Análisis de los atributos del método analítico SST

In this section we focus on common trends observed in our simulations and how banks introduced changes to the features in society. For societies with no banks, we observe a positive correlation between the total amount invested in the productive technology and the percentage of this amount wasted due to premature liquidation of the productive technology, having a correlation coefficient of 0.4609. Introducing banks into the society and forcing them to work in isolation actually increased the strength of such correlation to 0.7798. Permitting banks to interact in an interbank market reduces the strength of such correlation back to 0.4996.

Considering individual consumptions and its inequality level, we find that for the case of no banks the aggregate consumption level in the society is strongly positively correlated with the amount of successful investments in the long term asset (coefficient 0.994), as to be expected. The strong relation holds with the introduction of banks as well (0.894 correlation for the no interbank case and 0.874 for the interbank case). On the other hand, we find a negative weak relation between the Gini index and the consumption level in the case of no banks (-0.358). Interestingly, introducing banks alters the relationship between the aggregate individuals’ consumption and the Gini index: for societies with banks and no interbank the correlation coefficient is 0.525 and further increased to 0.6554 by allowing banks to interact. Such relationship is further highlighted by considering the aggregate individuals consumption as a percentage of the aggregate consumption combined with banks reserves accumulated at the end. The proportion of the individuals consumption is strongly and positively correlated to the Gini index (0.978 for no interbank case and 0.986 for the interbank case) and seen in Figure 7.10.

0.105 0.11 0.115 0.12 0.125 0.13 0.985 0.99 0.995 1 Gini Index % Aggregate Consumption 0.105 0.11 0.115 0.12 0.125 0.13 0.985 0.99 0.995 1 Gini Index % Aggregate Consumption

Figure 7.10: Individuals’ consumption Gini index and their relative aggregate con- sumption relative to the sum of the consumption together with banks reserves at the end of the 80th period for the 50 independent simulations of society with banks with No interbank market (upper), and for banks with interbank market (lower).

As indicated before introducing banks redirected the relation between individuals and investments in the economy. As a result the aggregate consumption level is actually negatively related to the percentage of survived banks in the society (-0.434 in no interbank case, and -0.518 in the interbank case). Further the inequality level

Omneia R.H. Ismail – PhD Thesis – McMaster University – CES

decreases with bank coverage and increases with bank success: the Gini index is strongly positively correlated with the percentage of individuals not in banks (0.820 no interbank case and 0.834 with interbank case) as seen in Figure 7.11), and negatively correlated with the percentage of successfully established banks (-0.624 and -0.718 no interbank case and interbank case respectively).

0.105 0.11 0.115 0.12 0.125 0.13 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Gini Index % Not in Banks 0.1 0.105 0.11 0.115 0.12 0.125 0.13 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Gini Index % Not in Banks

Figure 7.11: Gini index and the percentage of individuals not in banks at the end of the 80th period for the 50 independent simulations of society with banks with No interbank market (upper), and for banks with interbank market (lower).

Nevertheless the aggregate consumption level as well as the Gini index are strongly negatively correlated to the aggregate banks’ wealth measured by the total amount of reserves in the banks’ accounts at the end of the 80th period (-0.555 and -0.977 for the no interbank cases, -0.620 and -0.986 for the interbank case, correlation coeffi- cient between the consumption level/banks wealth and the Gini index/banks wealth respectively). As banks prevail in society, inequality decreases between individuals (see Figure 7.12), and aggregate consumption decreases with increases in banks re- serves (Figure 7.13).

Omneia R.H. Ismail – PhD Thesis – McMaster University – CES 0.1 0.105 0.11 0.115 0.12 0.125 0.13 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 Gini Index Banks’ Reserves 0.1 0.105 0.11 0.115 0.12 0.125 0.13 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 Gini Index Banks’ Rerserves

Figure 7.12: Individuals’ consumption Gini index and banks aggregate reserves at the end of the 80th period for the 50 independent simulations of society with banks with No interbank market (upper), and for banks with interbank market (lower).

0 1000 2000 3000 4000 5000 6000 7000 8000 9000 7.1 7.12 7.14 7.16 7.18 7.2 7.22x 10 5 Banks’ Reserves Consumption 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 7.1 7.12 7.14 7.16 7.18 7.2 7.22x 10 5 Banks’ Reserves Consumption

Figure 7.13: Aggregate individuals’ consumption and banks aggregate reserves at the end of the 80th period for the 50 independent simulations of society with banks and no interbank market (upper), and for societies with banks in the interbank case (lower)

Finally and as to be expected we find that bank reserves are negatively correlated with the total number of banks trying to be established ( -0.879, -0.924 no interbank and interbank case), negatively correlated to the percentage of individuals not in banks (-0.768 and -0.774), positively correlated to the percentage of survived banks (0.575, 0.713) and strongly negatively correlated with the amount of prematurely liquidated

Omneia R.H. Ismail – PhD Thesis – McMaster University – CES

investments in the productive technology in the case of no interbank market (-0.906) and less strongly in the case with the interbank market (-0.584).

Our conclusions should be viewed with the fact that our society is a balanced ran- domly structured one, there are no communities nor periodic shocks. Such structure implies that with no banks individuals have a good chance of finding trade partners when needed. We expect the results to be significantly different in other occasions where the society has different preference distributions or is less balanced. To examine our hypothesis we ran the above simulations once again (50 independent simulations for each case, for 80 × 80 society over the course of 80 periods) for societies with what we referred to before as communities or preference regions.