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).

Daniel

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.

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On 19th Century Tariffs & Growth

A few days ago, Pseudoerasmus published a blog piece on Bairoch’s argument that in the 19th century, the countries that had high tariffs also had fast growth.  It is a good piece that summarizes the litterature very well. However, there are some points that Pseudoerasmus eschews that are crucial to assessing the proper role of tariffs on growth. Most of these issues are related to data quality, but one may be the result of poor specification bias. For most of my comments, I will concentrate on Canada. This is because I know Canada best and that it features prominently in the literature for the 19th century as a case where protection did lead to growth. I am unconvinced for many reasons which will be seen below.

Data Quality

Here I will refrain my comments to the Canadian data which I know best. Of all the countries with available income data for the late 19th century, Canada is one of those with the richest data (alongside the UK, US and Australia). This is largely thanks to the work of M.C. Urquhart who recreated the Canadian GNP series fom 1870 to 1926 in collaborative effort with scholars like Marvin McInnis, Frank Lewis, Marion Steele and others.

However, even that data has flaws. For example, me and Michael Hinton have recomputed the GDP deflator to account for the fact that its consumption prices component did not include clothing. Since clothing prices behaved differently than the other prices from 1870 to 1885, this changes the level and trend of Canadian incomes per capita (this paper will be completed this winter, Michael is putting the finishing touch and its his baby).  However, like Morris Altman, our corrections indicate a faster rate of growth for Canada from 1870 to 1913, but in a different manner. For example, there is more growth than believed in the 1870-1879 period (before the introduction of the National Policy which increased protection) and more growth in the 1890-1913 period (the period of the wheat boom and of easing of trade restrictions).

Moreover, the work of Marrilyn Gerriets, Alex Chernoff, Kris Inwood and Jim Irwin (here, here, here, here) that we have a poor image of output in the Atlantic region – the region that would have been adversely affected by protectionism. Basically, the belief is a proper accounting of incomes in the Atlantic provinces would show lower levels and trends that would – at the national aggregated level – alter the pattern of growth.

I also believe that, for Quebec, there are metrological issues in the reporting of agricultural output. The French-Canadians tended to report volume units in manners poorly understood by enumerators but that these units were larger than the Non-French units. However, as time passed, census enumerators caught on and got the measures and corrections right. However, that means that agricultural output from French-Canadians was higher than reported in the earlier census but that it was more accurate in the later censuses. This error will lead to estimating more growth than what actually took place. (I have a paper on this issue that was given a revise and resubmit from Agricultural History). 

Take all of these measurements issue and you have enough doubt in the data underlying the methods that one should feel the need to be careful. In fact, if the sum of these (overall) minor flaws is sufficient to warrant caution, what does it say about Italian, Spanish, Portugese, French, Belgian, Irish or German GDP ( I am not saying they are bad, I am saying that I find Canada’s series to be better in relative terms).

How to measure protection?

The second issue is how to measure protection. Clemens and Williamson offered a measure of import duties revenue over imports volume. That is a shortcut that can be used when it is hard to measure effective protection. But, it may be a dangerous shortcut depending on the structure of protection.

Imagine that I set an import duty so high as to eliminate all entry of the good taxed (like Canada’s 300% import tax on butter today). At that level, there is zero revenue from butter import and zero imports of butter. Thus, the ratio of protection is … zero. But in reality, its a very restrictive regime that is not being measured.

More recent estimates for Canada produced by Ian Keay and Eugene Beaulieu (in separate papers, but Keay’s paper was a conference paper) attempted to measure more accurate indicators of protection and the burden imposed on Canadians. Beaulieu and his co-author found that using a better measure, Canada’s trade policy was 11% more restrictive than believed. Moreover, they found that the welfare loss kept increasing from 1870 to 1890 – reaching a figure equal to roughly 1.5% of GDP (a non-negligible social cost).

It ought to be noted though that alongside Lewis and Harris, Keay has found that the infant industry argument seems to apply to Canada (I am not convinced, notably for the reasons above regarding GDP measurements). However, that was in the case of Canada only and it could have been a simple outlier. Would the argument hold if better trade restriction measures were gathered for all other countries, thus making Canada into a weird exception?

