Malthusian Dynamics in a Diverging Europe: Northern Italy, 1650–1881

Malthusian Dynamics in a Diverging Europe: Northern Italy, 1650–1881

Demography
DOI 10.1007/s13524-012-0141-9

Alan Fernihough

Abstract

Recent empirical research questions the validity of using Malthusian theory in preindustrial England. Using real wage and vital rate data for the years 1650–1881, I provide empirical estimates for a different region: Northern Italy. The empirical methodology is theoretically underpinned by a simple Malthusian model, in which population, real wages, and vital rates are determined endogenously. My findings strongly support the existence of a Malthusian economy wherein population growth decreased living standards, which in turn influenced vital rates. However, these results also demonstrate how the system is best characterized as one of weak homeostasis. Furthermore, there is no evidence of Boserupian effects given that increases in population failed to spur any sustained technological progress.

Keywords: Economic history . Demographic economics . Malthus

http://www.springerlink.com/content/u451p72938072xg8/

Ungated version:

http://ideas.repec.org/p/ucn/wpaper/201037.html

The Historical Fertility Transition: A Guide for Economists

Guinnane, Timothy W. 2011. "The Historical Fertility Transition: A Guide for Economists." Journal of Economic Literature, 49(3): 589–614.

 
The historical fertility transition is the process by which much of Europe and North America went from high to low fertility in the nineteenth and early twentieth centuries. This transformation is central to recent accounts of long-run economic growth. Prior to the transition, women bore as many as eight children each, and the elasticity of fertility with respect to incomes was positive. Today, many women have no children at all, and the elasticity of fertility with respect to incomes is zero or even negative. This paper discusses the large literature on the historical fertility transition, focusing on what we do and do not know about the process. I stress some possible misunderstanding of the demographic literature, and discuss an agenda for future work. (JEL I12, J13, N30)

http://www.demographic-challenge.com/files/downloads/657de1cecd3e4cef9751b9e7df2c3287/dc_the-historical-fertility-transition.pdf

UCD School of Economics Research Bulletin

The UCD School of Economics has started a periodic research bulletin, edited by me. The first edition is here. I hope you enjoy it. The main article is a very interesting interview with our distinguished colleague Cormac Ó Gráda.

Two New Papers On Malthus

As if we needed any reminding of it in this climate, economics is often known as the “dismal science”. Malthus is largely to blame for this unfortunate term, thanks to his pessimistic theories on the nature of population growth and mortality. In a simple Malthusian world, an increase in wages increases population. This only results in an increase in mortality rates, ultimately returning society to its original equilibrium with no permanent increase in welfare.

Two recent papers by UCD economists re-examine this issue. Cormac Ó’Gráda and Morgan Kelly (Living Standards and Mortality since the Middle Ages) find that all strata of English society, including the nobility, were affected by food shortages before the Black Death. The relationship between food prices and mortality disappears in the mid 17th century (although not in London), but then reappears in the early 18th century. Interestingly (given Malthus’ objections to the Poor Laws), the authors suggest that social welfare had a part to play in this. This paper is also discussed on the Economic Logic blog.

Research in this area has tended to focus on England; however we know that the UK was exceptional for several reasons. Alan Fernihough (Malthusian Dynamics in a Diverging Europe: Northern Italy 1650-1881) examines the evidence for Italy. He finds support for the existence of Malthusian checks into the late 1800s. Both papers are relevant for the debate on the stages of economic growth (e.g. Galor and Weil, Population, technology, and growth: From Malthusian stagnation to the demographic transition and beyond).

Unemployment Data and Google: From Forecasts to History Class

A belated thanks to Michael Breen for pointing out a recent article on VoxEU.org about predicting unemployment using Google Trends. The article is by D'Amuri and Marcucci: "The predictive power of Google data: New evidence on US unemployment". I have followed the literature on Google-search data and unemployment ( previously, here), but wasn't aware of the work by D'Amuri and Marcucci until now.

The research mentioned on the blog before (by Varian and Choi) was conducted to predict U.S. unemployment insurance claims using Google Trend data based around keywords such as "unemployment" and "social insurance". D'Amuri and Marcucci differ in their approach by using the "Google Index" – the incidence of Google job-search related queries over total queries – proved to have predictive power in forecasting unemployment in Germany and Israel (see Askitas and Zimmermann 2009 and Suhoy 2009).

Both approaches improve the predictive power of unemployment forecasting, but each has some limitation. D'Amuri and Marcucci mention that the Google Index could be partly driven by on-the-job search, rather than unemployed job search activities. It can be argued that this is only a problem to the extent that on-the-job search happens during a recession. D'Amuri and Marcucci also consider that not everyone has access to the internet, and therefore that people using the internet for job search are not randomly selected among job-seekers. It follows that people using the internet for unemployment benefit information are not randomly selected among the newly unemployed. These are illustrations of the sample selection problem in econometric analysis (as distinct from self-selection; Heckman provides an overview here).

