In growth theory, changes in output (GDP) are explained through changes of production factors, i.e. changes in labour or capital. Economists consider the residual, i.e. the part of changes in output that one cannot explain with changes of production factors, as total factor productivity (TFP) or technological change. In contrast to labour productivity, that relates output only to labour, total factor productivity states how efficiently an economy uses all its production factors. Continue reading What is Total Factor Productivity (TFP)?

# What is Labour Productivity?

Newspapers, and in particular economists frequently talk about labour productivity. Especially when commenting the current state of the economy, labour productivity is of central concern. This post will explain the concept of labour productivity and highlight its importance in the context of business cycle analysis. Continue reading What is Labour Productivity?

# Review: The Conscience of a Liberal

In *The Conscience of a Liberal*, Paul Krugman provides a compelling explanation for the recent increase of inequality in the United States. In contrast to the widely believed idea that is was globalization that caused the increase in inequality, he argues that Continue reading Review: The Conscience of a Liberal

# Review: Hillbilly Elegy

Hillbilly Elegy is a tale of social decay. In an absorbing and fascinating manner, J.D. Vance outlines different episodes of his life that go along with the social decline of the white middle-class in the Midwest. In an impressive fashion, Continue reading Review: Hillbilly Elegy

# Difference between liberal and progressive

In the past, I had a lot of difficulties to understand the difference between liberal and progressive. In fact, I was convinced, and actively used the word *progressive* as a synonym for the word *liberal*. Continue reading Difference between liberal and progressive

# The Gini Coefficient

The Gini Coefficient is often used an indicator of inequality in a country. Additionally, one can also use the Gini Coefficient as an indicator of economic development. The Gini Coefficient is based on the Lorenz Curve and measures the degree of income or wealth inequality in an economy. The coefficient is bound between zero and one. This means that the coefficient can take on values between zero and one. A Gini Coefficient of one states complete inequality. That is, one single person receives all the income or holds all the wealth of the economy, while all others receive or own nothing. A Gini Coefficient of zero implies perfect equality. That is, all individuals obtain the same income. See the discussion of the Lorenz Curve for a clear illustration of the concept. Continue reading The Gini Coefficient

# Linear Regression in STATA

In STATA one can estimate a linear regression using the command ` regress`

. In this post I will present how to use the STATA function `regress`

to run OLS on the following model

# How to compute the Lorenz Curve

In contrast to our previous post, that is the post that summarized the Lorenz Curve in general terms, this post details how to construct the Lorenz Curve and provides a hypothetical example in R.

# The Lorenz Curve

The Lorenz Curve displays the actual income or wealth distribution of an economy. The concept was brought up by the American economist Max O. Lorenz in 1905. The curve represents a graphical representation of the income or wealth distribution of an economy or country. That is, it shows the proportion of income earned or wealth possessed by any given percentage of the population. In the case that everyone has approximately the same wealth, we have a very equal society. While in a case where few own the majority of wealth, we have high inequality. The following figure depicts the Lorenz curve for three economies with varying degrees of inequality.

# Cluster Robust Standard Errors in Stargazer

In a previous post, we discussed how to obtain clustered standard errors in R. While the previous post described how one can easily calculate cluster robust standard errors in R, this post shows how one can include cluster robust standard errors in stargazer and create nice tables including clustered standard errors.

Continue reading Cluster Robust Standard Errors in Stargazer