The effect of government spending on the current account, output, and expenditures: Evidence from latin America

JOUFNAL OF

ELSEVIER

Journal

of Development

Economics

44 (1994) 287-310

The effect of government spending account, output, and expenditures: Latin America

Development ECONOMICS

on the current Evidence from

Evan Tanner Department of Economics, Received

Utkersity

of Miami, Coral Gables, FL 33124, USA*

July 1991. final version

received

April 1993

Abstract This paper examines the linkages between government expenditures and current account balances in several Latin American economies, over the period 19741984. In theory, these linkages critically depend on private sector responses to changes in government expenditures, on both the demand and supply sides. The analysis provides evidence that the negative current account - government expenditure linkage is much stronger in the event of a temporary shock to government expenditures than in the event of a permanent shock. The source of this differential response appears to be primarily on the expenditure side, suggesting that private sectors in Latin America incorporate the present discounted value (rather than simply the current value) of government expenditures into their expenditure decisions. Key words: lntertemporal optimization; Dependent economy model; Real exchange rate; Traded and nontraded goods; Bequest motive; Current account; BeveridgeNelson decomposition JEL

1.

classijcation:

E62; F32; 011

Introduction

During the decades of the 1970s and 198Os, the Latin American economies experienced sharp swings in both their current account balances and growth rates of government spending. Fig. 1 displays average yearly rates of growth *The current revision of this paper was performed at the University of Miami. The original version was written while the author was a Visiting International Economist at the Department of State EB/PAS. Helpful comments on various drafts have come from Bill Gavin, Bill Dewald, Mike Ulan, Steve Webb, Sebastian Edwards, Arnold Harberger, Edward Learner, Dan Trefler, Bruce Kobayashi, Martin Bailey, Ross Levine, participants in the UCLA Latin American Economics Workshop, and two anonymous referees. The views expressed herein, and any mistakes, are my own. 0304-3878/94/$07.00 cj 1994 Elsevier Science B.V. All rights reserved SSDI 0304-3878(94)00015-5

288

E. Tanner / Journal

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Econonzicv 44 (1994) 287-310

of government expenditures in Latin America over the period 19741985. These rates were high during the 197Os, but much lower (and in some years negative) during the early 1980s. Fig. 2 displays the average change in the current account (net of factor payments), as a fraction of exports. While the 1970s were largely characterized by increasing deficits - especially during the years directly subsequent to the 1973 and 1979 oil price shocks - the 1980s were largely characterized by decreasing deficits (and in some cases surpluses), as countries made efforts to meet debt payments. The exact linkage between government expenditures and current account balances critically depends upon private sector responses to changes in government expenditures, on both the demand and supply sides. This paper more closely examines that linkage in several Latin American economies over the period 19741984. The analysis provides evidence that the negative current account - government expenditure linkage is much stronger in the event of a temporary shock to government expenditures than in the event of a permanent shock. The source of this differential response appears to be primarily on the expenditure side, suggesting that private agents in Latin American economies incorporate the present discounted value (rather than simply the current value) of government expenditures into their expenditure decisions. To incorporate private sector responses into an analysis of the government expenditure - current account relationship, a two-equation model of output and the current account is developed. Since the current account is the difference between the quantities of traded goods and services supplied and demanded, the effect of government expenditures on both schedules is examined. On the demand side, in addition to the direct effect of government purchases, government spending should affect private sector expenditures in (at least) two ways. First, an increase in government expenditures should induce a decrease (increase) in private sector expenditures if government and private sector expenditures are substitutes (complements).’ Second, an increase in government expenditures may induce a decrease in private sector expenditures, due to the change in the present discounted value of the tax burden. Consider next the supply side: an increase in government spending may affect production, both through the direct marginal productivity of government expenditures, positive or negative, and indirect effects on work effort which result from changes in the tax burden implied by permanent changes in government spending. In order to capture these effects, the analysis here utilizes both (i) a set of restrictions on

’ Government purchases that might be considered as substituting for private sector purchases include health care, police services, fire protection, and so on. Alternatively, government purchases of infrastructure (i.e. say, roads) may induce increases in private purchases (say, automobiles).

E. Tunner

289

/ Journal of Development Economics 44 (1994) 287-310

_I

13131914IJIS Fig. 1. Real government

1913

Fig. 2. Current exports.

1314

,976

,911

expenditures

1975

account

I316

(311

balances

,918

,319

,380

in Latin America:

,378

in Latin

,379

1980

America:

138,

1382

Weighted

I381

1382

Weighted

I383

1984

average

1983

1385

yearly

1984

average

I386

growth

1981

change

rates.

1986

as a fraction

290

E. Tanner 1 Journal qf Development

Economics

44

/ 1994) 287-310

the parameters implied by the theory, and (ii) a decomposition of government expenditures into temporary and permanent components. This procedure enables us to distinguish between the substitution/complementarity of government spending and the tax-burden effects on the demand side as well as between the direct marginal productivity effects and the tax-burden effects on the supply side. The decomposition technique is a present-discountedvalue variant of the method proposed by Beveridge and Nelson (1981). The model is estimated with pooled (time-series/cross-section) data. Other authors have attempted to distinguish between the aforementioned effects of government spending using a temporary/permanent decomposition and data from developed countries. Barro (198 1) used a closed economy model and data from the United States. A key feature of any closed economy model is that aggregate supply equals aggregate demand. Ahmed (1986) used an open economy model, in which all goods were internationally traded. The model was estimated using data from the United Kingdom. A key feature of any open economy model is that both the effects on aggregate supply and the trade balance (or the current account, net of investment income) may be examined, as the trade balance (in goods and services) is the difference between aggregate supply and aggregate demand. The model used here is similar to that of Ahmed (1986), but includes nontraded goods and two internationally traded goods, imports and exports. The system of equations is based on a more rigorous intertemporal model of consumption, the current account, and the real exchange rate, for a small open economy with non-traded goods and a government sector. This setup is similar in spirit to several recent equilibrium models of fiscal policy and the real exchange rate. The empirical model draws upon a body of theoretical work (i.e. papers by Dornbusch (1983), Edwards (1989a), Cuddington and determination Vinals (1986), and Murphy (1986)) m which the simultaneous of the current account and the real exchange rate are examined within a context of intertemporal optimization. Thus, in addition to the current account and output, the empirical formulation here includes as variables, the real exchange rate and the terms of trade. Figs. 3 and 4 display rates of growth of the real exchange rate (defined here as units of the domestic currency per dollar, multiplied by the ratio of the world price index to the domestic price index) and gross domestic product, respectively. Fig. 4 largely mimics government Spending in Fig. 1: while growth rates of output were high during the 197Os, they were low, and in some years negative, during the 1980s. Fig. 3 shows that, while real appreciations (decreases in the real exchange rate) were common during the 197Os, the 1980s have been largely characterized by real depreciations. The presence of these strong co-movements suggests that these variables should not be omitted when explaining current account and output movements.

