The Potency of Stabilization

Economies: Kenya, Tanzania, and Uganda

Christopher Green and Victor Murinde, Curdtfl Busirtess

School, Urtiversi?y of W&s College of Curdifl

In this paper WC investigate the comparutivc potcqcy of stabilization policy instru- ments in Kenya. Tanzania. and Uganda. We draw on a small, eclectic macroeconomic model that includes fcaturcs distinctive to dcvclopinp economics and is sufticiently flexible to bc capable of yielding cithcr “Structuralist” or “Orthodox” outcomes. The model is cstimatcd iointly on Kcnyu. Tanzani;i. and Uganda in a novel application of Zcllncr’s estimation proccdurc. Among the tindings of intcrcst arc that the data arc able to accept a number of common cross-country elasticity restrictions, suggesting that these three countries share some elements of a common economic structure. However. system-wide multipliers. generated by simulation experiments, uncover different properties of the model across the three countries. This implies that there arc important cross-country differences that must be taken into account in the design of stabilization policy. On the Structuralist-Orthodox controversy we find that the parameters of all three countries’ aggregate demand schedules are broadly good news for the Orthodox position. whcrcas the aggregate supply schedules are generally bad news for Orthodox policies. as all three economies appear vulnerable to supply-side inflation generated by policies such as monetary contraction, an interest rate reform. or a competitive depreciation of the exchange rate. Overall, the results imply that t_Mhodox policies can only be applied to these economies with considerable caution.

1. INTRODUCTION

The Structuralist approach to the analysis of stabilization policy problems in developing countries (LDCs) places particular emphasis on recognizing the distinctive institutional and other features of each

Atitlres.~ t.orrt~.~~~t~~l~t~t~~~t~ IO: V. Mwintle. Curtly Hltsint~.ss School. University of Wdes College

of Cttrth~. Ahtwtmrtrt~ 5uildittaq. Cohtm Driw, Curti& CF I 3EV f United Kitxtk~m .

Received November 1992: Final draft accepted February 1993.

This paper is based on a chapter of Victor Murinde’s PhD thesis. Useful comment5 on earlier

drafts wcrc provided by participants in seminars at the Institute of Economics and Statistics.

University of Oxford. the 1990 Economics C’c~llnquium of the University of Wales held at

Gregynog. and the 1992 Annual Conference of the Money. Macroeconomics. and Finance

Research Group at Imperial College I.ondon. The paper ;tl\o henetitted from suggestion by two

anonymous referees of this Journal. Financial assistance from the Association of Commonwealth

Universities is gratefully acknowledged.

Jortrmd (4 Polit~y Motklit~~ I5(4):427-462 f 1993) 427

51 Society for Policy Modeling, 1993 !!!61-893X/93i$h.O

ccononly. The argument is that thcsc structural fclttuws hrl\c an im- pc,rtant inlp;ict on nixroc‘conc~n~ic outwmr’s in indi\.idud cionomics. They therefore render nugatory even qualitative gcnaxlizations about the possible effects of common maxowanomicr policy nwsuTcs un- dcrtaken in different countries. The Structural appnwh is often wn- trastcd with the Orthodox approach to stabilization policy. usuall!~ cscmpliticd by IMF policy packages. The Orthodos approach strcsscs the stwcralit>. of certain “t’undamcnts”” ccononric propositions and urgucs that stabilization policy packages \vith common qualitative char- acteristics can achieve broadly comparatk results in ;1 wide mngc of dift‘crcnt economics that f;1cc cc~n~n~on cconomi~ problans. such 3s high inflation or chronic balance of payments d&its. SW. in panic- ular. Taylor (1W.J. IWO).

‘I’hcrc has been ;I bride range of cmpirial studies of stabilizrition p~~licics in LDCs. SW Khayum ( 1991) for a rcvie\v. Howevw, a major prohl~m with these studies. is that they invariably lack any mcsningfarl formal comparative clement. Thus. studies in :\ Structurtllist mode hwc !ixuscd almost c.uclusiwlv on ir.5vidusl economics. SW. for cssmple. Murindc ( 1992). This pr&dure highlights the distinctive festura of iin cwnony but makes it difticult to detwnine \vhcther these fcaturss art’ important in a system-wide sense in ths design of stabilization policies. EI pirical studies in the Orthodox nwk have more often involved cross-country datit. Erampl~s of these studies appear in Khan and Knight ( 1% 1. 1982) and Khan ct al. ( I W 1 j. The studies typicall> impost‘ a common structure on different cwnomks. thus t’ffec’ti\.t’l\ assuming iiH’;ly ;L lq elcmcnt in the Structuralist srqment.’

Murindc (lW0) and Green and Murindc (1903 recently devised 3 small but compktc nwroeconomic model suitable for implementation in ;1 dcwloping a.xxwmy. The model is based on the standard textbook IS-LM-aggqatc supply model for an open economy. but it incor- poratcs cxtcnsions appropriate for LDCs. In particular. it includes a distincticjn hctucen ofticial and curb-market intexst rdtes. md ;: sup- ply-side spccitication allw~in, ~7 for the influence of intcrcst mtcs on costs and the special roic of irnportcd inputs. The signs and nxqnitudss of the estimated cocfticients in the empirical model dqwnd on kc! clcnwnts in the Structuralist-Orthodou ctwtrovt’rh>. BS \vt‘ explain in

SCc’ticw 3 bekw The nitdd cm J as prO\.iding 3n 8\\er;lll tr,nnwukx-h for wclyins and 0 a Cuntrwers\ in an individual country contc;t. Murinde (I h. 5-7) and Green and hlurinde ( 1902) estinx&d this model using data for Kenya. Tan-

7anitt. and Upda. respectiveI>. with generally encourtlrging results.

The main goal of the presenr paper is to propose and implement a

pnw2durc for spwitically t-~vnporin, 0 the effwtivt’ness of stabilization

p0lic!. instruments in diffewni economies. \Ve use as a tiamew0x-k 0ur basic small macroeconomic model’ and apply it to the three East

African countries-Kenya. fttnzania. and Uganda. The novel feature

of this comparison is that we us+ Zellner’s (1962. 1963) method to

cstimalrc the m&ei sinaultaneousi~ for all r;~ree economies. Features _ of the three ewnomics that are common on the one hand or distinctive

on the other can be identitied by examining the sign. magnitude. and

si@icsn~e of the coefficients in each of the model equations. Common

but unknown features of the three economies affect the error terms in

the model. and these are utilized in Zellner’s procedure to improve the

efficiency of the estimates of :he model. The itier\ is that pooling the

data enables w to obtain more efficient estimaks of the coefficienl.

whose signs and magnitudes are at issue in the Orthodox-Structuralist

debate. In addition. an explicit cross-country test of our model prokrides

a valuable assessment of its robustness in the face of differing economic

structures. circumstances. and policies.

