A Schumpeterian growth model with random quality improvements
A Schumpeterian growth model with random quality improvements
复制标题
具有随机质量改进的熊彼特增长模型
DOI：
10.1007/s00199-011-0664-0
复制
发表时间：
2013
期刊：
影响因子：
1.3
通讯作者：
P. Segerstrom
中科院分区：
文献类型：
--
作者：
Antonio Minniti;C. Parello;P. Segerstrom
熊彼特增长理论中的一个常见假设是，创新规模是恒定的，并且在各个行业都是相同的。这与以下经验证据相反：（1）不同产业的创新规模不同;（2）创新利润的规模分布向低价值侧倾斜，高价值侧的尾部较长。在本文中，我们开发了一个熊彼特增长模型，这是与这一证据相一致。特别是，我们假设，当一个公司创新，其质量改进的大小是从帕累托分布随机抽取的结果。这使我们能够扩展类的质量阶梯增长模型，包括企业的异质性。我们研究了这一新的设置数值的政策含义，并发现这是最佳的，以大量补贴的R&D合理的参数值。虽然对某些参数值的R&D征税是最优的，但这种情况只发生在稳态经济增长率非常低的情况下。
A common assumption in the Schumpeterian growth literature is that the innovation size is constant and identical across industries. This is in contrast with the empirical evidence which shows that: (1) innovation size is not identical across industries and (2) the size distribution of profit returns from innovation is highly skewed toward the low value side, with a long tail on the high value side. In the present paper, we develop a Schumpeterian growth model that is consistent with this evidence. In particular, we assume that when a firm innovates, the size of its quality improvement is the result of a random draw from a Pareto distribution. This enables us to extend the class of quality-ladder growth models to encompass firm heterogeneity. We study the policy implications of this new setup numerically and find that it is optimal to heavily subsidize R&D for plausible parameter values. Although it is optimal to tax R&D for some parameter values, this case only occurs when the steady-state rate of economic growth is very low.