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Economic
Review
Federal Reserve Bank
of San Francisco
1993

George W Evans and
Seppo Honkapohja

James R. Booth

Sun Bae Kim

Number 1

Adaptive Forecasts, Hysteresis, and
Endogenous Fluctuations
FDIC Improvement Act and Corporate
. . Governance of Commercial Banks
Do Capital Controls Affect the
Response of Investment to Saving?
Evidence from the Pacific Basin

Table o f Contents

Adaptive Forecasts., Hysteresis and Endogenous Fliictaaflons ». . . . . 00 . .„ 0«. . . „ 3
George W. Evans and Seppo Honkapohja

FDIC Improvement Act and Corporate Governance of Commercial Banks ......... 14
James R. Booth

Do Capital Controls Affect the Response of Investment to Saving?
Evidence from the Pacific Basin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Sun Bae Kim

Federal Reserve B ank o f San F rancisco

1

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E con om ic Review / 1993, Num ber 1

Adaptive Forecasts, Hysteresis,
and Endogenous Fluctuations

A relatively recent major focus of macroeconomic theories

has been on nonlinear. models with multiple self-fulfilling

George W Evans and
Seppo Honkapohja
Professors of Economics, University of Edinburgh and
University of Helsinki , respectively. We are indebted to the
Economics Research Department of the FRBSF for numerous helpful comments. The first draft of this paper was
written while Evans was a Visiting Scholar at the Federal
Reserve Bank of San Francisco. The research was also
partially funded by the SPES program of the EC. The first
author acknowledges support from the National Science
Foundation.

This paper considers fluctuations and policy in an economic model with multiple steady states due to aproduction
externality. In the absence of policy changes, the driving
forces generating fluctuations are exogenous random productivity shocks. However, because there are multiple
steady states, large productivity shocks can shift the economy between high- and low-level equilibria, providing an
additional endogenous source offluctuations. The scope
for macroeconomic policy is large since changes in policy
can also shift the economy between equilibria. In this
setting macroeconomic policy exhibits hysteresis (irreversibilities) and threshold effects and can be used to
eliminate endogenous fluctuations.

equilibria and the potential for "endogenous fluctuations."
This category can be interpreted quite broadly to encompass models with solutions following regular periodic
cycles, "sunspot" solutions depending on extraneous random variables, or multiple steady states arising from coordination failures.!
These models may be contrasted with the recent "real
business cycle" theory and more generally with linear
models with exogenous random shocks generating business cycles around a unique equilibrium. Such models do
not generate as wide a range of dynamic time series
patterns as is possible in nonlinear models which can
generate asymmetries endogenously and manifest additional types of persistence. Models with multiple equilibria
are also a potential explanation for the empirical results
that the economy appears to exhibit regime-switching. 2
In the model below we combine aspects of both approaches. In the absence of policy changes, the driving
forces generating fluctuations are exogenous random productivity shocks. Without policy changes or productivity
shocks, the economy would settle down to a nonstochastic
steady state. Clearly productivity shocks will generate
fluctuations around a steady state even if it is unique.
However, for some cases of the model below, the economy
has multiple steady states and large shocks can shift the
economy between them. This provides an additional source
of fluctuations which is endogenous in the sense that it
arises from the structure of the model.
1. A very limited selection of well-known papers includes Azariadis
(1981), Diamond (1982), Grandmont (1985), Cooper and John (1988),
and Woodford (1990). See also the survey paper by Guesnerie and
Woodford (1991). The endogenous fluctuations in our model are closest
to those described in Howitt and McAfee (1992). Their "animal spirits"
cycles are generated by an extraneous sunspot variable, whereas the
fluctuations considered here are generated by intrinsic productivity
shocks. They do not consider the impact of policy, which is \a major
focus of this paper.
2. Such results are documented by Hamilton (1989), Boldin (1990) and
Potter (1992). They show that real GNP appears to switch probabilistically between high and low growth regimes.

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3

The scope for policy in models with multiple equilibria
is potentially large, since the levels of policy variables can
affect the likelihood of the economy being in alternative
equilibria and since changes in policy can shift the economy between equilibria. This is a fundamental issue for
policy. In linear models there is a continuous map from
control variables to the expected values of targets. This is
no longer so in these nonlinear models. Although policy
changes within a certain range have a continuous response,
beyond some threshold the economy may be displaced from
one equilibrium to another.

In this paper our objective is to consider these issues in a
specific model which has multiple stochastic steady state
equilibria arising from an aggregate production externality. In the model we develop below, the level of economic activity in the current period is positively related
to the level expected in the following period. Figure 1
shows the relationship between current and futureaggregate employment, nt = F(n t + 1) for different values of the
policy parameter 'Y ('Y measures government purchases
financed by seignorage, that is, by printing money). The
shape of the curve arises from the positive production
externality: Each agent's productivity is higher when aggregate output is higher. At low n, diminishing returns
yield the usual concave shape to F ..Above some threshold the production externality generates increasing social
returns and a steeper slope to F. This leads to the nonconcavity shown, though F again becomes concave at sufficiently high n since the magnitude of the external effects is
bounded.

FIGURE 1
EFFECT OF POLICY ON STEADY STATES

lowY
intermediate Y
high Y

There is thus the possibility of multiple interior steady
states, shown in Figure 1 for the intermediate 'Y case.
Because the model is forward-looking, the evolution of
the economy is determined in part by the forecast rules
employed by agents, and following recent literature we
assume that forecasting is based on adaptive learning algorithms. The steady states labeled nL and nH are stable
under adaptive learning, while n u is not. These steady
states can be stochastic in the sense of there being fluctuations around them due to productivity shocks. Furthermore, endogenous fluctuations can arise, under certain
learning rules, when productivity shocks are large enough
(and ofthe right sign) to move the economy between nL and
nH . These endogenous fluctuations could be eliminated by
using policy to shift up F until only the high-level steady
state nH remained.
Adaptive learning also makes the economy path dependent in the sense that the current equilibrium is determined
by initial expectations, the forecast rules, and the shocks.
In such environments economic policy can exhibit hysteresis (irreversibilities). Suppose the economy starts at nH
(with intermediate 'Y) as shown in Figure 1. As 'Y is increased nH will decrease and this will be tracked by actual
employment under adaptive learning. When 'Y is large
enough, nH and nu disappear and employment falls to nv
If 'Y is decreased to its original (intermediate) value,
employment will only increase to nL instead of returning to
nH • Thus, since a change in policy can move the economy
to a different equilibrium, reversing the policy need not
restore the equilibrium that prevailed before the change.
This paper develops in detail the results sketched above.
Section I specifies the model and in Section II we describe
the forecast rules and how they adapt to forecast errors
under learning. Sections III and IV present simulations
which illustrate hysteresis effects and endogenous fluctuations, respectively.

I.

THE MODEL

The Basic Overlapping Generations Model
We use a generalization of the overlapping generations
model incorporating a production externality, developed in
Evans and Honkapohja (1991), to derive the model outlined
above. 3 The externality leads to social increasing returns
over a certain range so that, for some structural parameter
values, there is the possibility of multiple steady states. In

"-.L..;.._....;.........;.._ _--"

nIL nl

nt =F(n t+1 ) for nonstochastic model

4

_ _~

~_~

n u nH n'H

n+

t 1

3. For brevity we will subsequently denote the references to our own
work by EH91, EH92a, EH92b, and EH92c.

Economic Review / 1993, Number 1

the version employed here We will also allow for random
productivity shocks and for fiscal-monetary policy.
Before turning to the detailed specification, we emphasize that we will be considering a highly stylized model. No
attempt has been made in this paperto make either the structural parameters or the time series properties of the solution
paths empirically realistic, though we thillk that the time
series properties for output are "suggestive." Our main
objectives are to show the potential of such models to
exhibit endogenous fluctuations generated by intrinsic
random shocks and to illustrate the effects of policy in this
setting.
In the basic overlapping generations (OG) model representative agents (who are producers-consumers) live
two periods. An agent born at time t maximizes utility
W = U(C t + 1) + Z(gpgt+ 1) - Vent), where ct+ 1 is private
consumption when old, nt is labor supply when young, and
gt is public consumption at t. gt and gt+1 are taken as
exogenously determined by the government. The budget
constraints for the agent are Pt+1Ct+1 =Mt and ptqt=Mp
where Mt is the money stock, qt is the quantity of output
produced, and Pt is the price of output. In the standard
formulation of the OG model, one unit of labor produces
one unit of output, that is, qt = nf' but we will modify this
assumption below. The household thus works and produces
output when young, and exchanges the goods produced for
money (held by the old) at price P.. This money is then carried forward to the following period when it is exchanged at
the possibly different price Pt+ 1 for goods to consume
when old. In the standard version of the OG model, the
stock of (fiat) money is held constant and there are no
government purchases.
We choose to analyze a version of the OG model because
it is one of the simplest fully specified dynamic general
equilibrium models in which expectations matter. The
young agent must decide how hard to work, or equivalently, since all income is saved as money, how much to
save when young. Since the rate of return on money (the
only permitted vehicle for saving in the model) is p/Pt+ l'
the expected price in the following period, or more accurately the probability distribution of Pt+ l' is crucial to the
agent's optimal decision.
It should be pointed out that the standard OG model has
the disadvantage that the time unit serves several distinct
purposes: the length of the working life, the length of the
retirement, and the frequency at which economic data are
generated. Clearly, we adopt such a model only for tractability and ease of exposition. In principle there is no
difficulty constructing analogous models with distinct horizons for these different time periods, as is done in some
empirical models. We anticipate that all the phenomena

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illustrated in this paper will arise in such more realistic
models.

The Model with Increasing Social Returns
We now introduce two modifications to the standardOG
model. First we allow for government consumption. The
government is assumed to purchase the proportion 'Yt of
output at t, that is, gt='Ytqt. For convenience we assume
that there are no explicit taxes, so that these purchases are
entirely financed by seignorage. 4 Thus the government
budget constraint is

Mt+1

=

Mt

+ Pt +1gt+1·

Using ptqt=Mt it follows that

M t + 11Mt = (1- 'Yt+1)
and

P/Pt+1 = (1-'Yt+1) qt+1 l qr
The other modification concerns the production function. A positive externality is introduced into production.
Moreover, we allow for random productivity shocks. Thus
the production function is assumed to have the form

(1)

qt = f(n p Nt)vp

where Nt = Kn t is aggregate employment, K is the number
of householillO: in each generation, and V t is a positive
identically and independently distributed random productivity shock.
The Nt term represents a positive production externality,
and we adopt the particular form developed in EH91:

fen, N) = Ana {max(I*, AN (1

+ aAN)-l)}13.

This form arises as follows. Individual output is assumed
to depend on "ideas" as well as labor effort. Ideas are
generated (and "broadcast" to other agents) at a rate A.
proportional to labor effort, and the "complementary"
ideas obtained from other agents, beyond some threshold
I~ exert a positive external effect on productivity. This
effect generates increasing returns over a range at the
aggregate level. However, because there is a fixed time
cost, a, for accessing a suitable complementary idea, the
range of increasing returns is bounded.
Because 0 < a < 1, the individual faces diminishing
marginal returns to individual labor effort (taking N as
exogenous) and we adopt a competitive model. The parameterization of the model is completed by assuming the isoelastic forms for the utility functions U( c) = c1 - ITI (1- IT)
4. Only a minor modification would be required to allow for using lumpsum taxes to raise part of the revenue.

5

and V(n)=n 1+ E
/(l+E). It can be shown that the law of
motion for the economy satisfies5
(2)

El(1-'Yt+1)qt+1)1-rr = n~+E/u.

Here Et denotes the expectations held by agents at time t.
In a rational expectations equilibrium this will be equal to
the true conditional expectation at time t.
Since by (1) output next period is given by qt+ 1 =
f(nt+1,Knt+1)Vt+1 it can be seen that (2) determines
current employment as a function of the expected state of
the economy next period (together with the current productivity shock this also determines current output and the
price level). That is, the reduced form of the model can be
written as
(3)

nt

= H(E tX(n t +1, V t +1' 'Yt+1)) ,

where H and X depend on the utility function and production technology parameters according to:
(4)

X (n, v, "1) = ((1-'Y)f(n, Kn) v)l-rr,

and
(5)

on the various parameters, the model can have 0,1,2, or 3
interior perfect foresight steady states and the number can
be affected by the policy parameter 'Y. Similar results arise
in the stochastic case with random productivity shocks.
Provided the range of the shocks is not too "large,"6 each
of the perfect foresight steady states will, in the stochastic
case, correspond to a rational (stochastic) steady state nt =
jj? and qt =f(fi,Kfi) v t · 8
When there are three steady states, the welfare in the
three steady states depends on the value of government
consumption. If government consumption yields no (or
sufficiently low) utility, then steady states with high n
Pareto dominate those with lower n and the nL and nu
steady states represent coordination failures. The interpretation of the multiple steady states is straightforward:
When other agents work hard, this raises the marginal
product of individual effort and induces a higher work
effort. At nL and n u agents work less hard than at nH only
because other agents are working less hard than at nH • It
would be more efficient if agents could coordinate on the
high effort level nH .

H (X) = UX1/(1+E).

The Effect ofPolicy on Steady States
Multiple Steady States
and Coordination Failures
The economics of the model can be most easily understood
by examining the nonstochastic case in which (1) reduces
to qt = f(npKn t)· Under perfect foresight, (3) relates n t to a
function of nt + l' that is, F(n t + 1) = n p where we have also
incorporated a constant policy parameter "1t + 1 = "1 into F.
Provided (J' < 1 the substitution effect dominates the income effect and function F is upward sloping. The S-shape
shown in Figure 1 arises because of the production externality: Below the "kink" point (corresponding to the
threshold of "free" ideas 1*) F is concave because ofdiminishing returns. Above this point social increasing returns set
in, generating a nonconcavity in F. However the region of
increasing social returns is bounded, andF eventually again
becomes concave.
If the externality is sufficiently strong relative to other
parameters there can be multiple steady states. Depending

An increase in ~i rotates the F function down around the
fixed origin. Figure 1 illustrates one possibility, which we
will focus on in this paper: For "1 sufficiently small, there is
only one interior steady state, the high-level equilibrium
nH . As "1 is increased we at some point enter a regime with
three interior steady states, nH , n u , and nL' Finally, when "1
is sufficiently large, only the interior steady state nL
remains.
Recalling that the policy parameter "1 represents a mixed
fiscal-monetary policy, it will be noted that, interpreted
as fiscal policy, the effects are anti-Keynesian in the
following sense. As we discuss below, only the steady
states nL and nH are stable under learning. If the economy
is at a stable steady state, for example, nv an increase in "1
lowers the level of steady state employment (and output).
This result is due to a supply side effect. The higher money
growth required to finance increased government consumption leads to a higher level of inflation and therefore a

EP' (p,q,lp'+l) (p,!p,+,)f, (n" N,) v, = V' (n,),

6. Technically suppose that v, has bounded support. Then not "large"
essentially means that the length of the support is sufficiently small. See
EH92a.

wherefl (e) is the partial derivative with respect to n. Using the market
clearing condition P'!P, + 1 = (1- 'Y,+l) q,+ llq, we obtain

7. If the productivity. shock were not proportional, then in a rational
steady state n, itself would be a function of v,.

5. The first order condition for utility maximization is

Ep' ( (1- 'Y'+l) q,+l) (1- 'Yt+ I) q'+1 = V' (n,)f(n" N,) I h (n" N,).
Substituting the assumed parametric forms for U, V andf(e,e) we obtain (2).

6

8. The model can also have other rational expectations solutions, solutions which depend on exogenous sunspot processes and nonstationary
solutions. Consideration of these solutions is not needed for the analysis
in this paper.

Economic Review / 1993, Number 1

lower rate of return on work and saving. Because we
assume the substitution effect dominates the income effect,
this leads to less work effort at higher 'Y.

