Trend in Hours: The U.S. from 1900 to 1950

During the first half of the 20th century the workweek in the United States declined, and the distribution of hours across wage deciles narrowed. At the same time, the distribution of wages narrowed too. The hypothesis proposed is (i) Households have access to an increasing number of leisure activities which enhance the value of non-market time; (ii) The rise of education accounts for the narrowing of the wage and hours distribution. Such mechanisms, embedded into a neoclassical growth model, quantitatively account for the observations. The rise in wages is the main contributor to the decline in hours. The decline in the price of leisure goods is second in importance, yet its contribution is large.Hours worked, leisure, home production, technological progress

The American Frontier: Technology versus Immigration

What drove western population growth in the U.S. during the 19th century? The facts are: (i) Natural increase was higher in the West than in the East; and (ii) in the early stages of the settlement process, net migration could account for up to 80% of population growth in some regions. A general equilibrium model is proposed, with three ingredients: endogenous fertility, investment in land, and migration. The relative abundance of land in the West promotes higher fertility. The model is simulated. It accounts well for the time-series decomposition of population growth between migration and fertility.Population growth, migration, fertility, westward expansion

Hours Worked: Long-Run Trends

For 200 years the average number of hours worked per worker declined, both in the market place and at home. Technological progress is the engine of such transformation. Three mechanisms are stressed: (i) The rise in real wages and its corresponding wealth effect; (ii) The enhanced value of time off from work, due to the advent of time-using leisure goods; (iii) The reduced need for housework, due to the introduction of time-saving appliances. These mechanisms are incorporated into a model of household production. The notion of Edgeworth-Pareto complementarity/substitutability is key to the analysis. Numerical examples link theory and data. This note has been prepared for The New Palgrave Dictionary of Economics, 2nd edition, edited by Lawrence E. Blume and Steven N. Durlauf (London: Palgrave Macmillan).

A quantitative analysis of China’s structural transformation

Between 1978 and 2003 the Chinese economy experienced a remarkable 5.7 percent annual growth of GDP per labor. At the same time, there has been a noticeable transformation of the economy: the share of workers in agriculture decreased from over 70 percent to less than 50 percent. We distinguish three sectors: private agriculture and nonagriculture and public nonagriculture. A growth accounting exercise reveals that the main source of growth was TFP in the private nonagricultural sector. The reallocation of labor from agriculture to nonagriculture accounted for 1.9 percent out of the 5.7 percent growth in output per labor. The reallocation of labor from the public to the private sector also accounted for a significant part of growth in the 1996-2003 period. We calibrate a general equilibrium model where the driving forces are public investment and employment, as well as sectorial TFP derived from our growth accounting exercise. The model tracks the historical employment share of agriculture and the labor productivities of all three sectors quite well.China

Explaining Educational Attainment across Countries and over Time

Consider the following facts. In 1950 the richest ten-percent of countries attained an average of 8.1 years of schooling whereas the poorest ten-percent of countries attained 1.3 years, a 6-fold difference. By 2005, the difference in schooling declined to 2-fold. The fact is that schooling has increased faster in poor than in rich countries even though the per-capita income gap has generally not decreased. What explains educational attainment across countries and their evolution over time? We develop a model of human capital accumulation that emphasizes productivity and life expectancy differences across countries and time. Calibrating the parameters of the model to reproduce historical data for the United States, we find that the model accounts for 95 percent of the difference in schooling levels between rich and poor countries in 1950 and 78 percent of the increase in schooling over time in poor countries. The model generates a faster increase in schooling in poor than in rich economies even when their income gap does not decrease. These results have important implications for educational policy.Educational attainment, productivity, life expectancy, education policy, labor supply.

Explaining Educational Attainment across Countries and over Time

Consider the following facts. In 1950 the richest ten-percent of countries attained an average of 8.1 years of schooling whereas the poorest ten-percent of countries attained 1.3 years, a 6-fold difference. By 2005, the difference in schooling declined to 2-fold. The fact is that schooling has increased faster in poor than in rich countries even though the per-capita income gap has generally not decreased. What explains educational attainment across countries and their evolution over time? We develop a model of human capital accumulation that emphasizes productivity and life expectancy differences across countries and time. Calibrating the parameters of the model to reproduce historical data for the United States, we find that the model accounts for 95 percent of the difference in schooling levels between rich and poor countries in 1950 and 78 percent of the increase in schooling over time in poor countries. The model generates a faster increase in schooling in poor than in rich economies even when their income gap does not decrease. These results have important implications for educational policy.Educational attainment, productivity, life expectancy, education policy, labor supply.

The Evolution of Education: A Macroeconomic Analysis

Between 1940 and 2000 there has been a substantial increase of educational attainment in the United States. What caused this trend? We develop a model of schooling decisions in order to assess the quantitative contribution of technological progress in explaining the evolution of education. We use earnings across educational groups and growth in gross domestic product per worker to restrict technological progress. These restrictions imply substantial skill-biased technical change (SBTC). We find that changes in relative earnings through SBTC can explain the bulk of the increase in educational attainment. In particular, a calibrated version of the model generates an increase in average years of schooling of 48 percent compared to 27 percent in the data. This strong effect of changes in relative earnings on educational attainment is robust to relevant variations in the model and is consistent with empirical estimates of the long-run income elasticity of schooling. We also find that the substantial increase in life expectancy observed during the period contributes little to the change in educational attainment in the model.educational attainment, schooling, skill-biased technical progress, human capital

The Evolution of Education: A Macroeconomic Analysis

Between 1940 and 2000 there has been a substantial increase of educational attainment in the United States. What caused this trend? Using a simple model of schooling decisions, we assess the quantitative contribution of changes in the return to schooling in explaining the evolution of education. We restrict changes in the returns to schooling to match data on earnings across educational groups and growth in aggregate labor productivity. These restrictions imply modest increases in returns that nevertheless generate a substantial increase in educational attainment: average years of schooling increase by 37 percent in the model compared to 23 percent in the data. This strong quantitative effect is robust to relevant variations of the model including allowing for changes in the relative cost of acquiring education. We also find that the substantial increase in life expectancy observed during the period contributed to only 7 percent of the change in educational attainment in the model.educational attainment, schooling, skill-biased technical progress, human capital

The Baby Boom and Baby Bust

What caused the baby boom? And, can it be explained within the context of the secular decline in fertility that has occurred over the last 200 years? The hypothesis is that: 1. The secular decline in fertility is due to the relentless rise in real wages that increased the opportunity cost of having children. 2. The baby boom is explained by an atypical burst of technological progress in the household sector that occurred in the middle of the last century. This lowered the cost of having children. A model is developed in an attempt to account, quantitatively, for both the baby boom and bust.Baby boom, fertility, technological progress

Measurement Without Theory: A Response to Bailey and Collins

Bailey and Collins (forth.) argue that Greenwood, Seshadri and Vandenbroucke (2005)'s hypothesis that the baby boom was partly due to a burst of productivity in the household sector is not supported by evidence. This conclusion is based upon regression results showing that appliance ownership is negatively correlated with fertility. They also argue that the Amish, who limit the use of modern technology, had a baby boom. First, it is demonstrated that a negative correlation between appliance ownership and fertility can arise naturally in Greenwood et al.'s model. Second, evidence is presented casting doubt upon the presumed technological phobia of the Amish.Amish, appliances, baby boom, Bailey and Collins, fertility, model laboratory, Monte Carlo simulations, regressions