How much technological progress has there been in structures? An attempt is made to measure this using panel data on the age and rents for buildings. This data is interpreted through the eyes of a vintage capital model where buildings are replaced at some chosen periodicity. There appears to have been significant technological advance in structures that accounts for a major part of economic growth.

This paper develops a unified model of growth, population, and technological progress that is consistent with long-term historical evidence. The economy endogenously evolves through three phases. In the Malthusian regime, population growth is positively related to the level of income per capita. Technological progress is slow and is matched by proportional increases in population, so that output per capita is stable around a constant level. In the post-Malthusian regime, the growth rates of technology and total output increase. Population growth absorbs much of the growth of output, but income per capita does rise slowly. The economy endogenously undergoes a demographic transition in which the traditionally positive relationship between income per capita and population growth is reversed. In the Modern Growth regime, population growth is moderate or even negative, and income per capita rises rapidly. Two forces drive the transitions between regimes: First, technological progress is driven both by increases in the size of the population and by increases in the average level of education. Second, technological progress creates a state of disequilibrium, which raises the return to human capital and induces parents to substitute child quality for quantity.

The process by which per capita income in the South converged to northern levels is intimately related to the structural transformation of the U.S. economy. We find that empirically most of the southern gains are attributable to the nation-wide convergence of agricultural wages to non-agricultural wages, and the faster rate of transition of the Southern labor force from agricultural to non-agricultural jobs. Similar results describe the Mid-West's catch up to the North-East (but not the relative experience of the West). To explain these observations, we construct a model in which the South (Mid-West) has a comparative advantage in producing unskilled-labor intensive agricultural goods. Thus, it starts with a disproportionate share of the unskilled labor force and lower per capita incomes. Over time, declining education/training costs induce an increasing proportion of the labor force to move out of the (unskilled) agricultural sector and into the (skilled) non-agricultural sector. The decline in the agricultural labor force leads to an increase in relative agricultural wages. Both effects benefit the South (Mid-West) disproportionately since it has more agricultural workers. The model successfully matches the quantitative features of the U.S. structural transformation and regional convergence, as well as several other stylized facts on U.S. economic growth in the last century. The model does not rely on frictions on factor mobility, since in our empirical work we find this channel to be less important than the compositional effects the model emphasizes.

A number of theoretical models of technology adoption have been proposed that emphasize technological switching, loss of expertise and subsequent technology-specific learning. These models imply that measured productivity may initially fall and then later rise after the adoption of a new technology. This paper investigates whether or not this implication is a feature of plant-level data from the Colombian manufacturing sector. We regress measures of productivity growth at the plant level on a plant-specific measure of technology adoption and its lagged values. We find that...

This paper presents a model in which a country's average propensity to save tends to rise endogenously over time. The paper uses a two-sector neoclassical framework to model the transition from agriculture to manufacturing which typically accompanies economic development. Key assumptions are that only the agricultural sector uses land and a simple version of Engel's law. When a country's income per capita is low, agricultural consumption is important; consequently, land is valuable and capital gains on it may account for most wealth accumulation, making the NIPA APS appear low. If exogenous technological progress raises incomes over time, Engel's law shifts demand to manufactured goods. Then land's importance in portfolios relative to reproducible capital diminishes and the measured average propensity to save can rise.