II.

that key parameters are altered in response to forecast
errors.
A convenient way to write this forecast rule is:
(7)

FORECAST RULES AND LEARNING

Expectations and Learning Rules
The possibility of multiple rational expectations solutions
(for example, multiple steady states) appears awkward for
the pure rational expectations approach. A now widely
used approach which overcomes the "multiple equilibria"
problem is to replace the assumption of rational expectations with the specification of a learning rule for expectation formation. 9 This may in any case be a more realistic
view of expectation formation. The model is thus written as
(6)

where the superscript e denotes the expectations of X held
by the agents at time t on the basis of a forecasting rule
which has been estimated using observed data. 10
This way of looking at the economy converts a rational
expectations model with multiple equilibria into a model
with path dependence in which the actual evolution of t~e
economy depends on:
(i) the adaptive forecast rules used by the agents,
(ii) the initial parameter estimates and forecasts held by

the agents, and
(iii) the sequence of stochastic shocks and structural shifts.

It may be noted thattypically not all equilibria are stable
outcomes of adaptive learning processes. Requirement of
convergence provides a stability condition which may be
used to select equilibria of interest. 11
We thus depart from strict rational expectations, though
for appropriate adaptive forecast rules, expectations may
.converge to rational expectations over time. Consider forecast rules in which agents treat the law of motion as a
stochastic steady state with an unknown mean. Suppose
agents estimate the unknown population mean using the
sample mean. Such forecast rules are adaptive in the sense

where ~\ = 11 t andX8 = Xo' Theformula (7) is the same as
the conventional adaptive expectations formula,12 except
that the coefficient specifying the size of the revision to the
forecast error, 0t, goes to at rate lit. This reflects the fact
that each new data point provides proportionately less
information compared to the history of data. 13 0t will be
referred to as the "gain" parameter at time t.
Will this learning rule converge to a rational steady
state? The problem is not straightforward to answer, since
the system is "self-referential" in the sense used by Marcet
and Sargent (1989): Agents change their expectations in
response to the evolution of the system, and the evolution
of the system depends in tum on the expectation rules the
agents use.
For the case at hand it is possible to characterize the
possible asymptotic outcomes when there are three steady
states (see EH92a). The adaptive rule which forecasts X by
means of the average of its past values can lead nt to
converge to either nH or nv depending on initial conditions

°

arId the sequence of random shocks. That is, either of these
two rational steady states can be the outcome of an
adaptive learning rule. In contrast, the middle steady state
n u is not stable under learning. When there is only one
steady state it will be stable under learning. 14

Structural Change
and Constant Gain Estimators
In the learning rule just described (estimation using the
sample mean), the gain parameter 0t decreases at rate t.
The choice 0t--+O, often referred to as "decreasing gain,"
is appropriate if agents confidently believe that they are in
an economy in which Xl' the variable being forecasted, has
a constant mean over time. While this would be reasonable
if agents believe that the structure of the economy never
changes, such an assumption does not seem realistic in
practice.
How should the learning rule be modified if agents

9. See EH92c for a recent review of the literature.
10. Note that in considering learning rules we are straining the overlapping generations interpretation of the model. Implicitly we are assuming that agents inherit forecast rules from their "parents," which they
then update. Alternatively, it may be possible to reinterpret the model in
terms of infinitely lived agents facing finance constraints, as "in Woodford (1988).
11. However, more than one equilibrium may be stable under learning;
see below for an example.

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12. We have introduced a one-period lag into the expectation formula (7)
in order to avoid simultaneity between (6) and (7).
13. For an early discussion of the adaptive expectations formula with a
possibly nonconstant gain, see Turnovsky (1969).
14. More exotic equilibria, for example, periodic solutions and "sunspot" solutions depending on extraneous variables, can be stable under
learning for certain parameter values and appropriate choices of learning rules. See EH92a,b for details.

7

believe that the structure of the economy may be subject to
change? In the context of recursive algorithms for parameter estimation, this is a general problem which has been
considered in the statistical and engineering literature; see
Benveniste, et al. (1990, ch. 1 and 4, part I). There are two
approaches. The first is for agents to build a model, with
hyperparameters, of how the system is evolving over time,
and to estimate simultaneously both parameters and hyperparameters. This approach requires knowledge of the form
of structural change.
The alternative approach, which appears more robust
and which we will adopt in this paper, is to replace the
assumption 0t-t 0 by the assumption that 0t is equal to
(or approaches) some fixed value 0>0. This procedure,
known as "constant gain," involves a trade-off between
bias and variance when used to adapt to an exogenous timevarying process. A larger value of 0 will allow changes in
structure to be tracked more rapidly, but will also produce
more noisy forecasts.
Although the choice of the gain parameter 0 is subject to
this trade-off, and the optimal choice of 0 will depend on
the size and frequency of structural change, the use of a
constant gain learning rule, in preference to a decreasing
gain rule, is clearly indicated when the structure is subject
to change.

An Example with a Time-Varying Policy
To illustrate the importance of using constant gain estimators when structural change is present, consider the behavior of the economy if the monetary-fiscal policy parameter,
"I f' varies systematically over time. In particular, suppose
that the share of government purchases is made to vary
according to:
(8)

Here U o specifies the mean level of 'Yf' 2u I is the range over
which "It varies, and w is the frequency.
Agents are assumed not to know the path (8), but to
allow for the structural change by using a constant gain
estimator in (7). Of course, a regular sinusoidal pattern in
"I t should be easy to detect, but our point would apply just
as well if the pattern for "It were highly irregular and
difficult to predict. 15 In the simulations of this section we
15. We are not allowing agents to condition their forecasts of X, on "{,.
This assumption is justifiable if the data on "{, are infrequent (compared
to d~a on X,) and of poor quality. Recent data on X, would then provide
most of the information relevant for forecasts.

8

choose U o and U I so that, given the other parameters of the
model, there is a unique steady state nv 16
The other crucial part of the specification is the distribution of the iid proportional productivity shock v. We
choose

vt = 1

+

'T

(0.5 - ut ),

where U t is iid uniform over the unit interval ('T is restricted
to 0 ~ 'T ~ 2). We set 'T = 0.20.
Figure 2 shows a simulation over 1,000 periods when the
policy parameters are U o = 0.07, u l = 0.02, and w = 0.04
and when agents use the gain parameter 0 = 0.15. The path
of employment over time reflects the combined effects of
the time variation of policy, random productivity shocks,
and the adaption of expectations through the learning rule.
To see the importance of using a constant gain learning
rule rather than a decreasing gain rule (such as averaging,
that is, 0t= lit) we can compare the quality of the forecasts. For convenience we adopt the mean square forecast
error criterion MSE = T-I If= I(Xt - Xf)2 and we choose
T = 10,000 periods. Suppose first that agents use a constant gain estimator with 0 = 0.15. Then simulations indicate that an individual agent would obtain a much higher
MSE with a decreasing gain estimator (0.0206 vs. 0.0149).
Even if all other agents were using a decreasing gain
estimator, a single agent could somewhat lower his MSE by
using an appropriate constant gain estimator (for exampie
0=0.05 yields 0.0148 vs 0.0150 with decreasing gain).
Thus with time-varying structure there is a forecasting
advantage in using a constant gain estimator. We discuss
the choice of 0=0.15 in the next subsection.

Equilibria in Learning Rules
The point just developed merits some further discussion. Is
a gain parameter 0 = 0.15 a good choice from a statistical
point of view? On the basis of the data shown in Figure 2,
agents could consider whether another choice of the gain
parameter 0 would have been better in terms of the mean
square forecast error, 17

(9)

MSE(o) = T-fIf=1 (XtC0o) - Xf(O))2.

Equation (9) is interpreted as follows: The data are
generated by the model (4)-(8) with agents using the gain
16. Throughout the paper we use the following structural parameters:

e=0.25, <T=0.1, A=0.0805, a=0.025, a=0.9, >"=0.5, K=40,
/*=19.5,13=1.007.
17. Other possible criteria could be devised based on utility losses.

Economic Review / 1993, Number 1

FIGURE 2

TABLE

EFFECT OF TIME-VARYING POLICY

MSE WITH TIME-VARYING POLICY

ACTUAL

1.9
(])

E
>.2
c..

18

E

UJ

1.6

A
a 100 200 300 400 500 600 700 800 900 1000
Period

parameter 0 = 00 (in our case 00 = 0.15). At the end of T
periods, agents consider whether they have made a good
choice of the gain parameter, given the data (that is, given
the choice of the gain parameter 0 = 00 made by other
agents).
Indeed, we can take this line of thought one step further.
For each 00 we can look for the value of 0 which minimizes
(9). If the minimum of (9), given 00 , is attained at 00 itself,
then we have an equilibrium learning rule with parameter
00 , in the usual sense. No agent would want to alter his gain
parameter 0 (based on the MSE criterion), given the choice
made by others.
We make no attempt to establish the formal existence of
such an equilibrium, but present the evidence for the case
at hand, using sample estimates of the MSE for T = 4,000.
Table 1 provides the simulation results. Table 1 shows
MSE(oo) for various values of 00 and also the value of 0,
and corresponding MSE, which minimizes (9) for each
choice of 00 , It can be seen that there does appear to be an
equilibrium learning rule with a gain parameter of approximately 0 0 = 0.15. This is no accident: We chose our value
of 0 on the basis of Table 1. It is also worth noting that a
wide range of 00 would be "reasonable" choices in the
sense that the MSE loss of using the wrong 0 would be
small.
We close this section with one final point: The "equilibrium" 0 will depend on the policy parameters. For
example, a higher frequency of change w can be expected
to lead to a higher equilibrium value of

o.

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MSE

80

2.0

c

1

(80 )

ARGMIN
MSE (8)

MIN
MSE (8)

DIFFERENCE
IN MSE, %

0.01
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
0.50
0.55
0.60
0.65
0.70
0.75
0.80
0.85
0.90
0.95

0.0169
0.0149
0.0147
0.0146
0.0147
0.0147
0.0149
0.0150
0.0151
0.0152
0.0154
0.0155
0.0157
0.0158
0.0160
0.0162
0.0163
0.0165
0.0166
0.0168

0.07
0.09
0.13
0.15
0.18
0.20
0.23
0.26
0.31
0.36
0.41
0.46
0.51
0.56
0.61
0.66
0.71
0.76
0.81
0.86

0.0155
0.0146
0.0146
0.0146
0.0147
0.0147
0.0147
0.0148
0.0149
0.0150
0.0151
0.0153
0.0154
0.0156
0.0157
0.0159
0.0160
0.0162
0.0163
0.0165

8.89
2.01
0.48
0.00
0.15
0.49
0.85
1.17
1.40
1.53
1.62
1.69
1.74
1.78
1.81
1.84
1.86
1.87
1.89
1.89

NOTE: Table shows MSE for gain 8 when data generated in a model
with time-varying policy and agents use actual gain 00 , Simulations
are over 4,000 periods.

m. HYSTERESIS EFFECTS
In the preceding section the variation in 'Y t was restricted to
a range over which the system had a unique steady state nv
Over this range, neglecting random shocks and transitional
learning dynamics, there is a continuous relationship between policy and employment and the policy is "reversible." However, an important feature of our model is that
certain variations in the policy parameter 'Yt will induce
discontinuous responses. To illustrate this aspect of policy
we again investigate the effects of a time-varying policy of
the form (8), but now set a o =0.04, a l =0.02, and w=
0.01. 'Yt thus varies continuously over the range 0.02 to
0.06. We use a gain parameter of 0 = 0.35, which is
approximately the equilibrium value in the sense of the
preceding section.
The values of'Y = 0.02,0.04, and 0.06 correspond to the
"low," "intermediate," and "high" 'Y cases shown in
Figure 1. Consider the effects as policy moves from a low
value. of 'Y to a high one. Starting from the low 'Y case "of

9

FIGURE 3

Figure 1, estimators will continuously track the mean of
X(nH,v;y) as we move through the low and intermediate "I

cases. However, when "I becomes sufficiently high, nH and
n u coalesce and then disappear. The system bifurcates to
the high "I case, inducing a discontinuous change in the
attracting steady state employment level to nL (a "catastrophe" phenomenon).
From a policy point of view, some of the more interesting features are the hysteresis effects illustrated in
Figure 3. Here we show the relationship between "It and nt
over one complete cycle of "It (from 0.06 to 0.02 to 0.06).
Over most of this range there are two distinct branches to
the policy relationship, with the lower branch corresponding to the nL steady state and the upper branch corresponding to nH'
The branch on which the system lies at some point in
time is determined by history. On a given branch, over a
range of "I, policy is reversible in the sense that an increase
in "I followed by an equal decrease in "I will return the
system to its original position (if an allowance is made for
random productivity shocks and for transitional learning
dynamics).
However, changes in "It beyond a certain point induce
policy irreversibilities when the system is forced onto the
other branch. Starting with "It = 0.06 and nr=1.9, the system moves (clockwise) along the lower branch until at low
values of "It employment becomes forced onto the upper
branch (when the low steady state disappears). When "It
begins to increase from its minimum of 0.02, it remains on
the upper branch until "It is sufficiently high.
The message for policy is this: If the system is trapped
into a low-level steady state, the policy variable can have a
strongly nonlinear response. Decreases in 'Y may have
initially small effects on employment, while beyond some
threshold value the induced response can be much larger as
the economy is pushed from the low-level to the high-level
steady state.

N

ENDOGENOUS CYCLES

Endogenous Shifts in Expectations
In the foregoing we have considered a model in which a key
driving force is variation in the policy variable 'Y t . However,
the qualitative results obtained suggest the following additional possibility. Suppose that agents use a constant gain
forecast rule. Could random productivity shocks lead to
shifts between high-level and low-level steady states, via
induced changes in forecasts, even in the absence of
structural or policy shifts? As we will see, the answer can be
yes.
Thus consider the system (4)-(7) with "It fixed at "I =

10

HYSTERESIS EFFECTS

3.6
3.2

c

Q)

E
>o
0..
E

w

2.8
2.4

: I~----,-----,
0.01

0.02

0.03
0.04
0.05
Policy parameter gamma

0.06

0,07

0.04. With this value of the policy parameter there are two
stable rational steady states. If agents use (7) with decreasing gain, for example, with 0t = c/ t, for some constant c,
then, as pointed out in Section II, the system will converge
to one of the two rational steady states corresponding to nL
or nH (and expectations will converge to the corresponding
fixed rational forecast).
However, if agents use a constant gain 0t = 0>0 this will
not be so-agents' forecasts X'f + 1 will retain some randomness even in the limit because of their sensitivity (through
0tXt-l) to random productivity shocks. Furthermore, there
is now the possibility that, say, with the system starting
near the low-level steady state, a large favorable productivity shock leads to a sufficiently large revision in X'f+ 1 so
that in subsequent periods the system is drawn, for an
extended period of time, to the high-level steady state.
This phenomenon is illustrated in Figure 4, which presents the results of a simulation with 0 = 0.15, "I = 0.04 and
,. = 0.20 (other parameters are unchanged). The system
appears to alternate between two noisy steady states,
centered near nH and nL • Occasionally productivity shocks
are sufficiently large and in the right direction to move
actual and thus subsequent expected aggregate economic
activity from one region of attraction to the other.
Why should agents use a constant gain expectations rule
in this situation? There are two reasons. First, although in
the simulation presented the policy parameter was held
fixed, agents may use a constant gain forecast rule because
they are concerned about the possibility of structural or
policy shifts. It seems plausible that agents would want to
make some allowance for this by maintaining 0 above some
minimum positive level.

