One of the fundamental questions of economics is why are some countries rich and others poor? Why do some countries experience heavy growth which allows them to catch-up with the economic giants of the world, whilst others are relegated to the bottom and are unable to jump on the growth train? Is it due to luck, geography, culture or institutional factors? This article explains some of the different theories of economic growth, beginning with the Solow growth model (neoclassical model), before criticising such a model and suggesting that endogenous growth models have more to tell us about the growth phenomenon. We highlights the pitfalls of each model, but conclude that the main reason that incomes are different between countries is due to institutional differences. [...]
Development accounting is the manipulation of a production function to examine whether cross-country income differences arise from differences in total factor productivity (TFP), or due to factor accumulation. It is useful to find this information out so that we can correctly inform policy decisions and let developing countries know if they need to simply increase quantity of factors of production (i.e. promote higher fertility, immigration, labour market inclusion and capital appreciation), whether they need to increase the quality of the factors of production (better education and more efficient use of investment funds) or if they need to increase efficiency and technological adoption.
The most important macro externality that high fertility can have is its effect on economic development. If high fertility leads to more rapid economic growth and development then we may consider the externality positive, if not we would say it is negative. This works if we consider the mortality rate to be below high fertility, such that high fertility means high population growth.
According to Prescott the reason for business cycles is due to technology shocks which manifest itself as changes in the TFP productivity term (or Solow residual) A. Summers criticises this explanation believing that Prescott doesn’t provide evidence for where these technology shocks come to. Furthermore he cites Berndt who shows that the oil shock crisis – recessionary periods in the 1970s for both the US and the UK – had little effect on labour productivity which would cast doubt on Prescott’s story. Summers also points out that US GNP declined by 50% between 1929 and 1933, and questions whether it is really plausible that such an output shock could be caused by a productivity shock which lead to inter-temporal substitution on such a scale, as Prescott’s model would predict.