This paper develops a new classification of non-bank currency systems based on a lexical analysis from French-language web data in order to derive an endogenous typology of monetary projects, based on how these currencies are depicted on the internet. The advantage of this method is that it by-passes problematic issues currently found in the literature to uncover a clear classification of non-bank currency systems from exogenous elements. Our textual corpus consists of 320 web pages, corresponding to 1,210 text pages. We first apply a downward hierarchical clustering method to our data, which enables us to endogenously derive five different classes and make distinctions among non-bank currency system and between these and the standard monetary system. Next, we perform a similarity analysis. Our results show that all non-bank currency systems define themselves in relation to the standard monetary system, with the exception of Local Exchange Trading Systems.
Ariane Tichit*, Clément Mathonnat*, Diego Landivar**
* Clermont University, Auvergne University, CNRS, UMR 6587, CERDI, F-63009 Clermont Fd. Email: ariane.tichit@udamail.f; Clement.MATHONNAT@udamail.fr; ** ESC Clermont, 63000 Clermont-Fd. Email: diego.landivar@france-bs.com.
Keywords
non-bank money, text mining, web data, downward hierarchical clustering, similarity analysis
To cite this article: Tichit, A., Mathonnat, C., and Landivar, D. (2016) ‘Classifying non-bank currency systems using web data’ International Journal of Community Currency Research 20 (Summer) 24-40 <www.ijccr.net> ISSN 1325-9547. http://dx.doi.org/10.15133/j.ijccr.2016.002
The paper aims to show the impact that a complementary currency may have on a national economy from a theoretical point of view. A system dynamics model is created to describe the mechanics of money issuance in capitalist economies as well as in economies where there is no inside money. As an example, the first outcomes of a barter network implemented in 2008 by the STRO foundation in El Salvador (called Punto Transacciones) are presented and analyzed. Finally, using data from a complementary currency experience in El Salvador the spending multiplier is calculated. The main result shows that there is a greater spending multiplier in digital community currencies systems than in regular money market. Although the magnitude of PT network is still negligible from a macroeconomic point of view, the result is a desired outcome which may help to cushion the impact of macroeconomic shocks on labour market, contributing to stabilize aggregate demand.
IJCCR 
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