Economic Review / 1993, Number 1

FIGURE 4

TABLE 2

ENDOGENOUS CYCLES

MSE WITH ENDOGENOUS CYCLES

WITH CONSTANT GAIN ESTIMATOR

S
0.05
0.10
0.15
0.20
0.25
0.30
0.40
0.50
0.60
0.70
0.90

2.8

2.6
......

ai 2.4

E
>.2
CL

&1

2.2

2.0

1.8

L....-........_ L . . . . -........----'_-'-----L_....L-----L_-'----'

o

500 1000 1500 2000 2500 3000 3500 4000 4500 5000

MSE
0.0268
0.0248
0.0246
0.0248
0.0253
0.0258
0.0272
0.0288
0.0307
0.0329
0.0386

NOTE: The MSE for a model with endogenous cycles was generated
by a fixed policy parameter 'Y = 0.04 and constant gain So = 0.15.
Simulations are over 4,000 periods.

.Period

Second, and more fundamental, the choice of a constant
gain learning rule may be an equilibrium learning rule in the
sense defined in Section II. That is, the choice 0 minimizes
the forecast mean square error for each agent, given that
other agents use that o. In this case we would have a selffulfilling prophecy in learning rules, with expectations
adapting to fluctuations in economic activity, and the
changes in expectations in turn inducing fluctuations in
the economy. Even if 0 is not strictly an equilibrium value,
it may still yield an MSE which is nearly optimal. Table 2
shows that this is indeed true for 0 = 0.15)8
Although the model is highly stylized, the results of this
section are attractive as a model of economic fluctuations
in the following sense: Unlike "sunspot" equilibria, in
which the solution depends on extraneous variables, the
precipitating variables here, as in real business cycle
(RBC) models, are productivity shocks. The difference
from RBC models is that a sequence of large shocks can
induce a self-fulfilling overreaction in which the economy
moves between its two stable steady states.
The policy implications are again straightforward. Faced
with an economy undergoing endogenous fluctuations, the
policy parameter 'Y can be shifted to a level at which there is
a unique steady state.

18. The choice of So=0.15 is only approximately an equilibrium,
because the S that minimizes MSE for this So lies between 0.14 and
0.15.

Federal Reserve Bank of San Francisco

Regime-Switching Models
But would agents stick with a constant gain estimator if
they observe the process shown in Figure 4? They might,
since the existence of two regimes may not be apparent in
the presence of the random shocks, and since the use of a
constant gain estimator is designed to allow for and adapt
to unspecified structural shifts. However, it is of interest to
know whether endogenous cycles would continue to exist
if agents did infer the existence of two regimes (corresponding to nL and nH ) and estimated a regime-switching
model in an attempt to improve their forecasts.
Thus suppose that agents·· believe that the conditional
mean level of X follows a two-state Markov process. We
will assume that agents believe the regime is triggered by
the recent average level of economic activity, rather than by
some hidden variable, and so use the "self-exciting"
framework of Potter (1992). Based on Figure 4, we choose
a regime switching parameter X* corresponding to n = 2.1
(X* = 2.1 (l + €)/ a). Agents assume that the economy is in
state 1 if Xt _ 1" the average of X of the recent past, is less
than x* and in state 2 if it exceeds X'}' We again use
a recursive estimation procedure, but now assume that
agents estimate both the conditional mean value of X in
each state and the conditional probability of being in each
state. Let Pi for i = 1,2 be the probability, given that we are
in state i at s, of staying in state i at s + 1. Pi at time t is
essentially estimated by the corresponding actual proportion Pit through time t. 19 The conditional means in the two
19. The estimation is actually done using the associated recursive
formula and initial estimates PI = P2 = 1.

11

FIGURE 5

states are estimated by

Xl t +l = Xl t + o(Xt-Xl t)

ENDOGENOUS CYCLES
WITH REGIME-SWITCHING ESTIMATORS

2.6

ifXt > X*

2.4
"E
Q)

For simplicity, the switch point x* is fixed exogenously
and not estimated. In the simulations we assume that Xt is
computed using the average over the last three periods. We
continue to use a constant gain estimator, 20 on the assumption that agents still want to allow for the possibility of
structural/policy shifts.
Agents then forecast X t + 1 at time t according to

Xi+ 1 = PI, tXlt

+

(1- PI, t) X2 t if Xt -

l ,;;

+ P2, t X2 t ifXt _ l > X*.

Figure 5 shows the results of a simulation (over 2,000
periods) with unchanged structural parameters and with
the same values for'Y and O. It is apparent that the broad
pattern of endogenous cycles remains. The main effect of
the "more sophisticated" forecast procedure is to speed
up the transition between regimes.
There are numerous other ways in which agents might
attempt to capture the dynamics of the system, but the
broad point seems clear. If agents allow for the possibility
of changes in regime when making their forecasts, this
reinforces the potential of productivity shocks and other
sources of intrinsic noise to induce, periodically, large selffulfilling changes in the level of economic activity.

V.

CONCLUSIONS

We have considered a macroeconomic model, incorporating production externalities and random productivity
shocks, which has the potential to generate two stable
stochastic steady states. For the structural parameter values
chosen, the number of stable steady states depends on the
monetary-fiscal policy parameter 'Y. When 'Y is low
(high), only the high- (low-) level steady state exists. Both
steady states coexist for intermediate values of 'Y.
If 'Y t varies sufficiently over time, and if agents use
20. If agents use a decreasing gain estimator, the system might converge
to a self-fulfilling solution in which the regime is a function of the
productivity shock.

12

2.2

Cl..

E

UJ

2.0

1.8

L..---'-_.L..-.........._ . J - -.........._ - ' - - - - - ' - _.........-..l.----.J

a

~

~

~

~

1~1~1~1~1~~OO

Period

X*,

and
Xi+l = (1-Pl, t) Xl t

E
~

adaptive forecasts with an appropriate constant gain
parameter, aggregate economic activity will periodically
shift between the high-level and low-level regimes. The
economy will exhibit hysteresis effects over the "business
cycle" in the response of output to policy. If instead 'Y t is
held fixed at an intermediate value, the economy can still
exhibit fluctuations bet\veen the t,vo regimes, driven no\v
by the productivity shocks themselves.
There is thus the potential for models with multiple
steady states to explain the empirical regime-switching
results documented by Hamilton (1989), Boldin (1990) and
Potter (1992).21
In our model the "switches" are determined by fundamentals, either by intrinsic productivity or taste shocks or
by policy changes. We emphasize, however, that no attempt
has been made in this paper to use empirically realistic
parameters or to fit macroeconomic data. 22 A large gap
currently exists between theoretical models of endogenous
fluctuations and their empirical implementation, and it
may be desirable to attempt calibration to observed fluctuations in future research.
We have emphasized the possibility that policy may have
a highly nonlinear response in these models, since it can
sometimes shift the economy between high-level and lowlevel steady states if the policy variable exceeds some
threshold. This is clearly an important phenomenon and
indicates that it would be worthwhile to examine the
performance of monetary feedback rules in such models.
21. Howitt and McAfee (1992) and Boldin (1990) have also noted this
potential connection.
22. A wider range of policy variables also could be incorporated.

Economic Review / 1993, Number 1

REFERENCES
Azariadis, C. 1981. "Self-fulfilling Prophecies." Journal ofEconomic
Theory 25, pp. 380-396.
Benveniste, A., M. Metivier, and P. Priouret. 1990. Adaptive Algorithms and Stochastic Approximations. New York: Springer
Verlag.
Boldin, M. D. 1990. "Characterizing Business Cycles with a Markov
Switching Model: Evidence of Multiple Equilibria." Research
Paper No. 9037. Federal Reserve Bank of New York.
Cooper, R., and A. John. 1988. "Coordinating Coordination Failures in
Keynesian Models." Quarterly Journal of Economics 113, pp.
441-464.
Diamond, P.A. 1982. "Aggregate Demand Management in Search
Equilibria." Journal of Political Economy 90, pp. 881-894.
Evans, G., and S. Honkapohja. 1991. "Increasing Social Returns,
Learning and Bifurcation Phenomena." Discussion Paper. London
School of Economics. (Forthcoming in Learning and Rationality
in Economics, ed. A. Kirman and M. Salmon. Oxford: Basil
Blackwell.)
_ _ _ _ _ , and
. 1992a. "Local Convergence of Recursive Learning to Steady States and Cycles in Stochastic Nonlinear Models." Mimeo.
_ _ _ _ , and
. 1992b. "On the Local Stability of
Sunspot Equilibria under Adaptive Learning Rules." Mimeo.

Federal Reserve Bank of San Francisco

_ _ _ _ _ , and
. 1992c. "Adaptive Learning and Expectational Stability: An Introduction." Discussion Paper. London
School of Economics. (Forthcoming in Learning and Rationality
in Economics, ed. A. Kirman and M. Salmon. Oxford: Basil
Blackwell.)
Grandmont, J-M. 1985. "On Endogenous Competitive Business Cycles." Econometrica 53, pp. 995-1045.
Guesnerie, R., and M. Woodford. 1991. "Endogenous Fluctuations."
Mimeo. Paris: DELTA.
Hamilton, 1. 1989. "A New Approach to Economic Analysis of Economic Time Series." Econometrica 57, pp. 357-384.
Howitt, P., and P. McAfee. 1992. "Animal Spirits." American Economic l'?eview 82, pp. 493-507.
Marcet, A., and T. Sargent. 1989. "Convergence of Least Squares
Learning Mechanisms in Self-referential Stochastic Models."
Journal of Economic Theory 48, pp. 337-368.
Potter, S. 1992. "A Nonlinear Approach to U.S. GNP." Mimeo. UCLA.
Turnovsky, S. 1969. "A Bayesian Approach to the Theory of Expectations." Journal ofEconomic Theory 1, pp. 220-227.
Woodford, M. 1988. "Expectations, Finance Constraints and Aggregate Instability." In Finance Constraints, Expectations and Macroeconomics, eds. M. Kohn and S.C. Tsiang, pp. 230-261. New
York: Oxford University Press.
_ _ _ _ _ , 1990. "Learning to Believe in Sunspots." Econometrica
58, pp. 277-307.

13

FDIC Improvement Act and
Corporate Governance of Commercial Banks

James R. Booth
Arizona State University and Visiting Scholar, Federal
Reserve Bank of San Francisco.

This paper examines provisions of the FDIC Improvement
Act related to corporate governance of banks. These
provisions focus on the composition and independence of
the audit committee and on increased regulatory influence
over executive compensation. The composition of audit
committees for a sample of banking firms for 1990 is
compared with those of industrial firms and with the
provisions of FDICIA. The findings suggest only minor
differences between banks and otherfirms; however, under
FDICIA provisions, large changes in the composition of
bank audit committees are likely. Provisions related to
compensation have focused on CEOs. To address this
issue, I compare the 1990 levels and factors explaining
differences in CEO compensation for a sample of banks
and industrialfirms. Thefindings suggest that bank CEOs
earn slightly less than their industrial counterparts and
that cross-sectional differences in CEO compensation in
banking and other industries are explained by similar
factors.

Most aspects of corporate governance have traditionally
been beyond the scope of corporate law and bank regulation. Recent problems in the savings and loan industry are
credited with motivating the FDIC Improvement Act of
1991 (hereafter FDICIA) provisions related to the role
of boards of directors in governing banks. Specific provisions are designed to strengthen the audit function of the
board and to have regulators develop guidelines for compensating directors and officers. Both provisions can be
viewed as increased regulatory influence on the previously
largely unregulated area ofcorporate governance in banks. 1
This article explores the provisions of FDICIA that
directly affect the board of directors' role in corporate
governance.2 After reviewing the issues of debate related to
compensation for boards of directors and CEOs, I compare
the composition of board audit committees for a sample
of banking and nonbanking firms. Additionally, I examine
whether the provisions of FDICIA related to the audit committee will substantially alter the composition of this
committee.
The provisions related to director and officer compensation appear to reflect the current national concern that CEO
pay is excessive. While the answer to this question is
beyond the scope of this paper, the focus here is to compare
levels of compensation for nonmanagement directors and
CEOs for the sample of banks and industrial firms. Additional analysis of CEO. compensation is undertaken to
determine if cross-sectional differences in CEO compensation reflect the same factors in banks as in industrial firms. 3

1. Nationally chartered banks have faced a minimal amount of regulation related to the size of the board and to stock ownership by the board
per the Banking Act of 1935 (see Brickley and James 1987 for a
discussion).
2. While one can argue that virtually all of the provisions will affect the
board, the focus here is on the impact of provisions related to the
composition of the audit committee and to guidelines for officer and
director compensation.
3. Recent controversy has developed in Japan over bank employee and
officer compensation relative to industrial firms. Some evidence suggests that, on average, Japanese bank executives eam 20 to 30 percent
more than their industrial counterparts.

14

Economic Review / 1993, Number 1

This will allow us to evaluate bank CEO compensation
relative to that of less regulated firms.
The empirical findings of this paper suggest that the
provisions of FDICIA related to the composition of the audit committee may cause major changes in current practices. For a sample of large banks I show that the audit
committee is composed of independent directors as traditionally defined. However, as interpreted under FDICIA,
considering outside directors of bank customers as a bank
customer likely will exclude current bank audit committee
members. The evidence related to compensation practices
suggests that, on average, CEOs ·of banks earn less than
their industrial counterparts. In analyzing cross-sectional
differences in CEO compensation between banks and
industrial firms the evidence presented suggests similar
factors appear to explain levels of CEO compensation
for banks and for industrial firms. These findings suggest
that banks do not appear to differ significantly from
their industrial counterparts in terms of the role of corporate governance in board audit committees and CEO
compensation.
The remainder of the paper is structured as follows: In
Section I, a brief description of the debate about the role of
boards of directors in corporate governance is summarized, followed by a brief review of the debate over
executive compensation. Section II describes the provisions of FDICIA related to the independence of the audit
committee and executive compensation. Section III presents the empirical analysis of the composition of audit
committees of banks, followed by the analysis of CEO
compensation for sample bank and industrial firms. The
article concludes with a discussion of the policy implications of these findings.

I.

BOARD OF DIRECTORS, CORPORATE
GOVERNANCE, AND CEO COMPENSATION

Board ofDirectors and Corporate Governance
Corporate governance has traditionally been beyond the
scope of corporate law and bank regulations. Regulations
related to transactions between directors and banks are
specific, but it is unlikely that these materially affect the
composition of bank boards of directors.
The last decade has seen numerous proposals for reforms in director selection and board composition. 4 The
traditional role attributed to corporate boards of directors is
to resolve conflicts of interest among decisionmakers and
residual risk-bearers. Their power arises from their ability
to hire, fire, evaluate, and compensate senior management
4. See Baysinger and Butler (1985) for a discussion of these proposals.

Federal Reserve Bank of San Francisco

teams. It is frequently argued that the selection of directors
is left almost totally to the discretion of the managers
whose behavior they are supposed to monitor (Dunn 1987,
Mace 1987, Vancil 1987). As a result, reform proposals
focus on greater board independence from firm managers.
These have ranged from requiring a majority of independent directors to requiring that no current or past employees
be on the board of directors with the exception of the CEO.
Empirical support for the benefits of board independence is reflected in a number of studies that have examined
market responses to changes in the composition of the
board and other managerial actions. Rosenstein and Wyatt
(1990) document a positive stock price response to the
appointment of an additional outside director but no significant price response to the appointment of an additional
inside director. Byrd and Hickman (1991) examine takeover activity and find a positive relationship between board
independence of bidding firms and wealth effects associated with tender offers. Additionally, Lee, et al. (1992) find
that greater board independence is associated with more
positive stock price response for firms undertaking leveraged buyouts.
Direct evidence on the monitoring actions of boards is
reported in Weisbach (1988) who finds that as the level
of board independence increases, the likelihood that the
board will replace the CEO after a period of poor performance increases. Brickley and James (1987) examine measures of perquisite consumption for a sample of banks and
conclude that a greater presence of outside directors reduces managerial consumption of perquisites when the
takeover market is limited by the presence of state regulation. They note that this may reflect differences in the cost
of producing banking services in the presence of increased
state banking regulations. In a more recent study of the life
insurance industry, Mayers, Shivdasani, and Smith (1992)
find evidence that for the companies where the takeover
market is absent (i.e., mutuals) outside directors are used
more extensively to monitor management.
Although virtually all previous studies have addressed
the composition of the entire board, many of the activities
of boards of directors are accomplished in smaller groups
or committees. A survey of the Fortune 1000 firms· by
Kesner (1988) showed an average of 4.3 committees, with
70 percent of sample firms maintaining between three and
five committees.
Kesner found that virtually all boards have audit, nominating, compensation, and executive committees, and that
their most common duties are as follows: The audit committee sets the scope and reviews audits with the external
auditors; the compensation committee reviews and makes
recommendations on compensation for senior management; the nominating committee considers stockholder

15

recommendations and selection of nominees for directors',
the executive committee acts in lieu of the full board if
immediate action is required and counsels the CEO on
ideas and proposals prior to disclosure to the full board.

