Fiscal Demarcations and Financial Power in Castile during a Transition Century (1450-1550): Analysis with GIS Technologies

Abstract

This project, funded by the Spanish Ministerio de Ciencia e Innovacion (HA R2010-15168), focuses on the Castilian fiscal system during the formation of the modern state. The project members seek to use Geographic Information Systems (GIS) technologies to construct a financial map of the kingdom and to demarcate its fiscal jurisdictions. We will then analyze quantitatively the growth of taxes in different regions, the methods used to collect them, and the financial networks undergirded by them.The fiscal data will be tagged to the Atlas de El Escorial, one of the most detailed sixteenth-century Castilian maps, to approximate the perception of space that people had in the sixteenth century and to ascertain if any relationship existed between, on the one hand, royal officials' knowledge of space and, on the other hand, the way that tax collection was carried out in early modern Castile. That is, was there a correlation between tax collection from various locales and geographical knowledge of those spaces? How did royal officials understand space in relation to taxation? The Atlas, then, might offer answers to these and other questions once the towns, bridges, rivers, mountain passes, and so forth have been properly geo-referenced and tagged.Better knowledge of these fiscal jurisdictions and of tax collection will also shed new light on the nature of power in the early modern world. Kings relied on local oligarchies (town councils, gentry, and clergy) to apportion and to collect taxes on the local level. In turn, the local notables often negotiated lower payments for themselves or apportioned the lion's share of the tax allocation to others. Thus more productive lands frequently had lower tax assessments than poorer lands. The crown in each fiscal jurisdiction also used its authority to grant individuals, corporations, and lands exemptions from taxation. Identifying the spatial dimensions of these privileges and exemptions will allow us to probe more deeply the relationship between space and power.Moreover, the project seeks to delineate the financial networks that transferred these monies from localities to the royal court or to the king's bankers in Italy or Northern Europe. For instance, loan contracts often specified that bankers be repaid from tax revenues in specific fiscal jurisdictions. So GIS technology should allow us to calculate the amount of tax revenues that actually left a region and the extent to which rural areas were connected to the international banking networks of Europe.The other benefit of GIS software is its ability to layer data from overlapping fiscal jurisdictions. By layering distinct tax information, we can determine more accurately the total amount of taxes collected from various regions as well as the relative size of specific taxes in certain years. For instance, clergy in the archdiocese of Toledo regularly contributed to royal coffers by providing a subsidy. This information on an extraordinary tax can be integrated with fiscal data from ordinary taxes (e.g., alcabalas and tercias) in two ways: first, with statistical analysis where a combination of both is calculated; and second, by superimposing a map of the archdiocese and maps of fiscal demarcations (partidos fiscales) to visualize fiscal spaces. This kind of mapping could show how, where, and why church divisions have affected the development of civil demarcations before the nineteenth-century Spanish nation-state. Moreover, such layering will allow us to gain a better sense of how much money particular regions paid in a given year and to better understand the fiscal burdens placed on taxpayers throughout Castile.One challenge for all GIS projects is to select a program. After examining several options, it was decided that free and open source software best met the project's requirements. In particular, we needed a system that allows for the management of a geographic database and has the ability to visualize and to analyze the datasets both spatially and temporally. …