Aggregate measures of well-being, England 1781-1850

I went in the field of economic history after I discovered how much it was to properly measure living standards. The issue that always interested me was how to “capture” the multidimensional nature of living standards. After all, what weight should we give to an extra year of life relative to the quality of that extra year (see all my stuff on Cuba)?

However, I never tried to create “a composite” measure of living standards. I thought that it was necessary, first, to get the measurements right. However, I had been aware of the work of Leandro Prados de la Escosura who has been doing considerable work on this in order to create composite measures (Leandro also influenced me on my Cuba reasoning – see this article).

A year ago, I discovered the work of Daniel Gallardo Albarrán from the University of Groningen at the meeting of the Economic History Society (EHS). Daniel’s work is particularly interesting because he is trying to generate a composite measure of well-being at one of the most important moment in history: the start of the British industrial revolution.

Because of its importance and some pieces of contradicting evidence (inequality, stature, amplitude of real wage increases, amplitude of income increases, urban pollution leading to increased mortality risks etc), the period has been begging for some form of composite measure to come along (at least a serious attempt at generating it). Drawing on some pretty straightforward microeconomic theory (the Beckerian in me likes this), Daniel generates this rich graph (see the paper here).


The idea is very neat and I hope it will inspire some economic historians to attempt an expansion upon Daniel’s work. I have already drawn outlines for my own stuff on Canada since I study an era when (from the early 1800s to the mid-1850s) real wages and incomes seem to be going up but stature and mortality are either deteriorating or remaining stable while inequality is clearly increasing.

4 thoughts on “Aggregate measures of well-being, England 1781-1850

  1. This a really cool way to combine factors. Excellent study.

    However, I wanted to comment on the inequality component.

    First, it seems extremely insubstantial (as a negative) compared to the improving factors.

    Second, it assumes inequality of income as measured by the Gini coefficient is a negative. This is not necessarily the case. The paper explicitly refers to this component as a measure of equality of opportunity, but it explicitly is not. It is a measure of equality of outcome regardless of contribution or lack thereof, and is ineffective when incomes vary within lifetimes, during times of immigration, or when demographics such as household size or labor participation changes.

    Third, because of the above factors and others, it is often the case that times of poverty reduction that inequality of annual incomes increases. Inequality as measured here can be a byproduct of improving living standards.

    For the above reasons, I think the paper would have been better without adding inequality into the composite measure. When we aren’t even sure of the sign (positive or negative) adding a measure of it is as a negative just makes the composite less credible.

    But this is a nit, in an overall awesome paper.

  2. I think that for those times, we can say that poverty is more correlated with inequality than today. After all, the contention of many inequality-reduces-growth proponents is that it inequality is a measure of deprivation that limits upwards mobility. I think that we can safely say that unequal and poor societies would be closer to this argument (like 18th century England), albeit not perfectly. At the very least, it corresponds more to this reality than inequality today in England, Canada or the US (where I think the argument is rubbish).

  3. I agree with your ending comment, Vincent, but am not really following the beginning (though in my defense I have yet to drink a cup of coffee this morning).

    If someone believes the abstract statistical mathematical relationship between top earners and the bottom causally limits (or once limited) upward mobility, then they should make that argument. I am pretty sure you and I wouldn’t argue that.

    I could certainly argue that RULE inegalitarianism, would, and has, limited economic growth, and that unequal rules (aka privilege or unfairness) can show up as inequality of income as measured by the Gini.

    But, in general, economic progress has often gone about via a process of some areas blazing a trail and others following or catching up. Inequality rose for two hundred years during the Great Divergence, hence its name. Yet, this modern breakthrough accompanied by massive inequality of outcome was probably the most positive event in the history of the human race.

    I think that in the current intellectual framework or paradigm of modern academia, it is simply assumed, as a given, that inequality of outcome is a negative. I think that is a terrible assumption. Unfairness is a negative thing. Inequality of outcome can be a bad thing or a good thing… it depends. The paper would be even better without just throwing in the Gini and assuming it is a bad.

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