CEO Compensation Debate
The motivation for incorporating regulatory oversight into
bank compensation appears to reflect congressional reaction to a few widely publicized abuses in the savings and
loan industry and to a growing sentiment that CEOs are
avel paid. The criticisms of CEO pay focus on concerns that
the level of pay in recent years is too high and that crosssectional differences do not reflect differences in firm
performance.
The concern about the level of CEO pay is not new.
Brownstein and Panner (1992) note that in 1939 President
Roosevelt railed against the "entrenched greed" of corporate executives. They also note that at that time the
U.S. Treasury published a list of executives earning more
than $15,000 dollars per year and the Securities and
Exchange Commission (SEC) started requiring corporations to submit detailed disclosure of executive compensation to shareholders.
The recent concern over pay has led to the SEC decision
that it will no longer permit corporations to exclude from
their proxy statements nonbinding shareholder proposals
concerning executive and/or director compensation. New
reporting requirements related to non~ash compensation
are also an outcome of this round of concern over CEO pay.
Additional pressure is forthcoming from large institutional shareholders and shareholder rights groups that have
negotiated changes in executive compensation at several
companies.
While FDICIA potentially affects a broad range of
compensation contracts, the primary focus is on CEO compensation. Previous studies have focused on economic
explanations for cross-sectional differences in CEO compensation and the degree to which compensation reflects
relative performance. Studies generally find that firm characteristics are able to explain 20 to 30 percent of the
variation in cash compensation (see Jensen and Murphy
1990b for a discussion). However, studies of the relationship between performance and compensation are mixed. 5
Generally, studies attempting to explain CEO compensation control for firm size, profitability, job tenure, plus
measures of ownership and control.

5. For a discussion of the issues, see Performance and Compensation:
An Issue of Corporate Governance pp. 1-102. Conference proceedings
from Northwestern University, January 13, 1992.

16

II.

PROVISIONS OF FDICIA RELATED
TO BOARD STRUCTURE AND COMPENSATION

While enhanced regulation likely will affect the composition of the entire board, proposals specifically focus on the
composition ofthe audit committee and on the activities of
the compensation committee. FDICIA introduces two regulations that potentially affect the structure and actions of
boards of directors in banks. The changes reflect the desire
to protect the soundness of the deposit insurance fund
through increased managerial accountability to the board
of directors and restrictions on employee compensation.
In an effort to improve accountability, the legislation
focuses on the composition and structure of the audit
committee of the board of directors. Specifically, under the
new legislation banks are required to have audit committees composed of outside directors that are independent of
the management of the institution. Additional requirements are imposed on "large" institutions: Their audit
committees must be composed of members who are not
large customers of the institution, who have banking or
related financial management expertise, and they must
have access to the committee's own outside counsel. The
magnitude of the changes in the composition of this
committee likely will reflect how precisely regulators
define "large customers" of the institution.
The legislation prescribes that the audit committee shall
review the external audit with management and the independent accountants. These actions are designed to
increase the independence of the audit committee, thereby
strengthening its ability to monitor management and curtail its risk-taking behavior.
The impact ofFOlCIA on board compensation committees is less direct. The activities of this committee typically
include reviewing and making recommendations to the
board, and in some cases setting senior management
compensation. The provisions do not specify the composition of compensation committees, but do provide more
oversight by regulators. The legislation calls for each
appropriate federal banking agency to prescribe guidelines
for reasonable compensation. Specifically the agencies are
to prohibit as unsafe and unsound any employment contract that could lead to a material financial loss to the
financial institution. Employment contracts are to include
any compensation or benefit agreement, fee arrangement,
perquisite, stock option plan, post-employment benefit, or
other compensatory arrangement that would provide any
executive officer, employee, director, or principal shareholder of the institution with excessive compensation,.
fees, or benefits. Additionally, the appropriate regulatory
agency is required to specify when compensation, fees, or
benefits are excessive. The factors to be considered include

Economic Review / 1993, Number 1

the combined value of all cash and noncash benefits provided to the individual, the compensation history of the
individual and other individuals with comparable expertise at the institution, the financial condition of the
institution, and compensation practices at comparable institutions, based on such factors as asset size, geographic
location, and complexity of the loan portfolio or other
assets. For post-employment benefits regulators must consider the projected total cost and benefit to the institutions,
any connection between the individual and any fraudulent
act or omission, breach of trust or fiduciary duty, or insider
abuse with regard to the institution, and other factors that
the agency determines to be relevant, and such other
standards relating to compensation, fees, and benefits as
the agency determines to be appropriate. These provisions
potentially restrict much of the power of board compensation committees in determining senior executives' salary
and board of directors' fees. Not surprisingly, this aspect of
FDICIA has been widely criticized within the industry.

TABLE 1
FIRM AND BOARD CHARACTERISTICS
BANKING
FIRMs a

NONBANKING
FIRMSb

SAMPLE CHARACTERISTICS

Size
Sales ($ millions)
Total Market Value ($ millions)
Profit ($ millions)
Number of Board Members

22
7,211.1
4,172.4
293.7
18.6

367
7,355.2
5,805.2
307.5
12.2

18,277
1,185
10.1
68%
34%
35%

20,021
923
7.7
45%
16%
34%

BOARD COMPENSATION

Annual Fee
Meeting Fee
Meetings per Year
Retirement Plan
Deferred Compensation Plan
Stock Purchase Plan
BOARD AFFILIATION AND OwNERSHIP

III.

EMPIRICAL ANALYSIS

To gauge the potential impact of FDICIA on bank boards I
examine the characteristics of boards for a sample of 22
banks and 367 nonbanking firms included in the S&P 500
in 1990. Public utility firms are excluded as a result of the
strict regulatory burden these firms face. Nonbank depository institutions are excluded from the banking firm sample. 6 Additional exclusions are due to incomplete data.
Sample data are based on 1990 proxy statements compiled
by the Investor Responsibility Research Center.
Summary statistics for sample firms are presented in
Table 1. Banks tend to have larger boards of directors than
nonbanking firms. The directors of banking firms meet
more frequently and are compensated at a slightly higher
level than those of nonbanking firms. Additional benefits
that may be provided to outside directors of corporations
include retirement plans, stock purchase plans and deferred compensation plans. Under a retirement plan, nonemployee directors receive all or part of their annual
retainer fee for a certain period of time after they retire
from the board. In a stock purchase plan, the company
grants nonemployee directors stock or stock options on
a regular basis, in addition to their regular compensation. Deferred compensation plans generally allow nonemployee directors to defer cash compensation (retainer
and meeting fees) until after they retire from the board, but
only if the funds are invested in shares of common stock or
stock equivalents.
6. Two savings and loan holding companies are excluded. Including
these firms does not materially affect the results.

Federal Reserve Bank of San Francisco

Ownership (mean)
Nonmanagement
Independent
Affiliated
Interlocking Directorships
Board Chairman is CEO

3.05%
81%
65%
16%
55%
89%

9.46%
73%
54%
19%
20%
70%

aIncludes two savings and loans.
bExcludes communications, electricity, water, and gas utilities.

The data in Table 1 indicate that banks use all three
methods of indirect compensation at least as frequently as
nonbanking firms and have director retirement plans and
deferred compensation plans more frequently than nonbanking firms. Data on the dollar value of each of these
plans are not available, but the frequency of their use
suggests that the benefits to being a bank director are
understated relative to nonbanking firms. However, it
should be noted that bank directors face increased potential
liability due to the presence of a maze of potentially litigious regulatory authorities.
Bank boards have, a larger percentage of nonmanagement directors (81 percent) than nonbanking boards in
the sample (73 percent). Nonmanagement directors are
divided into those affiliated with and those independent of
the company. To be classified as affiliated, a director must
hold one of the following relationships with the firm:
member of an insiders' stockholder group (10 percent or
more of voting stock); part of an interlocking directorship;
former employee; related to an officer; member of a professional firm that provides services to the company; a significant supplier/customer relationship; derive personal
benefit from the company. By these criteria, on average,

17

16 percent of banks' outside directors are affiliated and
19 percent of nonbanks' outside directors are affiliated.
These results are consistent with greater board independence for banking than for nonbanking firms. In contrast, evidence in favor of less independence for bank
boards is that the CEO is also chairman of the board in
89 percent of sample banks compared to 70 percent of
nonbanking firms. Interlocking directorships are present in
55 percent of sample banks versus 20 percent for the
nonbank firms. This difference likely reflects regulationinduced bank holding company structure under which
most banks operate. This structure encourages legally separate corporations under a bank holding company umbrella.
Although sample data are limited to a a small set of large
banks, they do suggest differences between the composition of boards of banks and nonbanking firms. The provisions ofFDICIA are intended to increase the independence
of bank boards in general and the audit committee in
particular. To gauge potential consequences of this legislation on board of director audit committees, I next consider
this committee in greater detail.

Evidence on Audit Committee Composition
Table 2 contains summary statistics for the composition of
the audit committees of sample firms. Commercial bank
audit committees average six directors as compared to four
for nonbanking firms. None in the sample report management directors on the audit committee. However, on average both banking and nonbanking firms have one affiliated
outside director on this committee. This indicates that
in percentage terms the audit committees of bank boards
are more independent than those of nonbanking firms.
Whether the composition of these committees meet the
requirements of FDICIA is unclear since it does not exclude
affiliated directors from this committee unless they are
judged to have a significant direct supplier/customer relationship. If ultimately directors with indirect relationships are considered to be de facto customers then the
composition of this committee will likely changesubstantially. For example, if outside directors of a bank customer
cannot serve on the audit committee of the bank, then
many .current bank directors will be precluded from this
committee.

TABLE 2
AUDIT COMMITTEE COMPOSITION

BANKING FIRMS

NONBANKING FIRMS

6.0
5.3
.7

4.2
3.5
.7

NUMBER OF MEMBERS (MEAN)
Independent
Affiliated
NUMBER
AFFILIATED DIRECTORS-FoRM OF AFFILIATION
Interlocking directorships
Fonner employee
Member of professional firm that provides services to the company
Derives personal benefit from company
Supplier/customer
Significant stockholder
INDEPENDENT DIRECTORS-OCCUPATION
CEO or other executive of large company
CEO or other executive of small company
Retired business person
University official
Academic
Works for non-profit
Self-employed
Investment and commercial bankers and insurers
Other

PERCENT

NUMBER

PERCENT

5
6
4
3
0
0

27.8
33.3
22.2
16.7
0
0

32
79
99
21
15
32

11.5
28.4
35.6
7.5
5.3
11.5

59
21
34
9
4

42.1
15.0
24.3
6.4
2.9
2.9
2.9

5

3.5

344
205
444
85
83
57
48
76
136

23.3
13.9
30.0
5.8
5.6
3.9
3.2
5.1
9.2

4
4

NOTE: ~eca~se data .were availa~le on audit committee composition for more nonbanking finns in the S&P 500, the size of that portion of the
sample III thIS table IS 462; the SIze of the sample of banking finns remains the same.

18

Economic Review / 1993, Number 1

Table 2 presents the form of director affiliation for the
members of the audit committees.· For bank audit committees, most affiliated directors are former employees (33.3
percent); in 27.8 percent of the cases, these directors are
part of an interlocking directorship; the remaining affiliated directors are either members of professional firms that
provide services to the firm (22.2 percent) or directors
that derive personal benefit from the company (16.7 percent). Nonbanking firms have fewer audit committee members that are part of interlocking boards of directors (11.5
percent) or are former employees (28.4 percent). Firms in
the nonbanking sample more frequently have members of
professional firms providing services to the firm (35.6
percent), significant stockholders (11.5 percent), and representatives of organizations that have significant supplier/customer relationships with the firm (5.3 percent).
For sample banks, independent director members of the
audit committee are composed more of current CEOs and
executives and relatively less of retired business persons
than are nonbanking firms. If independent directors having
affiliations with customers of the bank are considered to be
customers of the bank for regulatory purposes, as has been
suggested, this is not reflected here.
Under a standard interpretation of customers these findings suggest that the composition of audit committees of
large banks in the sample generally satisfies the spirit of the
related provisions of FDICIA. Under a more strict interpretation through third-party (outside director) affiliations, the analysis here understates the likely impact of
these provisions. While it is not possible to draw inferences
regarding smaller banks on this question, the provisions
are most strict for large banks. FDICIA guidelines likely
will lead to greater independence in the composition and
the operations of this committee. It is specified the committee will have access to its <Lwn outside counsel and thus
may provide a greater degree of direct monitoring of
management by this committee.

