Geoscience Reference
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on the question: “which policy is the most costly or risky” when the following
components are considered: COMPETITIVENESS and INCOME DISTRIBU-
TION under the COST cluster, and VOLATILITY, DEFLATION, and BANK
VULNERABILITY under the RISK cluster. It is important to note that the refer-
ence for analyzing RISK is capital flow reversal—as in many crisis episodes with a
boom-and-bust cycle, the biggest risk in massive capital inflows is precisely their
reversal (procyclicality). However, one needs to distinguish this reversal from
outflows by domestic investors. While useful in times of crisis, which is why one
policy option is to encourage them, a flow reversal from investors pulling out will
generate detrimental capital “flight” (see again the distinction between capital
“flight” and “retrenchment” discussed earlier).
The policies at the bottom of the network in Fig.
9.10
are weighted with respect
to each component and sub-component listed above them. For example, under
BANK VULNERABILITY in the RISK cluster, where bank capital may deteriorate
during a flow reversal, there is a risk that a bank's capital adequacy ratio (CAR) will
deteriorate. The relevant question then is: Which of the three policies will likely
create such a risk (most risky)?
All arrows under each component in Fig.
9.10
point in two directions, implying a
feedback effect for every influence from an element to the other elements below
it. Thus, the structure in each box under each cluster forms a network. Again, taking
the example of BANK VULNERABILITY in the RISK cluster, a typical question
to ask is: “Given a selected policy, which risk is least likely to be resolved by that
policy?” Applying pairwise-comparisons, priority rankings for each feedback was
made. The inputs used are a combination of the normalized quantitative data
derived from the FCGE model simulations and analytical perceptions. The rankings
based on the complex network structure are derived from the limiting super-matrix
(see Appendix).
Table
9.1
shows the results of priority rankings for the three policies under the
BOCR.
29
Thus, while to “Encourage Outflows” ranks highest in terms of its
capacity to generate BENEFIT and OPPORTUNITY, the policy is also considered
most costly and risky. For example, compared with “Assign Levy” and “Reg Safety
Nets,” “Encourage Outflows” will do the least in avoiding decreased competitive-
ness caused by the appreciation of real exchange rate (RER). On the RISK side,
capital flow reversals may cause VOLATILITY in the EQUITY market. To
“Encourage Outflows” will obviously make things worse.
Having calculated the above priorities, the next step is to apply them to some
BOCR formula. Two types are used here: (1) the multiplicative approach (B
O)/
29
For example, under the BENEFIT scenario in Table
9.1
, three eigen-vectors are shown
(“Ideals,” “Normals,” and “Raw”). While all three give the same ranking, i.e., encourage outflows
being most preferred, followed by assigning levies, and regional financial safety nets (hence the
ranking shown in the last column of Table
9.1
), the normalized eigen-vector (0.4381; 0.4358; and
0.1261) under “Normal” with the sum equals unity is the most often used. All numbers under the
column “Benefit,” “Opportunity,” “Cost,” and “Risk” in Table
9.2
show the normalized eigen-
vector.
