I do not use growth rates of GDP, but levels of GDP per capita as exogenous variable. This procedure is advised in macroeconomic analysis in order to avoid the kind of estimation bias that Barro and Sala-i-Martin (1995), for example, are confronted with when estimating the impact of female education on growth. Chapter 1 shows that Barro and Sala-i-Martin (1995) falsely find a negative impact of female education on growth, mainly because they use GDP growth rates instead of GDP levels as endogenous variables. We know from Solow (1956) that the higher the GDP levels of a country are, the lower are the yearly GDP growth rates (convergence mechanism). Hence, as poor countries have higher gender differences in education than countries with high levels of GDP, Barro and Sala-i-Martin’s estimation model falsely interpret low female education as growth promoting.
In order to capture proportional rather than absolute differences in the distribution of GDP levels, I use the natural logarithm of GDP per capita (lnGDP), which is standard in most macro-econometric works as seen in chapter I. The natural logarithm of GDP does not
represent the growth rate of GDP. Only the difference of the natural logarithm
(lnGDPt - lnGDPt-1 ) would approximate the year to year relative changes in GDP
( (GDPt - GDPt-1) / GDPt-1 ). The national logarithm reduces absolute increases in the GDP
levels.
GDP observations are the countries’ yearly GDP per capita (in constant 2000 US$). The gross domestic product per capita at purchaser prices is defined as the sum of the gross value added by all resident producers in the economy, plus any product taxes, less any subsidies not included in the value of the products, divided by the number of inhabitants.23 It is calculated without deductions for depreciation of fabricated assets or for depletion and degradation of natural resources.
Data on GDP per capita (in constant 2000 US$) are drawn from the World Bank’s World Development Index Data Base (2006). The data covers the years 1965 to 2004 for 184 countries. The 5966 observations of lnGDP range from 4,03 to 10,88 (see table 10), implying that yearly GDP per capita varies between 56,52 US$ and 52.943,34 US$ with a mean of 5.179,46 US$. The observations are distributed quite evenly over the years and over the countries.
Just as female labour market participation insufficiently represents women’s empowerment, GDP per capita insufficiently represents a nation’s welfare, not to mention a nation’s well- being or standard of living. First of all, measures of GDP discount the non-monetary economy and hence do not consider unpaid productive activities like voluntary work, domestic work and subsistence production. The evaluation and measurement of women’s housework is a difficult task, because housework, raising children and caring for family members is viewed as the opposite of market work and hence is not assigned an economic value. Only in a few countries, mainly in industrialised countries like Germany for example, there exist estimations of the equivalent value of housework (for Germany: time budget studies by the German Federal Statistical Office, available for the years 1991and 2001). Would all men and women dedicate equally many hours to housework and caring, it would suffice to measure GDP to capture differences in economic development across countries. As this is not the case, GDP is not an ideal measure of economic activity. Furthermore, GDP measures leave aside black market activities. These unaccounted activities bias income measures downward. Another consequence arising from these unrecorded activities is that GDP increases when non market production becomes marketable. This market shift biases measures of GDP upwards, for example when meals or other products that used to be made
at home are now sold at the market as semi-finished or finished products. Moreover, GDP as an indicator of a nation’s welfare is often criticised because it only reflects average national income, but does not indicate income distribution or expenditure patterns. GDP also ignores the quality of goods (durability) and negative externalities of growth such as the damage to the environment. As GDP assumes that if there were more goods in circulation, general welfare would automatically increase, GDP growth does not account for sustainability. Nobel Prize winner Joseph E. Stiglitz, for example, sees GDP as an imperfect indicator of a nation’s welfare because improvements in the quality of life, which do not show up in material consumption, do not increase GDP.
In order to take into account other determinants of well being, various kinds of “quality of life” indices have been developed recently. The most influential indicator is the Human Development Index (HDI), which was introduced by the United Nations Development Program in its annual Human Development Report in 1995. Ideas of Nobel Prize winner Amartya Sen were influential in the development of this indicator. The HDI combines normalised measures of life expectancy, knowledge (literacy and educational attainment) and living standard (GDP per capita in PPP US$). The use of the Purchasing Power Parity (PPP) takes into account the countries’ different price levels and converts the data into a common currency. The PPP can be a better indicator of living standards, especially of less- developed countries, because it compensates for the weakness of local currencies in world markets. A comparison of a country’s GDP and HDI can reveal a country’s policy choices. For example, Oman is a country with a relatively high GDP per capita, but has a relatively low HDI due to its relatively low level of average educational attainment. (c.f. UNDP, 1995). Yet, as even the HDI’s information value is limited, further research is made in the field of measuring “quality of life”, or even “happiness”, which is assumed to correspond to the freedom to make personal choices. In 2007, French President Nicolas Sarkozy appointed Joseph E. Stiglitz to head a commission to find a new method of economic calculation that will include quality-of-life factors such as personal freedom, livelihood, compassion and sharing and that will make more room for moral and ethical values, including social and environmental concerns.24
Today, the new indices are becoming a tool for judging the true wealth of nations, but due to limited data availability they rather enhance than replace GDP as a measure of a country’s well-being. The HDI is available from 1975 on, but not before 1975. In order to keep the data set large (with early observations from the 1960s on and from over 180 countries), I concentrate on GDP per capita as indicator for economic development, which is still the
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standard measure of welfare in economics. The major advantages to using GDP per capita as an indicator of standard of living are that it is measured frequently and widely. Furthermore, the technical definitions used within GDP are relatively consistent between countries. In addition, my empirical investigation of the “feminisation U” hypothesis, based on panel data, is directly linked to the cross country studies by Goldin (1994) and Cagatay and Ötzler (1995) discussed in the previous chapter, which use income levels instead of more complex welfare measures as growth indicators. Hence, my adherence to GDP per capita is mainly due to superior comparability of research results.