Upload
mathias-siems
View
103
Download
1
Tags:
Embed Size (px)
DESCRIPTION
The paper is available at http://ssrn.com/abstract=2387584
Citation preview
1
A Network-Based Taxonomy of the World’s Legal Systems
available at
http://ssrn.com/abstract=2387584
Mathias M. Siems
Durham Univ., CBR Cambridge, IALS London
Classifying countries common, eg,
language families
economic development
2
Motivation
lexical distance between languages
Inglehart-Welzel cultural map (based on World Values Survey)
3
Motivation (cont’d)
4
Can this also be done in law?
• Mainstream comparative lawyers use categories of common law, civil law, Muslim law, Socialist law, traditional law, Far Eastern law etc. Yet, these are seen as mere ‘didactic devices’ (David), ie they do not aim to classify all countries of the world
• Two (unsatisfactory) classification attempts are:
• La Porta et al / Djankov et al: English, French, Nordic, German, Socialist legal origins but classifications of countries not explained (eg, Saudi Arabia as English legal origins?); also not explained why only these legal origins (and not, eg, Muslim law, traditional law – as comparative lawyers suggest)
• The Ottawa map, http://www.juriglobe.ca, (next slide)
Motivation (cont’d)
5
But here too no explanations, in particular for precise mixtures, eg, why is Saudi Arabia is 'Muslim law', Iran a mixture of 'Muslim law' and 'civil law', the UAE a mixture of 'Muslim law' and 'customary law', and Kuwait a mixture of 'Muslim law', 'civil law' and 'customary law'?
Aim of my paper to fill this gap
Motivation (3)
6
Structure of paper:
I. Introduction (ie Motivation)
II. Reasons to develop taxonomies of legal systems
III. Variables and descriptive statistics
IV. Network analysis: general presentation and analysis
V. Examining the relevance of legal origins
VI. Factions and clusters of legal systems
VII. Conclusion
7
• Descriptive: facilitates understanding, eg, if legal systems belong to same legal family, focus can be on remaining differences
• Analytical: relationship between legal and non-legal similarities / differences (also: possibly, effect of the law – ie ‘does law matter’ for economic development?)
• Normative: if one legal family is more conducive for development (La Porta et al); or if only some legal transplants ‘work’ (Berkowitz et al 2003)
Reasons to develop taxonomies of legal systems
8
• Comparative lawyers refer to ‘determinant’ or ‘permanent’ features, eg, related to legal style and mentality, role of law in society etc.
• For this paper: variables that relate to law today, ie not simply assuming that history matters (eg, colonies) or that non-legal factors matter (eg geography)
Twelve variables in three main categories:
– legal mentalities and sources of law shared by a group of countries– variables (1) to (4)
– general legal infrastructure – variables (5) to (8)– specific areas of law– variables (9) to (12)
Variables and descriptive statistics
9
n = 157
10
• Network analysis requires relational data. Here, possible to turn attributes into relations by way of calculating difference between each variable and country, and then calculating average difference per country pair
Network analysis: general presentation and analysis
Full matrix: 157 countries 12,246 country pairs
11
• This matrix is
a valued net-work. Thus, in order to display the network graphically one needs to choose cut-off points (here: 0.11, 0.13, 0.3154)
12
Programs used: UCINET and NETDRAW
13
14
Examining the relevance of legal origins
English LOFrench LOSocialist LOGerman LONordic LO(based on La Porta et al)
15
• Figure seems to indicate clustering of some LOs.
• This can also be confirmed more formally:
• It is also possible to calculate which variables drive these similarities: see next slide
Relevance of legal origins? (cont’d)
16
17
• Yet, some features of Figure 3 not captured by LO classification (eg, groups of European countries; Muslim countries)
• Moreover, ‘cluster adequacy’ indicators show the limitations of legal origins (Eta -0.248, Q -0.048; Q-prime -0.060, and E-I 0.452) [PS: signs as expected, but for a better fit they’d need to be closer to +/- 1]
• Thus, the following tries to identify “community structures”, focussing on factions and clusters
first, division of 0.13 cut-off network into 12 factions:
Relevance of legal origins? (cont’d)
18
Factions and clusters of legal systems
19
• Yet, it is preferable to use a classification that does not depend on an arbitrary cut-off point
• In this respect the ‘world-systems’ literature (since Snyder and Kick 1979) uses CONCOR: this splits the network into groups of roughly equal size.
• But, in the present case, a priori assumption about equal size not justified (also CONCOR a bit outdated). Thus, here, ‘optimisation clusters’ calculated – with a division into four clusters having the best ‘fit’.
These are as follows (next slide) and this can also be visualised (subsequent slide)
Factions and clusters (cont’d)
20
21
22
23
• Network analysis good tool to identify mixtures between various sources of influence; also possible to identify four plausible groups of countries
• Thus, this may be helpful at initial descriptive level.
• Analytically, differences may be related to relational ones (eg, trade relations; cross-citations); it may also be calculated whether one model is more likely to lead to certain extra-legal developments
• Normatively, it shows that Europe transcends the LO categories; possible relevance for legal transplants
Conclusion
24
Thanks for your attention!