The rest of the paper is structuwd as follows. Ser%on 2 provides

a brief review of the circumstances of the East African economies:

Section 3 summarizes the model and data used in its estimation: Sec-

tion -l discusses the estimation procedure; Section 5 presents the em-

pirical results: Section 6 gives results of policy simulations for the

three economies and discusses the single-equation (estimated) and

system-xvide (simulated) ions-run evidence on the key policy instru-

ments against the backgound of the actual policy stance in the three

ewnomies; a summary and concluding remarks are contained in Sec- tion 7.

L. THE EAST AFRICAN EC3iWMlIES

Kenva. Tanzania. and Uganda share common territorial boundanes and r&urca b:w Coffet-. ct-rtton _ ami tea art’ the major cash and ckport crops. The three countries tirrmcd a sin& administrative regicn

430 C. Green aud V. Murinde

up to the early 19%. and during 19 19- I966 the East African Currency Board (EACB) ~,perated as the sole monetary authoritj~, responsible for issuing and redeeming the East African shilling in exchange for U.K. sterling. After the abolition of the EACB in 1966, each of the three countries inaugurated a central bank to take over monetary au- thority . Limited policy coordination continued for some time; the three central banks maintained a par-relationship among their currencies up to 197 1. The economies were also linked by the East African Com- munity (EAC). which operated as both a customs union and a common market, facilitating commodity, capital and labor flows. Following the coup d’etat in Uganda in 197 1. cooperative arrangements rapidly began to disintegrate. Nevertheless. some policy commonalties, including the harmonization of tariffs and common services existed up to 1976 when the EAC finally broke down; to date it is onPy survived by the East .Affican nevelopment Bank. I. _.. Y

Although the three countries share a broadly common heritage, they have had very different postindependence macroeconomic policy ex- periences. Kenya has broadly pursued a free market capitalist path but with a very restrictive trade policy. Tanzania. in contrast, has pursued a distinctively socialist route, with Nyerere pioneering an agrarian form of “African Socialism,” and with a fix-price regime for most of the period. Potentially, the best-resourced of the three economies. Ugan- da’s early independence experience could be described as less “ex- treme” than either of its neighbors. Post- 1971, however, the excesses of the Amin regime produced severe economic disruption culminating in a bloody civil war from which the economy is still recovering. All the three economies have been characterized by financial represson and thriving curb financial markets.

The combination of a broadly common heritage and widely different policy experiences makes the East African countries particularly suit- able as a test-bed for studying and comparing Structural and Orthodox rnacroecocomtc policy prescriptions.

ATA

Thz model we shall estimate is the “quasi-reduced form” of a complete macroeconomic model. The behavioral and technical equa- tions t>f the complete model are listed below followed by a description of its reduced form; the variables used are defined as follows. B: Curb-market interest rate C: Real consumption expenditure

Dl = I for all obsun ations before 1980 (the Upanda-Trinrsnrl \\‘itr in 1980 and the fixed exchange r;ftc per&i); 0 thereafter.

E: End-of-period exchange rate (domestic currency per unit of SDRs) F: Foreign exchange reserves (excluding gold) in domestic currency. G: Real government expenditures. recurrent and development. J-J: M, 1 + L 1 + F, 1 whete M is the quantity of

money and t - 1 denotes a one-period lag: I

I: c 1, I*1 is the sum of all past net investment which estimates I - 0

the capital stock and is proxied by 1, ,. 1, 2 and I, ‘r

J: Curb-market financed working inputs Ko: L:

LB: N:

Real capital/aid flows (exclu&tg reserves) in domestic currency. Interest-bcarinp loan obligations of the government sector esti- mated as IFS commercial bank claims on government;

Labor inputs: LB‘“: Labor demand: LB’: Labor supply. lmported intermediate inputs Retail price index GDP deflator ( 1980 = B 00) or domestic producer prices The expected change in Q. Foreign prices (proxied by the U.K. export price index’)

Official (regulated) interest rate; Real tax revenue

TY: income tax rate (calculated as total income tax revenue in percent of the GDP in the monetary economy)

W: Wage package XT: Export tax rate (calculated as total export tax revenue in pc;rcent

of totai export receipts) X: Real exports Y: Real gross domestic product (GDP), 1980 = 100 Z: Real imports a denotes change

eal consumption expenditure is 1 functic;a of after-tax income. wealth, and relative prices:

3C. The Pro4-ktion Sector

Production is assumed to be a function of labor inputs. imported intermediate in MS. and curb-market financed working capital inputs:

Y = YILB. N. J) y,. y:. y, > 0. (12)

L&x demand and supply are determined by the wage package (W) in real terms: a clearing labor market is assumed:

LB” = LB (WiP)” lb”, < 0. (13)

LB’ = LB (WiP)’ lb’, > 0. (14)

LB‘ = LB”. (15)

SD. External Sector

The balance of payments definition inckdes exogenous aid inflows; foreign investment in these economies is assumed td be negligible:

F=X--Z++Y.. 116)

3E. The redtmd form modd

Given the ki!~Cq data availability. Eq l;ations 1- 16 constitute too large a model to be estimated directly for Kenya. Tanzania, and Uganda. We therefore consider a three equation reduced form con- sisting of aggregate demand (AD) aggregate supply (AS), and the foreign balance schedule (BR ). AD consists of the solution of Equations 1- 11; AS consists of Equations I2-, 5 solved with 7- 11 to eliminate curb-market interest rates: BB uses 5-I 1 in ( 16) to eliminate curb- market interest rates. Each reduced form equation gives an implicit relatiunship between output (Y). domestk supply prices (Q), and either the exchange rate (E) or foreign reserves (F). Endogeneity of foreign reserves or the exchange rate corresponds to fined and flexible exchange variants of the model. The flexible exchange raiz;T lsariant adopted iir this paper can be written algebraically together with signs of the as- sociated partial derivatives as:’

The pre&cta~ ..ign.- of the E;juations ! 7 !? ;tre obtained h:: !ineaking and 4ving Fqations

I-lh 32 cwrlmed rn the Iz\r ExpeLred mflalicjn (Q’; &wppearr from the reduced f<:rrn tecauw

;m 3daptlve expeclations scheme is assumed. For brevity. the detailed algebra IS not reproduced

here but i\ obtainable from the authors. Price contwis and quantity rationing featured prominently

in Tanz.mia up lo the end of the Uganda-Tanzania war (1976-1980). Re dummy variable DI

detined in Se&w 3 iz alw used to control for the change in regime at 1’180. An attempt to set

up dlr‘ferent pnce equations for joint estimation on the three economtes proved counterproductive.

