Modeling the U.S. Current Account as the Savings-Investment Balance

Juann H. Hung 

Macroeconomic Analysis Division 

Congressional Budget Office 

Washington, DC 20515

Phone:(202) 226-2759

Fax:(202) 226-0332

Email: Juannh@cbo.gov

Charles Bronowski

Harvard Law School

 Cambridge, MA 02138

 Phone:(716) 573-1289

 Fax:(716) 656-9538

Email:Cbronows@law.harvard.edu

December 2002

2002-5

We would like to thank participants at the WEAI conference and colleagues at the

Congressional Budget Office, especially Bob Dennis, Kim Kowalewski, and Ufuk

Demiroglu, for helpful comments. We are grateful for research assistance provided by Eric

Warasta. Technical papers in this series are preliminary and are circulated to stimulate

discussion and critical comment. These papers are not subject to CBO’s formal review and

editing processes. The analysis and conclusions expressed in this paper are those of the

authors and should not be interpreted as those of the Congressional Budget Office.

References in publications should be cleared with the authors.
2

Modeling the U.S. Current Account as the Savings-Investment Balance

by Juann Hung and Charles Bronowski

Abstract

 This paper derives and estimates a current account model from the perspective

that the current account balance is the difference between national savings and

investment. This approach allows us to include determinants of savings, investment, and

capital flows to explain and forecast the evolution of the current account, an advantage

not offered by the elasticity approach, which views the current account balance as the

sum of net exports and net investment income. The savings-investment approach shows

that the three traditional variablesthe real exchange rate, domestic activities, and

foreign activitiesdo exert a significant influence on the current account, as postulated by

the elasticity approach. More important, it shows that some variables overlooked by the

elasticity approachnamely, the share of dependents in the foreign population, real U.S.

and foreign interest rates, and U.S. corporate profitsalso matter for the current-account

adjustment, while the government budget balance does not. The finding that the budget

balance is not a significant determinant of the current account suggests that U.S. private

savings may have tended to adjust to offset changes in the government budget. Overall,

models based on the savings-investment approach track and forecast the U.S. current

account much better than models based on the elasticity approach.
 1

 For example, see Krugman (1987).

 2 For example, the absorption approach offers a broader perspective of the current account than the elasticity

approach, recognizing the current account as the outcome of economic agents’ intertemporal utility maximization.

 3

 A typical U.S. current account model based on the elasticity approach also includes equations for net

investment income, with investment income being modeled as a function of foreign interest rates and U.S.

international assets, and investment payment a function of U.S. interest rates and U.S. international liabilities.

However, net investment income historically has been small relative to the trade balance, which has remained

the primary component of the U.S. current account balance.

3

Modeling the U.S. Current Account as the Savings-Investment Balance

Juann Hung and Charles Bronowski

1. Introduction

The current account balance has dual identities: (1) the sum of the trade balance

and net international investment income; and (2) the difference between income and

absorption; or equivalently, the difference between savings and investment. Because

each identity can be derived from the other in the framework of the national income and

product accounts, they do not pose theoretical conflict with each other. Nevertheless,

some economists tend to invoke the first identitythe elasticity approachto emphasize

the role of the exchange rate in the current-account adjustment, while others tend to cling

to the second identitythe absorption approachto emphasize that the exchange rate is

unimportant in the current-account adjustment.1

 

Despite the many theoretical appeals of the absorption approach,2 policymakers

and forecasters still tend to use the elasticity approach to construct current-account

models for forecasting purposes. In a typical elasticity approach, exports are modeled as

a function of foreign income and the terms of trade, imports as a function of U.S. income

and the terms of trade.3

 The approach thus has the benefit of giving straightforward
4

estimates of the price and income elasticities of exports and imports, making it easy to

predict the partial-equilibrium impact on the trade deficit of expected changes in the

terms of trade and relative income growth. For those reasons, it is not surprising that the

elasticity approach has been the standard approach for building models of the current

account. 

Nevertheless, estimating current account models based on the absorption

approach is worthwhile for at least three reasons.

First, in a world where capital flows dwarf trade flows, modeling the current

account based only on the elasticity approach could lead to erroneous conclusions and

policy recommendations. In open economies, agents’ intertemporal decisions influence

both trade and capital flows across national borders. Since the sum of the current account

and the financial account must equal zero ex post in a flexible exchange rate regime,

shocks that occur first in the financial account will affect the current account just as much

as shocks that occur first in the current account will affect the financial account. Because

the elasticity approach effectively treats financial account transactions as passive

responses to current-account transactions, it is incapable of analyzing the impact on the

current account of shocks that initially drive only the financial account. Thus, by making

it easier to incorporate determinants of financial account transactions into modeling the

current account balance, the absorption approach provides a more inclusive, and less

misleading, framework to analyze and forecast the current account than does the elasticity

approach.
 4

 The traditional view maintains that a real exchange rate adjustment is necessary to reduce an

external deficit. However, some economists have argued that an exchange rate change is not a

necessary element of the adjustment. For example, a decline in government expenditure could reduce

aggregate demand sufficiently to restore the trade balance without changing the real exchange rate.

This would tend to be true if the foreign and the domestic shares of spending on domestic goods were

equal at the margin. See Krugman (1987).

5

Second, because domestic activity, foreign activity, and the real exchange rate

are the three main determinants of the current account in the elasticity approach, the

estimation of a current account model based on the elasticity approach is likely to

exaggerate the explanatory power of those three variables in the current-account

adjustment, failing to show the importance of other possible drivers. As a result, relying

exclusively on an elasticity-based current account model has not helped to settle the

ongoing debate over the roles of the exchange rate and the budget balance in the currentaccount evolution. The role of the exchange rate in facilitating countries’ external

adjustments has been a subject of much debate among economists who emphasize the

absorption view and those who stress the elasticity view.4

 Relatedly, economists who

emphasize the absorption view have tended to point to the increase in the budget deficit

as the main cause for widening the U.S. current account deficit, while those emphasizing

the elasticity view are less ready to declare that the budget deficit is the main culprit. 

Estimating an absorption-based current account model will help shed light on those

issues.

Third, over the medium term, an absorption model is likely to generate forecasts

that are more accurate than those generated by an elasticity model, for two reasons. First,

the forecast performance of an absorption model depends less critically on the accuracy

of forecasts of the three main drivers in the elasticity approachthe real exchange rate,
6

output at home, and output abroad. Because those three variables are harder to predict

over the medium term than some of the variables included in the absorption

approachfor example, demographic trends at home and abroadan absorption model

could generate more accurate medium-term forecasts. Second, and more important, an

elasticity-based modelbecause it excludes relevant variables that affect savings,

investment, and capital flowsis likely to perform worse than an absorption model due to

the problems of omitted variables.