291

1973

,974

,975

Fig. 3. Real exchange

I973

,974

(971

Fig. 4. Real gross domestic

1976

191,

,9,B

,919

rates in Latin America:

,916

product

,971

$918

1919

,960

,9n,

Weighted

1980

in Latin America:

1981

Weighted

,982

average

,982

,983

t9nq

19n5

yearly growth

,983

average

,981

yearly

1986

rates.

1985

growth

,985

rates.

292

E. Tanner / Journal

qf Development Economics 44 (1994) 287-310

The principal finding of the paper is that positive temporary shocks to government expenditures have a greater (negative) effect on current account balances than do permanent shocks. An informal reduced-form test reveals that, while the hypothesis that permanent shocks have no effect on the current account cannot be rejected, the hypothesis that temporary shocks have no effect can be rejected. A more formal test of several cross-equation restrictions reveals further that (i) changes in government spending have strong effects on both output and aggregate expenditures and (ii) temporary changes in government expenditures have much stronger effects on aggregate expenditures (private plus public) than do permanent changes. The remainder of the paper is organized as follows. In Section 2, a system of equations is developed.2 Specifically, a system of reduced form equations which describe ‘temporary’ and ‘permanent’ changes in government spending, aggregate supply, non-tradable goods prices, and the current account is derived. The key issues which the model addresses, namely supply and demand effects of government purchases, are examined. Restrictions on coefficients (both within and across equations) and the relative signs and magnitudes of these coefficients are discussed. In Section 3 some technical remarks are made with respect to the decomposition of government expenditures into temporary and permanent components, the addition of monetary variables, and the estimation method. Section 4 presents the empirical estimates and their interpretation. In Section 5, a summary and some conclusions are provided.

2. The model In this section, I develop a system of testable equations which describes the behavior of output and demand as a function of several variables.

2.1. Structure

of the model

There are two sectors: a traded goods and services sector and a non-traded goods and services sector. I consider first each sector separately, and then aggregate supply for the whole economy. 3 In the traded goods sector, there are two goods, imports and exports. The prices of imports and exports are written EP, and EP,, respectively, where E is the nominal exchange rate

‘The model is based upon the more complete theoretical framework presented in an appendix available upon request from the author. 3 In the remainder of the paper, the word ‘goods’ will be a shorthand for ‘goods and services’.

E. Tanner / Journal qf Development Economics 44 (1994) 2X7-310

293

(expressed as domestic currency units per U.S. Dollar). If the country’s traded goods sector produces both exports (4;) and import substitutes (q;), the total quantity of tradables, measured in terms of the non-traded good is (EPxl/PN,)qS(,+(EPhlf/PNt)q~t. However, for our purposes (and consistent with the theoretical model), it will suffice to express these two goods as a single price is EP,,. Thus, in the composite traded good, q&, whose composite empirical work, we will be dealing with a traded goods supply function, expressed in terms of the non-traded good:

Q;,= W’,JPd&,.

(1)

Similarly, while the country consumes both imports (4;) and its own export goods (q$), the total demand for the composite traded good, expressed in units of the non-traded good, Qt, is written:

(2)

Qt,= W’,P,,)& At time t, the current account CA, is defined as the difference

(net of factor service payments between these two variables:

CA, = Q;, - Q;,.

and

receipts),

(3)

Unlike the traded goods sector, the non-traded goods sector consists of only one good, for which supply is written qf+ and demand is written qt. The good is assumed to be non-storable. At any time, for this good, supply equals demand: qit = q&. Aggregate supply, expressed in terms of the non-traded good, is simply q, = EPr,IC&,

(4)

+ &f.

Government spending (G) is composed of a permanent component (G*) and a temporary component (g). The decomposition, discussed at length in Section 3, is expressed as dG,=dG:+dg,, where d is the first difference

2.2. Sectoral

(5) operator.

demands

While the tests in this paper will concentrate on the traded goods sector, demands for both traded goods and non-traded goods are written. The consumption decision is explicitly modelled, The critical features of the structure of preferences are quite basic: utility is assumed to be separable across time. In order to focus on substitution in consumption resulting from

E. Tanner / Journd

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of Development Economks 44 (1994) 287-310

changes in the real exchange rate, (and to ignore substitution effects due to terms of trade changes) we aggregate consumption of imports and exports into a composite traded good, C,,4,5. Thus, the following utility function is maximized (subject to an intertemporal budget constraint):

u = f u,(Q&-E)/( t=o

The

terms

optimized

(6)

1 + p)’ = f U,(C,)/( 1 + p)‘. f=O

c,, and c’Tf are composite private sector purchases, defined

terms by

of government

sector

and

c,, = C,,(private)**G$‘,

c,, = C,,(private)**G;; where C,,(private)* and C,,(private)* denote optimal private purchases (conditional on some level of government purchases). Thus, oN and oT are gross coefficients of substitutability between government spending and, nontraded and traded goods respectively. To be more precise, government purchases and private sector purchases are substitutes (complements) as (T is less than (greater than) one. For the remainder of the paper, we assume that any change in government spending is composed of equal changes in both markets (AC,= AC,= AC). (The implications of this assumption are fully examined in an appendix available upon request from the author.) The structure of preferences yields demand functions, for traded and nontraded goods markets. Written in logarithmic differences, they are: A log qft = CQ+ [( 1~ ii) + #] AG*/G*

+ (1 - &)Ag/G

+ &( A log E + A log P, ~ A log PN) + ci( A log P, - A log PM) + error,

4The most complete and correct procedure would be to specify a utility sub-function period whose arguments are the three goods, imports, exports, and non-traded goods

(7)

for each

However, for the current purposes, this construction will needlessly complicate the analysis. induces substitution between traded and ‘A change in the real exchange rate EP,;‘P, non-traded goods, while a change in the terms of trade P,/P, induces substitution between imports and exports. While we ignore the latter substitution effect, changes in the terms of trade have important wealth effects which are incorporated into the model.