434 C. Green and V hlurinde

Table 1: Model System-Wide Responses

Policy instruments

Macro targets

Fixed exchange rate Flexible exchange rates

Q*E IL L R G F TY XT

Y Q + _ + 2 + -

+ t

rt 2

+ + -

- 2

- 2

F Y Q E 2

+ -c + - - + + + 2 + _ -t 2

- + k +

- +

+ - + -

+ _ + _ - 2

2 Lknotes indeterminate predicted s&n

- + + ‘j - + - - _+‘P’f

Y = D(Q.E.Q*.R,L.G,TY.XT.F.H,I.D,) AD/Output. (17)

+++ y+-+ (_ + - ? ‘)

Q = S(Y.F.Q*.R.L.G.1Y.>iI’.F.H.i.D,) AS/prices. (18)

++_ ?_+ -. + _C’?_‘?

E = A(Y.Q.Q*.R,L.G.TY.XT.F.H.I.K,,.D,) BBlExchange rate. (19)

Table I gives t’he signs of the system-wide multipliers obtained by simultaneous solution of Equations 17- 19 for the fixed as well as flexible exchange rate model version.

The advantages of the approach we have adopted are the following. First, the three equations can be generated in a way that eliminates variables that are difficult to measure in the LDC context. For example, investment appears with one and two lags as it is acting as a proxy for private wealth (Equations 7-8). which is solved out of the model. Second. a three equation system is more easily understood, estimated on the limited available data, and subsequently manipulated in simu- lations. An apparent cost of this approach is that many of the partial derivatives in Equations 17- 19 have ambiguous signs, as do many of the predictions in Table 2. However, ambiguities in the individual equations can largely be eliminated by making plausible assumptions about the relative magnitudes of different parameters. For example, we typically assume that wealth effects are “small” relative to income effects. Moreover. other ambiguities in individual equations and in the full solution of the model form an essential part of our test procedure. For example, the sign of the effect of a rise in the regulated official

STABILIZATION POLICY 425

interest rate is either positive or negative depending on the strength of

the McKinnon ( 1973)-Shaw ( 1973) “reform” effects vis-a-vis the more conventional deflationary effects. Obviously the more efficient the econometric estimates, the more precisely can the relative impor- tance of such effects be evaluated.

Equations 17- 19 and Table I have a number of unconvcntional- looking features. Many of these can be traced to two simple, but key assumptions. First, we assume that money is endogenous. In Equation 1 I, the authorities are assumed to finance government expenditures by tax revenues, foreign borrowing (aid). borrowing from commercial banks, or borrowing from the central bank. Tax rates, borrowing from abroad, and from commercial banks are determined parametrically. Thus the residual in the govemmcnt budget identity is the supply of (high-powered) money. The second assumption is that, in Equations 2, 6, 10, and 12 we allow for the existence of a parallel curb market in loans and deposits. The official interest rate is a policy ir.strument and therefore appears as an exogenous variable in the model. The market clearing interest rate is assumed to be the ctirb market rate, which in turn is solved out of the system to get the aggregate demand curve. Both the curb market and official rates help determine the levels of interest-sensitive expenditures and the demand for money. The ex- ogeneity of both the official interest rate and the quantity of dcm&c interest-bearing government debt. or “loans” (L), is made possible by the assumption that commercial banks are regulated. and ration credit to the private sector. Given the official interest rate, the au- thorities can sell more of their loans to the private sectcJr by increasing the secondary reserve requirements of commercial banks. We believe that these two assumptions incorporate important aspects of many LDCs including Kenya, Tanzania, and Uganda.

The policy instruments in the model consist of budgetary instruments and financial policy instruments. Budgetary instruments are real gov- ernment spending, income tax rate, and export tax rate. Financial p .jlicy instruments include the official interest rate (a rise in R corresponds to an interest rate liberalization), loans from commercial banks, foreign reserves or the exchange rate, and foreign aid inflows, which are determined partly by donor countries. The money supply can be made

‘In all. the model recognizes the importance of curb financial markets in the three ectmomics

for working capital finance in the rural sector (agriculture and small time trade) and urban sector

(manufacturing and commerce): it is argued that these markets are not thin. The departure from

more detrtiled modcling of the curb-market as in van Wijnbergen ( 19X7b) is that the coexistence

of the oftisial and curb money market is captxed through intcrcst rate influences.

exogenous ing (say). banks _

C. Ckcn and V. Murindc

in simulations by considerin g shocks to g~vemmcnt spend- which are tinanced by incrcascd loans from commercial

The main policy issues that the model tocuscs on are:

(1)

(2)

The theoretical ambiguity of the effects of a rise in the official (regulated) interest rate stems from the McKinnon-Shaw ar- gument, and we call it the “interest rate dichotomy” result. The ambiguity occurs because a rise in the ofticial rate increases the supply of bank deposits and reduces the demand for bank loans thus reducing credit rationing. As credit rationing in the official market is gradually climinatcd the unsatisfied demand that goes to the curb market is reduced; this induces a fall in the curb- market rate. Since one tate rises and the other falls. interest- sensitive spending. loan demands. and the co:;t of working cap- ital may either increase or decrease on balance.’ Hence aggregate demand. supply, and the exchange rate may each either rise or fall. Obviously. the ambiguities in individual equations generate sys- tem-wide ambiguities in the impact of a rise in the official interest rate. (See Table 1). van Wi_inbergen ( 1983a) and Snow- den ( 1987) have argued that interest rate liberalization is nec- essarily inflationary, and thus reduces aggregate supply due to cost-plus pricing decisions under imperfect competition. In our theoretical model, following the above assumptions on credit rationing. curb-market and official-market loans arc substitutes and both help determine the cost of working capital. Since a kc in the ofticial interest rate reduces the curb market rate. the net effect on the cost of working capital (from both official and curb rates) is ambiguous and. on balance. aggregate supply and prices may eithrr rise or fall. This we shall call the “substitut- ability result.” A rise in govemmcnt borrowing from commercial banks (L) is hypothesized as being stagflationary in its effects on aggregate demand and supply. but its system-wide effects are indetermi- nate. Increased government borrowing reduces the (endogenous) .~upply !~f money. raising the curb-market rate and (normally)

(3)