Evidence on CEO Compensation
No aspect of FDICIA has caused as much industry uproar
as the provisions related to officer and director compensation. Under FDICIA the appropriate federal banking
agency must prescribe compensation standards for all
insured depository institutions by August 1, 1993. The
standards are to apply to all forms of compensation for any
executive officer, employee, director or principal shareholder of the institution. The standards are to specify when
compensation, fees, or benefits are excessive, unreasonable, or disproportionate to services performed by the
individual after considering a long list of factors including

Federal Reserve Bank of San Francisco

all cash and noncash benefits, compensation history of the
individual compared to others of comparable expertise,
financial condition of the institution, compensation practices at comparable institutions, size, location, complexity
of loan portfolio, and other assets, and total projected
cost of post-employment benefits. Most of the debate in the
press has focused on CEO pay. In this study I focus on CEO
and board of director compensation.
Table 3 presents data on CEO compensation for the
sample of bank and industrial firms. CEOs of sample
banks have mean and median salaries of $936,000 and
$740,000 respectively, for 1990. Sample industrial firm
CEOs earned mean and median salaries of $1,183,000 and
$980,000 respectively, for the same period.
Assessing the value of noncash compensation is a difficult task subject to much debate. The most difficult component of compensation to value are stock option grants. For
the purposes of this paper I use the valuation technique and
data presented by Crystal (1991). This procedure assumes
the stock price will increase at the normally expected rate
for eight years, deducting the strike price and discounting

TABLE 3
. CEO COMPENSATION-SUMMARY STATISTICS
BANKING

NONBANKING

FIRMS

FIRMS

22

367

$740

$980

$420-1,580

$150-14,820

$936
$267
$409
$93
$1,705

$1,183
$1,246
$208
$190
$2,827

19%
86%
52%
19%

71%
24%
26%
5%

6.0
84%
14%

4.1
79%
17%

NUMBER OF CEOs

MEDIAN SALARY

+

BONUS

($ thousands)
RANGE OF SALARY

+ BONUS

($ thousands)
MEAN COMPENSATION

($ thousands)
Salary + Bonus
Stock Options
Restricted Stock
Preferred Grants
Total
USE OF NONCASH COMPENSATION

Stock Options
Restricted Stock
Preferred Grants
All Forms
COMPENSATION COMMITTEE COMPOSITION

Number of Members
Independent
Affiliated

19

the future gain. For restricted stock the value is assessed
as the product of the annualized number of restricted, or
free, shares granted to the executive and the market price
per share at the time of the grant. Performance grants
include awards of both stock-based performance shares and
performance units paid in cash. While these procedures
likely add some noise to the measure of total CEO compensation, the direction of any bias in the true value across
banks versus industrial firms as a result of these assumptions is unclear. Adding these components of compensation to the salary and bonus provides a measure of
total compensation for the sa.lllple of nonbanking firms
of $2,828,000, while for the sample of banking firms the
average is $1,705,000. This indicates that the addition of
noncash compensation further increases the divergence
between the total CEO compensation of nonbanking and
banking firms.
Table 3 also provides statistics on the percentage of each
group of sample firms using each type of noncash compensation. The sample of banking firms uses more forms of
compensation on average. Restricted stock is a particularly
popular form of compensation for bank CEOs, but as
indicated in the table, the size of these awards for 1990 are
a fraction of total compensation. Popular press accounts of
the excessive CEO pay debate suggest the lack of independence of the compensation committee is a factor. To
address this, the final section of Table 3 presents the
composition of the audit committees for sample banks and
industrial firms.
The data presented in Table 3 are used to determine
whether cross-sectional differences in the level of compensation between these two groups can be explained by firm
characteristics. Previous studies of the determinants of
CEO compensation suggest that among the factors important in explaining cross-sectional differences are firm size,
CEO tenure, whether the CEO is also chairman of the
board, ownership by insiders, and firm performance. These
studies have generally concluded that firm and performance characteristics have relatively low power to explain
cross-sectional differences in CEO pay. Since it is difficult
(and somewhat controversial) to value non-cash compensation the analysis initially will focus on cash compensation
and on a measure of total compensation. The cash compensation measure includes salary plus bonus as reported in
Crystal (1991) and is cross-checked against the data for the
same period from other sources. The estimates of the value
of non-cash compensation are those provided in Crystal
(1991).
The results from regressing CEO cash compensation
(salary + bonus) on firm characteristics are reported in
Table 4. Consistent with previous studies, cash compensation is a positive function of firm size measured by

20

TABLE

4

DETERMINANTS OF CROSS-SECTIONAL DIFFERENCES
IN THE LEVEL OF CEO CASH COMPENSATION

REGRESSION
VARIABLE

(1)

(2)

(3)

Constant

4.59
(18.78)*

4.58
(18.44)*

4.57
(18.44)*

Log (Sales)

0.12
(3.71)*

0.14
(3.77)*

0.14
(3.92)*

Log (Market Value)

0.15
(4.18)*

0.14
(3.97)*

0.14
(3.90)*

CEO Years

0.01
(1.99)*

0.01
(2.00)*

0.01
(1.94)*

Chairman

0.12
(1.98)*

0.12
(1.93)*

0.12
(1.87)*

Board Ownership

0.01
(2.51)*

0.01
(2.50)*

0.01
(2.66)*

-0.04
(0.38)

Bank

-0.17
(0.08)

-2.94
(0.84)

Bank

X

Sales

-0.18
(0.90)

-0.15
(0.70)

Bank

X

MV

0.23
(0.93)

0.48
(1.51)

Batik:

X

Chairman

Bank

X

Board Ownership

R2
F-value

0.01
(0.02)
-0.04
(1.93)*
.32

.32

.32

19.41

14.03

11.06

*Indicates the t-value is statistically different from zero at the 0.01
level.
NOTE: Values are corrected for heteroscedasticity using the procedure
by White (1980). Dependent variable: Salary + Bonus.

market value and total sales. Cash compensation is also
higher for those CEOs that also serve as chairman of the
board. CEO pay is a positive function of the number of
years the CEO has been in the job, and the percentage ofthe
firm owned by the board. The binary variable indicating
that the CEO is managing a banking firm is negative
though not statistically significant. These results suggest

Economic Review / 1993, Number 1

that bank CEOs earn cash compensation similar to that of
nonbank CEOs. To determine whether CEO pay is more or
less sensitive to firm characteristics the binary variable
bank is interacted with sales, market value, and return.
None of the interacted variables is statistically significant
at the 0.10 level.
In (3) the binary variable called "Bank" is interacted
with ownership percentage by the board of directors, with
whether the CEO is Chairman, and with the number of
years as a CEO. The coefficient on bank board ownership
percentage is negative and significant indicating that salary
and bonus of CEOs decline as ownership by the board
increases. This result is the opposite than that for nonbanking firms.
Using the measure of total compensation from Table 3
we are able to examine how the same independent variables relate to cross-sectional variation in CEO total compensation. The regression results are presented in Table 5.
Consistent with earlier findings for cash compensation,
total compensation is a positive function of firm size as
measured by sales and market value of equity. Total pay is a
positive function of CEO's tenure in the job and whether he
also serves as chairman of the board (though the coefficient
on "Chairman" is not statistically significant). The coefficient on total pay is negative, though not statistically
significant, relative to ownership percentage by the board
of directors. The coefficient on Bank indicates that total
pay for banks is not statistically different from total pay for
nonbanking firms. The coefficient on the ownership percentage by bank boards indicates that as board ownership
increases total compensation decreases (although the significance level on this coefficient is at the 0.11 level).
These results suggest that CEOs of banks earn levels of
cash and total compensation that are comparable to those
earned by nonbank CEOs. The most significant differences
between banks and nonbanking firms related to CEO compensation are related to how cross-sectional differences
in levels vary with ownership percentage by the board of
directors. For the sample as a whole, cash compensation is
a positive function of ownership percentage for the board
of directors. The measure of total CEO compensation is a
negative function of the ownership percentage by the board
of directors. For commercial banks total salary is less
sensitive to ownership percentage by the board and total
CEO compensation is more sensitive (negatively related)
than for the sample as a whole.

IV.

CONCLUSIONS

This paper examined the provisions of the FDIC Improvement Act related to the corporate governance of banks.
Specifically, the composition of the board audit committee

Federal Reserve Bank of San Francisco

TABLE

5

DETERMINANTS OF CROSS-SECTIONAL DIFFERENCES
IN THE LEVEL OF CEO TOTAL COMPENSATION
REGRESSION
VARIABLE

(1)

(2)

(3)

Constant

4.55
(12.70)*

4.53
(12.42)*

4.51
(12.46)*

Log (Sales)

0.13

,- 'i7)*

(?

'-·...,. ..... 1

0.14
'iQ)*

0.14
(2.62)*

Log (Market Value)

0.221
(4.20)*

0.21
(4.03)*

0.21
(4.07)*

CEO Years

0.01
(1. 73)

0.01
(1.70)

0.01
(1. 73)

Chairman

0.12
(1.27)

0.11
(1.20)

0.14
(1.47)

Board Ownership

-0.01
(1.32)

-0.01
(1.31)

-0.01
(1.11)

Bank

-0.09
(0.54)

1.12
(0.33)

5.12
(1.00)

(? ......

'/

Bank

X

Sales

-0.21
(0.72)

0.36
(Ll8)

Bank

X

MV

0.08
(0.22)

-0.16
(0.32)

Bank

X

Chairman

-0.30
(0.52)

Bank

X

Board Ownership

-0.05
(1.63)

R2
F-value

.27

.26

.27

15.92

10.65

9.02

*Indicates the (-value is statistically different from zero at the 0.01
level.
NOTE: See Note to Table 4.

for a sample of banks was compared to industrial firms and
to the guidelines under the Act. For 1990the 22 depository
institutions included in the S&P 500 show that for the most
part audit committees are composed of outside directors,
and typically one outside director has a direct affiliation to
the bank. These are likely to be replaced by more independent outside directors as a result of FDICIA. It has been

21

indicated that directors with affiliations as outside directors to customers of the bank are ineligible for the audit
committee. This suggests FDICIA will likely have a large
impact on composition ofthese committees for large banks.
Potential consequences of provisions related to officer
and director compensation are examined by focusing on
the levels of CEO and outside director compensation. A
comparison is made between banking and industrial firms
regarding the level and form of compensation. Crosssectional differences in the levels of CEO compensation are
examined to determine if firm characteristics can explain
cross-sectional variation in CEO compensation for banks
and nonbanking firms. The results indicate factors important in explaining CEO compensation for the S&P 500
firms also explain cross-sectional differences in CEO compensation for banking firms. Differences between banking
and nonbanking firms are primarily related to the relationship between equity ownership by the board of directors
and the level of CEO compensation. Both cash and total
compensation for bank CEOs is a negative function of
equity ownership by the board of directors. For the sample
as a whole, CEO cash compensation is a positive function
of ownership by the board, while total compensation is a
negative (though statistically insignificant) function of
ownership by the board of directors.
One interpretation of the findings of this study is that the
provisions of the FDIC Improvement Act of 1991 related to
corporate governance and CEO compensation were unnecessary. The basis for this is that audit committees for large
banks, the apparent target of this legislation, are already
composed mainly of outside directors. Secondly, the compensation of bank officers (CEOs) and directors (outside)
appears to be at similar levels and largely determined by
characteristics similar to those of nonbanking firms. While
it is beyond the scope of this paper to determine whether
the overall level of CEO pay is excessive, it does conclude
that there appears to be nothing special about banks in this
regard.

REFERENCES
Baysinger, B.D., and H.N. Butler. 1985. "CorporateGovernance and
the Board of Directors: Performance Effects of Changes in Board
Composition," Journal of Law, Economics, and Organization
(Spring) pp. 101-124.
Brickley, lA., and C. James. 1987. "The Takeover Market, Corporate
Board Composition, and Ownership Structure: The Case of Banking." Journal of Law and Economics (April) pp. 161-181.
Brownstein, A., and M. 1 Panner. 1992. "Who Should Set CEO Pay?"
Harvard Business Review (May-June) pp. 28-32.
Byrd, l, and K. Hickman. 1991. "Do Outside Directors Monitor
Managers? Evidence from Tender Offer Bids." Working Paper.
Washington State University.
Crystal, G. 1991. Executive Compensation in Corporate America '91.
Washington, D.C.: The United Shareholders Association Foundation for Research and Education.
Dunn, D. 1987. "Directors Aren't Doing Their Jobs." Fortune (March
16) pp. 117-119.
Herma1in, B., and M. Weisbach, "The Determinants of Board Composition." Rand Journal of Economics (Winter 1988), pp.
589-606.
Jensen, M.C., and K. Murphy. 1990a. "Performance Pay and TopManagement Incentives." Journal of Political Economy (April)
pp. 224-264.
Jensen, M.C., and K. Murphy. 1990b. "CEO Incentives-It's Not How
Much You Pay, But How." Harvard Business Review (May-June)
pp. 138-153.
Kesner, I. 1988. "Directors' Characteristics and Committee Membership: An Investigation of Type, Occupation, Tenure, and Gender."
Academy of Management Journal (March) pp. 66-84.
Lee, C., S. Rosenstein, N. Rangan, and W. Davidson. 1992. "Board
Composition and Shareholder Wealth: The Case of Management
Buyouts." Financial Management (Spring) pp. 58-72.
Mace, M.L. 1971. Directors: Myth and Reality. Boston: Harvard
Business School Press.
Mayers, D., A. Shivdasani, and C. Smith. 1992. "Board Composition
in the Life Insurance Industry." Working Paper. University of
Rochester.
Rosenstein, S., and lG. Wyatt. 1990. "Outside Directors, Board
Independence, and Shareholder Wealth." Journal of Financial
Economics (August) pp. 175-192.
Vancil, R. 1987. Passing the Baton: Managing the Process of CEO
Succession. Boston: Harvard Business School Press.
Weisbach, M. 1988. "Outside Directors and CEO Turnover." Journal
of Financial Economics (January/March) pp. 431-460.
White, H. 1980. "A Heteroskedasticity-Consistent Covariance Matrix
Estimator and a Direct Test for Heteroskedasticity." American
Economic Review (May) pp. 817-838.

22

Economic Review / 1993, Number 1

Do Capital Controls Affect
the Response of Investment to Saving?
Evidence from the Pacific Basin

Sun Bae Kim
Economist, Federal Reserve Bank of San Francisco. I am
grateful to Reuven Glick, Michael Dooley, and the editorial
committee ofBrian Cromwell, Mark Levonian, and Ramon
Moreno, for their numerous helpful comments and suggestions. I also wish to thank Gregory Holmes for his valuable
research assistance.

This paper examines the effect of capital controls on the
response of investment to savings in Pacific Basin countries. A robust finding is that the size of the savings
coefficient tends to be smaller (larger) in countries with
relatively higher (lower) capital controls. Additionally,
relaxation in capital controls for the most part had no
discernible impact on the savings-investment relationship
in individual country time-series regressions. At least a
partial resolution to these puzzles is found in the government policy response: Countries with a relatively high
saving-investment correlation tended to have governments
that countered widening current account imbalances with
fiscal policy; the reverse generally held true for countries
with low saving-investment correlation. In fact, for this
latter group ofcountries, financing the government deficit
throughforeign borrowing was a majorfactor in loosening
the link between national saving and investment.

Federal Reserve Bank of San Francisco

The last two decades have witnessed a successive wave of
deregulation ofinternational capital markets. How has this
greater freedom of movement of capital among countries
affected national saving and investment, two key macroeconomic variables? Theoretically the answer is relatively
straightforward: With greater capital mobility, the level of
investment a country can undertake need not be constrained by the level of domestic saving, since any shortfall
can be financed by foreign saving. In other words, the
dismantling of capital controls would loosen the link
between national saving and investment.
The empirical evidence, on the other hand, has been
more controversial. Most notably, Feldstein and Horioka
(1980) found that among industrial countries, the investment rate is highly correlated with the saving rate, thus
suggesting that capital is less mobile internationally than
commonly presumed. The study subsequently spawned
two additional puzzles: First, the saving-investment correlation does not appear to decline over time despite the
continued relaxation of capital controls (Feldstein 1983,
Penati and Dooley 1984); second, the saving-investment
correlation appears to be weaker for developing countries
than for industrial countries, despite the generally accepted
view that the latter group of countries tend to have more
developed financial markets with comparatively fewer restrictions on international transactions (Dooley, et aI.,
1987, Wong 1990). In sum, available evidence to date
suggests that the degree of capital control has relatively
little bearing on the observed response of investment to
national saving.
This paper examines the effect of capital controls on the
response of investment to saving in Pacific Basin countries.
The exercise is of interest for at least two reasons. First,
a frequently emphasized factor in the economic dynamism
of the Pacific Basin is the growing integration of the
region, in terms of flows of both goods and capital.
Whether one can find a systematic link between progressive dismantling of capital controls and loosened savinginvestment linkages in the region is an empirical question
that has not been addressed to date. Second, the Pacific

23

Basin encompasses a broad array of countries in varying
stages of economic and financial development, degree of
capital controls, and speed of dismantling these controls.
The region therefore provides us with substantial crosscountry variation to assess the impact of capital controls on
saving-investment linkages.
This study uses the Feldstein-Horioka (FH hereafter)
methodology with due adjustments made to address some
of the econometric criticisms levied against it. Unlike most
empirical work in the area, the paper focuses on time series
correlation between savings and investment. This approach allo\vs cross-countI"'j comparisons in the response
of investment to national savings, as well as analysis of the
relationship over time in a given country. The advantage of
this approach is that it makes it possible to exploit our
knowledge of the divergent history of capital controls of
the countries in the region.
The analysis reveals that capital controls have had little
impact on saving-investment relationships in the Pacific
Basin. In fact, the estimated size of the savings coefficient
tends to be smaller (larger) in countries with relatively
higher (lower) capital controls, and this result is robust
across several specifications. Additionally, relaxation in
capital controls for the most part had no discernible impact
on the saving-investment relationship in individual country
regressions. At least a partial resolution to these puzzles is
found in government policy response. Most notably, countries with a relatively high saving-investment correlation,
despite low capital controls, tended to have governments
that countered widening current account imbalances with
fiscal policy. The reverse generally held true for countries
with low saving-investment correlation, despite relatively
high capital controls. In fact, for this latter group of
countries, financing the government deficit through foreign
borrowing was a major factor in loosening the link between
national saving and investment.
The balance of the paper is organized as follows. Section
I surveys changes in capital controls in the Pacific Basin
countries over the past three decades. Section II briefly
discusses the FH test of capital mobility and reviews some
of the major .criticisms leveled against it. Section III then
undertakes various tests of saving-investment correlation
in the Pacific Basin countries and interprets the results in
light of what we know about the history of capital controls
in the region. Section IV concludes.