E. Tmrw

i Journal of Dewlopment

Economics

44 11994) 2X7-310

295

where i=T, N. Note that changes in both components of government expenditures are scaled by permanent government expenditures G*.(j The 3. terms (&, 2,) are net coefficients of substitutability in tradables and nontradeable markets, respectively: a one-percent change in government spending induces 2, and 1, percent changes in expenditures in traded and non-traded goods markets, respectively. As derived in the theoretical model, the I terms are functions of both the taste parameters in the representative consumer’s utility function (By, or) and the distribution of the initial government spending between traded goods and non-traded goods markets. The term r$ captures the response of the private sector to a permanent increase in government spending. The main reason why permanent increases in government spending may differ from temporary increases is due to their different implications for the tax burden. Most of the studies which have considered this aspect of government spending have used data from developed countries. Barro (1981) and Seater and Mariano (1985) used U.S. data, while Ahmed (1986) used data from the U.K. The underlying assumptions and the predictions generated from these assumptions were more appropriate for developed countries than for developing countries. Nevertheless, we can use the developed country framework as a ‘benchmark’ case. Two critical assumptions underlying most developed country studies are: (i) The form of taxation was assumed to be lump-sum. That is, the taxation does not distort the choice between present and future consumption;’ (ii) agents in the economy have a positive bequest motive: They respond to a future increase in the tax burden on their progeny by saving more. If these assumptions hold, private-sector expenditures will decrease with a permanent increase in government spending (i.e. 4 < 0). The former assumption may be questionable in the Latin American context, as taxes are likely to significantly distort the intertemporal allocation of consumption. These economies do rely to some degree on income taxation, much like developed economies. However, relative to most developed economies, a much greater share of taxation takes the form of valueadded taxes, tariffs, inflation, and currency devaluation. Clearly, tariffs alter the consumption decision between imported goods and other goods. As well, expected inflation or currency devaluation may induce more current consumption relative to future consumption (as both are taxes on current asset holdings), if it is sufficiently costly for agents to switch into closely ‘Two alternative scaling methods were tried but not reported: a logarithmic decomposition A logG= A logG*+ A logs and scaling by total government expenditures G. Since G tends to be close to G’, the three methods provided almost indistinguishable results. ’ However, departing from the assumption of lump-sum taxation will not necessarily weaken the prediction, as shown by Judd (1987) and Fremling and Lott (1989).

296

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1Journal c$ Development

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substitutable assets denominated in another currency. If this is the case, it is possible that a permanent rise in government expenditures leads to an increase in consumption (i.e. fj > 0). The coefficients fiT and flN capture expenditure switching from one sector to another resulting from a change in the real exchange rate. As the real exchange rate is a proxy for a measure of the relative price of tradables to non-tradables, an increase in (d log E + d log P, - A log PN) will induce a decrease in the quantity of tradables demanded &CO), and an increase in the quantity of non-tradables, demanded (& > 0). Finally, the terms Ed and cN capture the effects on expenditure which are induced by a change in the terms of trade (A log Px - A log PM). We are ignoring any potential substitution effects between imports and exports. Rather, an increase in the terms of trade induces an increase in wealth and thus spending in both sectors (Lo, cN > 0). (This issue was treated in detail by Laursen and Metzler (1950) Harberger (1950) and Svensson and Razin (1983). More recently, Tanner (1988) tested for these effects by decomposing export price changes into temporary and permanent components.) 2.3. Sectoral

supplies

The traded-sector composite good consists of exports and import substitutes. The logarithmic difference of sectoral supply functions 4; and qh are: A

log

q; = vi + [y +

p]AG*/G*

+ yg/G* + o,(A log E + d log P, - A log PN)

+ Hi(A log P, - A log PM) + error, y >O,

p>O,

o,>O,

oN ~0,

Q,, 0, unsignable,

where i=N, T. The coefficients y and 1-1may be interpreted as capturing a causal linkage between government expenditures and supply. As discussed by Barro (1981) and Ahmed (1986) there are at least two channels through which government spending may influence supply. First, government spending may be, in and of itself, productive. While governments may not be efficient, they nonetheless supply goods and services in response to the demands of their constituents. As well, a dollar spent by the government may complement private sector production. If this ‘marginal productivity of government’ is positive, y >08. Second, as Ahmed (1986) notes, permanent ‘This interpretation of the coefficient 7 should be these coefficients tend toward government’s share the government’s outlays may exceed the market’s services, estimates of government’s true productivity government’s productivity would be to regress government spending. The results of these tests are

made with caution, however. As the value of in gross domestic product, and the value of valuation of the corresponding goods and may be biased upward. An informal test for priuute sector gross domestic product on briefly discussed in the empirical section.

E. Tanner i Journal qf Development Economics 44 (1994) 287-310

291

increases in government spending will increase output by a greater amount than will temporary changes. If taxation is lump-sum and leisure is a normal good, permanent increases in government spending induce an increase in the quantity of labor supplied.’ Much recent work on the relationship between real exchange rate movements and output has focused on the effects of changes in the real exchange rate on the sectoral allocation of resources. An increase in the real exchange rate shifts resources out of the non-traded goods sector and into the traded goods (export or import substitute) sector. Consequently, w,>O and wN ~0. On the supply side, the treatment of changes in the terms of trade is somewhat different from that of the demand side, since it is assumed that producers, unlike consumers, substitute between exports and import substitutes. Thus, on the supply side, terms of trade effects are theoretically ambiguous since substitution and wealth effects are pulling in opposite directions: (0,s 0, f& 3 0).