(5)

appreciating the el;changc rate. .4ggrcgate demand falls but ag- gregrltc sup~i~ ma\’ cithcr rise or fdi depending on the strcnesh of the cx&n& rate and curb market effects. respectively. The system-wide effect of a rise in government spending is expsnsionsry but nq generate either higher or lower inflation. The indctemlinacy arises because increased government spend- ing is money-tinanced: hence the curb market interest rdte may either rise or fall. If the curb-market rate f~iis. lower prices can result (bccausc of iowcr working capital costs). otherwise higher prices are gcneratcd.‘ The fommer we shall call the “financial reform and budgetary reiativit) ” result. and it contributes to the scepticism about &‘Kinnon and Shaw’s argument that financial refomm that raises the official interest rate achieves higher output and lower prices. Our result suggests that the McKinnon-Shaw argument does not provide a special case for interest rate iib- eralization as a rise in government spending can have compa- rable effects. Our result also questions research that suggests that a rise in government spending is unambiguously inflation- ary: see. for example. Khan and Knight ( 198 1, 1982). Under fixed exchange rates. the effect of a devaluation on ag- sregate demand could be expansionary or contractionary de- pending on whether it lowers or raises the curb-market rate. respcctiveiy. Devaluation raises the domestic currency price of fore@ goods. This induces a rise in home consumption ex- penditure. mvestment expenditure. and foreign demand for ex- ports. The offsetting contractionary effect is that as export tax revenues increase and the budgetary position improves, the real money supply fails and the curb-market rate rises. Taken in isolation. a devaluation increases the incentives for agents to divert funds into the official markets. This tends to depress the curb-market rate. This we shall call the “devaluation;curb- market resuit.” It differs from some other work that shows devaluation as unambiguously contractionary, whether via in- termediate imports as in Buffie ( 1983). via imported consumer goods and reduced real credit volume as in van Wijnbergen

43x

(6)

C. Green and V. Murinde

( 1986). or becauss ssports do not respond strongly to a deval- uation thus widening th2 r2al trade _cap as in Krugman and Taylor (1978). A rise in foreign aid inflows improves the BOP under fixed exchange rates and appreciates the exchange rate under a flexible rates regime. Ho-:.ever. its effects on output and inflation are both indeterminate_ This result we call the “aid-growth pro- pulsion indeterminacy” and is. to some extent. a synthesis of earlier research. The n2oclassical critique argues that aid may perpetuate inefticient policies and thus, yield ‘immiserizing growth‘ sff2cts (~2 Johnson. 1967); in contrast Papanek (1973) argues that a ris2 in aid flows is a net increment to productive r2sourc2s and is thus unambiguously expansionary. Empirical work by Griftin and Enos t 1970) and Weisskopf ( 1970) shows a clear negative link b2tw22n aid and real growth. and that by Mosely ( 1980) yislds eith2r expansionary or contractionary ef- fects depending on th2 razz effort.

Th2 data set us2d in sstimating th2 model consists of annual obser- vations fi-om Uganda. Ksnya. and Tanzania covering the period 1963- 1985. IMail2&prss2ntation of the data sources is given Tab12 1.

in Appendix

4. ESTIMATION XND TESTING PROCEDURES

Th2 smpirical mod21 is disrived from Equations 17- 19 by assuming that all thn~ equations am linear in the logarithms of all variables except interest ratss and tax rates. which appear directly.” In addition, we carried out a 1imitsJ specification search by including both con- temporaneous and lasgsd valuss of right-hand side variables in the initial estimat2s. and dslsting certain insignificant variables until a pr2f2rmd spzcitication ~‘as rsachsd. In this search it proved convenieut to us2 lo9 first diff2nzncss as th2 12ft-hand side variables in all three 2qustions. which thsr2forcr suplain real growth. inflation. and the rate of change of th2 e~hangs rat2 or for2ign reserves. respectively.

To sstimate an? of t e thnx equations in the model (ski the ith), ~2 begin b>- stacking the S t = 23) obssmations for Kenya. Tanzania, and k’ganda. and ~~\\-titing th2 ntsult in v,ector-matrix notation as

STABlLIZATiON POLICY

where, using the notation C( = country) = K,T,U,

y,, is an N x I vector of dependent variables, and &i is an N x M matrix of right-hand side variables,

with M being the number of right-hand side variables in i,

&i is an M X I vector of coefficients, and Eci is an N x 1 vector of regression errors.

439

(20)

The statistical assumptions are that the errors for each country taken separately conform to the standard linear regression model, but that each country’s errors may also be correlated with the contemporaneous errors of the other countries. Hence,

(22)

-KK, uKT, uK,l,

.

Equation 20 can be written more compactly in obvious notation as

Y, = 74% + E,- (23)

It is tempting to consider estimating this system directly using Zellner’s (1962) procedure, in which case the estimated coefficients would be given by:

,. 8, = (Z,‘,C, ’ @ :)z,)-; (Z,$ @J l)y,,, (24)

*

where Ci is any consistent estimator of pi and @ is the Kronecker product.

However, the model is fully simultaneous in that contemporaneous values of endogenous variables appear as explanatory variables in all three equations. Hence the Zi do not satisfy the error orthogonality requirements of the standard linear regression model. We therefore partition each country’s explanatory variables into endogenous vari- ables (Ycr an N x 2 matrix) and predeterkned variables (Xc,---an N x M*(= M - 2) matrix). Now 23 can be rewritten as:

440 C. Green and V. Murinde

y, = Y, e;), + x, 6, + E,. (25)

Since the X, do satisfy the assumptions of the standard linear regression model, they can be used to form insttuments for the Y,. More precisely, let X be the matrix of predetermined variables of the linearly inde- pendent columns of (X, : X,: X,). Now, suitable instruments for Y, are given by P,Y,, with P, = X(X’X) ‘X’. The Zellner instrumental variable (ZIV) estimator of /3, in Equation 23 is then given by:

L

p, = (Z’PJI;, ’ @ I)Z,) ’ (ZV,P,i ’ @I by,) (26)

or

p, = (Z’,P,(i, ’ @ llP,Z,l ’ tz*,P,& ’ @ by,). (27)

which is equivalent to three stage least squares. The asymptotic cov- ariance matrix (S,) of Qi is given by Si = (Z’iP,(x ’ @ I)PxZi) ‘, and elements of 2, can be estimated from the residuals of the two-stage least squares estimates of Equation 20:

ci,,,, = N ‘(yc, - (Z’,, P,&,, ‘(Z’,, P,yc,))’

(yc, - (Z’,, P.Z,.,, ‘(Z’;, P,y<,)).

Finally, the informztion in the cross-country covariance matrix can be tested using N( Ln rrKK + Ln cm t Ln rruU - Ln Ix*I) (where the oCICz are the two-stage least squares residual variances and x* is the ZIV residual covariance matrix), which, in this problem, is asymp- totically distributed as X’(3).