 This paper derives and estimates a current account model based on the

absorption approach. Among its findings are: (1) some variables included in the

absorption approach, but excluded by the elasticity approachsuch as the foreign

dependency ratio, domestic corporate profits, domestic real interest rates, and foreign real

interest ratesplay a significant role in moving the current account; (2) the real exchange

rate exerts a significant influence on the current-account adjustment; (3) the budget

balance does not have a long-run impact on the current account; and (4) in forecasting the

U.S. current account, models based on the absorption approach outperform those based

on the elasticity approach, by a considerable margin.

The remainder of the paper is organized as follows. Section 2 rearranges the

current account identity to demonstrate how exogenous shocks that arise from the

international financial market can be transmitted into current-account movements.

Section 3 derives a reduced-form equation for the current account that includes

determinants of savings, investment, and capital flows. Section 4 tests whether the

current account is cointegrated with the explanatory variables suggested by the absorption
 5

 For the purpose of this paper, capital mobility can be thought of as capital-account liberalization.

7

approach and builds an error-correction model of the current account. Section 5

compares the forecasting performances of alternative models of the current account. 

Section 6 offers some conclusions.

2. Current-Account Identities

To distinguish the net effect of autonomous capital flows, let’s assume that the world

consists of two countries: the United States and Foreign. Now let’s imagine a

hypothetical world that is identical to the real two-country world in every aspect except

those affected by this assumption: there is no capital mobility between the United States

and Foreign in the sense that there are no autonomous capital flows.5

 That is, all crossborder capital flows in this hypothetical world would occur only as a result of settling

current-account transactions. 

We further assume that the real interest rate will adjust to clear the loanable funds

market. That is, 

(1) S(R) + S*(R) = D(R)

(2) SH (RH) + SH* (RH) = DH (RH)

Where, 

R is the equilibrium real interest rate in the United States in the real world. 

D(R) is real demand for funds in the United States at R.

S(R) is real domestic supply of funds in the United States at R.

S*

(R) is net real foreign supply of funds in the United States at R.
8

RH is the equilibrium real interest rate in the United States in the hypothetical

world.

DH(RH) is real demand for funds in the United States at RH.

SH*(RH) is net foreign supply of funds in the United States at RH.

SH

(RH) is real supply of funds to the United States at RH.

In the hypothetical world, net foreign supply of funds (SH*) is purely a result of

settling current-account transactions, independent of developments in the real interest rate

and other determinants of the financial account. In the real world, however, changes in

net foreign supply of funds (S*

) affect, and are affected by, the real interest rate in the

United States. Everything else being equal, an increase in R will increase S*

. The

increase in S* could in turn mitigate the contractionary effect of the original rise in R. 

Everything else being equal, if changes in other financial-flow factors cause the S*

schedule to shift downward, R will fall to induce more domestic spending. 

Consequently, by interacting with the U.S. real interest rate, net foreign supply of funds

would in turn affect U.S. savings and investment, thereby affecting the current account. 

To illustrate this more clearly, recall that U.S. domestic supply of funds (S) is equal

to total domestic savings in each period:

(3) S = Y - C - G = Y - C - (T -GB) = SP

 + GB

where Y is national income, C is consumption, G is total government spending, T is tax

revenue, GB is government budget balance, and SP

 is private saving. The aggregate

demand for funds (D) is equal to private investment (I):

(4) Dt

 = It
 6

 Let X denote exports of goods and services, including investment income, and M denote imports of goods

and services including investment payment. Let C be private consumption, I be private investment, G be

government spending, S be total saving, and Y be GNP. Because D = I and CAB = S - D, it follows that CAB

= X - M = (C+I+G+X-M) - (C+I+G) = (Y - C - G) - I = S - I. 

9

From the definition of the current account balance (CAB) and the national account

identity, we can obtain the following relationship between CAB, S, and D:

(5) CABt = St - Dt

6

To see how much difference capital mobility makes in the current account, let’s define 

DX = (D - DH) - (S - SH) and rewrite the CAB identity from equation (5) as follows:

(6) CAB = S - D = SH

 - DH - DX

In this equation, DX is the difference between additional investment induced by

net capital inflows and additional savings induced by net capital inflows; or, the part of

net demand for funds that would not have occurred without capital mobility. Equation

(6) makes it plain that in the hypothetical world, DX = 0, and CAB = SH - DH. In the real

world, however, CAB critically depends on DX, which is the ex post real transfer resulting

from capital mobility. Consequently, any shocks that affect DX will necessarily affect

CAB, regardless of the sources of the exogenous shocks. 

3. Deriving a Reduced-Form Equation of the Current Account

To derive a reduced-form equation of the current account based on equation (6),

we need to make assumptions about the determinants of SH, DH, and DX, which are not

observable in the real world. To circumvent this data problem, we use the real-world
10

counterparts of those variables as proxies for those determinants in deriving and

estimating the reduced-form equation. This method is justified by the assumption that

variations in those variables are mainly driven by forces independent of capital mobility. 

Substituting all of the explanatory variables that would prevail only in the

hypothetical world with their real-world counterparts removes the first hurdle in the way

of building a current-account model from the savings-investment approach. A second

hurdle we need to overcome is the heteroskedasticity problem that plagues the estimation

of nominal-variable equations. This is a problem here because we do not have readily

available and reliable data on "the current account deflator." To tackle this problem, we

normalize the current accountas well as all nominal explanatory variables of savings,

investment, and the net real effect of capital mobilityby "nominal" potential output

(Yp

)that is, the product of potential gross domestic product (GDP) and the GDP

deflator.

We therefore use the following variation of equation (6) to derive an equation of

the normalized current account:

(6) CAR = SR - IR - DRX

where CAR is the CAB/Yp ratio, SR is the S/Yp ratio, IR is the I/Yp ratio, and DRX is the 

DX/Yp

 ratio. To facilitate discussion, we will subsequently refer to CAR as the current

account ratio, SR the savings ratio, IR the investment ratio, and DRX

 the net effect of

capital mobility. We now are ready to discuss the determinants of SR, IR, and DRX.
 7

 The real exchange rate = the U.S. Price x the Nominal Exchange Rate/Foreign Price.

 8

 The GDP gap is defined as the GDP/Yp ratio.