2.4. Aggregate

supply

and the current account

Two steps are required to transform the above expression (3) (4), (7) and (8) into econometrically testable expressions. First, the sectoral supplies and demands are combined into aggregate supply and current account functions. Second, since it is difficult to obtain a true non-traded goods price P,, the domestic price index P, (= PRIYP+~“) is utilized to approximate the growth of non-traded prices as A log P, = l/ad log P, -( 1 - cc)/cr[Alog E + A log P,].” The growth of real output is obtained by adding up the supply changes in sectors N and T: A logq={~+p}AG*/G*+yAg/‘G* + [jo,

+ ( 1 -.j)wJ[A

+ [$I, + (1 -j)&][A = a, + uIAG*/G*

log E + A log P, - A log PJcc log P, - A log PM] + error

+ a,Ag/G*

+ a,[A log E + A log P, - A log P,]/u

’ Put differently, when the government increases lump-sum taxes, workers feel less wealthy; they work more and consume less leisure, implying that p >O. The controversial nature of this prediction stems from the assumption of lump-sum taxes, which is more critical on the supply side than on the demand side. This assumption is not in general true for the economies under study, as taxation often takes the distortionary forms of inflation or trade taxes. Nonetheless, a test of the hypothesis that p>O indicates how closely the behavior of the economy approximates the predictions of the benchmark model. ” Or, [A log E + A log P, - d log PN] = [A log E + A log P, ~ A log P,]/cc. Estimates of a, the share of non-traded goods in expenditure, are derived from sectoral data from the United Nations. On average, d(= 0.6.

298

E. Tanner

i

+ a,[d

Journal

of Developmenl

log P, -A

Economics

44 (1994)

287-310

log PM] + error

(9)

where j= [(EPT/PN)qT]/q is the share of traded goods in total output and the components of the coefficients a0-u4 are composites of the structural equations in equation (8) for the cases of i = N, T. Thus, Eq. (9) represents the weighted average of output growth rates in each sector. Exports and imports are directly observable, but traded goods supplied and demanded are not. For purposes of estimation, it is illegitimate to equate import demand with (unmeasurable) traded good demand, as traded goods demand contains imports and that portion of the export good consumed at home. Similarly, the supply of traded goods consists of both exports and import substitutes. We can, however, measure the difference between traded goods supplied and traded goods demanded, which is the non-interest current account. For the purposes of pooling, it will be convenient to scale the current account by exports. This function is written ACA/[(EP,/P,)q”x]

= k”,[(A log E + A log P, - A log P,)/x + A log &] - k;[( A log E + A log P, - A log PD)/r + A log q;]

(104 where the k terms express traded goods supplied and demanded as a fraction of exports: kg = (P&)/( P,q,) and k’: = ( PTq$/( P,q,). Substituting in expressions (7) and (8) we find that ACA/[(EP,/P,)q;]

-&)+$l)}AG*/G*

={(kR[y+pl)-kd,([(l +{(k;y)-k;(l

-&))Ag/G*

+ [(A log E + A log P, - A log P,)/a] x [k;( I+ wT) - kd,( 1 + /e&)1 + [d log P, - A log P&k;&

- k&l

+[{kg-kd,}]dlogPJ~(+error.

(lob)

Eq. (lob) can be easily interpreted for the special case of initially balanced trade (kg= kd,) and small changes in the explanatory variables. In that case, it reduces to

A C.M(EP,IP,)di

= { Iv + PI- I( 1- 2,) + 41)AG*/G* +I;‘-(1

-Q}Ag/G*

E. Tunner i Journal of‘ Developmenl Economics 44 (1994) 287-310

299

+ [oT - /&][A log E + A log P, - A log P,]/z

+ [Q, - cT] x [A log P, - A log PM] + error = k, + k,AG*/G*

+ k,Ag/G*

+ k,[A

log E + A log P, - A log P,]/cc

+ k,[A

log Px -A

log PM] + error.

(1Oc)

This equation expresses the change in the quantity of supplied less traded goods demanded, as a fraction of exports. (9) and (10~) form a reduced-form system, from which coefficients y, p, &, and 4 may be derived, using the following Y =

traded goods Together, Eqs. the structural relationships:

a,,

&=k,-a,+l. 4=k,-k,+u,-a,.

The issues under examination in this paper may then formal fashion in terms of the following four restrictions: Restriction

i: ‘;=O (i.e. government

Restriction

ii: A,=0

nor complements Restriction

expenditures Restriction

expenditures

expenditures

be thought

have no output

(i.e. government expenditures are neither to private sector purchases of traded goods).

iii: p=O

(i.e. permanent and temporary have identical effects on output).

changes

of in a

effects) substitutes

for

in government

iv: q!~=0

(i.e. permanent and temporary changes in government have identical effects on private sector expenditures).

These restrictions are both individually Additionally, in a more informal fashion, coefftcients a, and ki are performed.

3. The decomposition

and jointly tested in Section 4. some tests on the reduced form

of a series into temporary

and permanent

components:

some remarks

For the decomposition permanent components,

of government expenditures into temporary and I choose a variant of the method developed by

300

E. Tanner / Journal qf Developmenl

Table I Summary of decomposition of government (Beveridge-Nelson (1981) method)

spending

Economic.v 44 (1994)

into temporary

2X7-310

and permanent

components

country

Year span

Model

V.R.”

D.-W.b

Q-stat“

S.L.(Q)d

MA lags

AR lags

Brazil Colombia Dom. Rep.

69:3-854 64:2288:4 66.1~88:3

SM’ SM SM

0.94 I .05 0.94

1.79 1.83 1.95

23.44 17.95 34.97

0.32084 0.76000 0.08890

1,4,5 I

1,4,8

El Salv. Guatemala Honduras Panama Peru

71:lp87:3 69:1X34:4 7&l-86:2 69:2X7:3 74:1X38:1

SM SM SA’ SA SM

0.92 1.09 1.00 1.02 1.36

1.89 1.92 1.99 2.16 1.90

10.22 18.12 18.80 17.48 68.16

0.924 19 0.64139 0.59793 0.2836 0.00000

1,5

1,4,5 1,4,5 ~23

1,2,3 4,5

a V.R.: variance ratio (ratio of variance of permanent component to total government after Cochrane (1988) and Cogley (1990)). b D-W: DurbinWatson statistic. ‘Q-stat: Box-Ljung check for autocorrelation of residuals. d S.L.(Q): significance level of Box-Ljung statistic. e SM: standard multiplicative model (1 - B)(1 - B4) data not seasonally adjusted. f SA: first difference (1 -B), data seasonally adjusted.