I.

DEREGULATION OF CAPITAL CONTROLS
IN THE PACIFIC BASIN

In order to provide a more concrete context for the empirical analysis that follows, this section highlights some of the
important policy changes affecting capital flows that have

24

occurred in the thirteen Pacific Basin countries up until
1991 (Australia, Canada, Hong Kong, Indonesia, Japan,
Korea, Malaysia, New Zealand, the Philippines, Singapore, Taiwan, Thailand, and the U.S.). The purpose here is
not to provide an exhaustive and comprehensive account of
financial deregulation in the region. Rather, the basic aim
is to sketch out the salient features of the regulatory environment of the countries under review, then draw some
cross-country comparisons on the degree of capital mobility and how such mobility may have changed over time in
individual countries as a result of policy reforms.
Until at least the late 1970s, most Pacific Basin countries
maintained tight regulation and administrative control over
their financial systems, including interest rate restrictions, segmented financial markets and institutions, underdeveloped money and capital markets, and credit allocation
and control mechanisms. 1 These policies reflected the then
widely held view that economic growth and other national
goals would be better served by restraining market forces in
the pricing as well as the allocation of credit.
In order to prevent domestic entities from circumventing
these regulations through overseas transactions, most Pacific Basin countries also applied, to varying degrees,
controls over international capital movements. Capital
controls curbed capital flight, insulated domestic interest rates from the rest of the world, and maintained
the compartmentalization of domestic financial markets.
Additionally, these co,ntrols buttressed the fixed exchange
rate system and helped to achieve balance-of-payments
objectives.
As is evident from the summary of capital controls in the
Appendix, Pacific Basin countries diverge considerably as
to when liberalization of capital controls was intiated,
as well as with respect to its speed once the process was
under way.2,3 At one end of the spectrum are four coun-

1. For overviews of financial markets and liberalization in the Pacific
Basin up to the mid-1980s, see Cargill, Cheng and Hutchison (1986),
Mathieson (1986), Patrick and Cole (1986), and Greenwood (1986).
2. Countries also have diverged in the sequencing of deregulation; that
is, whether relaxation of international capital accounts followed or
preceded liberalization ofthe domestic financial sector. According to the
so-called sequencing theory (McKinnon 1991, Edwards 1990), internationalliberalization, particularly of the capital account, should come at
the last stage of economic liberalization. Within the Pacific Basin,
Singapore, Korea, and Taiwan have broadly conformed to this theory by
liberalizing the domestic financial sector while maintaining a considerable degree of capital control. Indonesia, Malaysia, Japan, and Thailand
appear to have adopted a reversed order of financial liberalization. See
Santiprabhob (1992).
3. Emphasis differs on what has been the prime impetus to relaxing
exchange and capital controls. Cargill, Cheng, Hutchison (1986) contend that strict exchange and capital controls were not compatible with

Economic Review / 1993, Number 1

tries, consisting of Canada, the United States, Hong Kong,
and Singapore, which traditionally have imposed few restrictions on international capital flows or removed any
existing restrictions relatively swiftly. The U.S. and Canada have long had a large and sophisticated financial
system relatively unencumbered by regulations, domestically as well as internationally. The U. S. imposed no
exchange controls in principle except for the period of
1963-1974 when some restrictions applied to capital outflows; these restrictions were removed in 1974. Canada,
the first industrialized country to shift to a floating exchange rate regime in 1970, also has been free of exchange
controls. Over the years, the country also streamlined
procedures for foreign direct investment flows which were
quite liberal to begin with by international standards. For
both countries, therefore, regulatory changes pertaining to
international capital flow since the 1970s have been small
by international standards.
Hong Kong and Singapore relaxed capital controls relatively early in a bid to become international financial
centers. Hong Kong abolished all exchange controls in late
1972, making its capital markets one of the least restricted
in Asia. Singapore progressively liberalized exchange controls through the 1970s and finally abolished them in 1978.
The city-state also established a favorable policy environment toward foreign direct investment, especially with
respect to repatriation of profit. The only notable remaining barrier to capital mobility is the restriction that banks
designated to operate in the offshore market are not allowed to transact in Singapore dollars. 4 From the standpoint of regulatory impediments at least, both Hong Kong
and Singapore can thus be considered to have had nearly
perfect capital mobility since at least the early to mid1970s.
In contrast to Hong Kong and Singapore, the two other
rapidly growing Asian newly industrializing economies
(NIEs), Korea and Taiwan, have initiated financial deregulation relatively late and substantial barriers to international capital mobility still remain. Taiwan traditionally

domestic interest rate liberalization and greater exchange rate flexibility.
In fact, exchange and capital controls are redundant in the face of
flexible interest rates and flexible exchange rates. Greenwood (1986), on
the other hand, holds the view that financial liberalization in the seven
East Asian countries do not appear to derive from the advent of floating
exchange rates in the early 1970s. Most of the changes come after 1979,
which timing suggests that financial liberalization was prompted more
by the volatility of interest rate differentials than by the advent of
floating rates.
4. Singapore thus has a bifurcated financial system with various regulations insulating the domestic banking sector from the offshore market.
Growth of the offshore sector, in particular the Asian dollar market, has
been spectacular since its establishment in 1974.

Federal Reserve Bank of San Francisco

has restricted capital outflow and did not liberalize controls
on current account transactions until 1987. Although significant progress has been made since 1989 in liberalizing
capital inflow and outflow, tight control is still applied on
foreign ownership of "strategic" industries, including
banking.
Korea began its financial liberalization process in 19811983. But government controls remain a pervasive feature
of its financial system, particularly in the domain of
international financial transactions. The authorities have
adopted a gradual step-by-step approach to liberalizing
Clli.-rent account transactions and restrictions continue to
apply to both capital inflows and outflows. 5 For example,
throughout the 1980s, government approval was required
for any external borrowing exceeding US$200,000. Beginning in the early 1980s, however, the Korean government initiated a series of steps deregulating foreign direct
investment to enhance competition in the domestic market
and to encourage transfer of advanced technology from
abroad.
The Philippines also still has extensive capital controls.
Unlike Korea and Taiwan, the Philippines initially had a
fairly liberal regime toward international capital flow. This
policy was abruptly reversed, however, with the advent of
the international debt crisis in 1983. As the only Pacific
Basin country facing serious debt servicing problems, the
Philippines reimposed foreign exchange controls in 1983.
Although policies have relaxed somewhat since, restrictions remain in virtually all categories of both current and
capital account transactions.
The experiences of the remaining six countries (Australia, Indonesia, Japan, Malaysia, New Zealand, and Thailand) fall somewhere between the extremes of the two
groups of countries discussed above. All six initially
had stringent international capital exchange controls. The
speed and the timing of the relaxation of these controls
have varied considerably among them, however.
Indonesia and Malaysia liberalized foreign exchange
controls in 1970 and 1973, respectively, thus initiating
moves toward fairly open capital markets much earlier than
Taiwan or Korea. Both countries also progressively relaxed
foreign direct investment rules from the mid-1980s on.
Some restrictions to capital flow remain, however. In the
case of Malaysia, capital outflows cannot be financed by
local borrowing and prior approval is necessary for foreign

5. As of December 1991, Koreans were still required to convert export
receipts into domestic currency within a specified time period. The main
objective of this policy is to prevent the accumulation of foreign
exchange above some minimum working balance. In addition, to limit
possible disguised capital flight, payments on invisibles were subject to
quantitative limits or advance approval.

25

direct investment or foreign lending or borrowing by financial institutions. Additionally, surrender requirements for
export proceeds still remained in place as of December
1991. Indonesia still restricts capital account transactions
in three ways: foreign exchange banks and nonfinancial
institutions must adhere to Bank of Indonesia directives
when borrowing abroad; foreign exchange banks are required to set aside special reserves on foreign borrowing;
and finally, prior approval must be obtained for foreign
direct investment. 6
Australia and New Zealand embarked relatively late in
financial liberalization, but once initiated, regulatory barriers to capital mobility were dismantled quite quickly.
Australia eliminated most exchange controls as of December 1983 when it moved to a flexible exchange rate regime.
Beside the frequently encountered requirement of prior
approval on foreign borrowing, the only notable restriction
to capital flows in Australia is that foreign governments and
international organizations are not permitted to borrow in
the domestic capital market. New Zealand launched a
comprehensive financial liberalization program in 1984
which, within a space of a few months, freed interest
rate controls, credit ceilings, and ratio requirements, and
floated the New Zealand dollar. 7 In this newly liberalized
regime, foreign exchange controls became redundant and
were disposed of accordingly. As of the end of 1991, the
only noteworthy restriction on capital account transactions
is that permission is required for foreign direct investments
of amounts NZ$lO million or greater.
Thailand and Japan, the last two countries under review,
have both adhered to a program of cautious and measured
pace of financial liberalization. Thailand freed inward capital flows in the early 1970s, but strict controls have
traditionally applied to capital outflows. This restriction
began to be loosened only recently in a stepwise fashion.
The first stage (May 1990) eased controls on current
account transactions and simplified capital account transactions. In the second stage (April 1991), further liberalization was implemented on current account transactions,
limits on outward capital flows without authorization was
raised, and banks were allowed for the first time to offer
foreign exchange accounts. 8 In the final stage, yet to be
6. Recently, concern about the country's external debt has led Indonesian authorities to set an annual quota of US$2.6 billion for borrowing to
finance private projects in 1992 and 1993.
7. New Zealand in fact initiated financial liberalization in 1976-1977,
but reversed course in 1981 by reimposing comprehensive controls over
interest rates and foreign portfolio investment by domestic residents.
8. According to the International Monetary Fund, Thailand still had,
as of December 1991, surrender requirement for export proceeds, advanced import deposits, and limitations on foreign currency deposits by
residents.

26

scheduled, all remaining foreign exchange controls are to
be lifted and residents are to be permitted to purchase
overseas property and financial instruments without prior
approval from the Central Bank.
Japan traditionally applied capital controls to influence
international capital flows in the desired direction, depending upon the prevailing balance-of-payments position
and exchange rate objective. Japan amended its Foreign
Exchange and Foreign Trade Law in 1980, the official
intention being to free, in principle, all international transactions from direct government intervention. In reality,
however, the process of financial liberalization, domestic
as well as international, was already set in motion by the
rnid-1970s. For example, interest rates on foreign currency
deposit were liberalized in 1974, foreigners were allowed
in the gensaki market in May 1979, and Japanese banks
were permitted to make short-term foreign currency loans
to residents (impact loans) in June 1979, and long-term
loans in March 1980. The 1984 Yen/Dollar Agreement provided further impetus to remove barriers to international
capital flows, including the abolition of yen-dollar swap
limits for foreign banks in Japan and the deregulation of
forward exhange transactions. The relaxation of capital
controls in Japan, however, as is the case with domestic financialliberalization, has been gradual and is still ongoing.
In summary, what can we say about capital mobility in
the Pacific Basin based on the foregoing survey of regulatory changes? First, most liberalization in the region did
not begin until the late 1970s or the early 1980s; notable
exceptions are Canada, the U.S., and the two city-states.
One implication is that saving-investment linkages would
be tighter in most Pacific Basin countries than, say, among
OECD countries, which began liberalizing in the early
1970s with the advent of flexible exchange rates. 9
The second point relates to the difference in the degree
of capital mobility among the Pacific Basin countries
discussed. Any cross-country comparison on capital
mobility based on these regulatory considerations is necessarily an imprecise exercise. For one, appraising the impact
of a change in policy on potential capital mobility requires
a dose of subjective and qualitative judgements. In addition, since these countries have pursued different policies
at different points in time, it is difficult to generalize across
a long period of time whether one country's policy has been
"on average" more restrictive than another with respect to
international capital flows. These caveats notwithstanding,
one may hazard to divide the Pacific Basin countries into
three groups on the basis of how early each deregulated
international financial transactions, and on how rapidly

9. The usual ceteris paribus condition applies here.

Economic Review / 1993, Number 1

capital controls were dismantled once deregulation was
initiated. The first group, which includes Canada, the
U.S., Hong Kong, and Singapore, may be categorized as
having a relatively low degree of capital controls, while the
second, consisting of Korea, the Philippines, Taiwan, and
possibly Thailand, may be deemed to have a high degree of
capital controls. It is difficult to assign a precise ranking to
the remaining countries; hence they may be grouped under
a third category of intermediate degree of capital controls.
The balance of the paper investigates the extentto which
these varying degrees of capital controls in the region
explain observed differences in the response of domestic
investment to national saving.

II.

THE FELDSTEIN-HoRIOKA TEST
OF CAPITAL MOBILITY

It is natural to expect that the degree of capital controls is
an important determinant of investment's response to
national saving. Consider two extreme cases. If capital
controls prevent a country from borrowing (or lending)
internationally, all investment within the country must
necessarily be financed out of its own saving; in other
words national saving and investment will be perfectly
correlated. On the other hand, if there were no impediments to international capital flows, one would expect no
systematic relation between national saving and investment. One direct way to test these propositions is to run a
regression of the form:
(1)

(GDIIGDP)i

=

ex + f3(GNSIGDP)i +

Ei

where GDI and GNS are gross domestic investment and
saving, respectively, and GDP is gross domestic product.
This is in fact the regression that Feldstein and Horioka ran
on a cross-section of sixteen OECD countries over the
period 1960-1974. The regression using data averaged over
the entire sample period yielded a coefficient on saving of
0.88, which is significantly different from zeto but not
significantly different from unity. Similar estimates of f3
were obtained when the regression was repeated on shorter
subsample periods. FH interpreted these results to mean
that about 90 percent of domestic saving is invested in the
country of origin, thus leading them to reject the hypothesis of perfect capital mobility. 10 However, this conclusion
has been subjected to a number of criticisms.

10. Feldstein (1983) subsequently estimated the same equation using
pooled time series cross-section. data. Again, the coefficient on the
saving rate did not differ significantly from unity.

Federal Reserve Bank of San Francisco

Criticisms
The most frequently levied criticism against the FH methodology concerns the fact that the explanatory variable in
their regression, domestic saving, is itself endogenous.
This will be the case, for example, if saving and investment
are both procyclical, as they are commonly known to be.
Simultaneity problems also will arise if governments are
averse to large current account balances and respond
endogenously to offset private net capital flows so as to
reduce the size of these imbalances (Fieleke 1982, Westphal 1983; Summers 1988). In a time series context. the
inclusion of large countries in the sample may be an~ther
cause of endogeneity. For instance, if a country is sufficiently large, a decrease in saving in that country would
raise the world interest rate, thus reducing investment at
home as well as abroad (Murphy 1986).
On the theoretical front, a plethora of models has been
constructed to formalize the notion that rather than reflecting any. genuine lack of capital mobility, the high
saving-investment correlation may arise because saving
and investment are influenced in the same direction by
common exogenous disturbances affecting the economy.
For example, even with perfect capital mobility, exogenous
changes in population growth, the growth rate of income,
productivity, or terms-of-trade shocks, may all generate
co-movements in savings and investment (see, for example, Obstfeld 1985, Summers 1988, Glick and Rogoff
1992).1 1
Co-movements in saving and investment also may be
reconciled with perfect financial capital mobility by the
presence of nontraded consumption goods or immobile
factors of production (Frankel 1985, Murphy 1986; Engel
and Kletzer 1987, Wong 1990). The basic intuition here is
that the integration of capital markets is not a sufficient
condition to break the link between domestic saving and
investment; imperfect integration of goods. markets or
other factors of production may act as a binding constraint
and force the economy to behave more like a closed
economy in terms of saving and investment.
Finally, several authors have suggested that government
policy itself may be a source of endogeneity. Summers
(1988) and Bayoumi (1990) among others have suggested
that the observed high correlation between saving and
investment rates is evidence of a successful balance-ofpayment policy on the part of national governments. For
instance, governments may impose constraints on crossborder capital flows whenever the deficit (or surplus) in the
current account exceeds a predetermined level. Alternatively, they might adjust their budget deficits to offset
11. See Tesar (1991) for a survey of these models.

