions growth. The carbon emissions growth increases with the decline in fertility rate, but decreases with the extension of life expectancy at first and then increased. With the aggravation of population aging, life expectancy plays an increasingly important role in the impact of age structure on carbon emissions. In terms of the main mode of action of fertility rate and life expectancy, the leading mechanism differs between the developing and developed countries. The developing and developed countries are mainly driven by the change of scale and change of efficiency, respectively. This study enriches the research of the relationship between population age structure and carbon emissions growth. Furthermore, the results have policy implications for the path of carbon emissions reduction during the time of population aging.

Key words: age structure, population aging, fertility rate, life expectancy, carbon emissions, nonlinearity, panel data analysis

刘丰, 王维国. 人口年龄结构变动对碳排放的影响——基于生育率和预期寿命的跨国面板数据[J]. 资源科学, 2021, 43(10): 2105-2118.

LIU Feng, WANG Weiguo. The impact of age structure on carbon emissions: Based on a cross-country panel data of fertility rate and life expectancy[J]. Resources Science, 2021, 43(10): 2105-2118.

图/表 11

图1

图2

表1

表2

表3

图3

图4

表4

图5

表5

表6

各经济体碳排放作用机制分解

经济体	总和生育率-各路径贡献百分比				预期寿命年限-各路径贡献百分比
经济体	lnpop	lnl	lnye	lnci	lnpop	lnl	lnye	lnci
日本	15.540	-6.858	49.609	41.710	25.625	108.443	-289.930	255.862
挪威	20.235	-4.077	40.026	43.816	44.188	233.265	-569.848	392.395
意大利	20.885	0.859	43.984	34.271	26.161	118.865	-321.600	276.574
阿根廷	25.640	2.200	32.564	39.596	22.255	34.307	-61.101	104.538
瑞士	21.977	2.268	42.641	33.114	33.235	176.908	-464.491	354.348
英国	23.033	2.983	40.592	33.392	28.802	121.362	-308.630	258.466
加拿大	26.007	4.399	34.117	35.478	29.584	129.796	-331.399	272.019
澳大利亚	26.080	5.397	35.079	33.444	32.845	145.519	-359.136	280.772
法国	25.591	6.348	37.517	30.544	31.384	129.195	-314.606	254.027
欧盟（其他）	24.449	8.674	43.338	23.539	22.378	81.794	-223.685	219.513
美国	28.161	9.037	33.627	29.174	22.954	69.330	-176.509	184.225
德国	26.771	14.371	43.620	15.238	18.981	73.423	-223.158	230.754
新加坡	35.784	16.519	21.513	26.185	23.832	73.969	-185.371	187.570
俄罗斯	28.243	17.109	42.785	11.863	14.600	16.223	-61.166	130.343
沙特阿拉伯	54.648	18.359	-27.846	54.839	26.205	8.626	60.021	5.148
智利	37.077	21.904	24.243	16.776	19.345	16.178	-22.202	86.679
越南	48.442	26.084	-1.925	27.399	26.301	27.531	-4.579	50.748
中国	43.355	28.650	14.943	13.052	17.736	-11.200	59.330	34.133
马来西亚	50.362	28.854	-3.945	24.730	25.447	27.426	-11.195	58.322
墨西哥	53.837	29.669	-12.487	28.981	26.761	23.461	13.257	36.521
韩国	43.900	33.369	18.941	3.789	17.712	14.364	-29.278	97.202
泰国	49.634	38.770	9.566	2.031	18.350	2.953	15.407	63.289
巴西	52.502	43.200	6.887	-2.589	17.834	-1.161	25.413	57.914
菲律宾	70.850	49.864	-35.460	14.746	25.140	19.539	13.574	41.747
印度尼西亚	60.570	59.738	4.080	-24.389	15.110	-19.841	67.741	36.990
土耳其	65.297	64.017	-3.848	-25.466	16.540	-12.277	53.274	42.463
孟加拉国	67.769	65.060	-9.386	-23.444	17.025	-15.511	68.430	30.056
南非	66.598	66.980	-3.955	-29.623	16.824	-19.139	79.331	22.983
印度	65.529	68.817	1.097	-35.444	14.083	-27.223	84.874	28.265
巴基斯坦	85.705	73.431	-48.618	-10.518	19.924	-12.530	81.821	10.786
埃及	88.355	82.611	-45.184	-25.782	20.015	-6.841	62.890	23.936
尼日利亚	201.471	249.588	-159.910	-191.149	14.690	-34.189	113.928	5.570