4,5 spending,

Beveridge and Nelson (1981). This variant, outlined in Tanner (1993), incorporates the discounting of future income flows. I choose this method for two reasons. First, the method allows for a stochastic (rather than deterministic) trend.l’ Second, the variant of the method, outlined in this Tanner (1993) is theoretically sound, in that it mimics what a rational, maximizing individual would do in predicting his/her permanent income. Of course, other decomposition methods which explicitly incorporate this feature are available. Ahmed (1986) utilizes a method based upon the agent’s forecasts of the present discounted value of expenditures. In Tanner (1993) I also show, in fact, that the B-N decomposition is roughly equivalent to the present discounted value technique. For the decomposition, quarterly data were used.12 In most cases, government expenditures exhibited seasonality. Consequently, the model generally chosen was of the multiplicative form (1 -B)( 1 - B4)G, where B is the backshift operator. In Table 1, details of the initial ARIMA estimations are given: the country, the time span for which the data was available, the ratio of the variance of the permanent component to the total variance (V.R.), the Box-Ljung Q-statistic and its the DurbinWatson (D-W) statistic,

” The issue of whether such variables as income and government spending have a stochastic trend has been the subject of considerable controversy in the context of data for the U.S. Authors such as Nelson and Plosser (1982) and Stulz and Wasserfallen (1985) have rejected the hypothesis of a non-stochastic permanent (or trend) component for income in the U.S. ” All data for this study are available upon request from the author.

E. Tunnrr 1 Journul of‘ Development Economics 44 (1994) 287-310

301

significance, the moving average lags and the autoregressive lags.13,r4 As the remainder of the variables are yearly, the government variables are summed over four quarters, which is appropriate as they are flow variables.

4. Data and estimation The data set is described in detail in an appendix. It includes 8 Latin Dominican Republic, El Salvador, American Countries (Brazil, Colombia, Guatemala, Honduras, Panama, and Peru), all of whose data begin in 1974 and end in 1984 (with the exception of Peru which begins in 1975). (The total number of observations is 87.) Eqs. (9) and (10~) are estimated both as written and with several modifications. First, I account for the possible endogeneity of the domestic price level by utilizing an instrumental variables (IV) technique.15 Second, the implications of pooling data are considered. Pooling data requires the assumption that the structural parameters are the same across countries. Additionally, similarities in the cross-country error structure may be exploited. The estimations incorporate several different versions of the model which correspond to alternative assumptions about the error structure: a common intercept model, a country-specific intercept model, a yearly dummy model. In total, 12 variations of the model are estimated. Finally, I address the possibility of causation by monetary, as well as real variables. While an alternative model in which money plays a role is not explicitly developed, it is nonetheless important to examine the degree to which the inclusion or deletion of monetary variables alters the initial results.16 Table 2 presents OLS and IV estimates of Eqs. (9) and (10~) excluding and including the monetary variables, respectively. Table 3 presents joint estimations of the current account equations utilizing Zellner’s seemingly unrelated regressions (SUR) technique. l7 Table 4 presents a summary of the estimation results. To summarize the structural estimates, the mean, minimum, and maximum of the structural parameters &, p, and 4, are reported. Then, tests I3 The variance ratio (V.R.) concept is identical to that computed by Cochrane (1988) and Cogley (1990) for U.S. GNP and GDP in developed countries, respectively. l4 Both the D-W and the BoxLjung Q statistics indicate that, on the whole, the estimates were successfulin obtaining uncorrelated residuals. l5 The instruments utilized for the domestic price index include current and lagged changes in money and lagged changes in the nominal exchange rates. ” Following Learner (1978, p.194), while the variables explicitly incorporated into the theoretical model serve as ‘focus’ variables, the monetary variables serve as ‘doubtful’ variables. ” The utilization of instrumental variables in a SUR model is, essentially, a three-stageleastsquares method. While SUR estimates and standard errors of both output and current account equations differ from the non-SUR estimates, SUR estimates of the output equation were very close to OLS and are thus not reported.

E. Tanner 1 Journal of‘ Development Economics 44 (1994) 287-310

302

Table 2

Basic estimates, output estimates

(standard

Ordinary

and current account equations, no monetary variables parameter errors in parentheses)

Least Squares

Country dummy Output

equation

Instrumental

Time dummy

Common intercept

Country dummy

Time dummy

Common intercept

(9b)

_

a0

variables

0.0308** (0.0080)

0.0301** (0.0090)

a,

0.1880** (0.0828)

0.1612* (0.0900)

0.2245** (0.0800)

0.1X12** (0.0830)

0.1526* (0.0910)

0.2181** (0.0810)

a2

0.1178 (0.0763)

0.1148* (0.08 18)

0.1285 (0.0753)

0.1224 (0.0767)

0.1231 (0.0833)

0.1345* (0.0758)

a3

-0.0053 (0.0763)

0.0032 (0.0710)

0.0045 (0.068 1)

- 0.0364 (0.0554)

-0.0136 (0.0555)

-0.0210 (0.0525)

a4

0.0147 (0.0403)

- 0.0027 (0.0486)

0.0 172 (0.0401)

0.0112 (0.0404)

0.0129 (0.0402)

0.0129 (0.0403)

I?

0.223 1

0.0485

0.2 134

0.2319

0.0484

Current

account

0.2385 equation

(1Oc) 0.0619** (0.0295)

k, _

-.

0.0663** (0.029 1)

k,

-0.4441 (0.2873)

-0.3549 (0.2901)

- 0.4609* (0.2683)

PO.3801 (0.2818)

-0.3309 (0.2932)

- 0.4040* (0.263 1)

k,

- 0.7260** (0.2648)

- 0.6644** (0.2619)

-0.7256** (0.2522)

-0.7908** (0.2575)

- 0.7490** (0.267 1)

-0.7278** (0.2460)

k,

0.6253** (0.2653)

0.6993** (0.22 14)

0.6009** (0.2282)

0.3786** (0.1879)

0.4469** (0.1780)

0.4195** (0.2862)

k,

0.5354** (0.1379)

0.5463** (0.1559)

0.5334** (0.1344)

0.5173** (0.1354)

0.5160** (0.1565)

0.5168** (0.1305)

R2

0.2808

0.1378

0.1938

0.1474

0.2398

0.1980

* Indicates significance at 907, confidence level or better. ** Indicates significance at 955; confidence level or better.

of the joint versions

restrictions, of the model.‘8

Interpreting

the

results:

as developed

An

initial

in section

examination

I, are

of the

reported

estimation

for

all

12

results

“The joint restriction is tested by constructing the standard F-statistic ([R&SE-USSE]/ USSE*(n-k1)/r), where RSSE is the sum of squared errors for the restricted version, USSE is the sum of squared errors for the unrestricted version, r is the number of restrictions, n is the number of observations, and k is the number of right-hand side variables.

