An Exploration of the Japanese Slowdown during the 1990s

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Technology Diffusion and Postwar Growth

In the aftermath of World War II, the world's economies exhibited very different rates of economic recovery. We provide evidence that those countries that caught up the most with the U.S. in the postwar period are those that also saw an acceleration in the speed of adoption of new technologies. This acceleration is correlated with the incidence of U.S. economic aid and technical assistance in the same period. We interpret this as supportive of the interpretation that technology transfers from the U.S. to Western European countries and Japan were an important factor in driving growth in these recipient countries during the postwar decades.wars, economic growth, technology adoption, cross-country studies.

The Intensive Margin of Technology Adoption

We present a tractable model for analyzing the relationship between economic growth and the intensive and extensive margins of technology adoption. The "extensive" margin refers to the timing of a country's adoption of a new technology; the "intensive" margin refers to how many units are adopted (for a given size economy). At the aggregate level, our model is isomorphic to a neoclassical growth model, while at the microeconomic level it features adoption of firms at the extensive and the intensive margin. Based on a data set of 15 technologies and 166 countries our estimations of the model yield four main findings: (i) there are large cross-country differences in the intensive margin of adoption; (ii) differences in the intensive margin vary substantially across technologies; (iii) the cross-country dispersion of adoption lags has declined over time while the cross-country dispersion in the intensive margin has not; (iv) the cross- country variation in the intensive margin of adoption accounts for more than 40% of the variation in income per capita.Economic Growth, Technology Adoption, Cross-country studies.

The CHAT Dataset

This note accompanies the Cross?country Historical Adoption of Technology (CHAT) dataset. CHAT is an unbalanced panel dataset with information on the adoption of over 100 technologies in more than 150 countries since 1800. The data is available for download at: http://www.nber.org/data/chat. We discuss the main aim of CHAT, its scope and limitations, as well as several ways in which we have used the data so far and ways to potentially use the data for other research. Suggested acknowledgment: If you use the CHAT dataset for your research, please include the following citation: "Our technology measures come from the CHAT data set which is an extension of the data set described in Comin and Hobijn (2004)"

An Exploration of Technology Diffusion

We develop a model that, at the aggregate level, is similar to the one sector neoclassical growth model, while, at the disaggregate level, has implications for the path of observable measures of technology adoption. We estimate our model using data on the diffusion of 15 technologies in 166 countries over the last two centuries. We evaluate the implications of our estimates for aggregate TFP and per capita income. Our results reveal that, on average, countries have adopted technologies 47 years after their invention. There is substantial variation across technologies and countries. Over the past two centuries, newer technologies have been adopted faster than old ones. The cross-country variation in the adoption of technologies accounts for at least a quarter of per capita income differences.economic growth, technology adoption, cross-country studies.

Was the Wealth of Nations Determined in 1000 B.C.?

We assemble a dataset on technology adoption in 1000 BC, 0 AD, and 1500 AD for the predecessors to today's nation states. We find that this very old history of technology adoption is surprisingly significant for today's national development outcomes. Our strong and robust results are for 1500 AD determining per capita income today. We find technological persistence across long epochs: from 1000 BC to 0 AD, from 0 AD to 1500 AD, and from 1500 AD to the present. Although the data allow only some suggestive tests of rival hypotheses to explain long?run technological persistence, we find the evidence to be most consistent with a model of endogenous technology adoption where the cost of adopting new technologies declines sufficiently with the current level of adoption. The evidence is less consistent with a dominant role for population as predicted by the semi?endogenous growth models or for country-level factors like culture, genes or institutions.Technology adoption, technology history, economic development.

World Technology Usage Lags

We present evidence on the differences in the intensity with which ten major technologies are used in 185 countries across the world. We do so by calculating how many years ago these technologies were used in the U.S. at the same intensity as they are used in the countries in our sample. We denote these time lags as technology usage lags and compare them with lags in real GDP per capita. We find that (i) technology usage lags are large, often comparable to lags in real GDP per capita, (ii) usage lags are highly correlated with lags in per-capita income, and (iii) usage lags are highly correlated across technologies. The productivity differentials between the state of the art technologies that we consider and the ones they replace combined with the usage lags that we document, lead us to infer that technology usage disparities might account for a large part of cross-country TFP differentials.

Medium Term Business Cycles in Developing Countries

We build a two country asymmetric DSGE model with two features: (i) endogenous and slow diffusion of technologies from the developed to the developing country, and (ii) adjustment costs to investment flows. We calibrate the model to match the Mexico-U.S. trade and FDI flows. The model is able to explain the following stylized facts: (i) U.S. and Mexican output co-move more than consumption; (ii) U.S. shocks have a larger effect on Mexico than in the U.S.; (iii) U.S. business cycles lead over medium term fluctuations in Mexico; (iv) Mexican consumption is more volatile than output.Business Cycles in Developing Countries, Co-movement between Developed and Developing economies, Volatility, Extensive Margin of Trade, Product Life Cycle, FDI.

An Exploration of the Japanese Slowdown during the 1990s

Why did the Japanese slowdown of the 90s last so long if none of the shocks that hit the Japanese economy had a comparable persistence? In this paper, I use the Comin and Gertler (2006) model of medium term fluctuations to explore whether their endogenous technology mechanisms can amplify and propagate the wage markup fluctuations observed in Japan over the early 90s to drive a Japanese productivity slowdown. The model can reproduce the observed decline, relative to trend of R&D expenditures and the slowdown in the diffusion of new technologies. This slowdown in the development and adoption of new technologies constitutes a powerful propagation mechanism. As a result, the model does a good job in reproducing the evolution of output, consumption, investment, TFP and hours worked in Japan during the "lost decade", specially up to 1998. During the last two years of the decade, the propagation mechanisms in the model seem to run out of steam, while the Japanese economy continued to deteriorate.