 9

 Whether a terms-of-trade deterioration would increase or decrease savings is one of the central

controversies in the debate over whether currency devaluation is an effective tool to improve a country’s balance

of payments. Harberger (1950) and Laursen and Metzler (1950) postulated that savings, and thus the current

account, for a given level of income decreases (increases) with a deterioration (improvement) in the terms of

trade. Using an intertemporal utility-maximizing framework, however, Obstfeld (1982, 1986) argues that an

improvement in the terms of trade will decrease savings and, thus, decrease the current account balance.

 10 The dependency ratio is defined as the share of the dependent population—those at or below 14 years old

or those 65 or older—in the total population. 

11

Savings. The savings ratio is a negative function of the real exchange rate (RXR)7

,

the dependency ratio (DEP), the output gap (GAP)8, the private wealth/Yp ratio (W), and

a positive function of the real interest rate (R), the government budget balance/Yp ratio

(GB), and the corporate profits/Yp ratio (CP), as shown in equation (7).

() ( , , , , , , ) 7 SR SR RXR DEP GAP W R GB CP = − − − −+ + +

An increase in the real exchange rate (RXR) will tend to decrease the savings ratio

because the terms of trade (that is, export prices relative to import prices) tend to improve

as the real exchange rate increases. As the terms of trade improve, U.S. residents are able

to buy more volume of imported goods per unit of exported goods. An increase in RXR

also means an increase in the dollar’s purchasing power abroad relative to its purchasing

power at home, thereby encouraging U.S. residents to travel and consume abroad. Both

effects would cause the volume of U.S. consumption to rise relative to output, thereby

lowering the savings ratio.9 An increase in the dependency ratio10 (DEP) will decrease

the savings ratio because, according to the life-cycle hypothesis, the young and the old
12

are net consumers while the remainder of the population is net savers. An increase in the

output gap (GAP) will reduce the savings ratio because disposable income and the

consumption share tend to increase during an expansion. An increase in the private

wealth ratio (W) will decrease the savings ratio because of the positive wealth effect on

consumption. An increase in the real interest rate (R) will increase the savings ratio

because it increases the rate of return on saving. An increase in the government budget

ratio (GB) will have a non-negative impact on the savings ratio. It will increase the

savings ratio if it does not lead to an offsetting decrease in private savings, but will have

no impact on savings in a Ricardian-equivalence world where private savings adjusts to

completely offset changes in government savings. Finally, an increase in the corporate

profits ratio (CP) will increase the savings ratio because corporate profits are a positive

component of total saving.

Investment. The I/Yp

 ratio (IR) is a positive function of the output gap (GAP), the

corporate profits ratio (CP), and the government budget ratio (GB), but a negative

function of the real interest rate:

() ( , , , ) 8 IR IR GAP CP GB R = + + +−

An increase in the output gap (GAP) will increase the investment share because consumer

demand tends to increase during an expansion, boosting demand-led investment. An

increase in the corporate profits ratio (CP) will increase the investment share because it

increases incentive to invest while it mitigates the need for external financing. An

increase in the real interest rate (R) will decrease the investment share because it
13

decreases expected net profits. An increase in the government budget ratio, everything

else being equal, will increase investment by reducing uncertainty over how to finance

the increase in government deficit.

Net Effect of Capital Mobility. The net effect of capital mobility on real

expenditure as a share of potential GDP (DRX

 ), which rises and falls as net autonomous

capital inflows, is a negative function of the real exchange rate (RXR), the foreign

dependency ratio (DEP*), the foreign output gap (GAP*), and U.S. private wealth (W);

but it is a positive function of the U.S. output gap (GAP) and the real interest rate

differential (R - R*):

() ( , , , , ,

*

) * * 9 DR D RXR DEP GAP W GAP R R X X = − − − − − + +

On the negative side, an increase in the real exchange rate (RXR) decreases net

autonomous capital inflows because U.S. assets become more expensive for foreigners to

acquire while foreign assets become more affordable for U.S. investors to purchase. 

Therefore, an increase in RXR decreases DRX. An increase in the foreign dependency

ratio (DEP*

) decreases foreign savings, thereby decreasing net capital inflows. An

increase in the foreign output gap (GAP*

) reduces net capital inflows for two reasons: (1)

it reduces foreign savings, thereby lowering gross capital inflows to the United States;

and (2) it increases the attractiveness of foreign economies as destinations for U.S.

investment, thereby increasing gross capital outflows. An increase in U.S. private wealth

(W) will decrease net capital inflows because wealthier U.S. investors will increase their
 11 Symmetric reasoning would require the inclusion of foreign private wealth in this equation because

wealthier foreign investors will purchase additional U.S. assets to diversify their portfolio, thereby increasing net

capital inflows. Unfortunately, it is impossible to gather data on foreign wealth. Because data on foreign wealth

are not available to be used in the actual regression, foreign wealth is not included in equation (9).

14

purchase of foreign assets to diversify their financial portfolio.11 On the positive side, an

increase in the U.S. output gap (GAP) increases net capital inflows because it increases

the attractiveness of the United States as a destination for international capital. Finally,

an increase in the real interest rate differential (R-R*) will increase net capital inflows by

increasing the expected rate of return on U.S. bonds relative to that on foreign bonds. 

The Current Account Ratio Substituting equations (7)-(9) into (6') results in the

following reduced-form equation:

() ( , , , , ,,, , , ) * ** 1 0 CAR CAR DEP GAP R DEP GAP W R RXR GB CP =

+ ++ − − +− +− +− +− +−

The impact on the current account of DEP, DEP*, R*, GAP and GAP* is 

unambiguous a priori. The net impact on the current account of the other five

variablesnamely, private wealth (W), the real U.S. interest rate (R), the real exchange

rate (RXR), the government budget ratio (GB), and the corporate profits ratio (CP)is

less clear. An increase in private wealth could reduce savings and thereby decrease the

current account, but it could also increase capital outflows and thereby increase the

current account. Similarly, an increase in the real interest rate could increase savings

while discouraging investment, thereby increasing the current account; but it could also 

increase net capital inflows and thereby decrease the current account. An increase in the
 12 The assumptions of the classical regression model necessitate that both dependent and independent timeseries variables be stationary and the residuals have a zero mean and finite variance. If nonstationary variables

are present, what Granger and Newbold (1974) refer to as spurious regression may occur. That is, the regression

output could look good with a high R2

, but the least-squares estimates would not be consistent and the customary

tests of statistical inference would not hold. 