Aggregate demand, aggregate supply, and the balance of payments are each estimated separately for all three countries simultaneously using the ZIV procedure. In addition, we carried out tests for the equality of parameters across countries. In addition to being relevant to our analysis of the Orthodox-Structural debate, re-estimation of the model imposing valid restrictions offers a frtr:her increase in efficiency. Since all three behavioral equations include both current and lagged values of certain variables, we tested for the equality of both “short- run” and “long-run effects.” Thus, comparing aggregate demand in Uganda and Tanzania we could have

y,,(n) = Y,,(n) C),, + Y,,(n - 1) CL-,-, + X,,(n) Fi,, + X,,(n - I) $,, + t,,.

y,,(n) = Y,.,(n) O,, L Y,,,(n - I) p,, + X,,(n) 6,, + X,,,(n - 1) c),., + E ,,,. (28)

Equality of coefficients across the two countries in respect of short- run effects may be represented by the hypotheses

tj*,, = C-),,, : p,,, = p,.,, ; 6,, = F,.,, ; $,,, = cb,,,, ; for any j.

Equality in respect of long-run cffeck is given by

STABlLlZATiON POLICY 441

f),,, + cl-laa = 0, I, + p., ,, : fi,,, + cb,,, x 6, ,, + 4, ,, : for any j.

Restrictions of this kind have the general form Rip, = r, and were tested using the (asymptotically valid) F statistic:

F@.3N - Ml = tRJ3, - r,)‘fR,S,R,‘) ‘(R,& - r,)lg,

(where g is the number of restrictions). For further detail on estimation and inference in systems such as this see, for example, Greene (1990).

5. EMPIRICAL RESULTS

We estimated fixed and flexible exchange rate versions of the model for Kenya. Uganda, and Tanzania using the ZIV procedure. None of the three countries could be said unambiguously to have had an un- changed exchange rate regime (either fixed or floating) throughout the estimation period. Until about 1980 all three economies were char- acterized by relatively fixed exchange rates. However, in the 1980s Uganda and Tanzania have had frequent exchange rate changes, ar- guably amounting to de facto flexibility.” The fixed and flexible ex- change rate model variants are not easy to compare directly as neither can be nested in the other. Non-nested testing procedures are not directly applicable as the foreign balance schedule has a different endogenous variable in the two model variants. Both variants contained some anomalous results. Overall though. we judged the flexible ex- change rate variant to be more plausible. One factor in this judgement was that the fixed-rate variant proved marginally unstable in simula- tions. Accordingly, we confine our discussion to the flexible exchange rate variant. Comparable results for the fixed-rate variant are reported in the appendix; see Tables A2-A4. For both variants, we exhibit the most restricted version of the model that the data were able to accept.

The F-test results ior certain restrictions relating to the equality of coefficients across two or thret; economies are reported in Table 2 and show that these restrictions are dicepted. The X’ statistics, which test the information in the cross=country covariance matrices, are all sig- nificant., and clearly establish that the cross-county ZIV procedure offers the potential of valuable efficiency gains in estimating crucial macroeconemic parameters ill LDCs.

‘A crude lest of structural stability in the regressions was carried out by including a dulnmy

variable with 0 for all observations up to 1980 and I thereafter. This dummy captures a number

of changes around this time, in particular the change from fixed to flexible rates (de-jure in

Uganda: de-facto in Kenya and Tanzania). The dummy variable proved insignificant in all

equation5 except the aggregate demand equations (Table 3).

Table 2: Tests of PXUIICIL’~ Restrictions and ot’ the: Co\.mm~c 3l;tm\.

(Flexible Exchange Rates Vari;tnt) _

Equation

Real growth rate

Inflation rate Exchange r&e

SA. The Real Growth Rate Equation (Aggregate demand: Table 3)

Under flexible exchange rates. the postulated negative slope of ths aggregate demand schedule En (Y.Q, space is empirically validated for all three economies. with the coetficient on domestic prices accepting an equality restriction for Upanda and Tnnzania. the two countries that experienced price-control programs for all but thnv years ( 1% l- 1984)

Real growth rate

tin Y,- In Y, ,I Constant

ln 9, In I,_ L In I,_:

In A-, In F,

R, In L,

InL, I T-y, I XT, In G,

In M, , InY, ,

at out stud\ . A rise in real inkcstment _ contrxtionq- etf‘rct in all thee ecvnomi entefS our m 1 as a proxy for w Ith and Iaged investment an

same impact as a As far 3s policy instruments are co

inftwst .ww (li~~~i~~ti~n 1 increases aggregate economies. and with an eyual semklasticity in The impact of a i-i-w in interest rates ap which has a more pervasive curb mark hvo economies. This result sheds light or: the ‘interest-rate dichotomy’ in OUT model. It sugests 3~ transmission mechanism whereby a rise in the official interest rate induces :i;fvers to shift from the curb to the otticial mark andSor to move out of real assets into interest-bearing assets. This inCreases ofticial loanable funds for financinp working capital and boosts consumption expenditure. hence raising real income. A rise in 10~an.s is deflationary in Uganda and Kenya, but has a net espansionary efkct in Tanzania. As a rise in commercial bank loan financing of the government budget deficit is equivalent to a cut in the (endogenous) supply of money. the Tanzanian result is counterintui- tive. but the impact effect of increased loan financing in Tanzania does have the expected negative sign. However. the parameters on loans are mostly not very significant. Real gowmment spending displays a common positive sign across all thee countries. Moreover. the elas- ticity of demand with respect to real government spending is equal in Uganda and Tanzania. while in Kenya it is rather hisher. This vahdates the transmisskw nxchanism hqwthesized in our model (item 4). Fi- nally. rut- rare increases mostly have the expected contractionary effect (with the income tax semi-eiasticity beins equal for Ug;cnda and Kenya). but the export tax rate in Kenya and income tax rate in Tan- zania exhibit counterintuirive signs.

