The Diffusion of New Technology and the Evolution of Industry Structure: The North American Maritime Industries Since c.1789

本研究项目以1789年至20世纪的北美商船造船和商船航运业为背景，对新技术的传播、产业结构的演变和企业生存进行实证研究。该项目的两个主要目的是：(1)在基于特定年代的人力资本和基于学习的两种相互竞争的技术扩散理论之间进行测试，以及(2)研究产业演变模式和企业生存的决定因素，特别侧重于在最近的行业淘汰模型之间进行判别测试。这些测试将使用美国造船厂和加拿大托运人的新面板数据，以及离开加拿大大西洋港口的航行中海员与其雇主之间签订的个人工资合同的大型数据集。数据跨度在80年到120年之间。加拿大的数据最近向研究人员提供，而美国的数据将从主要来源构建。这些数据对技术研究具有独特的价值，因为它们确定了公司使用的精确技术和员工使用的精确技术。对扩散理论的检验将集中于从人力资本特定于某一特定年代的技术的模型和个别公司和工人了解并花费资源以转向新技术的模型中产生的歧视性预测。在企业层面，特定年份人力资本模型预测技术扩散率与技术使用差异之间呈负相关，而学习模型预测呈正相关。在个体工人层面，特定年代人力资本模型预测，与最近的技术年代相匹配的员工的年龄收入曲线更陡峭，但所有工人的预期终身收入是相同的。相比之下，学习模型预测，较早掌握新技术的工人的预期终身收入更高。最近的行业演化理论关注的是洗牌，这是行业生命周期中企业退出率在短时间内急剧上升的一个强劲特征。最近的几项研究从采用新技术的不同成功程度来解释这种淘汰，而另一些研究则认为，退出率的变化仅仅是早期进入率变化的结果。在支持技术重要性的研究中，企业规模的作用被不同地对待。这项研究主要集中在两条主线上：第一，采用新技术对企业生存有多大影响？换句话说，企业年龄是企业成长和生存的充分统计数据，还是技术选择重要？第二，当前规模是衡量企业最终成功采用新技术可能性的重要指标吗？这些问题将使用船厂面板来衡量企业规模的影响来解决。公司的年龄，和当前的技术对公司成长和生存的影响。

This research program is concerned with empirical investigations of the diffusion of new technology, the evolution of industry structure, and firm survival, all in the context of the North American merchant shipbuilding and merchant shipping industries from c.1789 to the twentieth century. The two main pur-poses of this project are: (1) to test between two competing theories of technological diffusion based on vintage-specific human capital and on learning, and (2) to study patterns of industry evolution and the determinants of firm survival with the particular focus of conducting discriminating tests between recent models of industry shakeouts.These tests will be conducted using new panel data on US shipyards and Canadian shippers, and on a large dataset of individual wage contracts struck between mariners and their employers on voyages leav-ing Canadian Atlantic ports. The data span periods of between 80 and 120 years. The Canadian data were recently made available to researchers, while the US data will be constructed from primary sources. These data are uniquely valuable for the study of technology because they identify the precise technology em-ployed by firms and the precise technology with which employees were working.Tests of theories of diffusion will focus on the discriminating predictions arising from models in which human capital is specific to technology of a given vintage, and those in which individual firms and workers learn about, and expend resources in order to switch to, new technologies. At the firm level, the vintage-specific human capital model predicts a negative correlation between the rate of technological diffusion and the variance of technologies in uses, while the learning model predicts a positive correla-tion. At the individual worker level, the vintage-specific human capital model predicts a steeper age-earnings profile for employees matched with recent vintages of technology, but that expected lifetime earnings for all workers are the same. The learning model, in contrast, predicts higher expected lifetime earnings for workers who master new technologies earlier.Recent theories of industry evolution have focused on the shakeout, a robust feature of the industry life cycle in which firm exit rates rise dramatically in a short period of time. Several recent studies have explained the shakeout in terms of differential success in adopting new technologies, while others have argued that variations in exit rates are simply a result of earlier variations in entry rates. Among studies arguing for the importance of technology, the role of firm scale has been treated differently. The research focuses on two main lines of inquiry: First, to what extent does the adoption of new technology matter for firm survival? Put another way, is firm age a sufficient statistic for firm growth and survival, or does technology choice matter? Second, is current scale an important indicator of the probability that a firm will eventually succeed in adopting new technology? These questions will be addressed using the panel of shipyards to measure the effects of firm size. firm age, and current technology on firm growth and sur-vival.