Using aggregate data from 31 Organization for Economic Co-operation and Development (OECD) countries covering periods from 1982 to 2017, this study examines the notion that the level of product complexity is a good determinant of economic growth in the long run. We use the impulse-response function (IRF) computed from the consistent generalized method of moment panel vector autoregressive (GMM pVAR) model to estimate the response of the real output growth to a change in the economic complexity index. The IRF shows that the economic complexity index has a significant impact on economic growth; a 1 standard deviation shock to the economic complexity index at time 0 contributes around 2.34 percentage points to the average rate of growth of output within the first period. The point estimates are positive and significant up to the third period. The cumulative IRF shows that the aggregate impact on economic growth is about 4.4% in the long run. Compared to some widely used innovation proxies such as the gross expenditure on research and development and secondary school enrollment, the economic complexity index performs relatively better in our model in determining economic growth in the long run.

本研究使用来自 31 个经济合作与发展组织 (OECD) 国家的 1982 年至 2017 年期间的汇总数据，研究了产品复杂程度是长期经济增长的良好决定因素这一概念。我们使用从一致广义矩面板向量自回归 (GMM pVAR) 模型计算的脉冲响应函数 (IRF) 来估计实际产出增长对经济复杂性指数变化的响应。IRF显示经济复杂性指数对经济增长有显着影响；在时间 0 对经济复杂性指数的 1 个标准差冲击对第一时期内产出的平均增长率贡献约 2.34 个百分点。直到第三个时期，点估计都是正的且显着。累计IRF显示，长期来看对经济增长的总体影响约为4.4%。与一些广泛使用的创新指标（如研发总支出和中学入学率）相比，经济复杂性指数在我们的模型中在确定长期经济增长方面表现相对更好。