表6

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符号	变量	单位	均值	标准差	最小值	最大值
CAR	CO₂排放量	百万t	365.613	963.003	0.293	10291.930
tfr	总和生育率	-	2.626	1.504	0.977	7.313
tle	预期寿命	岁	70.766	8.222	36.976	84.211
ur	城市化率	%	62.263	20.727	5.135	100.000
inds	产业增加值比重	%	28.608	13.502	2.365	84.796
ftd	外贸依存度	-	61.304	82.146	0.275	2750.919
gdppc	人均GDP	美元/人	17008.760	13699.610	131.300	83851.230
pop	人口规模	百万人	81.160	198.972	0.314	1409.517
kl	资本劳动比	-	140308.700	130093.500	895.070	685852.400
l	单位人口就业率	-	0.420	0.086	0.188	0.726
ye	有效人均产出	美元/人	38897.020	27944.880	485.805	173048.000
ci	碳排放强度	t/百万美元	0.468	0.374	0.020	9.614

	模型1	模型2	模型3	模型4
tfr	-0.334*** (0.070)	-0.335*** (0.070)	-0.220** (0.088)	-0.275*** (0.072)
tle	0.050*** (0.014)	0.050*** (0.014)	0.053** (0.027)	0.064** (0.028)
控制变量			加	加
时间效应				加
个体效应	RE	FE	FE	FE
R²	0.709	0.709	0.754	0.777

	模型5	模型6
tfr	-1.031 (0.880)	-1.788*** (0.595)
tle	-0.393* (0.211)	-0.523** (0.234)
tfr×tle	0.013 (0.011)	0.022** (0.009)
tfr²	-0.024 (0.032)	-
tle²	0.003** (0.001)	0.004** (0.002)

经济体	生育率效应/%	预期寿命效应/%	人口年龄结构总效应/%	生育率贡献率/%	经济体	生育率效应/%	预期寿命效应/%	人口年龄结构总效应/%	生育率贡献率/%
日本	0.054	2.726	2.780	1.952	墨西哥	2.144	2.788	4.932	43.465
瑞士	0.235	2.263	2.499	9.418	越南	1.955	2.514	4.469	43.747
意大利	0.259	2.370	2.630	9.854	马来西亚	2.112	2.399	4.510	46.819
挪威	0.202	1.832	2.034	9.926	尼日利亚	1.059	-1.085	-0.026	49.397
法国	0.304	2.307	2.611	11.628	中国	2.151	2.108	4.259	50.498
阿根廷	0.211	1.594	1.805	11.716	韩国	3.057	2.942	6.000	50.956
英国	0.268	1.753	2.021	13.273	埃及	2.511	1.974	4.485	55.984
德国	0.363	1.657	2.020	17.969	泰国	2.833	2.130	4.963	57.079
欧盟（其他）^(a)	0.354	1.603	1.956	18.091	巴基斯坦	2.078	1.446	3.524	58.973
澳大利亚	0.507	2.176	2.683	18.894	巴西	2.794	1.877	4.671	59.810
加拿大	0.649	1.893	2.542	25.543	菲律宾	2.549	1.441	3.990	63.882
沙特阿拉伯	1.722	4.217	5.939	28.995	土耳其	3.368	1.857	5.226	64.457
美国	0.663	1.338	2.001	33.148	孟加拉国	3.583	1.308	4.891	73.257
智利	1.479	2.636	4.115	35.943	印度尼西亚	2.649	0.742	3.391	78.124
新加坡	1.908	2.728	4.636	41.161	南非	2.942	0.527	3.469	84.803
俄罗斯	0.470	0.667	1.137	41.301	印度	3.153	-0.150	3.003	95.448

	lnpop	lnl	lnye	lnci
tfr	-0.358*** (0.082)	-0.664*** (0.219)	-0.299** (0.131)	0.816*** (0.307)
tle		-0.293*** (0.096)	0.565*** (0.101)	0.088*** (0.026)
tfr×tle	0.004*** (0.001)	0.009*** (0.003)		-0.013*** (0.004)
tfr²			0.037* (0.021)
tle²		0.002*** (0.001)	-0.004*** (0.001)