SB. Inflation Rate Equation (Aggregate Supply: Table 4

The impact of eschange rate depreciation and foreign price increases on costs is pai+tic;;My ir Axesting rviria the &malt35 sugesting that more than one-half of a devaluation is passed into domestic prices bvithin twc> vears in both Uganda and Tanzania. and as much as 75%

Model Economy

Macroeconomic target variable L’ganda Kenya Tanzania

Inflation raw

(InQ;-InQ, ,I Con4ant

ln W,

InO”, , In E,

InE. , In I, , In L,

In L, , In f’,

InF, , !?,

InQ, I In G,

In Y,

InY, ! T\‘,

In M, , XT, , Dumm> ( IYWI

7 YKIX

0 4lS4

- 0 O-176’

0 Jl5-4

-0 415’) 0 0675

- 0 OIOX 0.0707

- 0 0107*

- 0.02 I

- 0.!?!?55

-0.339 - 0.2378

-0.127

-0.127

-O.MKil 0.0758

-O.OOIY^*

-0.01311**

-- 7 ,Y

0 O-167’

- O.W)H 0.3127 0.2469

- 0.0702

O.OOY5*

rl.039

- o.rwv

- 0.02 I

- 0.0106

-0.7196

- 0 0429* -0.33

0.762

0.01353

o.oxu*

-0.001X=* 0.0198

in the longrun.” These are remarkably high percentages given that the GDP deflator (our empirical estimate of domestic prices) includes a substantial proportion of nontraded goods.!’ On the other hand, Kenyan prices appear far more resistant to a devaluation suffering a sharp temporary rise that is all but reversed in the following year. This SuggcSts that opt odox policies may find more fertile pound in Kenya;

STABlLlZATlON FOLK3 445

it is also consistent with the dit and Tanzania in turning to su phasized that these are all single- effects.

As far as policy instruments are conce imerest rate increases aggregate supply in a lends further support to the ~c~innon-Show van Wijnbergen’s ( 1983a) prediction of inflation validates the transmission mechanism that market rate. as suggested in our m el theoretical prediction i issue ( I ). It also ties in with the idence on the aggregate (expansionary effect in Section 5A). Red gorvrrmtwt sperr price-reducing across the three economies. an appmntly that is nevertheless consistent with the estimated interest I

in this equation. and with our model. (See footnote 7.) emphasizes the point that if a McKinnon will produce higher output and lower prices. a money-fmanctd rise in government spending could have the same effect! Combining these results with our findings for the aggregate demand schedule, we con- clude that our “financial reform and budgetary relativity” result is empirically validated overall. Moreover, a rise in loan financing raises prices in two of the three economies, a finding that has broadly the same rationale as the financial reform and budgetary relativity result. The impressive consistency among these different parameter estimates gives us some confidence that this apparently counterintuitive result has some real plausibility.

Other coefficient estimates contain a number of anomalies. The tar

rate effects are rather mixed in sign. This may be due to the difficulty of measuring these rates accurately. Likewise, foreign reserves enter the supply curve with a ‘wrong’ (negative) sign for all three economies. An explanation of this is to interpret a rise in foreign reserves as a policy move towards the removal of an existing foreign exchange bottleneck. as argued by the New Structuralists in their explanation of

inflation. ’ ’ If so, higher foreign reserves would indeed reduce supply- side inflation.

Overall, while the estimates of the aggregate thought of as mildly good news for proponents of policies, the aggregate supply estimates can. in contrast.

‘Vhis argument is supported in tRer study which models znd :e>ts s in Uganda. Kertja. and Tanzania. tively See ~~~~~d~ 4 IW. bottleneck. with respect tu the mrlation pw-oblrm h thxsstd III Stiiithers f 198l I.

446 C. Green and V. Murinde

Table 5: Restricted ZIV Estimation Results for Exchange Rate Equation. Flexible Exchange Rates Mgodel Variant

Model

Macroeconomic target variable Uganda

Economy

Kenya Tanzania

Exchange ralt (In E,- In E, .,I Constant

In Y, InY, , In& , In Q*, InQ*, , In Qt InQ, , In 4 , R

lil i, ,

XT In F, In G,

tnL , TY, , InM, , Dummy (1980)

- 9.062 - 28.22

I .627 0.264

-0.873 0.751

-0.697 I X8

-0.663 -0.663

- 0.936 0.2s

0.845 0.845

0.111** - I.511

- 0.2036 -0.2036

0.1 lb7 - 0.01648

-0.2037 0.07696

o.OOOOb9** 0.0089**

0.2049 0.03346

0.0997 0.5672 -0.01196* - 0.1466

-0.02012 -0.0112

-0.116 -0.116

I .3596 0.2177

- 4.626

- 0.495 - 0.873

-0.561

0.039**

-0.245 0.291

0.111**

- 0.2036

0. I167

0.0353

- 0.00636

0.2049

0.5672

-0.1466 0.1036

- 0.0465

- 0.2577

Note: All coefficients are significant at the 958 level (t 2 I .96) except those that are marked

*. which are significanl al the 90% level (t 2 I .645) and those marked **, which are significant at lower levels bul bear the predicled parameter sign.

as bad news for this view, with all three economies vulnerable to supply-generated inflation as a result of orthodox policies. Moreover, our linding of a (to us) surprising number of equal elasticities among the three economies, especially between Uganda and Tanzania, cannot necessarily be regarded as a source of comfort for proponents of Or- thodox policies, as a number of these equal elasticities are precisely those that suggest that such policies will tend to produce supply- generated inflation.

5C. The Exchange ate and Foreign Reserves Equations (BOP equilibrium)

For the reasons already given, the exchange rate equation ir Table 5 is the most problematic of the three model equations. Reassuringly though, Uganda, which has come closest to a flexibie rate regime, also produces the most “sensible’* exchange rate equation. The main an-

STARILIZATION PQ)LIC~’ 4-U

;>malics arc that domestic prices have the ‘wrong’ net sign for Ken,d an4 real incomc h; , the ‘wrong’ net xign for Tanzania. However, a rise ii? “:treign prices has the cxpccted effect of appreciating each currency, although perhaps not surprisingly. the net (long-run) elas- ticities differ rather widely from unity in all three economies.

As far as policy instruments are concerned. a rise in the c@iciul infarvst r-cm has a common effect in depreciating the exchange rate in Uganda and Tanzania. while producing an appreciation in Kenya. A rise in rectl gowr~urrer~t spendir~g produces the expected depreciation of the exchange rate in all the three countries. The transmission mech- anism is via higher import demand due to higher income. Loam ji- muwing and IDLY r~lt~ changes produce one or two anomalous signs but. in general. conform to the model theoretical predictions. Finally. an increase inji,rcji,qtI trid inflows leads to the expected exchange rate appreciation in Uganda. but to a depreciation in Kenya and Tanzania.

Cross-country elasticity restrictions for at least two economies are accepted for four policy instruments: real government spending, loans, foreign reserves, and the official interest late. However, we do not obtain restrictions with respect to all three economies, nor do the rest of the policy instruments accept a restriction. Thus, the exchange rate equation produces evidence more in sympathy with the Structuralist view than with the Orthodox view.