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Table 3 GLS estimates, current account equation, monetary parameter estimates (standard errors in parentheses) Ordinary

Least Squares

Country dummy

Time dummy

Current k”

account

equation

Common intercept

variable

(domestic

Instrumental

Variables

Country dummy

Time dummy

303

credit)

included

Common intercept

(1Oc) 0.0861** (0.0493)

0.0890* (0.0500)

~

k,

- 0.4507 (0.2892)

-0.3397 (0.2818)

-0.4760* (0.2701)

~ 0.3892 (0.2807)

-0.3303 (0.2947)

-0.4164* (0.2655)

k,

-0.7265++ (0.2622)

-0.6592** (0.2617)

-0.7364** (0.2535)

-0.7134** (0.2565)

-0.7525** (0.2685)

-0.7341** (0.2475)

k,

0.6618** (0.2818)

0.6511** (0.2672)

0.6826** (0.2586)

0.5129** (0.2167)

0.4999** (0.2074)

0.4790** (0.1987)

k,

0.5371** (0.2662)

0.5517** (0.1558)

0.5362** (0.1349)

0.5251** (0.1350)

0.5147** (0.1573)

0.5177** (0.131 I)

&

- 0.1062 (0.228 1)

PO.1618 (0.1500)

- 0.0993 (0.1462)

R2

0.1288

0.2825

0.1885

R2 for system (output 0.2884

and current 0.3858

account 0.2965

-0.3031 (0.2467)

~ 0.0766 (0.1515)

- 0.0743 (0.1483)

0.1541

0.23 19

0.1904

0.3653

0.1733

0.1713

equations)

* Indicates significance at 902, confidence level or better. ** Indicates signilicance at 957,;,,conlidence level or better.

suggests that government spending is a critical determinant of both the current account balance and output. Moreover, temporary shocks to government spending consistently have a more negative impact on the current account balance than do permanent shocks. Estimates of k2 ranged from -0.79 to -0.67, and the restriction of k, =0 (i.e. no effect of temporary government expenditures on the current account) was rejected at levels greater than the 95% in all cases. In contrast, the effects of permanent changes in government expenditures on the current account appear to be much weaker. Estimates of k, ranged from -0.44 to -0.33, the restriction of k, =0 was never rejected at the 95% level and only rejected two out of twelve times at the 90% level.rg While temporary changes in government expenditures were more critical in explaining current account movements, permanent changes in government expenditures were more critical in explaining output growth. In nine of the ” An anonymous referee suggested that a good informal test of the differential effects of temporary and permanent shocks on the current account would be to test k, = k,. Unfortunately, this restriction was never rejected.

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Table 4 Summary

/ Journal

of estimation

Estimates of structural coefficients

A, P

4

ny Development

results,

underlying

Eummics

44 (1994)

287-310

parameters

Mean

Min

Max

0.158 0.064 ~ 0.243

0.126 0.030 - 0.375

0.225 0.096 -0.151

Test of joint restriction: y=o, p=o, f$=o, 1, =o Model:

Country dummy

Yearly dummy

Common intercept

(1) OLS, no monetary variables

F-value Pr.>F

2.264 (0.065)

2.113 (0.082)

3.013 (0.020)

(2) IV, no monetary variables

F-value Pr.>F

2.372 (0.054)

2.06 1 (0.089)

3.051 (0.018)

(3)GLS, monetary variables

F-value Pr.>F

2.248 (0.066)

2.158 (0.077)

2.970 (0.021)

F-value Pr.>F

2.375 (0.059)

2.056 (0.090)

3.007 (0.020)

(4) IV, GLS, monetary variables

Test of joint Country dummy

Model:

restriction: -. Yearly dummy

y=O,

I$ =0 Common intercept

(1) OLS, no monetary variables

F-value Pr.>F

3.634 (0.045)

2.257 (0.099)

4.493 (0.013)

(2) IV, no monetary variables

F-value Pr.>F

3.134 (0.046)

2.643 (0.075)

4.456 (0.013)

(3)GLS, monetary variables

F-value Pr.>F

3.137 (0.046)

2.643 (0.074)

4.487 (0.013)

F-value Pr.zF

3.100 (0.048)

2.558 (0.081)

4.396 (0.013)

(4) IV, GLS, monetary variables

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twelve specifications, the hypothesis that permanent government spending has no effect was rejected at the 95% level; coefficient estimates ranged from 0.18 to 0.22. In only 4 of the 12 specifications could a similar rejection be made for temporary government expenditures (a, =O), and only at the 900/, level. The effects of permanent shocks to government spending on output were somewhat greater than temporary shocks. Estimates of the difference of the two coefficients (a, -a2 =p) ranged from 0.016 to 0.052. The hypothesis that permanent and temporary shocks to government spending had identical effects (i.e. a, -a2 =p=O) was never rejected, however. (The results of these tests are not reported.) Thus, the results of the reduced form estimates - the nearly universal rejection of the restrictions that a, =0 and k, =0 combined with the far less numerous rejection of the restrictions that k, =0 and k, =0 ~ constitute some evidence supporting the hypothesis that agents incorporate the present discounted value of tax payments into current decisions. More formally, the pertinent issues are expressed in restrictions (i)giv). As Table 4 indicates, the joint hypothesis (y =O, p=O, $J=O, and &=O) is always rejected at least at the classical 90% significance level for all models, and at the 95% level for the common intercept model. Values of the F-statistic ranged from 2.056 to 3.051, and the corresponding classical probabilities ranged from 0.082 to p is simply the 0.018. The parameter y is simply a,, while the parameter difference a, -u2. Estimates for 1, ranged from 0.084 to 0.214., with a mean of 0.162: a temporary one-percent increase in government spending is met with an (approximate) 0.160/, decrease in expenditures in the traded goods sector. Estimates of 4 ranged from -0.363 to -0.098: on average a onepercent increase in permanent government spending induced a greater cutback in private sector expenditures (approximately 0.230/, greater) than that induced by a temporary increase in government expenditures. However, a joint rejection of several restrictions may be a weak test, as that rejection may be due solely to the rejection of one single component. Considering the restrictions in various subsets (including individual restrictions) yields mixed results. Apparently, the results with respect to y and 4 are not dependent upon the results with respect to p and 1,: as Table 4 indicates, the joint restriction (y =O, 4=0) is rejected for all twelve models times at better than the 90% level and eight out of twelve times at levels exceeding 95%. Similarly, the joint restriction (y =O, p=O, and (b =O, not reported) is rejected six out of twelve times at levels exceeding 90% and four out of twelve times at better than the 95”/, level. Unfortunately, individual tests were not as successful. Individually, only the hypotheses ;‘=O (equivalent to the test a, =0) is consistently rejected, while the individual restrictions of 3,, = 0, p = 0, and 4 = 0 are never rejected. Nonetheless, the results do suggest that tax burden effect associated with permanent changes in government spending are present and discernable in