 13 See Engle and Granger (1987).

15

real exchange rate could decrease savings and thus the current account, but it could also

decrease capital inflows and thereby increase the current account. An increase in the

government budget balance could increase the savings ratio in a non-Ricardian world, but

it could also increase investment by reducing uncertainty over how to finance the

government deficit. Finally, an increase in corporate profits would increase savings

through accounting identity, but it could also increase investment by increasing the

incentive to invest while mitigating the need for external financing. 

4. Estimating an Absorption-Based ECM of the Current Account

A potential pitfall in constructing a time-series model is that spurious inferences

may result if nonstationary variables are treated as stationary.12 To avoid this pitfall, we 

begin our modeling efforts by conducting unit-root tests of all 11 variables in equation

(10). As shown in Table 1, we find that only four of the 11 variablesnamely, the

current account ratio, the foreign dependency ratio, U.S. private wealth, and the U.S.

budget balanceare I(1) variables. This finding appears consistent with casual

observations of the histories of these variables since 1970 (Figures 1a & 1b). 

We modify the Engle-Granger two-stage method13 to estimate an errorcorrection model (ECM) of the current account ratio (CAR). In the first step, we use the
16

Ordinary Least Squares (OLS) regression to estimate the cointegrated, or long-run,

relationship between CAR and the explanatory variables. In the second step, we include

the error-correction termthat is, the residual from the estimated cointegrated

equationas an explanatory variable along with first differences of other explanatory

variables in the ECM to determine the short-run dynamic adjustment process of the U.S.

current account.

 The finding that not all explanatory variables are I(1) variables creates a

dilemma for us. We could follow Campbell and Perron’s (1991) recommendation,

ignoring all I(0) explanatory variables in the first step and reintroducing them in the

second step. Doing so, however, would be effectively restricting all coefficients of the

I(0) variables to zero while they may help explain the stationary component of the CAR

over the long run. This method thus would result in biased estimates of long-run

coefficients due to omitted variables. Or, we could include all I(1) and I(0) explanatory

variables in the first step in estimating the long-run equation and hope that doing so

would not significantly distort the cointegrating test. Given the purpose of this paper, we

chose the latter approach and include all explanatory variables in the long-run regression.

4.1 The Long-Run Cointegrating Equation of the Current Account

To obtain consistent and efficient estimates of the long-run coefficients of

equation (10), two problems must be overcome. The first is the simultaneity bias that

would arise because some regressorsnamely, the real exchange rate, the U.S. GDP gap,

the foreign GDP gap, corporate profits, and the budget balanceare endogenous in the
 14 In theory, if the residuals from the OLS estimation of the long-run equation do not have a unit

root (that is, the equation is indeed cointegrated), then the fact that CAR is I(1) means not only that

the OLS estimators of the long-run coefficients are consistent, but also that they converge more

rapidly to its limiting distribution than is usually the case. If the regressors are endogenous, however,

the resulting bias in the estimators can still be substantial in small samples. (We first used the

parametric correction suggested by Saikkonen (1991) and Stock and Watson (1990) to obtain

consistent estimates for equation (10). However, we found that point estimates of that method were

sensitive to the number of leads and lags used for the correction.)

 15 This conclusion is based on the critical values generated by Phillips and Ouliaris (1990) with the Monte

Carlo method. The critical value is -4.11 at the 5 percent significance level for equations that have three I(1)

explanatory variables, and -3.37 for one I(1) explanatory variable. 

17

system. The second is serial correlation among residuals. The former problem is dealt

with by using the one-quarter lagged value of each endogenous regressor as the

instrumental variable for that regressor to obtain consistent estimates.14 The second

problem is solved by using the Generalized Least Squared method to correct for serial

correlation among residuals to obtain efficient estimates. 

The estimated long-run coefficients of absorption-based models are reported in

columns (1) and (2) of Table 2. Column (1) includes all of the explanatory variables in

equation (10). Column (2) includes only those explanatory variables that are estimated to

have a statistically significant coefficient, excluding the three insignificant variablesthe

U.S. dependency ratio, private wealth, and the budget balance. Because there are only

three I(1) regressors in column (1) and only one in column (2), both the ADF statistics

and the Phillips-Perron statistics suggest that the CAR and the regressors are cointegrated

at the 5 percent significance level.15 The adjusted R2s for both regressions are reasonably

high, suggesting that the overall goodness of fit is satisfactory. 
 16 These results may appear surprising at first, since researchers have tended to find that U.S. (goods) import

demand has a greater income elasticity than foreign demand for U.S. exports does. The novelty of this result

fades, however, when one recalls that the share of services trade in the current account has increased substantially

since the late 1980s, and that the income elasticity of U.S. demand for services imports has been found to be

smaller than that of foreign demand for U.S. exports of services. 

18

Column (2) shows that 6 out of the 10 stochastic explanatory variables in

equation (10)the real exchange rate, U.S. output gap, foreign output gap, foreign

dependency ratio, corporate profits, and the real U.S. interest ratehave coefficient

estimates that are statistically significant and can be explained by theory. 

A 1 percent increase in the real dollar exchange rate lowers the CAR by about 0.03

percentage points over time, suggesting that a real dollar appreciation decreases

savings by more than it decreases net capital inflows. 

A 1 percentage-point increase in the U.S. output gap lowers the CAR by 0.43

percentage points over time. Almost symmetrically, a 1 percentage-point increase in

the foreign GDP gap increases the CAR by 0.42 percentage points over time.16 

A 1 percentage-point increase in the foreign dependency ratio gap increases the CAR

by about 0.38 percentage points over time. 

A 1 percentage-point increase in the U.S. corporate profits ratio increases the CAR

by about 0.32 percentage points over time, suggesting that its positive impact on

savings more than offsets its positive impact on investment. 

A 1 percentage-point increase in the real U.S. interest rate raises the CAR by about

0.08 percentage points over time, suggesting that an increase in the real interest rate

lowers domestic demand by more than it raises net capital inflows. 

 Quantitatively, those coefficient estimates are within reasonable ranges. 
19

Coefficient estimates on the U.S. budget balance are not significant, suggesting

that U.S. private savings have tended to adjust to offset changes in the government

budget. Likewise, the insignificant coefficient estimate on U.S. private wealth suggests

that opposing impacts of private wealth on the current account roughly cancel each other

out, resulting in an insignificant net impact over the long run. The coefficient estimate on

the U.S. dependency ratio is also statistically insignificant, suggesting that U.S. aggregate

savings are not driven significantly by the share of dependents in the total population.