6. DYNAMIC SIMULATIONS AND POLICY EXPERIMENTS

We used the ZIV estimates of the flexible exchange rates model variant to carry out dynamic historical simulations (using the Gauss- Seidel technique) to evaluate the overall performance of the model for each country taken separately. These were satisfactory and are reported in full in Murinde (1990). Following this, seven simulations were performed for each country separately to study the system-wide impact of a step change in the policy instruments:

1. A 10% increase in loans; 2. A 1% rise in the official interest rate ( 100 basis points); 3. A 10% increase in government spending; 4. A 10% increase in the income tax rate; 5. A 10% export tax surcharge; 6. A 10% increase in foreign reserves; 7. A 10% ictressr in foreign aid inflows.

The results are plotted in Figures l-9, and the long run multipliers for each simulation are summarized in Table 6, alongside the long-

C. Green and V. Murinde

0.036

0.024

0.020

0.016

0.012

0.008

O.OW

O.ooO

4001

.a L-u38

.0.012 ; ( f / , g , , , , I , I I , I , I , ,

63 64 65 66 61 68 69 i0 71 72 73 74 15 76 ;- 18 79 80 81 a2 83 84 m

Annual series

Figure 1. Real Growth Rate Trajectories Due to Policy Simulation Experiments:

Uganda.

0056

-007:.~~- , ( , , I , ( 63 64 65 66 67 68 69 10 71 72 73 14 75 76 77 78 79 80 s'l 8;5

Annual series

Figure 2. Inflation Rate Trajectories Due to P4icy Simulation Experiments: Uganda.

STABILIZATION

Figure 3. Exchange Rate Trajectories Due to Policy Simulation Experiments: Uganda.

4.10: , ( , , , , , , I , I I 1 I / I I I I , 1

63 64 65 66 67 68 69 ‘0 71 72 73 74 75 76 77 78 i9 SO 81 82 s; &, 85

Annud series

Figure 4. Real Growth Rate Trajectories Due to Policy Simulation Experiments:

Kenya.

C. Green and V. Morinde

63 6’ 66 6

Annual smcs

Figure 5. Inflation Rate Trajectories Due to Policy Simuhion Experiments: Kenya.

0.16

-0.16

-0.24

0.2%

-0.32 ,,1I!,I11~1~1111tt1 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 04 83

Annual serifs

Figure 6. Ex c a h n ge Rate Trajcetories Due to Policy Simulation Experiments: Kenya.

L 0.012

0 5 0.010 u M

; 0.008

ii 0.006

f

f o.o!M

b to OX?02 a z

0000

-0.002

-0.004 I I I I I I I I I I I I,, , , , , I, I,

63 0 65 66 67 68 69 70 71 72 13 70 75 76 77 78 19 80 81 82 83 ad 83

.4nnual series

Figure ?. Real Growth Rate Trajectories Due to Policy Simulation Experiments:

Tanzania.

1 .L 2-R 3-G ‘S-PI 5.X-f 6-F 7 . Ko

KCY

I-L 2-R 3-G r-n s.xT 6-F 7.Ko

Figure 8, Inflation Rate Trajectories Due to Policy Simulation Experiments: Tanzania.

C. Grew and V. Murinde

0.04

0.0s

0.02

I 2 5 0.00

%I 9 1 .0.02

t

I *om

&I = : 4.06

: w

-0.08

.o 10

Annual series

Figure 9. Exchange R:w Trrljrxtories Due to Policy Simulation Experiments:

Tanzania.

run single equation effects. The htter (shown as LRE in Table 6) are derived from the ZIV coefticicnt estimates in Table 3-5 on an equation by equation basis by assuming that in the long-run all variables are stationary in the levels. Long-run effects are then calculated by setting all x,, = x,, , . . . = x,, L. where each Xi is a variable in the regression. and k is its maximum lag length. The long-run simulation effects (shown as LRS in Table 6) are calculated by summing the s+ulation-derived multipliers (d(LnY, - Ln Y, ,)/dXi etc.) over the enthe simulation period. This gives a comparable estimate of the long- run elasticity of the level of the policy target with respect to the policy instrument.

A rise in the o#icial intcwst rate increases both aggregate demand and supply (reduces prices) in all three economics, but its long-run system-wide effects are not uniform, being more conventional in Cfpanda and Kenya. In Tanzania, raising the official interest rate would mean that in the short run higher interest costs (mark-up pricing) would i:~a~:t’l\( fall on parastatals and hence ultimately on central government; the )%tng run scenario assumes that curb-market influences might be %.@icant. The contrast between the uniform single-equation effects and the more heterogeneous system-wide outcomes is in sympathy with the Structuralist argument that the overall structure of the economy

--

Tab

le

6:

Su

mm

ary

of

the

Par

tial

an

d S

yste

m-w

ide

Lo

ng

R

un P

olic

y E

ffec

ts a

cro

ss t

he

Eas

t A

fric

an

Eco

no

mie

s

Mac

roec

onom

ic

targ

ets

Fle

xibl

e ex

chan

ge

rate

s*

Pol

icy

vari

able

s’

Rea

l gr

owth

ra

te (

Yrt

) In

flat

ion

rate

(Q

rt)

Exc

hang

e ra

te

(Ert

)

Yrt

N

J)

Yrt

W

I Y

rt

(T)

Qrt

W

I Q

rt W

I Q

rtO

E

rt (

Uj

Ert

(K

) IG

-t (T

)

In L

R

In G

TY

XT

in

F

LR

E

- 0.

088

LR

S

0.00

027

LR

E

0.01

02

LR

S

- 0.

0479

8

LR

E

1.19

LR

S

0.11

442

LR

E

- 0.

047

LR

S

0 08

736

-0.1

28

0.06

3 -

0.01

6 0.

177

-0.1

0966

0.

0067

-0

.303

1 0.

0047

3

0.00

44

I .62

-

0.02

6 -

0.01

8

- 0.

0573

0.

0070

89

0.47

5 0.

4947

1.04

0.

0298

5 I.

19

0.05

393

0.59

5 0.

0193

1

- 0.

986

-0.7

19

-0.1

96

-0.1

2019

-0.0

2

-0.1

657

0.01

8 -0

.016

-0.4

106

-0.8

681

0.05

2 1.

609

- D

.!?

Z.s

K

- 2.

386

- 0.

0504

- I .

6914

0.01

8

4.45

41

-0.0

17

-0.1

I

- 0.

0326

0.

0069

3

0. 1

67

-- 0

.0 1

24

0. H

07S

O

.n40

5

0. I

43

0.42

7 -

0.07

749

0.02

227

- 0.

029

- O

.OO

K

- 0.

5607

3 -

0.14

693

0 26

1

i~.(

l?7H

h

(J.Z

OH

.- ;;

24‘%

‘5

I 02

9

0 01

424

0 I8

47

-- 0

.012

7

LR

E

-0.0

0-M

LR

S

fi 3

0927

LR

E

0.26

3

LR

S

- 0.

