Was the Wealth of Nations Determined in 1000 B.C.?
Diego Comin, William Easterly, Erick Gong
(dica do Shikida).
We assemble a dataset on technology adoption in 1000 B.C., 0 A.D., and 1500 A.D. 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 A.D.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 countrylevel
factors like culture, genes or institutions.
Post-1500 Population Flows and the Long Run Determinants of Economic Growth and Inequality
Louis Putterman, David N. Weil
We construct a matrix showing the share of the year 2000 population in every country that is descended from people in different source countries in the year 1500. Using this matrix, we analyze how post-1500 migration has influenced the level of GDP per capita and within-country income inequality in the world today. Indicators of early development such as early state history and the timing of transition to agriculture have much better predictive power for current GDP when one looks at the ancestors of the people who currently live in a country than when one considers the history on that country's territory, without adjusting for migration. Measures of the ethnic or linguistic heterogeneity of a country's current population do not predict income inequality as well as measures of the ethnic or linguistic heterogeneity of the current population's ancestors. An even better predictor of current inequality in a country is the variance of early development history of the country's inhabitants, with ethnic groups originating in regions having longer histories of agriculture and organized states tending to be at the upper end of a country's income distribution. However, high within-country variance of early development also predicts higher income per capita, holding constant the average level of early development.
I can not say that the papers deal with the veeery long-run because the brilliant Michael Kremer set a new standard.