27

the gap between investment and saving. Finally, Roubini
(1988) argues in the context of an intertemporal model of
consumption and taxation that fiscal deficits play an important role in the determination of the current account and the
saving behavior.

Robustness of the FH Result

higher regression coefficient on saving and a better goodness of fit. Wong also found that a Chow test rejected at the
5 percent significance level the null hypothesis that the two
country groups exhibit the same structural saving-investment relationship. Splitting the sample into finer groups
confirmed the basic finding that as countries' import ratios
decrease the saving-inv~stment correlation increases.

In their original 1980 study, Feldstein and Horioka were in
fact cognizant of potential problems that might arise due to
the endogeneity of domestic saving. To control for cyclical

m.

endogeneity, the authors ran their cross=section regressions

Simple Saving-Investment Correlation

using averaged data over sufficiently long periods so as to
cancel out any business cycle effects. As an added measure, FH also reran their regressions using instrumental
variables that are correlated with saving but not investment. 12 This did not materially alter the results, however.
Moreover, instrumental variable estimations were subsequently performed by Dooley, et al. (1987) and Bayoumi
(1990) on cross-section data, and by Frankel (1985) on U.S.
time series data. But again, all of these studies found that
the high savings-investment correlation persisted.
At least for a sample of industrialized countries, the FH
finding of a high saving-investment correlation thus seems
to have stood up surprisingly well to the econometric
critiques levied against it. As noted above, however, numerous theoretical models have cast doubt on whether
this empirical finding can be taken as evidence of low
capital mobility. To the extent that one. questions whether
FH's equation is genuinely structural, the high savinginvestment correlation may be attributed to a set of "omitted variables," such as some common shocks or the extent
of integration of domestic goods and factor markets. However, relatively little empirical work has been done to test
directly how sensitive FH's saving-investment correlation
is with respect to the inclusion of such variables.
A notable exception is Wong (1990), which examined
whether the relative size of the nontraded goods sector of an
economy has any effects on the correlation between its
saving and investment ratios. Wong ranked a sample of 40
developing countries by theirimport-GDP ratios, as a proxy
for the inverse of the size of the nontraded goods sector.
Breaking the sample into two and running separate regressions on them, Wong found that the group with the lower
import ratios (that is, larger nontraded goods sector) had a
12. The instruments consisted of the proportion of retirees and dependents in the total population, the benefit-earning ratio of the social
security program, and the labor force participation rate. All of these
variables affect saving according to the income hypothesis, but they have
no obvious relevance for investment.

28

SAVING-INVESTMENT CORRELATION
IN THE PACIFIC BASIN

To serve as a benchmark, Table 1 presents the ordinary
least squares results for individual country time series
regression:

(2)

t!.(GDIIGDP\ = a

+ t!.f3(GNS/GDP)t + Et .

The sample period runs from 1961 to 1990 and all data used
are nominal annual national account data from the IMF's
International Financial Statistics. Gross domestic investment, GDI, is defined as the sum of gross fixed capital
formation and the change in stocks. Gross national saving,
GNS, is defined as gross domestic saving (GDS) plus net
factor income and net current transfers from abroad; GDS,
in turn, is defined as gross domestic product (GDP) minus
private and government consumption. 13 Since both the
saving and investment exhibited a tendency to rise over
time in many of the sample countries, the regressions were
run on first-differenced data. 14
One advantage of running individual country time series
regressions is that it allows for any possible differences in
the degree of capital mobility. Inspection of Table 1 readily
reveals the diversity in the size and statistical significance
of the regression coefficient. Indeed, F tests rejected the
validity of pooling for various combinations of the sample
countries: countries with relatively low capital controls
(Canada, U.S., Hong Kong, and Singapore); countries
with relatively high capital controls (Korea, Taiwan, Philippines, and Thailand); industrialized versus developing
countries; and finally, larger versus smaller countries as
measured by the size of GDP.

13. As in Feldstein and Horioka (1980), the focus is on gross rather than
net saving and investment so as to minimize the possibility of spurious
correlation due to measurement errors in depreciation.
14. Dickey-Fuller tests could reject the null hypothesis of a unit root in
GDSIGDP and GDIIGDP only for New Zealand and Philippines. The
same test on the first-differenced series rejected this null, that is, year to
year changes in saving and investment rates appear stationary.

Economic Review / 1993, Number 1

TABLE

1

TOTAL INVESTMENT-SAVING CORRELATION,

1961-1990
tJ.(GDIIGDP)t

= ex + f3tl(GNSIGDP\
[3

R2

D.W.

Australia

0.001
(0.157)

0.00

2.40

Canada

1.017***
(0.160)

0.60

2.27

Hong Kong

0.616***
(0.162)

0.31

2.13

Indonesia

0.211
(0.141)

0.08

2.32

Japan

0.981***
(0.139)

0.65

1.54

Korea

0.446***
(0.154)

0.24

1.76

-0.112
(0.152)

0.02

1.43

0.116

0.01

1.97

0.360*
(0.218)

0.06

1.54

-0.041
(0.263)

0.09

1.92

Taiwan

0.076
(0.249)

0.00

2.10

Thailand

0.639***
(0.181)

0.31

2.36

U.S.

0.939***
(0.126)

0.69

1.56

Malaysia

New Zealand

(0.249)
Philippines

Singapore

NOTE:OLS estimation; standard errors in parentheses.
*Significance levels:
* = 10 percent
** = 5 percent
*** = 1 percent

An immediately striking pattern in the table is that
Canada, the U. S., and Japan have a regression coefficient
on saving that is not significantly different from unity; that
is, a 1 percent increase in the growth of the national saving
rate leads to a 1 percent increase in the growth of the

Federal Reserve Bank of San Francisco

domestic investment rate. 15,16 It is difficult to reconcile this
result with what we know about ca~ital controls in these
countries. As the earlier discussion stressed, Canada and
the U.S. have had among the least restrictive policies with
respect to international capital flows while Japan may be
considered an intermediate case.
Significantly lower coefficients are obtained for Korea,
Thailand, and the Philippines (0.446, 0.639, and 0.360,
respectively), despite the fact that these countries traditionally have imposed much greater regulatory barriers to
international capital flows. In a similar vein, Australia,
New Zealand, and Taiwan-countries which maintained
relatively strict capital controls until at least the early
1980s-all have coefficients that are not statistically different from zero.
To investigate whether deregulation ofcapital controls in
the Pacific Basin has increased capital mobility and thereby
weakened the linkage between national saving and investment, regressions were run with the coefficient on saving
interacted with a dummy variable. This variable took a value
of 0 until a given breakdate and a value of 1 thereafter. The
breakdates for each country were chosen to coincide with
the shift in regulatory regime or, in the case of advanced
industrialized countries, the advent of the flexible exchange
system after the collapse of Bretton Woods. For a subset of
countries where the deregulation process did not yield a
strong prior on a single breakdate (Indonesia, Malaysia, and
Thailand), two alternative breakdates were considered.
As reported in Table 2, a statistically significant change
in savings-investment relationship is detected in only five
of the thirteen countries in the sample. Futhermore, where
such changes occurred, the results often were difficult to
interpret in terms of changes in capital mobility. For
instance, Singapore's saving coefficient turns from being
negative and statistically insignificant to being positive
and significantly different from 0 (at 5 percent) after the
breakdate. In the case of the U. S., the coefficient rises
from 0.632 to 1.097 after the breakdate, both statistically
significantly positive at the 5 percent level. Both of these
results appear anomalous in light of our priors based on the
regulatory and institutional background on capital mobility in these countries. The results are equally puzzling for
the two cases where the saving coefficient declines in size
over time. In Korea, 13 turns from 0.528 (significantly

15. Recall that the regression was performed on first-differenced series
of the savings and investment rates.
16. Both the Ljung-Box Q statistic and the generalized LM test (not
reported) indicate the presence of serial correlation for only two
countries in the sample: Malaysia and Taiwan.

29

TABLE

2

TOTAL INVESTMENT-SAVING CORRELATION
ALLOWING FOR STRUCTURAL BREAK

!::.(GD/lGDP)t

=

+ f3o!::.(GNSIGDP)t
+ f31 * D * !::.(GNSIGDP)t

ex

BREAK DATE

130
Australia

0.27

2.64

1973

Hong Kong

D.W.

1983

Canada

R2

1973

Indonesia

0.604***
(0.213)

1970; 1983

1973

Japan
Korea

-0.035
(0.230)

0.528***
(0.155)

-0.591 ** 1985
(0.278)

Malaysia

1.94

1973; 1983

New Zealand

0.34

1984
- 0.037

Singapore

0.970** 1983
(0.435)

0.27

1.55

(0.257)

Philippines

-0.312
(0.328)

0.327** 1975
(0.137)

0.24

2.37

Taiwan

1983

Thailand

1970; 1983

u.s.

0.632**
(0.215)

1.097** 1973
(0.560)

0.74

1.31

NOTE: OLS estimation; standard errors in parentheses. The critical
values for 13 were determined by a bootstrap procedure. D denotes the
bivariate dummy variable which takes a value of 1 in the years indicated and a value of 0 in the earlier years. Blank spaces in columns
130 and 131 indicate that no statistically significant structural break was
found for the break date. For Indonesia, Malaysia, and Thailand, two
alternative break dates were tested. The result reported for Indonesia
pertains to the 1970 break date. See Table 1 for significance levels.

different from 0 at 1 percent) to - 0.591 (significant at
5 percent) after the breakdate. The coefficient on saving
in Indonesia also turns negative (but insignificant) after
the breakdate.
Finally, for purposes of broader international comparison, Table 3 reproduces time series estimates of 13 for a
number of OECD countries reported by other authors. As
can be readily inspected, the size of the coefficient on
saving tends to be uniformly larger for the group of OECD

30

countries than for the group of Pacific Basin countries; that
is, according to the PH interpretation, capital mobility has
been lower for the OECD countries than for the Pacific
Basin countries. The average size of 13 for these OECD
countries is 0.71 compared to 0.41 for the Pacific Basin countries; excluding the countries that overlap (that is,
U. S., Japan, and Canada) brings the average for the Pacific
Basin down to 0.23. These comparisons further call into
question whether one can draw unqualified inferences
about capital mobility on the basis of a simple savinginvestment analysis.

Sensitivity of the Saving Coefficient to
Endogeneity Problems
As discussed in Section II, the "naive" version of the PH
saving-investment analysis may be fraught with endogeneity problems. This could be due to the omission of some
third factor, such as growth or the relative size of the
nontradable sector. Alternatively, endogeneity may be present in the form of policy responses by a government averse
to large external imbalances. This section explores the
extent to which the puzzles reported in the preceding section are statistical artifacts of such endogeneity problems.

Controlling for the Cyclicality
of Inventory Investment
If saving and investment both respond to some common
exogenous shocks, ordinary least squares estimates of 13
will be upwardly biased. One simple way to correct this
problem is to use fixed investment rather than total investment as the dependent variable (Bayoumi 1990).17 The
difference between the two is inventory investment, which
arguably is much more susceptible to unexpected shocks to
the economy.
The results reported in Table 4 indeed show the size and
the significance of the regression coefficient falling for a
number of countries when fixed investment is used as the
dependent variable. The fall is particularly marked for
Canada, Japan, and the U. S., with the size of 13 roughly
half of that obtained from the regression using total investment. A non-neglible decline in the coefficient is also
observed for Korea and Hong Kong. These results suggest
that for a subset of the sample countries at least, aggregate
demand and supply shocks may explain a significant part
17. As mentioned earlier, another method to deal with the endogeneity
problem is instrumental variable estimation. For most of the sample
countries, however, the variables typically used in the literature as being
correlated with saving but not investment (see footnote 12) turned out to
be poor instruments. The instrumental variable estimation results are
therefore not reported.

Economic Review / 1993, Number 1

TABLE 3

TABLE

TOTAL INVESTMENT-SAVING CORRELATION

FIXED INVESTMENT-SAVING CORRELATION,

FOR TWELVE

f)..(GDIIGDP)t

4

1961-1990

OECD COUNTRIES, 1961-1986
= a + rpf)..(GNSIGDP)t

f)..(GDFIIGDP)t

=

a

+

rpf)..(GNSIGDP)t

13

13

R2

D.W.

Austriaa

0.72
(0.28)

Australia

0.011
(0.085)

0.00

1.76

Belgium

0.63
(0.12)

Canada

0.401 ***
(0.140)

0.23

1.43

Canada

0.83
(0.16)

Hong Kong

0.461 ***
(0.175)

0.20

2.00

Federal Republic of Germany

0.87
(0.17)

Indonesia

0.252
(0.108)

0.17

Finland

0.98
(0.30)

Japan

0.522***
(0.130)

0.37

1.31

France

0.80
(0.26)

Korea

0.261 **
(0.128)

0.13

1.34

Greece

0.73
(0.13)

Malaysia

-0.338***
(0.117)

0.24

0.91

Italya

0.75
(0.29)

New Zealand

-0.039
(0.145)

0.00

1.93

Japanb

0.84
(0.15)

Philippines

0.259
(0.195)

0.06

1.29

-0.21
(0.31)

Singapore

0.176
(0.198)

0.03

1.20

-0.266**
(0.128)

0.14

1.09

Norwayb

2.23

United Kingdom

0.33
(0.18)

Taiwan

United States

1.00
(0.10)

Thailand

0.203
(0.139)

0.07

1.32

U.S.

0.492***
(0.081)

0.57

1.32

SOURCE: Bayoumi (1990), Table 7; data for Austria and Italy taken
from Obstfeld (1989), Table 7.6.
NOTE: Standard errors in parentheses. R2 and D.W. statistics are not
reported by the authors.
aData for 1967-1984.
bData for 1966-1986.

Federal Reserve Bank of San Francisco

NOTE: OLS estimation; standard errors in parentheses.
See Table 1 for significance levels.

31

of the time series correlation between total saving and
investment. 18 Even adjusting for such an endogeneity
problem, however, Table 4 leaves a puzzling pattern: 13
tends to be largest and statistically significant in Canada,
Hong Kong, Japan, and the U.S. With the exception of
Japan, these are also countries with relatively lower barriers to capital mobility.19

Controlling for Growth
and the Role ofNontradables
As noted earlier, a number of formal models demonstrate
that saving and investment will be correlated, even with
perfect capital mobility, due to factors such as productivity
shocks or lack of integration of goods markets. This section
explores, albeit in a preliminary fashion, whether any systematic changes in saving-investment correlation can be
detected for the Pacific Basin countries when the simple regression equation (2) is controlled for some of these omitted variables.
The analysis focuses on two variables. The first is the
rate of growth in GDP, which has been suggested in several
studies as a possible spurious variable in the savinginvestment regression (for example, Obstfeld 1985, Fry
1986). For instance, countries with rising incomes are
likely to exhibit both higher rates of saving and investment
over time. If this argument is correct, one would expect the
regression coefficient on saving to decline when growth
is included as an explanatory variable. Following Wong
(1990), the second variable examined is the ratio of imports
to GDP, as an inverse proxy for the relative size of the
nontraded goods sector. The maintained assumption here is
that the larger the ratio of imports to GDP, the more open
or integrated is the economy with respect to the goods market. The inclusion of this variable in the regression equation is therefore hypothesized to also reduce the size of 13.
The individual country regression equations were of the
form: 20
GD!)
(3) Jl (GDP t = «

+ 13Jl
A

+'L.1

(GNS)
GDP t
(

GDP t
GDP t

+ 'Y Jl
)

1

( M )
GDP t

+ Et .