It is harder to explain the coefficient estimates on the real foreign interest rate

within our framework. The coefficient estimate on the foreign interest rate is significant

with the wrong sign: over time, a 1 percentage-point increase in the foreign interest rate

lowers the CAR by about 0.09 percentage points. This apparent contradiction to theory

may be due to the risk premium imbedded in the measured inflation-adjusted foreign

interest rate. If the increase in the foreign interest rate mainly reflects an increase in

investors’ unwillingness to invest in foreign countries, it would not make foreign assets

more attractive for international investors. 

To assess the combined contribution of the nontraditional explanatory variables

introduced by the absorption approach, we also estimate an admittedly overly simplified

elasticity-based equation of the current account over the same sample period. The

estimated long-run coefficients of this elasticity-based equation are reported in column

(3) of Table 2. Both the ADF statistics and the Phillips-Perron statistics suggest that the

current account ratio is not cointegrated with the three explanatory variables included in

the elasticity equationU.S. output gap, foreign output gap, and the real exchange rate. 
 17 If foreign assets are held constant, increases in foreign holdings of U.S. assets are likely to increase

foreigners’ desire to diversify away from U.S. assets, thereby lowering net capital inflows to the United States

and increasing the current account balance. 

20

This is not surprising, given that the CAR is a I(1) variable while all three regressors are

I(0) variables. The adjusted R2s indicate that the goodness-of-fit of the elasticity-based

equation is inferior to that of an absorption-based equation. In contrast to the absorption

approach, the real exchange rate has no significant and stable long-run relationship with

the current account, while the coefficient estimates of U.S. output gap and foreign output

gap are all considerably greater than those in the absorption equations. 

4.2 The Error-Correction Model 

We follow the "general-to-specific" method to find the ECM of the current

account. In addition to the traditional variables included in the right-hand side of the

equationthat is, the lagged residual from the long-run equation (the equilibrium error),

and lags of the first difference of the dependent and all independent variables in the longrun equationwe also include the first differences of foreign portfolio holdings of U.S.

assets.17 Variables with statistically insignificant coefficients were dropped sequentially. 

We estimate two versions of the Absorption-ECM of the current account ratio. 

The Full Model includes all 10 explanatory variables in the long-run equation, while the

Parsimonious Model includes only those 7 significant explanatory variables. In

estimating both models, we use data from 1974 through 1996 so that the coefficient

estimates can be used to perform out-of-sample forecasts over the 1997-1999 period. 
21

Table 3a reports the results of the Full Model, while Table 3b reports results of the

Parsimonious Model. Together, Table 3a, Table 3b, and Table 2 indicate that long-run

coefficient estimates remained reasonably stable across the two different sample

periods1974 through 1996 and 1974 through 1999.

In both Tables 3a and 3b, the adjusted R2

s for ECM are near 0.30, which is 

reasonably good for this type of regression. Reassuringly, the coefficient estimate on the

lagged equilibrium error (μt-1)the deviation of the actual CAR from the long-run

equilibrium CARis statistically significant and negative. This finding indicates that the

gap between the actual and the long-run equilibrium CAR will be eliminated over time if

everything else is held constant. However, the fact that the coefficient estimates are

moderate (-0.24 and -0.25) suggests that the adjustment toward the long-run equilibrium

does not occur quickly. The fact that the coefficient estimate on the equilibrium error is

statistically significant and has the right sign also means that increases in any of the

explanatory variables will always have dynamic effects on CAR through changes in the

equilibrium error, even though not all of their lagged first differences enter significantly

in the ECM.

In addition to the lagged equilibrium error, the lagged first difference of real

exchange rate, U.S. output gap, U.S. interest rates, and foreign interest rates also have

significant coefficients in the ECM. An increase in the lagged first difference of the real

exchange rate (that is, a real dollar appreciation) or the U.S. output gap lowers CAR. An

increase in the lagged first difference of the real U.S. interest rate lowers CAR, while that

of the foreign interest rate raises CAR. 
22

5. Comparing Forecast Performances of Alternative Current-Account Models 

To ascertain how well absorption-based current account models fare relative to 

elasticity-based models, this section estimates and compares four additional models of the

current account: (1) an ECM of CAR based on the elasticity approach; (2) a first

difference (FD) equation of CAR based on the elasticity approach; (3) a parsimonious

first difference equation of CAR based on the absorption approach; and (4) a full-scale

first difference equation of CAR based on the absorption approach. The latter three

models use the first difference, instead of the level, of the explanatory variables and

impose an Almon-lag structure on the first differences of the explanatory variables. 

Theoretically, forecast performances of a cointegration-ECM method should be

superior to those of a first-difference (FD) method because the latter does not take

advantage of level information. This is indeed what we find. For in-sample forecasts, we

use coefficient estimates obtained from regressions using data from 1974 through 1999 to

generate dynamic forecasts over the 1974-1999 period for all six models under

comparison. For out-of-sample forecasts, we use coefficient estimates obtained from

regression using data from 1974 through 1996 to generate dynamic forecasts of all six

models for the 1997-1999 period. For ECM models, we use long-run coefficient

estimates obtained from regressions over the 1974-1996 sample period and historical data

for all right-hand-side variables to forecast the long-run equilibrium CAR from 1997

through 1999, and then use the first differences of explanatory variables and the ECM

coefficient estimates to generate dynamic out-of-sample forecasts.
23

Estimation results of the elasticity-based ECM are reported in Table 4. Insample forecasts of the three ECMs are plotted in Figure 2a, and their out-of-sample

forecasts are plotted in Figure 2b. Estimation results of the three FD equations are

reported in Table 5. In-sample forecasts of the three FD equations are plotted in Figure

3a, and their out-of-sample forecasts are plotted in Figure 3b. 

Do absorption-based models really outperform elasticity-based models? A

casual observation of Figures 2a-3b suggests that the answer is yes. Overall, forecasts of

absorption-based models appear to track the actual current account reasonably well over

the 26-year span from 1974 through 1999 and considerably better than those of elasticitybased models. This finding is confirmed by all three indicators of forecast

performancethe root-mean-square error (RMSE), the root-mean-square percent error

(RMS%E), and the Theil’s Ureported at the bottom of Tables 3a, 3b, 4, and 5.