James Buchanan to the rescue

My last argument is about political economy. Was the institutional arrangement of protection a way to curtail government growth? Protection is both a method for helping national industries and for raising revenues. However, the government cannot overprotect at the risk of loosing revenues. It must protect just enough to allow goods to continue entering to earn revenues from imports.  This tension is crucial especially since most 19th century countries did not have uniform general tariffs (like a flat 5% import duty) which would have very wide bases. The duties tended to concern a few goods very heavily relative to other goods. This means very narrow tax bases.

Standard public finance theory mandates wide tax bases with a focus on inelastic sources. However, someone with a public choice perspective (like James Buchanan) will argue that this offers the possibility for the government to grow. Basically, a public choice theorist will argue that the standard public finance viewpoint is that the sheep is tame. Self-interested politicians will exploit this tameness to be elected and this might imply growing government. However, with a narrow and elastic tax base, politicians are heavily constrained. In such a case, governments cannot grow as much.

The protection of the 19th century – identified by many as a source of growth – may thus simply be the symptom of an institutionnal arrangement that was meant to keep governments small. This may have stimulated growth by keeping other sectors of the economy more or less free of government meddling. So, maybe protection was the offspring of the least flawed institutional arrangement that could be adopted given the political economy of the time.

This last argument is the one that I find the most convincing in rebuttal to the Bairoch argument. It means that we are suffering from a poor specification bias: we have identified a symptom of something else as the cause of growth.

On Cuba’s Fake Stats

On Monday, my piece on the use violence for public health purposes in Cuba (reducing infectious diseases through coercion at the expense of economic growth which in turn increases deaths from preventable diseases related to living standards) assumed that the statistics were correct.

They are not! How much so? A lot! 

As I mentioned on Monday, Cuban doctors face penalties for not meeting their “infant mortality” targets. As a result, they use extreme measures ranging from abortion against the mother’s will to sterilization and isolation.  They also have an incentive to lie…(pretty obvious right?)

How can they lie? By re-categorizing early neonatal (from birth to 7th day) or neonatal deaths (up to 28th day) as late fetal deaths. Early neonatal deaths and late fetal deaths are basically grouped together at “perinatal” deaths since they share the same factors. Normally, health statistics suggest that late fetal deaths and early neonatal deaths should be heavily correlated (the graph below makes everything clearer).  However late fetal deaths do not enter inside the infant mortality rates while the early neonatal deaths do enter that often-cited rate (see graph below).

Death Structures.png

Normally, the ratio of late fetal deaths to early neonatal deaths should be more or less constant across space. In the PERISTAT data (the one that best divides those deaths), most countries have a ratio of late fetal to early neonatal deaths ranging from 1.04 to 3.03. Cuba has a ratio of more than 6. This is pretty much a clear of data manipulation.

In a recent article published in Cuban Studies, Roberto Gonzales makes adjustments to create a range where the ratio would be in line with that of other countries. If it were, the infant mortality of Cuba would be between 7.45 and 11.16 per 1,000 births rather than the 5.79 per 1,000 reported by the regime – as much as 92% higher. As a result, Cuba moves from having an average infant mortality rate in the PERISTAT data to having the worst average infant mortality in that dataset – above that of most European and North American countries.

So not only is my comment from Monday very much valid, the “upside” (for a lack of a better term) I mentioned is largely overblown because doctors and politicians have an incentive to fake the numbers.

On the Canadian economy: the “real” problem

In Canada, the state of the economy has everyone worried. The fall in oil prices is causing the oil sector in the western provinces and in some of the Atlantic provinces to contract. As a result, everyone has the impression that Canada is sliding towards a recession and governments should act.

I disagree. My disagreement is fueled by two factors. The first is that we should never reason from a price change. The fall in the price of oil is mostly the result of increasing supply of oil. Such a price change is actually a good thing for the Canadian economy. The slowdown in economic activity is merely the result of frictions in the reallocation of resources. The second reason is that the slowdown is caused by “real factors” – policy decision affecting key regions of the Canadian economy. Any government action would worsen a situation caused by too much interference in the first place.

