Elsevier

Explorations in Economic History

Volume 71, January 2019, Pages 112-134
Explorations in Economic History

The evolution of ottoman–European market linkages, 1469–1914: Evidence from dynamic factor models

https://doi.org/10.1016/j.eeh.2018.10.002Get rights and content

Abstract

This paper exploits data on a set of traded goods to undertake the first comprehensive empirical analysis of market integration between the Ottoman Empire and Europe from 1469 to 1914. Computing dynamic factor models via Bayesian inference, we overcome such data constraints as missing observations and a small sample size. The results of this analysis suggest that there were persistent market linkages until the first half of the 19th century, followed by a decline in price convergence. We also find that the intensity of Ottoman–European conflict had a negative effect on integration, especially during the 1844–1914 period.

Section snippets

Motivation

Economists have long debated the origin and evolution of commodity market integration as well as its implications for economic development. The reason for this debate is that measuring the extent to which global and regional markets are connected is crucial for understanding market efficiency—that is, how quickly price signals are transmitted across borders—and thus for assessing the effectiveness of market institutions designed to improve allocative efficiency. Despite the importance of this

The development of ottoman–European economic relations

How strong were the links between Ottoman and European markets? How did the extent of integration between them evolve and respond to the economic and political changes shaping more than 400 years of bilateral commercial relations? To answer these questions, we start by giving some background information about the evolution of those economic linkages that will help readers assess just how much commodity market integration was actually present. Thus we shall focus on the intensity, composition,

Data

We use two types of annual data: the CPI and the prices of a set of traded goods (i.e., wheat, rice, butter, olive oil, honey, soap, charcoal, wood, and chickpeas) for the years 1469 to 1914. Data for Ottoman Empire are from Pamuk’s (2000) extensive collection of Istanbul’s prices. The CPI for Istanbul, which Pamuk constructs using constant relative weights that reflect consumption patterns, includes both food and nonfood items (e.g., flour, rice, cooking oil, honey, mutton, chickpeas, olive

Econometric methodology

There is a rich literature on market integration in both historical and contemporary settings. The standard methods used to test for market integration include the simple computation of coefficients of variation, OLS regressions, and more advanced econometric techniques that focus on co-integration analysis.20

Results

We start by presenting the results on market integration between Istanbul and each European city for the entire 1469–1914 period. Then, to investigate changes in integration patterns over time, we split the sample into five sub-periods—for which the posterior probabilities are reported in Tables A2–A40. The particular subsample divisions were guided by how the CPI was constructed, which in turn was motivated by the Ottoman Empire’s underlying economic and monetary trends (as suggested by Pamuk,

Patterns and drivers of market integration

Our empirical analysis has delivered four key findings, which can be framed by looking at market integration in terms of time, geography, and commodity types. First, the historical period during which the strong model of integration is most definitively supported by the data was from the 17th century to the mid-19th century. Second, over these approximately 250 years we observe an evolution in the patterns of integration across locations—one that reflects a gradual and partial shift from the

Conclusion

Our study of integration between Europe and the Ottoman Empire shows that the intensity of links between these two regions’ markets varied across time, location, and commodity type. Exploiting a rich data set that covers 20 cities, nine commodities, and nearly five centuries, we provide new empirical evidence on the nature and extent of market connections between these two key players in the international economy. By employing Bayesian inference to compute dynamic factor models, we overcome

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  • We acknowledge financial support from the Faculty of Business and Economics, University of Melbourne (Faculty Research Grant, 2017) and from the Australian Research Council (DE150100809). For helpful comments we thank participants at the Brown Bag, Department of Economics, University of Melbourne and at the Fourth EH-Clio Lab Conference, Instituto de Economia of the Pontificia Universidad Catolica de Chile. We are grateful to Jeff Borland, Jeanne Lafortune, Jeffrey Williamson, three anonymous referees, and editor Kris Mitchener for useful suggestions that improved earlier versions of this paper as well as to Bob Allen and Şevket Pamuk for clarifications about the data. Finally, we thank Matt Darnell for assistance with copy-editing. All remaining errors are our own.

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