6. Data 

GDP Gaps: Both U.S. and foreign output gaps are measured as the ratio of actual

GDP to potential GDP. The Congressional Budget Office’s estimate of potential GDP is

used to measure the U.S. GDP gap. The foreign GDP gap is a geometric trade-weighted

average of GDP gaps of 18 major U.S. trading partnersJapan, Germany, France, Italy,

the Netherlands, Belgium, the United Kingdom, Canada, Switzerland, Sweden, Australia,

Mainland China, Taiwan, Korea, Hong Kong, Singapore, Mexico, and Brazil. Estimates

of GDP gaps for individual foreign countries are from the Board of Governors of Federal

Reserve Banks. 
 18 In constructing the “long-term” interest rate on foreign government bonds, we confronted two issues: (1)

different countries issue government debt securities that mature at different rates, and (2) some countries do not

issue long-term government debt or issue such debt for a few years but then discontinue the practice. We settled

on interest rates of government bonds with maturity of or near 10 years from 10 foreign countries—France,

Germany, Japan, the United Kingdom, Canada, Australia, Belgium, Korea, the Netherlands, and Switzerland—to

obtain a continuous times-series from 1974 through 1999.

24

Real Interest Rates: Both U.S. and foreign real interest rates are proxied by

inflation-adjusted nominal interest rates. Real foreign interest rates are obtained by

subtracting the trade-weighted consumer price inflation of 10 major U.S. trading partners

from the trade-weighted nominal interest rates of those same countries. Nominal foreign

interest rates are "long-term government bonds" of 10 major U.S. trading partners

obtained from International Financial Statistics, which is published by the International

Monetary Fund.18

U.S. Private Wealth: U.S. private wealth is measured by the net worth (= assets -

liabilities) of U.S. households and nonprofit organizations in the United States. The data

are obtained from "Flow of Funds Accounts of the United States," which is published by

the Board of Governors of Federal Reserve Banks. 

Dependency Ratios: Both U.S. and foreign dependency ratios are the ratio of the

dependent population (those under the age of 15 years or over the age of 65 years) to the

total population. For both the United States and all 18 foreign countries except Taiwan,

annual data up to and including 1994 are from the World Bank Savings Database. Data

from 1995 through 1997 are taken from Demographic Yearbook, which is published by

the United Nations. Foreign data, with the exception of Taiwan, for 1998 and 1999 are
 19 First, the number of people who were age 15 or younger, or age 60 or older, in 1998 and 1999 in each

country (except Taiwan) was obtained from the U.N. Statistics Division Web site. The historical relationship

between the number of individuals older than 65 and that older than 60 was then estimated for each country. (The

UN Demographic Yearbook reports population in five-year age brackets as far back as 1971.) Finally,

dependency ratios for 1998 and 1999 were developed by assuming that the historical relationship between those

older than 65 and those older than 60 held for 1998 and 1999.

 20 They are Japan, Germany, France, Italy, the Netherlands, Belgium, the United Kingdom,

Canada, Switzerland, Australia, China, Taiwan, Korea, Singapore, Hong Kong, and Mexico. 

25

our own forecasts.19 U.S. data from 1998 through 1999 are taken from the Census

Bureau’s Population Estimates. Data for Taiwan are taken from its web site

(www.dgbassey.gov.tw).

U.S. Government Budget: Federal, state, and local government budget balances

were obtained from the Bureau of Economic Analysis.

Corporate Profits: After-tax corporate profits were obtained from the Bureau of

Economic Analysis. 

Real Exchange Rate: The real exchange rate is calculated as U.S. consumer price x

trade-weighted nominal dollar exchange rate/trade-weighted foreign consumer price. 

The nominal exchange rate and consumer price for each of the 16 major U.S. trading

partners20 are indexed to 1 in 1996 before they are collapsed into the trade-weighted

indexes.

7. Conclusion

Little work has focused on building a forecasting model of the current account from

the absorption perspective that the current account balance is the difference between

domestic savings and investment. We believe that the rapid growth of capital flows
26

across national borders makes it essential to construct a current account model that lends

itself to analyzing the impact of developments that affect the current account through

financial flows. The traditional elasticity approach is poorly equipped to fulfill this role

and has fallen short in its ability to forecast the current account and to shed light on

important policy issues such as the role of the exchange rate and the government budget

balance in shaping the current-account development.

In this paper, we derive and estimate alternative current account models based

on the absorption, or the savings-investment, approach. This approach shows that the

three traditional variablesthe real exchange rate, domestic activities, and foreign

activitiesdo exert a significant influence on the current account, as postulated by the

elasticity approach. More important, it shows that some variables overlooked by the

elasticity approachnamely, the share of dependents in the foreign population, real U.S.

and foreign interest rates, and U.S. corporate profitsalso matter for the current-account

adjustment, while the government budget balance does not. The finding that the budget

balance is not a significant determinant of the current account suggests that U.S. private

savings may have tended to adjust to offset changes in the government budget.

Overall, models based on the absorption approach track and forecast the U.S.

current account much better than simple models based on the elasticity approach. To be

sure, in reality elasticity-based models of the current account are much more

sophisticated than the simple ones constructed here for comparison purposes. 

Nevertheless, the finding of this paper suggests that, at the very least, forecasters should

consult absorption-based models in forming current-account forecasts.
27

REFERENCES

Campbell, J. and Perron, P. 1991. Pitfalls and Opportunities: What Macroeconomists

Should Know About Unit Roots. NBER Macroeconomics Annual, Cambridge,

Mass.: MIT Press.

Dickey, D. and Fuller, W. 1981. Likelihood Ratio Statistics for Autoregressive Time

Series with a Unit Root. Econometrica 49.

Engle, R. and Granger, C. 1987. Co-integration and Error Correction. Econometrica 55. 

Engle, R. and Yoo, B.S. 1987. Forecasting and Testing in Co-integrated Systems. 

Journal of Econometrics 35.

Farugee, Hamid and Guy Debelle. 1998. "Saving-Investment in Industrial Countries: An

Empirical Investigation." In Exchange Rate Assessment: Extensions of the

Macroeconomic Balance Approach, edited by Peter Isard and Hamid Farugee,

International Monetary Fund Occasional Paper No. 167.

Granger, Clive and P. Newbold. 1974. "Spurious Regressions in Econometrics." Journal

of Econometrics 2, pp. 111-20.

Harberger, Arnold C. 1950. "Currency Depreciation, Income, and the Balance of Trade."

Journal of Political Economy 58, No. 1, pp. 47-60.

Krugman, Paul. 1987. "Adjustment in the World Economy." NBER Working Paper No.

2424.

Laursen, Svend and Metzler, Lloyd A. 1950. "Flexible Exchange Rates and the Theory of

Employment." Review of Economics and Statistics 32, pp. 281-99. 

Obstfeld, Maurice, 1982. "Aggregate Spending and the Terms of Trade: Is There a

Laursen-Metzler Effect?" Quarterly Journal of Economics, 97, pp. 251-70.

