Table 9 Overview of expectations and observed effects of hypotheses; depicting the selected coefficients (columns: \(\delta _{1}\), \(\delta _{2}\) and \(\beta _{3}\)) from all models (rows) tested and reported, reporting only the combined results of individuals and companies when feasible
From: The effect of anti-money laundering policies: an empirical network analysis
Hypothesis | Variable | Expectation | Laundry (\(\delta _{1}\)) | No laundry (\(\delta _{2}\)) | All clusters (\(\beta _{3}\)) |
|---|---|---|---|---|---|
H1 | Cluster Size | Positive | 5.555∗∗∗ | 4.087∗∗∗ | 2.776∗∗∗ |
Cluster Diameter | Positive | −0.038 | 0.270∗∗∗ | 0.501∗∗∗ | |
Cluster Density | Negative | −0.076∗∗∗ | −0.154∗∗∗ | −0.049∗∗∗ | |
Crime Assortativity | Positive | 0.194 | 0.049 | ||
Crime Dis-proportionality | Positive | 0.016∗ | −0.018∗∗∗ | ||
Nationality Assortativity | Positive | 0.010 | −0.016 | 0.035∗∗∗ | |
Nationality Diversity | Positive | 0.045∗∗∗ | 0.088∗∗∗ | 0.038∗∗∗ | |
H2 | Degree Centrality | Positive | 1.038∗∗ | 0.270∗∗ | 0.721∗∗ |
Closeness Centrality | Positive | 0.046∗∗∗ | −0.009∗∗∗ | −0.103∗∗∗ | |
Betweenness Centrality | Positive | 0.004∗∗∗ | 0.0002 | 0.003∗∗∗ | |
Burt’s Constraint | Negative | −0.085∗∗∗ | 0.001 | −0.015∗∗∗ |