Analysis of Beyond GDP: Welfare across Countries and Time Article by Jones and Klenow Peter - Essay Example

Although different nations have varying prices, measuring their GDPs requires the use of the same prices (Charles and Klenow 7-9). The authors used Rawls's prowess in economics to calculate life expectancy, inequality, and other welfare components (Charles and Klenow 10-11). In constructing welfare over time, Charles and Klenow compared how Rawls valued living in the same country but in different years.

Using Figure 4 and Table 3, they correlated welfare and income growth, as well as, displayed a summary of statistics of the same. Between 1980 and 2000, the US registered an income average growth of 2.04% (Charles and Klenow 23-25). The researchers had to make several assumptions from the Rawls utility functions. They checked the robustness of their calculations using alternative specifications of utility and welfare measures. The alternatives they used held up well to account for the differences between income and welfare (Charles and Klenow 29-34)They used various sources of data to perform their calculations.

Consumption, as well as, income data for macro calculations was sourced from the Penn World Tables and life expectancy data from the World Bank’s HNPStats database. In addition, the inequality data was sourced from the UNU-WIDER World Income Database (Charles and Klenow 12-15). The microdata was of immense importance because it analyzed working hours and consumption rates for adults and older children in households. The data collected from the Household Survey enabled the researchers to calculate consumption inequality rather than creating assumptions from income inequality (Charles and Klenow 38-41).

The researchers, in particular, found out that the living standards of Western European were 71% for income and 90% for welfare compared to the U.S. This is because people in these countries live longer, have equal consumption rates, as well as, a lot of leisure time at their disposal. The developing countries particularly in sub-Saharan Africa have low income and welfare levels. The low welfare and income levels are particularly due to the short life expectancy and inequality (Charles and Klenow 46-50).

The article has a wealth of information that computes GDPs for various countries in comparison to that of the United States of America. I concur with the results of their study that income, life expectancy, and other life experiences differ depending on when one lives. It is expected that the quality of life is low in Asian, Latin American, and African countries is low because of the high levels of inequality and low incomes. It is also not a surprise that the living standards in Western Europe are similar to those in the U.S. due to increased leisure time and low levels of inequality. Their calculation methods are explicit and sources of information are credible.