______, (1986) "Capital Mobility in the World Economy: Theory and Measurement,"

(Carnegie-Rochester Conference Series on Public Policy, Spring 1986, Brunner and

Meltzer (ed). 

Persson, Torsten and Lars E. O. Svensson, (1985) "Current Account Dynamics and the

Terms of Trade: Harberger-Laursen-Metzler Two Generations Later," Journal of Political

Economy, 93, pp. 43-65.
28

Saikkonen, P. 1991. "Asymptotically Efficient Estimation of Cointegration Regression."

Econometric Theory 7:1-21.

Stock, J. H. 1987. "Asymptotic Properties of Least Squares Estimators of Cointegrating

Vectors’, Econometrica, 55. pp. 1035-1056.

Stock, J. H., and Watson, M.W. 1990. "A Simple MLE of Cointegrating Vectors in

Higher Order Integrated Systems." NBER Technical Working Paper No. 83.

Svensson, Lars and Assaf Razin, 1983. "The Terms of Trade and the Current Account:

The Harberger-Laursen-Metzler Effect," Journal of Political Economy, vol. 91, no. 11,

pp. 97-125.
29

1971 1976 1981 1986 1991 1996

8

6

4

2

0

US Corporate Profits, Percentage of Potential GDP

1971 1976 1981 1986 1991 1996

40

38

36

34

32

U.S. Dependency Ratio, Percent

0

1971 1976 1981 1986 1991 1996

40

38

36

34

0

Foreign Dependency Ratio, Percent

32

1971 1976 1981 1986 1991 1996

2

1

0

-1

-2

-3

-4

-5

US Current Account Bal., Percentage of Potential GDP

1971 1976 1981 1986 1991 1996

3

2

1

0

-1

-2

-3

-4

-5

-6

-7

US Gov.’t Budget Bal., Percentage of Potential GDP

1971 1976 1981 1986 1991 1996

450

400

350

300

500

US Net Private Assets, Percentage of Potential GDP

0

Figure 1a. Variables in the Current Account Models
30

1971 1976 1981 1986 1991 1996

106

104

102

100

98

96

0

Foreign GDP Gap, Index (1992 = 100)

1971 1976 1981 1986 1991 1996

110

105

100

95

90

0

US GDP Gap, Percent

1971 1976 1981 1986 1991 1996

1.40

1.30

1.20

1.10

1.00

0.90

0

Real Dollar Exchange Rate, Index (1996 = 1.00)

1971 1976 1981 1986 1991 1996

-12

-9

-6

-3

0

3

6

9

Foreign Real Interest Rate, Percent

1971 1976 1981 1986 1991 1996

14

12

10

8

6

4

2

0

-2

-4

-6

US Real Interest Rate, Percent

Figure 1b. Variables in the Current Account Models

Note: US GDP Gap = (Actual GDP x 100) / Potential GDP
31

 Table 1. Time-Series Property of Variables in the Current Account Model

VARIABLES PROPERTY

Current Account Ratio I(1)

Log (Real Exchange Rate) I(0)

U.S. GDP Gap I(0)

Foreign GDP Gap I(0)

U.S. Dependency Ratio I(0)

Foreign Dependency Ratio I(1)

U.S. Private Wealth I(1)

U.S. Corporate Profits I(0)

U.S. Budget Balance I(1)

U.S. Inflation-Adjusted Interest Rate I(0)

Foreign Inflation-Adjusted Interest Rate I(0)

Note:These results are based on augmented Dickey-Fuller unit root tests for the 1971 through 1999 period. 

Lags were chosen based on the Akaike information criteria. 
32

Table 2. Long-Run Equations of the Current Account Ratio

(Estimation method: OLS, Sample period 1974-1999)

(Absolute value of t-statistics in parenthesis)

Dependent Variable: CAR (The Current Account/Potential GDP Ratio)

1 Regressor (1) 

Absorption

Full Model

(2)

Absorption 

Parsimonious 

Model

(3)

Elasticity 

Approach

Constant -24.54

(3.13)

-14.82

(3.29)

-25.25

(3.34)

2

 Log (RER)t-1 -0.030

(3.92)

 -0.032

(4.83)

-0.007 

(0.89)

GDP Gap t-1 -0.45

(12.86)

-0.43

(12.46)

-0.53

(12.46)

GDP Gap*t-1 0.45

(6.97)

0.42

(6.65)

0.77

(9.65)

Dependency Ratio 0.173 

(1.36)

Dependency Ratio* 0.44

(3.39)

0.38

(6.67)

3

 Private Wealth 0.002 

(0.54)

3

 Corporate Profits t-1 0.26

(3.46)

0.32

(5.99)

3 Budget Balance t-1 0.057 

(0.89)

4

 Real Interest Rate 0.075

(2.87)

0.078

(2.94)

4

 Real Interest Rate* -0.043 



(1.12)

-0.093

(3.38)

5

 Dummy 1991Q1 1.43

(10.26)

1.34

(9.74)

0.64

(4.68)

Adjusted R2 0.88 0.88 0.54

ADF Statistics -4.59 -4.42 -2.54

Phillips-Perron Stat. -4.88 -4.88 -2.94

NOTES

1. Foreign variables are denoted by "*".

2. Real Exchange Rate = (U.S. prices)*(nominal exchange rate)/(foreign prices).

3 These variables are normalized by nominal potential GDP (= potential GDP x GDP deflator). 

4. These are inflation-adjusted interest rates.

5. Dummy 1991Q1 is intended to capture the effect of the large increase in U.S. net unilateral transfers that

resulted from the Gulf War.

