Toolkit for measuring quality of life under spatial frictions

(c) Gabriel M. Ahlfeldt, Fabian Bald, Duncan Roth, Tobias Seidel

General remarks

This toolkit implements a numerical solution algorithm to invert unobserved quality of life from observed data in various programming languages. The intuition is that, in spatial equilibrium, individuals will accept higher real living cost (taking into account differences living costs and wages) if the quality of life a city offers is greater. Unlike previous measures, our measure accounts for trade (trade costs and local services) and mobility (local ties and idiosyncratic tastes) frictions. Notice that quality of life is identified up to a constant. Therefore, the inverted QoL measures measure has a relative interpretation only. We normalize the QoL relative to the first observation in the data set. It is straightforward to rescale the QoL measure to any other location or any other value (such as the mean or median in the distribution of QoL across locations). For more information, we refer to our working paper.

The toolkot is available from GitHub in MATLAB, Stata, R, and Python. To install the Stata ado file version, simply type "ssc install ABRSQOL" (use "help ABRSQOL" for the syntax).

Application

The results of an application or our new approach to measuring the quality of life for German cities can be viewed below. Bar height is proportionate to current quality of life. Arrows indicate the change since 2007.