Growth, Income Distribution, And well-Being In Transition Countries

In this paper we use several well-being measures that combine average income with a measure of inequality to undertake international and intertemporal well-being comparisons in transition countries. Our well-being measures drastically change the impression of levels and changes in well-being from a traditional reliance on income measures. They also significantly affect the ranking of countries, when compared to rankings based on real incomes. Due to low inequality and moderate income levels, socialist countries enjoyed relatively high levels of economic well-being. In the transition process, rising inequality and falling incomes have led to a dramatic decline in well-being in many transition countries, and a corresponding worsening in rank when compared to other countries. There is great variance in the income and inequality performance of transition countries. We find a close correlation between income losses and inequality increases suggesting the ability of appropriate policies to reduce the income losses and reduce rising inequality. While the political dimension of transformation remains largely successful, our indicators suggest that most transition countries have yet to reach the level of economic well-being enjoyed in the late 1980s

Using wavelets for time series forecasting: Does it pay off?

By means of wavelet transform a time series can be decomposed into a time dependent sum of frequency components. As a result we are able to capture seasonalities with time-varying period and intensity, which nourishes the belief that incorporating the wavelet transform in existing forecasting methods can improve their quality. The article aims to verify this by comparing the power of classical and wavelet based techniques on the basis of four time series, each of them having individual characteristics. We find that wavelets do improve the forecasting quality. Depending on the data's characteristics and on the forecasting horizon we either favour a denoising step plus an ARIMA forecast or an multiscale wavelet decomposition plus an ARIMA forecast for each of the frequency components. --Forecasting,Wavelets,ARIMA,Denoising,Multiscale Analysis

Growth, Inequality and Well-Being: Comparisons across Space and Time

We use several well-being measures that combine average income with a measure of inequality to undertake international, intertemporal, and global comparisons of well-being. The conclusions emerging from the analysis are that our well-being measures drastically change our impression of levels of well-being of countries. They also significantly affect the ranking of countries, when compared to rankings based on real per capita incomes. These results appear not very sensitive to the data on inequality which this analysis is based upon. However, since the inclusion of inequality has an important impact on well-being comparisons, it is of great importance to generate more consistent and intertemporally as well as internationally comparable data on inequality that are necessary for such comparisons.

Growth, Inequality and Well-Being: Intertemporal and Global Comparisons

We use several well-being measures that combine average income with a measure of inequality to undertake intertemporal and global comparisons of well-being. The conclusions emerging from the intertemporal analysis are that the impact of these measures on temporal trends in well-being is relatively small on average, but changing across the decades. In particular, it suggests that changes in well-being were understated in the 1960s and 1970s and overstated in the 1980s and 1990s. Our global analysis covering ca. 81 per cent of the world’s population demonstrates that global well-being is at least 50 per cent smaller than world per capita income if the unequal income distribution is also factored in. Conversely, growth in world well-being has been larger than world income growth between 1970-1998. Since the inclusion of inequality has an important impact on well-being comparisons, it is of great importance to generate more consistent and intertemporally as well as internationally comparable data on inequality.

Growth, Inequality and Well-Being: Comparisons across Space and Time

We use several well-being measures that combine average income with a measure of inequality to undertake international, intertemporal, and global comparisons of well-being. The conclusions emerging from the analysis are that our well-being measures drastically change our impression of levels of well-being of countries. They also significantly affect the ranking of countries, when compared to rankings based on real per capita incomes. These results appear not very sensitive to the data on inequality which this analysis is based upon. However, since the inclusion of inequality has an important impact on well-being comparisons, it is of great importance to generate more consistent and intertemporally as well as internationally comparable data on inequality that are necessary for such comparisons.

Has transition improved well-being? An analysis based on income, inequality-adjusted income, nonincome, and subjective well-being measures

In this paper we examine trends in economic well-being in transition countries from 1988-2002. To do this, we examine economic performance, inequality-adjusted well-being measures, subjective well-being measures, and non-income dimensions of well-being. While for some of the transition countries in Central Europe, the level of well-being is now higher than prior to transition, it is far below those levels in most other transition countries. The only indicator which has shown consistent improvements are measures of political and civil liberties.

Growth, Inequality, and Well-Being: Intertemporal and Global Comparisons

We use several well-being measures that combine average income with a measure of inequality to undertake intertemporal and global comparisons of well-being. The conclusions emerging from the intertemporal analysis are that the impact of these measures on temporal trends in well-being is relatively small on average, but changing across the decades. In particular, it suggests that changes in well-being were understated in the 1960s and 1970s and overstated in the 1980s and 1990s. Our global analysis covering ca. 81 per cent of the world’s population demonstrates that global well-being is at least 50 per cent smaller than world per capita income if the unequal income distribution is also factored in. Conversely, growth in world well-being has been larger than world income growth between 1970-1998. Since the inclusion of inequality has an important impact on well-being comparisons, it is of great importance to generate more consistent and intertemporally as well as internationally comparable data on inequality.

Growth, Income Distribution, and Well-Being: Comparisons across Space and Time

We use several well-being measures that combine average income with a measure of inequality to undertake international, intertemporal, and global comparisons of well-being. The conclusions emerging from the analysis are that our well-being measures drastically change our impression of levels of well-being at the national and, more so, at the global level. They also significantly affect the ranking of countries, when compared to rankings based on real incomes. The impact on these measures on temporal trends in well-being is smaller on average, but significant for a number of countries where inequality changed considerably in past decades. These results appear not very sensitive to the data on inequality which this analysis is based upon. However, since the inclusion of inequality has an important impact on wellbeing comparisons and it is of great importance to generate more consistent and intertemporally as well as internationally comparable data on inequality that are necessary for such comparisons.

Growth, Income Distribution, And well-Being In Transition Countries

In this paper we use several well-being measures that combine average income with a measure of inequality to undertake international and intertemporal well-being comparisons in transition countries. Our well-being measures drastically change the impression of levels and changes in well-being from a traditional reliance on income measures. They also significantly affect the ranking of countries, when compared to rankings based on real incomes. Due to low inequality and moderate income levels, socialist countries enjoyed relatively high levels of economic well-being. In the transition process, rising inequality and falling incomes have led to a dramatic decline in well-being in many transition countries, and a corresponding worsening in rank when compared to other countries. There is great variance in the income and inequality performance of transition countries. We find a close correlation between income losses and inequality increases suggesting the ability of appropriate policies to reduce the income losses and reduce rising inequality. While the political dimension of transformation remains largely successful, our indicators suggest that most transition countries have yet to reach the level of economic well-being enjoyed in the late 1980s.