The results reported in Table 5 show that the import-toGDP ratio, or the "openness" variable, turns out to be
highly significant for all countries in the sample, with
Singapore as the notable exception. The growth variable,
on the other hand, is significant in only two. countries
(Australia and Indonesia). When controlled for these two
effects, the linkage between saving and investment appears .
to weaken for at least a subset of Pacific Basin countries. 21
Again, the decline in 13 is most conspicuous in Canada and
the U.S., from 1.017 to 0.695 and from 0.939 to 0.710,
respectively, while in the case of Hong Kong, 13 turns from
0.616 (significant at 1 percent) to being statistically insignificant. A decline in 13 is also observed for Japan and
Thailand, but the change in the size of the estimated coefficient appears too marginal relative to the size of the
standard error to warrant a firm conclusion.
The augmented model thus provides some limited evidence of the omitted variable problem in the simple savinginvestment correlation analysis. Some "anomalies" nevertheless remain in the results of the augmented model.
Notably, 13 rises in the Philippines from a marginally
significant 0.360 in the simple model to 0.496 (significantly different from zero at the 1 percent level) in the
augmented model. For the remaining countries, the regression coefficient on saving is statistically not different from
zero in the augmented model as in the basic model. The
discrepancy between the earlier assessment of capital
controls in the sample countries and the estimated size of 13
therefore remains largely unaccounted for.

The Role ofPolicy Response
toward External Imbalances
A number of studies have suggested that the high correlation between saving and investment reflects successful

as well as interactively, that is:

~ (CDI) , =
CD?

(X

+

(~
l + "Io~ (~) , + ~o~ (~))
CD?
CD?'_I

* ~ (CNS) +
CD?
t

18. Similar time series results are reported by Bayoumi (1990) for ten
GEeD countries over a slightly shorter sample period of 1960-1986.
19. Structural break tests using CDFl did not yield results that were
materially different from those in Table 4. For the sake of brevity,
therefore, tlIese results are not reported.
20. Openness and growth were nonstationary and hence were first
differenced. Regressions were run with these variables entered directly

32

"11

~ (~)
CD?

t

+ ':>1 ~ ( CD?
r
CD?,

(-1

)

+

E

'

The interactive terms turned out to be statistically insignificant; hence
only the model featuring tlIe direct effects of openness and growth is
reported.
21. Again, the standard F test rejected the pooling of data. Only the
individual country time series results are therefore reported. The BoxLjung Q statistics indicate tlIe presence of serial correlation only in the
Malaysia equation.

Economic Review / 1993, Number 1

TABLES
EFFECTS OF IMPORT SHARE AND GROWTH ON THE INVESTMENT-SAVING CORRELATION

(GDI)
d . GDP t

=

a

+

f3d (GNS) t
GDP

+

~d

M t +
GDPt
-yd ( GDP ) ( GDP _
t

)

+

Et

1

~

"I

~

R2

Q-msl

Australia

0.141
(0.082)

1.149***
(0.129)

0.167***
(0.046)

0.750

0.925

Canada

0.695***
(0.210)

0.491 ***
(0.152)

0.047
(0.070)

0.685

0.909

Hong Kong

0.595
(0.150)

0.174**
(0.088)

-0.065
(0.059)

0.468

0.972

Indonesia

0.015
(0.151)

0.404***
(0,139)

-0.007***
(0.002)

0.246

0.266

Japan

0.892***
(0.134)

0.433***
(0.111)

0.759

0.352

Korea

0.482***
(0.164)

0.457***
(0.160)

0.356

0.607

Malaysia

0.015
(0.157)

0.422***
(0.090)

0.012
(0.061)

0.447

0.021

New Zealand

0.237
(0.178)

0.763***
(0.128)

0.025
(0.076)

0.543

0.327

Philippines

0.496***
(0.191)

0.502***
(0.105)

0.077
(0.066)

0.474

0.547

Singapore

0.Q75
(0.280)

0.082
(0.051)

0.056
(0.114)

0.030

0.251

0.691 ***
(0.081)

-0.036
(0.026)

0.810

0.177

Taiwan

-0.191*
(0.110)

0.042
(0.047)
~0.001

(0.004)

Thailand

0.555***
(0.141)

0.578***
(0.121)

0.106
(0.055)

0.600

0.292

U.S.

0.710***
(0.146)

0;632
(0.279)

0.123
(0.123)

0.736

0.960

NOTE: OLS estimation; standard errors in parentheses. Q-msl is the marginal significance level of the Box-Ljung Q statistics for serial
correlation.

Federal Reserve Bank of San Francisco

33

balance-of-payment policy on the part of national governments (Fieleke 1982, Summers 1988, Bayoumi 1990).22 In
particular, Summers (1988) argues that if governments are
averse to large capital inflows or outflows, they might
adjust their budget deficits to offset the gap between
private saving and investment. 23
To see whether such policy responses may account for
the puzzling cross-country difference in the size of [3, the
following set of regression equations was estimated:
(4) MDEFIGDP)t = a

+ 4>t1(CPS-GDI)IGDP)p

where DEF is general government budget deficit and PS is
private saving. <I> = 1 implies that fiscal policy completely
offsets any imbalance in private saving and investment so
that no capital flow occurs; in the polar opposite case of
<I> = 1, which is an implicit assumption in FH, deficits are
exogenous.
As reported in Table 6, the coefficient 4> is significantly
different from zero and positive in all of the countries
except Australia, Taiwan, and the Philippines. More revealing, however, is the cross-country comparison of the
size of the estimated regression coefficient. The government's propensity to offset current account imbalances
tends to be weaker in countries with lower saving-investment correlation. With the notable exception of Korea, and
to a lesser extent New Zealand, countries with high or
intermediate cases of capital control (Tai\van, Philippines,
Thailand, Malaysia, and Indonesia) have a relatively low or
statistically insignificant [3 (as reported in Tables 1, 4, or 5)
and also tend to have a low or statististically insignificant
<1>. By contrast, countries with low or intermediate degrees
of capital controls (Canada, the U. S., and Japan) and a
relatively high [3, tend to have relatively high 4>; that is, the
"endogenous" policy response to maintain external balance tends to be higher in Pacific Basin countries with a

TABLE

6

TEST OF THE ENDOGENOUS POLICY RESPONSE
HYPOTHESIS

ACDEFlGDP)t

= ex

+

~A((PS-GD[)/GDP)t

SAMPLE PERIOD

<I>

Australia

1962-90

0.064
(0.078)

Canada

1962-89

0.569***

R2

D.W.

0.02

1.68

0.38

2.21

(0.141)

23. This is not to say that fiscal policy is determined exclusively, or even
primarily, out of balance of payments considerations. Rather, it is when
the current account balance exceeds some predetermined level that fiscal
or even monetary policies are implemented to reduce or eliminate those
deficits or surpluses. One example is efforts initiated by the U.S. in the
second half of the 1980s to reduce the budget deficit, and thereby put
a check on the ballooning current account deficit. Another example of a
policy reaction in the opposite direction is Japan which, in a bid to
reduce unprecedented current account surpluses. that emerged in the
second half of the 1980s, pursued expansionary fiscal and monetary
policies.

34

1972-90

0.232***
(0.107)

0.22

1.91

Indonesia

1962-89

0.237***
(0.059)

0.38

2.13

Japan

1971-89

0.473***
(0.145)

0.38

1.69

Korea

1962-90

0.925***
(0.032)

0.77

1.72

Malaysia

1965-90

0.300***
(0.052)

0.58

1.49

New Zealand

1962-90

0.435***
(0.085)

0.49

2.42

Philippines

1962-90

0.160*
(0.094)

0.10

2.62

Singapore

1962-90

0.597***
(0.072)

0.72

2.39

Taiwan

1962-90

0.04

2.34

Thailand
22. Possible justifications for discouraging capital outflows include:
social return to domestic investment exceeding that of foreign investment, risk of capital expropriation by foreign government or labor, and
negative terms of trade effects. Aversion to a large influx of foreign
capital may be due to a large appreciation in the real exchange rate and
its deleterious impact on the economy's traded goods sector.

Hong Kong

1964-90

0.360***
(0.129)

0.24

2.33

U.S.

1962-90

0.786***
(0.110)

0.65

2.11

-0.072
(0.064)

NOTE: OLS estimation; standard errors in parentheses. DEF denotes
general government budget deficit and PS denotes private saving.
See Table 1 for significance levels.

high saving-investment correlation. 24 These findings thus
do help to reconcile the puzzling pattern that the savinginvestment correlation tended to be relatively weaker
or insignificant in countries which traditionally imposed
higher restrictions on international capital flows.
24. The exception here is Singapore which had an insignificant f3 but a
relatively high <1>.

Economic Review / 1993, Number 1

TABLE

7

why saving-investment linkages are weaker in these Pacific
Basin countries despite their traditionally more stringent
capital controls. 27

EXTERNAL DEBT INDICATORS

INDONESIA

KOREA

MALAYSIA PHILIPPINES THAILAND

IV

PuBLIC DEBT AS PERCENT OF GNP
1970
1975
1980
1985
1990

25.6
25.5
20.1
31.9
44.0

20.3
27.5
26.3
32.7
7.5

9.5
14.2
17.0
52.0
39.9

8.8
9.2
19.2
43.6
51.7

4.6
4.2
12.4
26.9
15.8

TOTAL DEBT AS PERCENT OF GNP
1980
1985
1990

28.0
43.8
66.4

48.7
52.5
14.4

28.0
71.9
48.3

49.5
83.9
65.4

26.0
47.8
32.6

GOVERNMENT DEFICIT AS PERCENT OF GNP
1970
1975
1980
1985
1990

3.02
3.70
2.42
0.98
0.90

0.77
1.98
2.23
1.17
0.70

3.77
8.47
13.33
7.36
2.70

0.14
1.19
1.39
1.95
3.46

3.66
2.06
4.88
5.46
4.84

FOREIGN BORROWING AS PERCENT OF GOVERNMENT DEFICIT
1970
1975
1980
1985
1990

87.1
97.0
92.9
74.4
NA

66.6
77.2
38.3
46.9
27.2

0.4
47.8
4.4
16.8
NA

100.0
18.7
66.0
0.0
11.1

NA
83.0
23.5
32.8
0.0

SOURCES: World Bank, World Debt Tables, and IMF, International
Financial Statistics.

In fact, Table 7 presents evidence suggesting that for this
latter group of countries, the goverIlment itself has played a
central role in the flow of foreign borrowing, thus driving
a wedge between national saving and investment. Throughout the 1980s, public or publicly guaranteed debt usually
accounted for anywhere between one-half to three-quarters
of total foreign borrowing in all five countries,25 with
significant proportions of the foreign borrowing going
toward financing the government budget deficit. 26 Though
comparable data are unavailable for the earlier period, the
relative importance of public borrowing was undoubtedly
even higher, and this may constitute an additional reason

25. The sources cited do not report data for Taiwan.
26. Kharas and Kiguel (1988) provides a systematic analysis on this
issue.

Federal Reserve Bank of San Francisco

CONCLUSION

This paper examined the time series evidence on the savinginvestment correlation for a group of Pacific Basin countries. Its main findings may be summarized as follows.
First, the simple bivariate saving-investment model (as
originally formulated by FH) yielded coefficients on saving
that often contradicted our priors based on our knowledge of
capital controls in the region. Most notably, the saving
coefficients were much higher and statistically significant
in countries that have traditionally imposed much looser
capital controls. Additionally, structural break tests in
saving-investment correlation failed to detect the effects of
regulatory shifts for most of the sample countries.
Part of this anomalous pattern across countries in the
size of the estimated coefficient can be accounted for by
simultaneity problems. For a subset of countries, controlling for the procyclicality of inventory investment reduced
the size of the estimated coefficient on saving. The growth
rate and the openness of the economy (as a proxy of the
integration of the goods market) were also found to exert a
negative impact on the overall saving-investment correlation. These results thus provide some support to models
that emphasize the role exogenous shocks or the nontradable sector play in explaining observed co-movements in
savings and investment.
A more significant factor accounting for the puzzling
pattern of tighter saving-investment linkages found in
countries with relatively lower capital controls, however,
appears to be the greater propensity of government policy
to counteract large external imbalances. By contrast, such
policy reactions appear much weaker in those Pacific Basin
countries with relatively higher capital controls. In fact, for
this group of countries, the financing of the public sector
deficit itself has been an important impetus to capital
inflow, and this appears to have helped to weaken the link
between domestic investment and savings.

27. Again, the Korean evidence is difficult to interpret. The result in
Table 6 suggests a very high propensity of the Korean government to
engage in fiscal policy thaf counteracts external imbalances. The
evidence in Table 7 appears to contradict this interpretation.

35

ApPENDIX
SUMMARY OF CAPITAL CONTROLS IN PACIFIC BASIN COUNTRIES

KEy:
X

HEAVY RESTRICTIONS:

full surrender of export proceeds; advanced export deposits required; tight restrictions on size of pennitted payments for
invisibles; foreign currency deposits not allowed; foreign borrowing/lending with prior approval only; taxes or reserve
requirements on foreign borrowing.

*

MODERATE RESTRICTIONS:

surrender of export proceeds required above set limit; fractional advanced import deposits required; fewei iestrictions or
moderate limits on payments for invisibles; foreign currency deposits allowed with set limits and with transaction
notification requirements; foreign borrowing/lending pennitted within set limits.

o

MILD RESTRICTIONS:

payments for invisibles subject to verification; fewer restrictions on size and flexibility of foreign currency accounts;
foreign borrowingllending permitted without approval but limits apply to net foreign currency position.
No RESTRICTIONS:
indicated by a blank.

1960 - 1969

1970 - 1979

1980 - 1989

1990 - 1992

AUSTRALIA

+----

Required Surrender of Export Proceeds
Advanced Import Deposits
Payments for/Proceeds from Invisibles
Foreign Currency Deposits by Residents
Foreign Lending/Borr. by Financial Institutions
Tax or Special Reserve Req. on Foreign Borr.

+----

+---- +---- +---- +---- +--

xxxxx xxx xx xxxxx xxxxx xxx
xxxxx xxxxx xxxxx xxxxx xxx
xxxxx xxxxx xxxxx xxxxx xxx
xxxxx xxxxx xxxxx xxxxx xxx

CANADA

+----

+----

+----

+----

+----

+----

+--

+----

+----

+----

+----

+----

+----

+--

Required Surrender of Export Proceeds
Advanced Import Deposits
Payments for/Proceeds from Invisibles
Foreign Currency Deposits by Residents
Foreign Lending/Borr. by Financial Institutions
Tax or Special Reserve Req. on Foreign Borr.
HONG KONG

Required Surrender of Export Proceeds
Advanced Import Deposits
Payments for/Proceeds from Invisibles
Foreign Currency Deposits by Residents
Foreign Lending/Borr. by Financial Institutions
Tax or Special Reserve Req. on Foreign Borr.

36

00000 00000 00

***** ***** **
***** ***** **
***** ***** **

Economic Review / 1993, Number 1

Federal Reserve Bank of San Francisco

37

38

Economic Review / 1993, Number 1

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39