IMF-熊彼特对吗？金融科技与经济增长（英译中）

2024Abstract关键字:3更有效地展示与分析特别相关的关键贡献并发现更多的金融可能与更少的增长相关(Rou00（十亿美元）2023).4andLi,2023).Whilefinancialdefinitionandinnovationcanmovembil2这项研究通过使用一个新的金融科技直接衡量标准数据集对文献做出了贡献，并digitalcapitalraising).WhiledigitallendingasashareofGDPhas5通过增加金融中介和为固定资本提供金融资源本文的其余部分结构如下。第二节提供了数据概述本文提出的实证分析是基于一个不平衡的年度面板数据集。金融科技交易（不包括加密货币）占GDP的份额。主要6对于金融科技的发展，我将数字贷款和数字资本筹集与其他类型的控制与以下因素相关的其他人口和经济变量的影响education,whichareobtain变量ObservationsMean标准。dev.最小值最大值实际GDP增长1,7382.25.9-5固定资本形成总额1,48523.18.0数字借贷5940.10.3数字资本筹集1,0930.00.00.0Total1,1180.10.2实际人均GDP1,73813,70618,765通货膨胀1,6205.321.1-4.3贸易开放1,58190.958.410.0对私营部门的国内信贷1,52855.043.51.1258.9政府支出1,51717.18.63.6教育造诣94447.817.0政府稳定1,2427.11.14.0官僚质量1,2422.21.10.07and(iii)totalincludingallfintechinstrumentsasashareofGDP.Thesefiwhere푦푖푡表示实际人均国内生产总值增长或固定资本形成内生和预先确定的变量由它们自己的适当滞后来衡量8与自己的第一个差异的合适的滞后。我应用系统的一步版本GMM在系统GMM估计中使用变量的所有可用滞后水平会导致andtheHansenJ-testfortheoveridentificationrestrictions.Theval是一阶差分中一阶和二阶自相关扰动的p值实证分析为金融科技和金融科技之间的关系提供了有趣的见解。表明金融科技的规模和统计意义根据金融科技9AllAEEM数字资本筹集Totalfintech政府支出人口增长教育造诣政府稳定观察次数0.406[0.329]0.406[0.329][1.391]9.805[8.621]9.805[8.621][11.700]0.789[0.323]-12.802**-9.936***-9.539***-9.148-10.427[4.121][3.803][3.783][4.514][4.130]-0.047-0.077***-0.076***0.0310.159[0.041][0.006][0.006][0.173][0.081]0.0540.063*0.059*0.0270.019[0.030][0.023][0.022][0.019][0.014]-0.022-0.009-0.015-0.011-0.004[0.008][0.005][0.006][0.009][0.003]-1.525***-1.015***-0.989***-1.667***-1.573***[0.180][0.219][0.225][0.157][0.181]1.765***0.630***0.609***1.053***0.883***[0.442][0.082][0.091][0.209][0.247]0.0220.0070.0070.0050.013[0.012][0.019][0.020][0.009][0.021]0.1360.1490.1440.0900.075[0.080][0.090][0.091][0.095][0.061]0.2540.9800.587[0.665][0.642][0.686][1.596][1.588]YesYesYesYesYesYesYesYesYesYes0.490.390.380.580.570.100[0.427]-33.076[29.223]1.3080.453[0.796][0.376]-7.193-18.120***-9.563***-10.252***[4.951][4.469][2.540][2.631]0.070-0.132***-0.061***-0.062***[0.133][0.021][0.005][0.005]0.0230.121**0.105***0.100***[0.011][0.040][0.030][0.031]-0.009-0.070**-0.037-0.037[0.006][0.023][0.016][0.019]-1.556***-1.283***-0.613***-0.622***[0.218][0.305][0.170][0.174]0.822**2.440**0.407***0.422***[0.235][0.321][0.118][0.128]0.0060.0600.0110.006[0.016][0.028][0.024][0.021]0.1020.2580.2220.208[0.066][0.151][0.130][0.127]1.3530.0321.1071.021[1.658][0.509][0.631][0.610]223174YesYesYesYesYesYesYesYes0.520.480.360.36AllAEEM0.354***0.429***0.439***0.237***0.308***0.300***[0.039][0.095][0.099][0.054][0.091][0.849***1.909*[0.176][0.785]17.61014.627[9.039][9.074]0.718***2.089**-0.459***-0.358*-0.379*-0.484-1.095-0.939-0.824*[0.074][0.148][0.148][0.780][0.528][0.499]-0.112**-0.049***-0.049***-0.266-0.275-0.296*[0.038][0.007][0.007][0.137][0.129][0.110]0.0020.0020.0020.0020.0030.0030.0110.011*0.010*[0.002][0.002][0.002][0.001][0.001][0.001]-0.003-0.002-0.003-0.005-0.003-0.003-0.001[0.004][0.004][0.003][0.006][0.005][0.005]-0.094-0.080-0.078-0.066-0.052-0.042[0.040][0.033][0.032][0.055][0.046][0.049]0.138***0.158*0.176*0.668**0.592**0.613**0.0290.1680.184[0.114][0.065][0.072][0.217][0.202][0.182]0.0170.0130.0120.0020.0090.0100.033**0.021*0.021*[0.008][0.007][0.007][0.007][0.011][0.011]0.1450.234***0.221***0.1270.1890.1860.0280.219[0.091][0.067][0.068][0.093][0.080][0.081]0.3850.2510.3240.0110.3830.3980.2310.050[0.195][0.159][0.156][0.344][0.323][0.299]YesYesYesYesYesYesYesYesYesYesYesYesYesYesYesYes0.0050.0000.0000.0030.0040.0010.0040.0000.0000.2170.4250.3170.6140.3420.2910.2090.7350.6860.2670.3690.3630.9920.8490.8020.2850.5990.467在发展中国家是负面的，这可能反映了金融科技在这方AllAEEM固定资本形成总额0.854***[0.145]0.700***[0.136]0.790***[0.134]Totalfintech0.322***[0.091]0.566***[0.115]-0.680***[0.204]实际人均GDPt-1-0.019*0.560-0.124[0.006][0.977][0.340]通货膨胀-0.051**0.169-0.052**[0.018][0.125][0.018]贸易开放0.001-0.0020.005[0.002][0.003][0.007]金融发展0.004-0.0070.004[0.003][0.006][0.003]政府支出-0.025-0.060-0.055[0.041][0.078][0.066]人口增长0.085*0.0770.168*[0.017][0.104][0.035]教育造诣0.0090.0010.014[0.011][0.001][0.016]政府稳定0.022***0.0590.100***[0.007][0.126][0.015]官僚质量0.369*0.0850.261*[0.137][0.596][0.032]观察次数533228305国家数量963264国家FE