A fall in oil prices can indeed affect the Canadian economy. The oil produced in Canada is generally profitable when prices are relatively high (they require very capital-intensive methods of extraction and refining). An increase in the world oil supply (which is the case right now) would indeed affect the Canadian oil industry. However, Canadians win through lower oil prices – one important input has gotten cheaper. The problem is that once such a slowdown happens, resources are not reallocated without frictions. Business plans are positively affected by the lower oil prices and numerous firms are laying out new plans to expand production. Employment and output will fall in the oil industry before they will pick up in other industries. Eventually, there might even be greater output and employment because of the greater worldwide supply of oil. Right now, Canada is in-between those two situations.

My second reason for dissenting from the majority opinion is that certain regions of the Canadian economy are plagued by poor policy. To make my argument, consider a two-region (West and East) and two-industry economy (oil and manufacturing/services). In the West, the dominant industry is oil. In the East, the dominant industry is manufacturing/services.  The West economy has a more flexible market for inputs (limited regulation, freer labor market and low taxes on capital). The East economy suffers from greater rigidity in its market for inputs – high taxes, burdensome regulation and stringent labor laws.

In a way, this describes the Canadian economy. The provinces of Alberta, Saskatchewan, Manitoba and British-Columbia have been pulling the rest of the Canadian economy for the last twenty years. That’s the West. In the East, the historically poorer province of Quebec has been constantly pulling everyone behind, but less so in recent years as the province of Ontario (the most populous of Canadian provinces) began to slow down. Ontario dramatically expanded the size of its public sector, implemented important regulations and raised taxes – straight in the middle of the recession. In fact, if you exclude Ontario from the rest of Canada, you find (as Philip Cross did) that Canada’s performance is actually quite decent. So in the East, you have Quebec whose policies have not changed and you have Ontario who has adopted increasingly anti-growth policies. The East also has consistently higher taxes. The West has lower taxes. Etc.

Given the accuracy of this stylized description, imagine the effect of a shock on the western economy through a shock on its oil industry. Normally, firms in the East could adapt to lower oil prices by expanding their output in the manufacturing/services sector (thanks to cheaper inputs) while firms in the West contract their output and liberate inputs. However, in the presence of government-imposed frictions, this reallocation of resources is much harder and output has a harder time expanding in the East.

No demand-side policy can solve this problem! You could have easy money and a massive stimulus program, but if firms are discouraged from increasing output, little will happen. In Canada, the current slowdown is explained by “real factors”. Improving provincial policies would be the best channel for improving the state of the Canadian economy.

Can we use tax data to measure living standards (part 2)?

Yesterday, my post on the differences in per capita income and total income per tax unit caused some friends to be puzzled by my results. To their credit, the point can be defended that tax units are not the same as households and the number of tax units may have increased faster than population (example: a father in 1920 filled one tax unit even though his household had six members, but with more single households in the 1960s onwards the number of tax units could rise faster than population for a time).

The problems regarding the use of tax units instead of households is not new. In fact, it is one of the sticking point advanced by skeptics like Alan Reynolds (see his 2006 book) and, more recently, by Richard Burkhauser of Cornell University (see his National Tax Journal article here).

Could it be that all the differences between GDP per person and income per tax unit are caused by this problem? Not really.

There is an easy to see if the problem is real. Both measures are ratios (income over a population). Either the numerator is wrong or the denominator is wrong. Those who view tax units as the problem argue that the problem is the denominator. I do not agree since I believe that the numerator is at fault. The way to see this is simply to plot total income reported by all tax units and compare this with real GDP. What’s the result?

Even with tax-reported income being deflated with the Implicit Price Deflator (IPD) instead of the consumer price index, we end up with a difference (in 2013) of roughly 3 orders of magnitude between GDP and tax-reported income relative to the 1929 base point. Basically, GDP has increased by a factor of 14.749 since 1929 while IPD-deflated tax-reported income has only increased by a factor of 11.546.

TaxData

As a result, I do not believe that the problem is the tax unit issue. The problem seems to be that tax data is not capturing the same thing as GDP is!