6. Coefficient estimates with significant level higher than 10 percent are indicated by "

".
33

Table 3a. The Absorption-ECM of the Current Account: Full Model 

(Estimation method: OLS; sample period: 1974-1996)

(Absolute value of t-statistics in parenthesis)

Dependent variable: CAR Dependent variable:



(CAR)

1

 Regressor 1974-96 Regressor 1974-96

Constant -29.31

(3.47)

2

 μt-1 -0.24

(2.78)

 Log (RER)t-1 -0.028

(3.51)



log(RER) -0.031

(2.06)

GDP Gap t-1 -0.47

(12.76)



(GDP Gap) -0.17

(4.22)

GDP Gap*t-1 0.51

(7.16)



(Real Interest Rate)t-1 -0.075

(3.45)

Dependency Ratio 0.19 

(1.43)



(Real Interest Rate )t-2 -0.062

(2.82)

Dependency Ratio* 0.44

(3.21)



(Real Interest Rate*)t-1 0.058

(2.35)

Private Wealth -0.002 

(0.35)



(Real Interest Rate*)t-2 0.049

(2.01)

Corporate Profits t-1 0.28

(3.54)

Budget Balance t-1 0.024

(0.33)

Real Interest Rate 0.078

(2.80)

Real Interest Rate* -0.039

(-1.00)

Dummy 1991Q1 1.39

(9.44)

Adjusted R2 0.86 Adjusted R2 0.28

Out-of-sample

Theil’s U (1997-1999)

0.423

ADF Statistics -4.43 Out-of-sample 

RMS%E (1997-1999)

0.168

Phillips-Perron Stat. -4.87 Out-of-sample 

RMSE (1997-1999)

0.416

NOTES

1. See Table 2 for definitions of variables.

2. This variable is the residual from the long-run regression.
34

Table 3b. The Absorption-ECM of the Current Account: Parsimonious Model 

(Estimation method: OLS; sample period: 1974-1996)

(Absolute value of t-statistics in parenthesis)

Dependent variable: CAR Dependent variable: 

(CAR)

1

 Regressor 1974-96 Regressor 1974-96

Constant -19.20

(3.85)

2

 μt-1 -0.25

(2.94)

Log (RER)t-1 -0.036

(4.79)



log(RER)t-1 -0.032

(2.13)

GDP Gap t-1 -0.44

(13.22)



(GDP Gap)t-1 -0.18

(4.31)

GDP Gap*t-1 0.45

(8.11)



(Real Interest Rate)t-1 -0.077

(3.51)

Dependency Ratio* 0.44 

(5.77)



(Real Interest Rate )t-2 -0.063

(2.84)

Corporate Profits t-1 0.28

(4.47)



(Real Interest Rate*)t-1 0.063

(2.55)

Real Interest Rate 0.080

(2.92)



(Real Interest Rate*)t-2 0.051

(2.11)

Real Interest Rate* -0.077

(-2.38)

Dummy 1991Q1 1.33

(9.45)

Adjusted R2 0.87 Adjusted R2 0.29

Out-of-sample

Theil’s U (1997-1999)

0.362

ADF Statistics -4.18 Out-of-sample 

RMS%E (1997-1999)

 0.165 

Phillips-Perron Stat. -4.73 Out-of-sample 

RMSE (1997-1999)

0.356

NOTES

1. See Table 2 for definitions of variables.

2. This variable is the residual from the long-run regression.
35

Table 4. The Elasticity-ECM of the Current Account

(Estimation method: OLS; sample period: 1974-1996)

(Absolute value of t-statistics in parenthesis)

Dependent variable: CAR Dependent variable: 

(CAR)

1

 Regressor 1974-96 Regressor 1974-96

Constant -26.57

(3.50)

 2 μt-1 -0.095

(2.20)

Log (RER)t-1 -0.007 

(0.81)



log(RER)t-1 -0.035

(2.16)

GDP Gap t-1 -0.55

(9.44)



(GDP Gap)t-1 -0.14

(3.30)

GDP Gap*t-1 0.79

(8.64)

Dummy 1991Q1 0.62

(4.44)

Adjusted R2 0.44 Adjusted R2 0.17

Out-of-sample

Theil’s U (1997-1999)

 0.576

ADF Statistics -2.37 Out-of-sample 

RMS%E (1997-1999)

 0.193 

Phillips-Perron Stat. -2.78 Out-of-sample 

RMSE (1997-1999)

0.561

NOTES

1. See Table 2 for definitions of variables.

2. This variable is the residual from the long-run regression.
Table 5. First-Difference Equations of the Current Account Ratio 

(Estimation Method: OLS; sample period: 1974-1996)

(Absolute value of t-statistics in parenthesis)

(Dependent Variable: 



CAR) 

(Coefficient Estimates are the sum of coefficients on the distributed lags.1

)

2

Regressor Absorption

FD (A)

Absorption

 FD (B)

Elasticity

FD Eq. 



 CAR t-1 -0.20

(1.71)

-0.08

(0.68)

-0.001

(0.009)



 log (RER)t-0 to 3 -0.06

(2.09)

-0.06

 (1.99) 

-0.05

 (1.75) 



GDP Gap t -0 to 3 -0.32

(2.48)

-0.18

 (1.38) 

-0.17

 (1.33)



 GDP Gap*t-0 to 3 0.48

(2.06)

0.18

 (0.79) 

0.10

 (0.47) 



 Dependency Ratio t-0 to 3 0.8

(1.00)



 Dependency Ratio*t-0 to 3 0.35

(0.40)

0.74

 (1.08)



 Private Wealth t-0 to 3 -0.00

(0.26)

 



 Corporate Profits t-0 to 3 -0.28

(0.91)

-0.19

 (067) 



 Budget Balance t-0 to 3 0.09

(0.47)



 Real Interest Rate t-0 to 1 0.10

(2.60)

0.11

(2.67)



 Real Interest Rate* t-0 to 1 -0.01

(0.22)

-0.06

(1.36)

Adjusted R2 0.23 0.09 0.04

Out-of-sample

Theil’s U (1997-1999)

0.511 0.442 0.790

Out-of-sample 

RMS%E (1997-1999)

0.164 0.122 0.215

Out-of-sample 

RMSE (1997-1999)

0.506 0.460 0.760

Note

1. The same polynominal lag restrictions are used for all regressions reported here.

2. See Table 2 for definitions of variables.
37

74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99

(%)2

1

0

-1

-2

-3

-4

-5

Figure 2a. Actual vs Fitted Current Account Ratio

In-sample Forecasts of ECM 

Actual Absorption-Full Model

Absorption-Parsimonious Model Elasticity Model

82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99

(%)1

0

-1

-2

-3

-4

-5

Figure 2b. Actual vs Fitted Current Account Ratio

Out-of-sample Forecasts of ECM 

Actual Absorption-Full Model

Absorption-Parsimonious Model Elasticity Model
74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99

(%)4

2

0

-2

-4

-6

Figure 3a. Actual vs Fitted Current Account Ratio

In-sample Forecasts of First Difference Equations 

Actual Absorption-Full Model

Absorption-Parsimonious Model Fitted-Elasticity 

82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99

(%)1

0

-1

-2

-3

-4

-5

Figure 3b. Actual vs Fitted Current Account Ratio

Out-of-sample Forecasts of First Difference Equations 

Actual Absorption-Full Model

Absorption-Parsimonious Model Fitted-Elasticity