So while Google Trends is a useful tool in unemployment (and other) predictions, there are reasons to be cautious; in particular, in relation to sample selection. Another limitation that has been remarked upon is that Google Trends only provides data from 2004 onwards. This is why I was intrigued when I typed "unemployment" into Google earlier today, investiagted the "options" at the top of the page, and then clicked "timeline" instead of "standard view". What I got was a picture along the lines of the one below, except that the chart was for unemployment from 1900-2010, instead of "Book of Revelation". I was unable to take a screen-grab of the unemployment chart; but you can follow a link to it here.


It's possible to click on any decade in the chart, any year and any month. Associated news stories appear in each of these categories. This is a powerful tool for finding out what was beeing reported in the media at the time any major news story was being covered. All of this is powered by Google News Timeline: a web application that organises information chronologically. "It allows users to view news and other data sources on a zoomable, graphical timeline. You can navigate through time by dragging the timeline, setting the "granularity" to weeks, months, years, or decades, or just including a time period in your query." However, using the News Timeline application directly is somewhat different to using the "timeline view" in web search. The latter provides charts such as the one shown above.

The unemployment chart shows two spikes: one at the start of the 1930's, and one in 2009. But what does this mean? According to the Google Blog, "the graph across the top of the page summarizes how dates in your results are spread through time, with higher bars representing a larger number of unique dates." Where does this historical data come from? From Google's "News Archive Search" service. News Archive Search produces the same results as the "timeline view" in web search. Search results include content from a number of sources, including both partner content digitized by Google through their News Archive Partner Program and online archival materials. More information about News Archive Search is available here.

There are some parallels to be drawn between News Archive Search (particularly the associated graphical illustrations) and the "news reference volume" feature in Google Trends. However, it is important to note that Google's "timeline" news graphs are based on monthly data-points; not daily data-points such as those used in (Trends) news reference volume. According to Google, Archive Search works as follows: "Articles related to a single story within a given time period are grouped together to allow users to see a broad perspective on the topics they are searching."

Irish History Online

For those interested in history, this may be useful:

"Irish History Online is an authoritative guide (in progress) to what has been written about Irish history from earliest times to the present. It was established in association with the Royal Historical Society Bibliography of British and Irish History (of which it is now the Irish component) and London's Past Online."

N.B. Particular attention is being paid to enhancing coverage of the Irish abroad: during 2008 over 500 new records on the Irish abroad were added, including many references collected in libraries in the U.S.A. and Canada.

BMI and Health Status

The flaws of using body mass index as a measure for overall health status are apparent. It is a 19th century technique which ignores the distribution of both muscle mass and bone in the body. In addition, the relationship between and health status is likely to be non-monotonic, most likely quadratic.

However, the use of BMI in research does have some advantages. It is very quick and inexpensive to measure. In addition, it is plausible that BMI is a strong indicator of individual's health preferences and behaviours. Also, BMI is a continuous metric. Therefore, if we choose to use BMI as a proxy for health status we do not have to constrict ourselves to discrete choice statistics when estimating the conditional distribution for 'health'.

The way in which BMI is used in estimation strategies needs to be redefined. BMI's definition of 'overweight' is outdated, and does not recognise that the population has become bigger, stronger and healthier in the last 150 years. Bone structures with greater density and increased muscle mass are not the same as body-fat increases. They are health promoting, not health deterring. Obesity is rising, and the negative health effects are undeniable. However, the shift from 'normal' BMI to 'over-weight' BMI and the negative health outcomes are dubious. For example, Romero-Corral et al. show how coronary deaths amongst 'over-weight' BMI cases are lower those individual's defined as having 'normal' BMI.

So how should the eager researcher approach this issue? In my opinion, we should accept that the bounds defined by the BMI scale are now invalid and have no basis acting as a proxy for overall health. The mean of health and BMI has shifted in over the last century, however I would argue that the new mean indicates improvements in health - strongly supported by life-expectancy increases, height increases, etc. - and that it is the deviations away from this mean which give a more precise measure of overall health status. One estimation strategy which maintains the continuous properties of this metric would be to measure BMI in z-scores (deviations from the mean controlling for the size of the standard deviation) or the z-score squared.

Economic History and the Banking Crisis

Some of the recent trouble in the Irish banking system might have been avoided if the warnings of one of Ireland's great economists had been heeded. Richard Cantillon (1680-1734) was likely referring to the Mississippi Bubble in France (1719-20), but he could have been writing about the current crisis. His "Essai Sur la Nature du Commerce en Général" ends with the following paragraph:

"It is then undoubted that a Bank with the complicity of a Minister is able to raise and support the price of public stock and to lower the rate of interest in the State at the pleasure of this Minister when the steps are taken discreetly, and thus pay off the State debt.

But these refinements which open the door to making large fortunes are rarely carried out for the sole advantage of the State, and those who take part in them are generally corrupted. The excess banknotes, made and issued on these occasions, do not upset the circulation, because being used for the buying and selling of stock they do not serve for household expenses and are not changed into silver.

But if some panic or unforeseen crisis drove the holders to demand silver from the Bank the bomb would burst and it would be seen that these are dangerous operations."