HDI measures average achievement in three dimensions: Health (life expectancy at birth), Education (expected years of schooling and mean years of schooling for adults), and Standard of Living (gross national income per capita). It is the geometric mean of normalized indices for each dimension.
PPPs are indicators of price level differences across countries used to convert national currencies into an artificial common currency (Purchasing Power Standard, PPS) for accurate comparisons of living standards.
Long-term growth is estimated using Ordinary Least Squares (OLS) regression of the natural logarithm of per capita GDP on time, where the cumulative annual growth rate is approximately the regression coefficient.
What are the main explanatory factors of long-term economic growth?
Productivity and Innovation. Productivity, including Total Factor Productivity (TFP), and Innovation are essential for enhancing productivity and long-term economic growth.
What are the key metrics for assessing economic growth?
Key metrics include Per Capita Income (GDP / Population), Labour Productivity (GDP / Employment), Employment Rate (Employment / Population aged 16-64), and Demographic Factor (Population aged 16-64 / Total Population).
HDI trends in the EU show variations in human development levels across different countries and provide a mean HDI value for the EU27, segmented by development levels and compared globally.
Why is adjusting for purchasing power and inflation important in measuring GDP?
Adjusting for purchasing power and inflation ensures that GDP comparisons across countries and over time reflect real differences in living standards and economic performance, not just price level changes.
What is the importance of innovation in economic growth?
Innovation is crucial for enhancing productivity, which in turn drives long-termeconomic growth by improving efficiency and creating new products and markets.
How does the confidence interval for a coefficient in a regression model inform us?
A confidence interval provides a range within which the true value of the coefficient is likely to fall. If the interval does not include zero, the coefficient is significantly different from zero at the given confidence level.
R² represents the proportion of the variance in the dependent variable that is predictable from the independent variable(s). In this context, an R² of 0.06 means 6% of the variance in savings is explained by annual income.