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the data. Values of these parameters are fairly constant across specifications, and the joint hypothesis can be rejected in only 4 of the 12 specifications. While it is not possible to directly compare the results here to studies made in a developed country context (i.e. Kormendi (1983) and Aschauer (1985)), the magnitudes discussed here are not a priori implausible. How good are the estimates? Some remarks. Overall, the results were ‘better’ for the current account equation than for the output equation. The current account equation exhibited, on average, higher adjusted R-squares, and the variables in that equation had much lower standard errors than the variables in the output equation. Some further general concerns about the estimation techniques that might arise are addressed below. First, was pooling of the data appropriate? Clearly, pooling of the data alleviates collinearity by providing more variation in the explanatory variables. Nonetheless, pooling of data implies some well-known problems for which some well-known remedies and tests exist. A partial remedy for pooling problems is to assume fixed country specific or time-period specific errors. The country-specific intercept model corresponds to the fixed-effect, country specific error model discussed by Judge et al. (1980, pp. 329-331). Addition of country-specific dummy variables added considerably to the explanatory power of the output equation; one can interpret the coefficients on these dummy variables to be country-specific average growth rates. The yearly-dummy model is similar in spirit to the common intercept model, except that it holds constant shocks which occurred to all countries during a particular year. Addition of yearly-dummy variables added considerably to the explanatory power of both the output and current account equation. For the case of the current account, the years for which the tstatistic on the intercept term exceeded 2 were 1975, 1976, 1979, 1980, 1982 and 1983, indicating the presence of multi-country shocks to current account balances in those years, most likely due to oil-price shocks, shifts in the supply of capital in world credit markets (1975, 1976, 1979, 1980) and the onset of the debt crisis (1982, 1983). While the terms-of-trade was a critical determinant of current account balances, it consistently entered the output equation with t-statistics less than one in absolute value. Perhaps the best remedy for pooled data problems is to assume a randomeffect error components model, along the lines suggested by Fuller and Batesse (1974). Estimates available from the author yielded qualitatively similar results.”

2o An effort was made to obtain single-country time-series estimates, using quarterly data from 19741984. Any study using quarterly data faces severe data limitations: neither gross domestic product nor the non-interest current account are available. Instead, the determinants of the trade balance were estimated country-by-country, utilizing a variety of assumptions with respect

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307

Second, was the endogeneity of the domestic price level dealt with adequately? The real exchange rate term (d log E + d log P, - d log Pu) was included in the model because real exchange rate movements are often theorized to be critical determinants of both output and the current account. As well, during the period in question, many Latin American countries exhibited sharp swings in their real exchange rates. If real exchange rate movements are important in output and current account determination, their omission from the equation may yield a specification bias in the other variables. However, in a ‘reduced form’ version of the model in which the real exchange rate term was omitted, the results concerning the differential effects on temporary and permanent effects of government expenditures were largely the same as in the structural model. Third, is the government spending-output coefficient merely reflective of an identity, or a true economic relationship? Measured purchases of government goods and services may exceed their true market value. If so, the coefficients a, and u2 may overstate the true impact of government purchases on total output. However, this overstatement does not appear to be a serious problem. An alternative test of the government spending-output relationship which avoids the estimation of an identity would be to regress the growth of private sector output (q-G) on the government spending variables. Estimation of various versions of this equation yielded evidence supportive of the hypotheses of a positive government spending-output relationship.‘l Finally, is it appropriate to make inferences about structural parameters from aggregate data? One of the goals of this paper was to distinguish output and expenditure effects of government expenditures. Estimates of the structural parameters obtained from an aggregate output equation are worth little if, in fact, an increase in government expenditures had a very different effects on traded and non-traded goods markets. As an alternative Eq. (9) was reformulated to include only those sectors of the economy which are

to lag and error structure. While the results were not as good, it was clear that the main result that temporary changes in government expenditures affected the trade balance to a much greater degree than permanent shocks was nonetheless apparent in most countries. There are several explanations for the results not being as good as with pooled data. First, as the trade balance omits services, it is only a proxy for the variable we really want to measure. As well, collinearity was a problem. As mentioned above, pooling data alleviates collinearity. ” A representative finding was: Aq(private)=0.149AG*+O.l15Ag/G+ (0.083) (0.077) ~ O.O292(Alog E + Alog P, ~ Alog P&cc - O.O238(Alog P, (0.076) (0.044) R’=0.2033; country dummies estimated signiticant at the 90% level. Other versions variables) yielded similar results.

but not reported; (i.e. yearly dummy,

Alog PM),

the coefficient on AG*/G* is common intercept, instrumental

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commonly agreed upon as ‘tradable’, and the model was estimated for a somewhat smaller dataset. Once again, the estimations (available from the author) yielded largely the same results.

