the ideal scenario that is unlikely to occur. Thus, the main focus of this paper will be on conditional convergence. This paper will carry out a cross-country analysis of 86 countries over the period 1960-2005, in order to evaluate whether there is empirical evidence of conditional convergence. The next chapter will look at the basic Solow model and introduce the key variables which will be used to carry out the empirical analysis later in the paper. Chapter 3 discuss a number of additional variables that have been identified in the growth literature and which could affect the dynamics of the model and assess to what extent these variables are important for the main discussion. After that, chapter 4 will outline the data and the methodology used. Chapter 5 will continue the detailed outline of the model. After which, Chapter 6 will proceed with a discussion of the results. Finally, chapter 7 concludes by summarizing the main results and outlining some possible future research opportunities. Chapter 2 Economic growth and convergence, the Solow model Some of the differences in economic growth are associated with the initial conditions prevailing in the country. The position in 1960 depends on things such as political stability of the country, demographic developments, issues of nutrition, child mortality rates, number of patients per doctor, etc. However, it is very difficult to represent all of these conditions at once. In this paper, as it is standard in the literature, the initial level of GDP per worker will be used as a representation of the initial position of the country. 2.1 The basic Solow model The predecessor of most of today’s growth models, even if they are not directly drawn from it, is the Solow model. This model is also known as the Solow-Swan model, and was first introduced in 1956. Although, it is a simple model, the Solow model has a number of advantages. Earlier models did not distinguish between old and new technology, simply looking at the two types as one. Solow, on the other hand, was the first economist to distinguish between current and ‘old’ technology, by giving
The natural resource augmented Solow model states that the larger the amount of natural resources, the more growth the country should experience. In this case, the model uses the natural resources of a country to see whether there is any impact of natural resources on the convergence hypothesis. The data set used is obtained from the World Bank Wealth Estimates, 2005. The value of subsoil assets is used as a proxy for natural resource abundance within a country. The data obtained is based on the total amount of resources available, thus, it was divided by the working population to evaluate the effects that natural resources have on the country’s growth. As the wealth estimates only provide data for one specific year, 2005 in this case, it must be used as a proxy for natural resources. 4.3 Country Classifications To out the analysis for separate groups of countries, we have constructed six dummy variables which refer specifically to a classification of the data: Low income, Middle income, High Income, Non-oil, Intermediate and OECD. The latter two variables, Non-oil and OECD, are taken as given using the paper of Mankiw et al. (1992). The paper classified three sets of countries: Non-oil, Intermediate and OECD. The classification is as follows. The classification of the country groups are based on different criteria, which are outlined below. Non-oil countries There are a number of countries for which oil production is the dominant industry. This implies that the large percentage of GDP comes from oil production and sale. Oil is an important market throughout the world. The prices of oil are very volatile and can affect not only the GDP per worker, but also numerous other economic factors, such as trade and saving and investment rates. Thus, in order to exclude the oil bias from the data, we have introduced a non-oil dummy. There are a number of different classifications of oil producing and exporting countries. In this, case, however, we used the same classification as the paper of Mankiw, et al. (1992). In their case, the oil producing country is defined as a country, for which oil production is a dominant industry in 1960. The sample of non-oil producers consists of 78 countries. Intermediate countries
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