The invention and adoption of new technologies is one of the main driving forces behind economic growth. The PI's have developed the Historical Cross Country Technology Adoption (HCCTA) dataset. It contains a set of historical time series that documents the adoption patterns of over twenty major technologies in more than twenty of the world's leading industrialized countries over the past two hundred years. Though very useful for understanding many important questions, the current version of the HCCTA dataset has at least two limitations. First, developing countries are in many dimensions fundamentally different to developed economies. Thus, it is not clear whether the lessons learnt from exploring the technology adoption patterns in rich countries are transferable to poor countries. Second, the more than 20 technologies contained in the current version of the HCCTA dataset do not cover the economy comprehensively enough to draw inference on the determinants of productivity in the economy as a whole. The PI's propose expanding the HCCTA dataset to cover over 30 additional technologies and a total of over 160 countries. This expansion would substantially mitigate the limitations of the current version of the HCCTA dataset. In addition to extending the dataset, the PI's describe, in this proposal, various projects that they will undertake and that take full advantage of the three dimensional nature (country-technology-time) of the HCCTA dataset. These projects include, among others, exploring the role of technology adoption in aggregate productivity growth in developed and developing countries, estimating the effect of lobbying activities on the diffusion of new technologies, evaluating the importance of the various potential sources of growth in the East Asian miracles and studying the similarities between the growth processes of China and the East Asian miracles. Interestingly, some of these debates seem to have reached a dead end partly due to the current lack of data necessary to make progress. The structure and depth of the information contained in the extended HCCTA dataset are suitable to enhance knowledge on these important topics. Broader Impact The main externality from this proposal will be the creation of an extensive dataset on historical cross-country technology adoption patterns. At this point, the only comparable dataset is the current version of the HCCTA dataset. The potential value of such a dataset for the evolution of understanding of the determinants of living standards both in advanced and in developing countries seems very large. Just like the current version, the extended HCCTA dataset will be publicly available at the NBER web site. The experience so far is that many researchers in the fields of productivity growth, macroeconomics, technological change and economic history are and will be using it. In addition, both the research projects described in this proposal and the papers written in the future by other researchers using the HCCTA dataset will be about issues that typically have very important policy implications. It is well known, at least since Lucas (1993), that policies that affect the growth rate of an economy by accelerating the speed of diffusion of technologies may have significant permanent effects on living standards. In this sense, the research that we hope that the extended HCCTA dataset will facilitate will not only have policy implications but these will be very important. Last but not least, the construction and analysis of this dataset will provide the opportunity to train two students both in data collection and statistics as well as in dynamic macroeconomic theory.
