We analyze the impact of increasing longevity on technological progress within an overlapping generations research and development (R&D)-based growth framework and test the model's implication on Organization for Economic Co-operation and Development (OECD) data from 1960 to 2011. The central hypothesis is that—by raising the incentives of households to invest in physical capital and in R&D—decreasing mortality positively affects technological progress and productivity growth. The empirical results confirm the theoretical prediction. This implies that the demographic changes we observed in industrialized economies over the last decades were not detrimental to economic prosperity, at least as far as technological progress and productivity growth are concerned.

The process of structural transformation from the farm to a nonfarm sector is accompanied by technological change in both sectors and massive population growth. We investigate the effects of increasing population size (the population effect) and sector-specific productivity (the push and pull effects), both factor-neutral and factor-biased, in a parsimonious general equilibrium model under general forms of utility and production functions. All three effects may co-exist and interact in important ways. Generalizing the agricultural sector production function to CES is crucial for the population growth effect. Our analysis highlights how the relative importance of the three effects changes as the country develops and production and consumption conditions become more flexible.

This study investigates the rates of technological progress, total output growth, and per capita output growth when population growth is negative using a semiendogenous research and development (R&D) growth model. The analysis shows that within a finite time horizon, the employment share of the final goods sector reaches unity and that of the R&D sector reaches zero; accordingly, the rate of technological progress tends toward zero. In this case, the growth rate of per capita output asymptotically approaches a positive value.

We generalize a trade model with firm-specific heterogeneity and R&D-based growth to allow for endogenous education and fertility. The framework is able to explain cross-country differences in living standards and trade intensities by the differential pace of human capital accumulation among industrialized countries. Consistent with the empirical evidence, scale matters for relative economic prosperity as long as countries are closed, whereas scale does not matter in a fully globalized world. The average human capital of a country, by contrast, influences its relative economic prosperity irrespective of trade-openness.

Latin America participated in the electric revolution which profoundly transformed the most developed Western economies between 1880 and 1930. The qualitative empirical evidence shows that Latin American electrification began with little delay compared to those economies. This article provides new quantitative evidence consisting of annual series about a reliable indicator of the degree of electrification of the Latin American nations. The database built shows that towards 1930 electricity consumption per inhabitant in Latin America was far below that of most advanced economies, and only Latin American leaders in the electrification process had reached power consumption levels similar to the European late comers. Unlike other newly industrializing economies, the region was not able to quickly incorporate new technology to overcome their backwardness.

Recently, several researchers have succeeded in producing expectation–driven cycles by balancing the tension between the wealth effect and the substitution effect stemming from the higher expected future productivity. Especially, seminal research by Christiano et al. (“Monetary Policy and Stock Market Boom–Bust Cycles,” mimeo, Northwestern University, 2007), explains “stock market boom–bust cycles,” characterized by increases in consumption, labor inputs, investment, and stock prices relating to high expected future technology levels. We, however, show that such expectation–driven cycles are difficult to generate based on “growth expectation,” which reflects expectations of higher productivity growth rates.

This paper presents a computable general equilibrium model of endogenous (stochastic) growth and cycles that can account for two key features of the aggregate data: balanced growth in the long run and business cycles in the short run. The model is built on Schumpeter's idea that economic development is the consequence of the periodic arrival of innovations. There is growth because each subsequent innovation leads to a permanent improvement in the production technology. Cycles arise because innovations trigger a reallocation of resources between production and R&D. The quantitative implications of the calibrated version of our model are very similar to those of Kydland and Prescott's (1982) model. Moreover, under some parameterizations, our model can correct two shortcomings of RBC models: It can account for the persistence in output growth and the asymmetry of growth within the business cycle.

The objective of the paper is to develop a model of optimal endogenous technological progress that will exhibit two properties sought in growth models: (1) The bias will depend on the parameters of the model—particularly those affecting the cost of inputs—instead of being constrained to be Harrod neutral; (2) factor shares will be constant in steady state. Using previously derived sufficient conditions, we show the conditions under which such a model can be constructed.