Is Winter Coming in Population Aging and Technological Progress: Empirical Evidence from OECD Countries
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摘要: 在梳理人口老龄化与技术进步关系的基础上, 利用36个OECD成员国1990—2017年的跨国面板数据, 实证研究人口老龄化对技术进步的影响效应。结果表明: 现阶段人口老龄化对技术进步的影响显著为正, 其内在机制可能是家庭与企业对人口老龄化做出了最优回应, 使得人口老龄化对技术进步的正向效应高于其负向效应; 目前OECD国家的人口老龄化尚未阻碍其技术进步, 采用替换变量、反向因果识别等多种方法进行稳健性检验, 上述结论依然成立。这一结论有助于正确理解人口老龄化对技术进步的影响, 进而可减轻人口老龄化对技术进步的负面效应。Abstract: On the basis of reviewing the relationship between population aging and technological progress, and using the cross-border panel data of 36 OECD member countries from 1990 to 2017, this paper empirically investigates the effect of population aging on technological progress. The empirical results show that: at present, the effect of population aging on technological progress is significantly positive, and its internal mechanism may be that families and enterprises have made the optimal response to population aging, which makes the positive effect of population aging on technological progress higher than its negative effect; at present, the population aging of OECD countries has not hindered technological progress, which is still valid by using alternative variables, reverse causal identification and other methods for robustness test. The findings are conducive to a correct understanding of the impact of population aging on technological progress, which can reduce the negative effects of population aging on technological progress.
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Key words:
- population aging /
- technological progress /
- total factor productivity /
- OECD /
- economic growth /
- innovation input
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图 6 老年抚养比与TFP
注:图6、图7中各变量均为残差形式; 非参数估计均使用伊潘科尼可夫(epanechnikov)核函数，基于拇指法则带宽估计法估计的最优带宽分别为0.06和0.05;图中浅色虚线部分为95%置信区间，黑色实线为相应的局部回归值。
图 7 老年抚养比与WTFP
注:图6、图7中各变量均为残差形式; 非参数估计均使用伊潘科尼可夫(epanechnikov)核函数，基于拇指法则带宽估计法估计的最优带宽分别为0.06和0.05;图中浅色虚线部分为95%置信区间，黑色实线为相应的局部回归值。
表 1 各变量的描述性统计分析(N=1 008)
变量 变量含义 均值 标准差 最小值 最大值 TFP 全要素生产率 0.974 0.0982 0.640 1.224 WTFP 与福利相关的全要素生产率 0.979 0.102 0.580 1.322 OADR 老年抚养比(%) 21.47 5.776 7.532 45.03 Age65 老龄化系数(%) 14.30 3.755 4.269 27.05 y 实际人均国内生产总值(美元) 31 477 13 965 7 631 83 912 k 实际人均物质资本存量(美元) 140 953 61 914 21 991 342 641 Labor 劳动力人口占总人口比重(%) 66.64 2.391 56.68 73.36 Urban 城市化水平(%) 75.44 11.15 47.91 97.96 Open 进出口总额占GDP比重(%) 85.79 51.66 16.01 424.0 Industry 工业增加值占GDP比重(%) 26.06 5.201 10.67 41.11 HC 人力资本指数 3.129 0.396 1.802 3.807 
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表 2 人口老龄化对技术进步的影响
变量 (1) (2) (3) (4) (5) (6) 静态面板模型 动态面板模型 RE FE RE FE Diff-GMM Sys-GMM L.lnTFP 0.731*** 0.816*** (0.084) (0.066) lnAging 0.127 0.122 0.142* 0.153** 0.220** 0.135** (0.080) (0.080) (0.079) (0.075) (0.101) (0.057) lny 0.560*** 0.615*** 0.582*** 0.674*** 0.255*** 0.148*** (0.064) (0.069) (0.063) (0.075) (0.080) (0.042) lnk -0.298*** -0.335*** -0.312*** -0.337*** -0.412*** -0.172*** (0.097) (0.113) (0.097) (0.107) (0.092) (0.035) lnLabor -0.013 -0.186 -0.116 -0.411 0.646 0.405* (0.427) (0.383) (0.430) (0.366) (0.413) (0.240) lnUrban -0.299** -0.499** -0.314** -0.445* -0.219 0.028 (0.137) (0.232) (0.142) (0.231) (0.275) (0.075) lnOpen 0.023 -0.004 0.022 0.009 0.043** 0.039*** (0.027) (0.037) (0.027) (0.034) (0.020) (0.011) lnIndustry 0.006 0.034 -0.004 -0.005 0.013 -0.002 (0.043) (0.038) (0.041) (0.043) (0.038) (0.031) lnHC -0.315* -0.127 -0.306* 0.042 0.162 -0.157 (0.168) (0.304) (0.178) 0.124 (0.251) (0.106) Constant -1.075 0.206 -0.701 (1.709) -0.627 -1.711 (1.825) (1.711) (1.905) (1.663) (1.990) (1.089) 国家FE Yes Yes Yes Yes 时间FE No No Yes Yes 组内R-squared 0.699 0.705 0.723 0.736 Hausman test 177.62*** 205.78*** AR (1) 0.017 0.008 AR (2) 0.393 0.111 Sargan test 0.991 1.000 Observations 1 008 1 008 1 008 1 008 936 972 注：***、**和*分别表示在1%、5%和10%水平上显著；静态和动态面板回归模型括号内分别为稳健标准误和聚类稳健标准误；动态面板回归模型均为two-step; AR(1)、AR(2)和Sargan检验分别报告相应检验统计量的p值；L.表示变量滞后一期。下表同。
