Factor Returns, Institutions, and Geography: A View From Trade

We examine the importance of institutions and geography for determining workers' wages and the return to capital. These returns to labor and capital are examined through the lens of labor and capital's productivities, which are directly related to the factors' returns. We estimate productivities of labor and capital based on trade flows across countries and present statistical evidence that these productivities are related to total factor productivities which rationalize output differences across countries. We examine whether these labor and capital productivities are related to countries' political institutions and geography. Protection of property rights is the dominant influence on both labor and capital productivity. There is some evidence that a democratic government affects productivity, but once property rights are included in the analysis, the overall democracy index has little influence on factor productivity.. Geography is only important in terms of distance to a large market. Factors such as the incidence of malaria are relatively unimportant. The unimportance of geography is not only statistical. For example, if the Philippines kept its geography but had the United Kingdom 's institutions, the Philippines ' labor productivity would increase from seven percent to 75 percent of the U.S. 's and capital productivity would increase from 25 percent to 58 percent of the U.S. 's. On the other hand, if the Philippines were to keep its institutions and were magically more to the United Kingdom 's geographic location, labor productivity would increase only from seven percent to 28 percent and capital productivity would increase from 25 percent to 26 percent.

How important are capital and total factor productivity for economic growth?

The authors examine the relative importance of the growth of physical and human capital and the growth of total factor productivity (TFP) using newly organized data on 145 countries that span more than one hundred years for twenty-four of these countries. For all countries, only 3 percent of average output growth per worker is associated with TFP growth. This world average masks interesting variations across countries and regions. Of the nine regions, TFP growth accounts for about twenty percent of average output growth in three regions and between ten and zero percent in the other three regions. In three regions, TFP growth is negative on average. The authors use priors from theories to construct estimates of the relative importance of the variances of aggregate input growth and TFP growth for the variance of output growth across countries. Across all countries, variation in aggregate input growth per worker could account for as much as 35 percent of the variance of the growth of output per worker across countries, and variation in TFP growth could account for as much as 87 percent of that variance. Much of the importance of the variance of TFP growth appears to be associated with negative TFP growth.Productivity ; Economic development ; Capital ; Industrial productivity

Modern economic growth and recent stagnation

During the past 200 years, most countries have entered a period of modern economic growth-consistent increases in output, input, and productivity per worker that were rare in previous centuries. Even so, a few regions of the world have experienced stagnant or falling living standards in recent years, which some have interpreted as typical of modern economic growth in the last two centuries. ; Using data for most countries in the world since the 1800s and early 1900s, the authors find that (1) economic growth has improved the lives of people all around the world compared to those of their ancestors and (2) the economic stagnation or decline in some parts of the world in recent decades is unusual in the broader context of the history of the world since 1800. ; The authors find that economic growth had become nearly global by the 1950s, and the recent economic declines in four regions in recent decades are atypical. Decreases in income and productivity are likely to be transitory in Central and Eastern Europe but may be longer lasting in the Middle East and Latin America. While modern economic growth may never have begun in Sub-Saharan Africa, government policies in that region have done more to throttle economic growth than to encourage it.Economic history ; Economic development

Potential of nonlocally filtered pursuit monostatic TanDEM-X data for coastline detection

This article investigates the potential of nonlocally filtered pursuit monostatic TanDEM-X data for coastline detection in comparison to conventional TanDEM-X data, i.e. image pairs acquired in repeat-pass or bistatic mode. For this task, an unsupervised coastline detection procedure based on scale-space representations and K-medians clustering as well as morphological image post-processing is proposed. Since this procedure exploits a clear discriminability of "dark" and "bright" appearances of water and land surfaces, respectively, in both SAR amplitude and coherence imagery, TanDEM-X InSAR data acquired in pursuit monostatic mode is expected to provide a promising benefit. In addition, we investigate the benefit introduced by a utilization of a non-local InSAR filter for amplitude denoising and coherence estimation instead of a conventional box-car filter. Experiments carried out on real TanDEM-X pursuit monostatic data confirm our expectations and illustrate the advantage of the employed data configuration over conventional TanDEM-X products for automatic coastline detection

Data appendix for economic growth in the long run

This extended data appendix describes the sources and methods used to construct the data used in our paper "Economic Growth in the Long Run.

Data appendix for economic growth in the long run

This extended data appendix describes the sources and methods used to construct the data used in our paper "Economic Growth in the Long Run.

Economic growth In the long run

We present new data on real output per worker, schooling per worker, human capital per worker, real physical capital per worker for 168 countries. The output data represent all available data from Maddison. The physical capital data represent all available data from Mitchell. One major contribution is a new set of human capital per worker, the foundation of which comes mostly from Mitchell. We provide original estimates of schooling per worker & per young worker. We find strong support for intergenerational accumulation of human capital with spillovers. With our preferred measure of human capital, over 90 percent of the variation in long run growth can be explained by variation in the growth of inputs per worker, and less than 10 percent from variation in TFP growth. Furthermore between 55% and 70% of the variation in log of output per worker can be explained by variation in the log input levels, and less than half of the log level output per worker variation is explained by variation in log TFP levels. These results are robust to different time periods, and different parameter values on the human capital accumulation technology. We find positive correlation with micro based cross country estimates of human capital, particularly those provided by Hendricks (2002) and Schoellman (2012)

Economic growth In the long run

We present new data on real output per worker, schooling per worker, human capital per worker, real physical capital per worker for 168 countries. The output data represent all available data from Maddison. The physical capital data represent all available data from Mitchell. One major contribution is a new set of human capital per worker, the foundation of which comes mostly from Mitchell. We provide original estimates of schooling per worker & per young worker. With our preferred measure of human capital, between 66 percent to 90 percent of all the variation in long run growth can be explained by variation in the growth of inputs per worker, and only 10-34 percent from variation in TFP growth! Furthermore between 66 percent and 80 percent of the variation in log levels can be explained by variation in the log input levels and only 20 percent to 34 percent is explained by variation in log TFP levels

Economic growth In the long run

We present new data on real output per worker, schooling per worker, human capital per worker, real physical capital per worker for 168 countries. The output data represent all available data from Maddison. The physical capital data represent all available data from Mitchell. One major contribution is a new set of human capital per worker, the foundation of which comes mostly from Mitchell. We provide original estimates of schooling per worker & per young worker. We find strong support for intergenerational accumulation of human capital with spillovers. With our preferred measure of human capital, over 90 percent of the variation in long run growth can be explained by variation in the growth of inputs per worker, and less than 10 percent from variation in TFP growth. Furthermore between 55% and 70% of the variation in log of output per worker can be explained by variation in the log input levels, and less than half of the log level output per worker variation is explained by variation in log TFP levels. These results are robust to different time periods, and different parameter values on the human capital accumulation technology. We find positive correlation with micro based cross country estimates of human capital, particularly those provided by Hendricks (2002) and Schoellman (2012)