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Table 4 Results of random effects regressions on cluster size

From: The effect of anti-money laundering policies: an empirical network analysis

 

Dependent variable

 

Node count

People count

Company count

Diameter

Laundry

3.911

2.731∗∗

0.393

1.086∗∗∗

(2.547)

(1.107)

(2.025)

(0.270)

No Laundry

2.081

2.473∗∗∗

−0.215

1.051∗∗∗

(1.680)

(0.729)

(1.486)

(0.177)

After AML4

2.776∗∗∗

2.062∗∗∗

0.610∗∗

0.501∗∗∗

(0.357)

(0.214)

(0.272)

(0.051)

Laundry: After AML4

5.555∗∗∗

1.458∗∗

4.607∗∗∗

−0.038

(1.044)

(0.614)

(0.781)

(0.149)

No Laundry: After AML4

4.087∗∗∗

2.742∗∗∗

1.914∗∗∗

0.270∗∗∗

(0.626)

(0.371)

(0.521)

(0.089)

Constant

8.153∗∗∗

4.573∗∗∗

4.496∗∗∗

2.723∗∗∗

(0.746)

(0.335)

(0.617)

(0.080)

Observations

2411

2320

1850

2411

\(R^{2}\)

0.112

0.136

0.042

0.121

Adjusted \(R^{2}\)

0.110

0.134

0.039

0.120

F Statistic

59.878∗∗∗

70.139∗∗∗

15.590∗∗∗

62.212∗∗∗

(df = 5;2405)

(df = 5;2314)

(df = 5;1844)

(df = 5;2405)

  1. Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01.