5. Summary

and conclusions

In this paper, I have attempted to characterize the link between government spending and the current account in some Latin American economies, through the effects which government spending has on output and expenditures. The policy implications of this study are indirect but potentially quite powerful. Edwards (1989b). among others, has noted that the ‘financial programming’ model utilized by the International Monetary Fund in its adjustment plans has ignored several recent theoretical developments in macroeconomics; among those developments are the movements towards intertemporal models. Perhaps the failure to incorporate these recent developments lies in the absence of empirical evidence. The main purpose of this paper was to address this gap in our knowledge. The strongest results of this study concerned the relationship between the current account and government spending: temporary increases in government spending induce increases in current account deficits to a much greater degree than do permanent increases. There is some evidence, as well, that an increase of government spending induced a decrease in private sector spending: a one percent increase in government spending induced an approximate 0.16 percent decrease on spending in traded goods markets. Policy makers are currently faced with the question of how new savings will be generated. An important policy issue, then, which this paper has addressed, is the relationship between public and private expenditures. What private sector behavior can we expect to accompany decreases in public spending? How will the desired level of domestic savings be generated? The results of this paper indicate that the magnitude of crowding out in the Latin American economies needs to be studied further, in order to obtain a more precise understanding of these issues. Studying the traded goods market (i.e. the current account balance) is only one way of approaching this question; making the temporary/permanent decomposition only answers one set of questions. Informative extension of this project would include an examin-

‘* Disaggregated data was obtained from the United Nations national accounts. For Colombia, Dominican Republic, El Salvador, Guatemala, Honduras, and Peru, the ‘tradable’ GDP figure included data from manufacturing, agriculture, and mining. For Panama, this figure included services, due to Panama’s unique role as a supplier of banking services. Data were unavailable for Brazil.

E. Tanner 1 Journal of Development Economics 44 (1994) 287-310

3op

ation the economy as a whole, and breaking down government expenditures different functional categories. There is one major caveat which should be raised about both the theory and the econometric results in this paper. I have assumed that government spending is exogenously determined in this model (or is at least a predetermined variable) and that the government faces a budget constraint which spans an infinite horizon. These assumptions may not be reasonable. Rather, governments may be constrained in their spending by tax revenues (or foreign borrowing) garnered over a shorter term. Put differently, the government spends when it has the chance to spend. It has the chance to spend more during times of high income and high tax revenues. (Indeed, the large deviations of government spending from trend in most of the Latin economies occur concurrently with large deviations of income from trend.) If this assumption were to hold, one might be able to build a mode1 whose econometric formulation was identical to the formulation in this paper, but whose implications were somewhat different. Appendix Description of Variables All variables are taken from the International Monetary Statistics Database. Variables are defined as follows: P,: domestic (consumer price index), series 64 G: government expenditures, series 82 P,: export prices, series 74..d E, nominal exchange rate, series rf MON, money, series 34 DC, domestic credit, series 32 Current account balance, series 77a.d Gross domestic product, series 99b.p

Fund’s

Financial

References Ahmed, S., 1986, Temporary and permanent government spending in an open economy: Some evidence for the United Kingdom, Journal of Monetary Economics 17, no. 2, 197-224. Aschauer, David Alan, 1985, Fiscal policy and aggregate demand, American Economic Review 75, no. 1, 117-127. Barro, R., 1981, Output effects of government purchases, Journal of Political Economy 89, no. 6, 10861121. Beveridge, S. and C. Nelson, 1981, A new approach to decomposition of economic time-series into permanent and transitory components with particular attention to the measurement of the ‘business cycle’, Journal of Monetary Economics 7, no. 2, 151-174. Cochrane, J., 1988, How big is the random walk in GNP, Journal of Political Economy 96, no. 5. 8933920.

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qf Development Economics 44 (1994) 287-310

Cogley, T., 1990, Some international evidence on the size of the random walk in GNP, Journal of Political Economy 98, no. 3, 501-518. Cuddington, J.T. and J. Vinals, 1986, Budget deficits and the current account: An intertemporal disequilibrium approach, Journal of International Economics 21, nos. l/2, l-24. Dornbusch, R., 1983, Real interest rates, home goods, and optimal external borrowing, Journal of Political Economy 91, no. 1, 141-153. Edwards, S., 1989a, Tariffs, capital controls, and equilibrium real exchange rates, Canadian Journal of Economics XXII, no. I, 79992. Edwards, S., 1989b, The IMF and the developing countries: A critical evaluation, CarnegieRochester Series on Public Policy 31, 7768. Fremling, G.F. and J.R. Lott, Jr., 1989, Deadweight losses and the savings response to a deficit, Economic Inquiry XXVII, Jan., 117-129. Fuller, W.A. and G.E. Batesse, 1974, Estimation of linear models with crossed-error structure, Journal of Econometrics 2, 67-78. Harberger, A., 1950, Currency depreciation, income, and the balance of trade, Journal of Political Economy 58, no. 1, 47760. Judd, Kenneth, 1987, Debt and distortionary taxation in a simple perfect foresight model, Journal of Monetary Economics 20, no. 1, 51-72. Judge, G.G., W.E. Griffith, R.C. Hill and T.-C. Lee, 1980, The theory and practice of econometrics (Wiley, New York). Kormendi, Roger C., 1983, Government debt, government spending, and private sector behavior, American Economic Review 73, no. 5, 9941010. Learner, E.E., 1978, Specification searches (Wiley, New York). Laursen, S. and L. Metzler, 1950, Flexible exchange rates and the theory of employment, Review of Economics and Statistics 32, 281-299. Murphy, R., 1986, Productivity shocks, non-traded goods, and optimal capital accumulation, European Economic Review 30, no. 5, 108551095. Nelson, C.R. and C.I. Plosser, 1982, Trends and random walks in economic time series: Some evidence and implications, Journal of Monetary Economics 10, no. 2, 1399162. Seater, J. and R. Mariano, 1985, New tests of the life-cycle and tax discounting hypotheses, Journal of Monetary Economics IS, no. 2, 195-215. Stulz, R. and W. Wasserfallen, 1985, Macroeconomic time-series, business cycles, and macroeconomic policies, Carnegie-Rochester Conference Series on Public Policy 22, 9-54. Svensson, L. and A. Razin, 1983, The terms of trade and the current account: The HarbergerLaursen-Metzler effect, Journal of Political Economy 91, no. 1, 97-125. Tanner, E., 1988, Exchange rate and reserves regimes: Theory and the Latin American experience, Unpublished Ph. D Dissertation (University of California, Los Angeles, CA). Tanner, E., 1993, A present-discounted-value formulation of the Beveridge-Nelson decomposition, Mimeo. (University of Miami, Coral Gables, FL).