Published by EH.Net (December 2014)

Mark Casson and Nigar Hashimzade, editors, Large Databases in Economic History: Research Methods and Case Studies. Abingdon, UK: Routledge, 2013. xviii + 278 pp.  $145 (hardback), ISBN: 978-0-415-82068-4.

Reviewed for EH.Net by Les Oxley, Department of Economics, University of Waikato.

Reading this book I realized that “size does matter.”  Large datasets are not the “big data” we hear so much about today, and large datasets need not be “wide” nor “broad,” but they surely should be “long”! These are not simple semantics, but important issues to bear in mind when considering, evaluating, and considering the contributions of this new book by edited by Mark Casson and Nigar Hashimzade.  The editors do mention “big data” in the Introduction, but only in passing and as a “how to build” project.  An exception would perhaps be chapter 6 by John and Sheryllyne Haggerty where they use Visual Analytics (VA) methods to consider networks in Liverpool, 1750-1810.

The ten chapters authored by seventeen contributors plus two editors, present a mixture of “how to do” modern cliometrics and what the editors often refer to as “case studies.”   The editors stress that the ethos of the book (intended for doctoral and post-doctoral researchers in business history, economic history and social history) is to put principles into practice with the aid of practical historical studies. They criticize modern cliometrics for being “typically single equation” based “making limited use of simultaneous equation models, stochastic trends” and other concepts featured in their book. However, this seems to have missed the development and broad application of cointegration into quantitative economic history. When one considers the actual contributions published in the book, however, some chapters seem to over rely (often “due to convergence issues”) on OLS even when the stated best, theoretical, approach would be logit-type models and methods.

The range of authors include many regular contributors to economic history (Sara Horrell, Jane Humphries, E.A. Wrigley) and others who have a strong connection to the University of Reading (Adrian Bell, Chris Brooks, Anna Campbell, Jane McCutchan, Tony Moore, and Margaret Yates).

As a cliometrician, I am always looking to see how economic hypotheses can be tested through the lens of historical data.  Discovering, interrogating, estimating and testing data is what I like to do.  However, there were many surprises and a few disappointments that were revealed in this book.

In terms of surprises, the book includes just eleven figures of which only three are plots of actual data (two are photographs, two are schematic diagrams and four are VA-output plots which I defy anyone to be able to read without the aid of a microscope!). Univariate and multivariate plots, especially of time series are a crucial and simple first step in discovering the “hidden patterns in the data researchers fail to discover” which is a fundamental principle of the book.

Other surprises are related to the ability to use the chapters as “case studies.”  Yes, the authors present their research questions and allude to the data used and results presented, but with the exception of the readily available and well-mined data sets of e.g., Bob Allen and Greg Clark, much of the data used are not readily available. As a minimum, I would have thought that the large datasets used by the authors would be readily available, ideally as a link, or if not, easy to recreate (including not having to input nineteen pages of numbers presented as the data in chapter 3 by Nick Mayhew).  However, this simply is not the case.  To give a couple of examples; the data used in chapter 4, “Medieval Foreign Exchange,” by Adrian Bell, Chris Brooks and Tony Moore, “draws on exchange rates quoted in merchants’ letters from Barcelona, Bruges and Venice, written between c. 1385 and c.1410.”  The original data are identified by links presented as footnote 1 (see  and footnote 2 (see but it would be a Herculean task to recreate what the authors use derived from what are “huge” source materials, especially when the authors state (fn.3) that, “we identified data points that deviated significantly from contemporaneous rates, checked them against the original letters from the Datini archive and made corrections where necessary.”  Secondly, Jane McCutchan’s chapter 9 on “The Diffusion of Steam Technology in England: Ploughing Engines, 1859-1930,” uses data “derived from the unpublished business records of John Fowler & Co., which are held at the Museum of English Rural Life (MERL), University of Reading……The research was made possible by Robert Oliver of the Steam Plough Club (SPC) who painstakingly, over seven years, teased individual engine records from the Fowler archive.” In conclusion McCutchan states that this chapter “has presented the first comprehensive and definitive database of steam ploughing engines produced in the UK.”  My problem is that I can’t actually see it.

Apart from the lack of plots/figures and ready access to the databases, a few more niggles include; i) a general lack of summary statistics and diagnostic test results, ii) the rather too often casual use of language (especially if the book is targeted at doctoral and post-doctoral researchers) for example, “trial and error suggests that the impact of longer lags is relatively insignificant’ (p.88); “suggests that the value of the constant is quite substantial” (p. 135); “the proportion of the variation in women’s ownership that is explained …. is relatively small” (p. 217); “the overall fit of the regression is impressively high: (p. 237), etc., etc.

There are some useful and helpful references to econometric packages (p.21) and here I would also add-in “R” (which is free) and Matlab (which is certainly not); the chapter on Visual Analytics by Haggerty and Haggerty is an excellent example of the approach and a fascinating read.  They list a number of pieces of software that are now available for such analysis, and I would certainly endorse Pajek (2013) (see and suggest anyone interested also purchase Pajek’s useful book.  I also enjoyed the paper on “Women’s Landownership in England in the Nineteenth Century” by Janet Casson, and “Cupidity and Crime” by Horrell, Humphries and Sneath.

Overall, the book brings together a number of interesting papers on economic, business and social history.  Doctoral and post-doctoral researchers may find it to be a useful collection of research findings that will inform and facilitate their own research.

Les Oxley is Professor in Economics, University of Waikato, New Zealand.  He has published extensively in cliometrics with co-author David Greasley and recently on environmental economic history in papers published in the Journal of Environmental Economics and Management and Scandinavian Journal of Economics.

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