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表 3 稳健性检验之替换变量和反向因果识别
变量 (1) (2) (3) (4) (5) (6) (7) 替换变量 反向因果识别 WTFP TFP WTFP TFP TFP TFP TFP L.lnTC 0.734*** 0.810*** 0.725*** 0.811*** 0.792*** 0.745*** 0.753*** (0.053) (0.067) (0.054) (0.057) (0.048) (0.054) (0.053) lnAging 0.188** 0.139*** 0.195*** (0.074) (0.051) (0.068) L. lnAging 0.150*** 0.135** (0.045) (0.053) L2. lnAging 0.136** 0.134** (0.056) (0.056) lny 0.214*** 0.149*** 0.217*** 0.152*** 0.152*** 0.195*** 0.184*** (0.058) (0.042) (0.063) (0.037) (0.036) (0.045) (0.045) lnk -0.220*** -0.172*** -0.229*** -0.165*** -0.154*** -0.192*** -0.173*** (0.063) (0.033) (0.063) (0.028) (0.038) (0.041) (0.039) lnLabor 0.009** 0.335 0.464** 0.371** 0.269 0.308 0.226 (0.004) (0.220) (0.192) (0.161) (0.259) (0.220) (0.193) lnUrban -0.058 0.029 -0.051 0.017 -0.025 0.015 -0.017 (0.096) (0.078) (0.100) (0.083) (0.105) (0.088) (0.075) lnOpen 0.025 0.039*** 0.025 0.040*** 0.032* 0.043*** 0.044*** (0.015) (0.010) (0.017) (0.011) (0.016) (0.013) (0.013) lnIndustry 0.081** -0.002 0.077* 0.004 0.007 0.005 0.002 (0.040) (0.031) (0.040) (0.030) (0.033) (0.031) (0.030) lnHC -0.238* -0.173* -0.236 -0.214** -0.177* -0.203** -0.254** (0.135) (0.096) (0.154) (0.086) (0.096) (0.099) (0.121) Constant -0.622 -1.375 -1.872** -1.640** -1.085 -1.491 -1.001 (0.379) (0.999) (0.736) (0.801) (1.246) (1.044) (0.886) AR(1) 0.007 0.008 0.007 0.008 0.006 0.008 0.009 AR(2) 0.106 0.115 0.107 0.107 0.100 0.401 0.386 Sargan test 1.000 1.000 1.000 1.000 1.000 1.000 1.000 Observations 972 972 972 972 972 972 972 注：L.和L2. 分别表示变量滞后一期和滞后二期。
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表 4 增加控制变量后的稳健性检验
变量 (1) (2) (3) (4) (5) 增加控制变量 L.lnTC 0.817***(0.071) 0.836***(0.075) 0.761***(0.064) 0.814***(0.073) 0.823***(0.077) lnAging 0.142**(0.056) 0.136***(0.053) 0.223**(0.095) 0.192**(0.079) 0.178**(0.087) 其他控制变量 Yes Yes Yes Yes Yes lnTax -0.001(0.015) 0.002(0.018) -0.002(0.016) -0.002(0.012) -0.002(0.014) lnPopulation 0.005(0.007) 0.011(0.015) 0.006(0.008) 0.003(0.008) lnSave 0.057**(0.027) 0.053**(0.027) 0.057*(0.030) lnEducation -0.029(0.018) -0.027(0.018) lnLifexp 0.255(0.280) Constant -1.818*(1.073) -1.611(1.362) -3.311*(1.926) -2.657(1.665) -3.324*(1.932) AR (1) 0.009 0.006 0.012 0.012 0.011 AR (2) 0.112 0.117 0.107 0.091 0.116 Sargan test 1.000 1.000 1.000 1.000 1.000 Observations 972 972 972 972 972
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表 5 稳健性检验之自助法和非线性估计
变量 (1) (2) (3) (4) 自助法估计 非线性检验 L.lnTC 0.840***(0.067) 0.791***(0.079) lnAging 0.039**(0.018) 0.039**(0.018) 0.007(1.545) 0.065(0.955) (lnAging)2 0.020(0.265) 0.021(0.190) lny 0.189***(0.019) 0.189***(0.019) 0.135***(0.041) 0.151***(0.044) lnk -0.066***(0.019) -0.066***(0.019) -0.159***(0.029) -0.175***(0.047) lnLabor 0.066(0.120) 0.027(0.113) 0.362(0.486) 0.409(0.441) lnUrban 0.068***(0.025) 0.068***(0.025) 0.033(0.083) 0.039(0.099) lnOpen 0.002(0.006) 0.002(0.006) 0.037**(0.016) 0.035***(0.013) lnIndustry 0.005(0.017) 0.005(0.017) 0.010(0.035) 0.023(0.029) lnHC -0.298***(0.027) -0.298***(0.027) -0.147**(0.058) -0.231**(0.094) Constant -1.574***(0.540) -1.394***(0.509) -1.423(0.955) -1.669(1.270) AR(1) 0.005 0.009 AR(2) 0.100 0.138 Sargan test 1.000 1.000 自助样本 500 500 Observations 972 972 注：自助法估计模型括号内为使用自助法得到的标准误。
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