0547

7

0.17

3 -

0.05

95

- 0.

0003

-

0.00

57

- 0.

0022

O

.OO

OI

0.00

67

-- 0

.01

I3

0.42

4 -0

.001

9 -

0.02

9 -0

.135

1 4.

397

- 0.

03’)

I5

-0.2

137

0.22

9

0.26

0.

046

-0.1

02

- 0.

274

- 0.

0075

0.

346

0.02

5 0

3h5

-0.3

9010

-0

.012

76

0.09

191

0.04

999

I .75

787

0.24

2 0.

2151

I

0.02

625

LR

E

LR

S

0.01

264

- 0.

29

0.05

8 0.

w

- 0

0766

-0

.811

3 0.

0564

0.

841

- 0.

0027

4 -

0.03

89

- 0.

2641

3.

7545

*Yrt

=

In

Y,

- In

Y

, ,:

Qrt

=

InQ

, -

InQ

,.,;E

n

= In

E,

- In

E,

,; U

. K

. T

. -

Ug

and

a,

Ken

ya.

Tan

zan

ia,

resp

ecti

vely

.

‘LR

E

- L

on

g r

un

sin

gle

eq

uat

ion

eff

ects

der

ived

fro

m T

abs

3-5;

L

RS

- L

on

g r

un

sim

ula

tio

n c

ff(*

cts;

See

tex

t fo

r fu

ll ex

pla

nat

ion

of

the

calc

ula

lmn

t

I L

RE

an

d L

RS

.

does have a signihcant yw/itcrti\*c cfftxt on 1ll;a~r(;ec011~~1111( outcomc‘s.

In this case. the comparison is prticuftirl~ intcrcsting ;I:> the acLual

interest rate policy stance in the three economics has been fairly similar. AII three central banks regulated their ofticial interest rates within rather narrow limits from independence until the c:tt-ly 1980s. Liberalization was initiated in Uganda in 198 1, in Kenya I!) 1982. and in Tanzania in 1984. However. only Uganda has follo~~J up liberalization with a substantially more active ofticial interest r&c policy.

The results for gowrwntv~t sprndi~~,q she* n rhat a rise is expansionary and disinflationary according to both the Gn;le-equation and system- wide estimates across the three economics. early. this validates the transmission mechanism hypothesized in t “financial rt>form and budgetary relativity” result. This also underlines the point that cuts in government spcndin, ~1 are by no means ~uar~ntccd to contribute to a fail in inflation. In these economies_ the SY cI V idence suggests exactly the opposite. Moreover, as -with interest rate policy, the pattern of gov- ernment spending in the three economies was rather similar until the early eighties. At this time spending rose in Uganda and Tanzania in connection with the war; in Kenya, government spending rose sharply in 1984-86 due mainly to a food subsidy program adopted by the government in the face of serious drought conditions and consequent fear of famine.

The results of shocking the model with a 10% increase in mnmerciul

bank lmnfinunc*ing of thr budget deficit differ widely across the three economies. Its system-wide effects arc stagPati0nat-y in Kenya, exactly the reverse in Uganda. while prices and output increase in Tanzania! Ironically, both Kenya and Tanzania have mride some efforts at non- central bank financing of the budget deficit in recent years, whilst in Uganda, residual financing of the budget deficit over the last 15 years has invariably been entirely by the monetary authorities. In our model. increased loan financing is accommodated mainly by a monetary con- traction. ” Therefore. although we would not overemphasize individual estimates, these results again underline the dangers of naive pursuit of monetary contraction to fight inflation.

Both the imwme-trru surchurge and eqmrt-tm srrrcharge experi- ments produce further divergent results across the East African ccon-

“Thus. the wansmlwon mechanism evidenced in Kenya ih as hypothesized; a fall in money

induces a rise in the curb market rate: this lowers output and raises prices. The excessive use of central hank financing of the budget deficit in Uganda means that a shock on L is inactive.

The predominancy of the parwt;itsi wzctor in TanzaG nw;!n \ that prices are notoriously rigid downward\.

omicx. WC pl;~cc mthcr Icss cmphasih on these rcsuli:, than our others m;linl~ he~ilu~~ of the difficulty of‘ nlcasu~ing ~ZI.K tax rates. Thcrc arc obvious problems with our particular measures. although we would argue that they arc suvrior to nominal tax rates that invariably arc widely divergent from cffcctivc tax rates in LDCs. Our measures con- stitutc reasonable though crude cstimatt’s of effective tax rates. In practice. most of the changes in effective tax rates in the three ccon- omits since independence have been due to changes in coverage rather than in nominal tax rates and there is obviously an important endo- geneity in the former not captured by our model. The main result we would point to in these simulations is that Tanzania is the only economy in which the tax surcharges have a (sharp) inflationary effect. This suggests that tax increases (especially those mainly involving improvc- mcnts in coverage) may not have such adverse supply-side implications as is often bciicved.

In aii three counirics. a r-k in jkeig:n TtiseiTcs has cxpansima~y

and disinflationary “partial” effects but exactly the opposite (i.e. stag- flationary) system-wide effects. Finally, increasedfurt+g12 aid iq7ows yields stzgflationsry reults for Tanzania but expansionary and disin- flationary results for Kenya and Uganda. These differences may well reflect the extent to which aid inflows are integrated into the public finance processes in each of the three economies.

7. SUMMARY AND CONCLUSION

In this paper we have proposed some r,r.vel procedures for evaluating macroeconomic policy issues in LDCs. These include, in particular, sct- ting up a model capable of generating predictions consistent with several different schools of thought but consisting of just three empirical equa- tions, and the use of Zellner’s estimation procedure to pool time series and cross-country data and thus obtain more efficient estimates of the model parameters than is usually possible. We implemented these pro- cedures on postindependence data for Kenya, Tanzania, and Uganda. While there arc undoubtedly some anomalies in our results, we believe that, overall, they justify the claim that our methodology represents a significant improvement on empirical studies in this area.

The main conclusions to be drawn from our analysis can be divided into three areas: estimation results, simulation results, and more general conclusions concerning overall methodology.

As far as the estimated model equations (for flexible exchange rates) arc concerned, the demand, supply and foreign balance schedules gen- erally have the theoretically predicted slopes in price-output-exchange

4% C. Green and V. Murinde

rate space. There are some important differences between the aggregate demand schedules on the one ha& and the aggregate supply schedules on the other. For all three r.ountries, aggregate demand is broadly con- sistent with an Orthodox-cum-McKinnon-Shaw viewpoint, with in- creased government spending or a monetary expansion producing an increase in aggregate demand, as also does a rise in the official interest rate. Aggregate supply, in contrast, is more consistent with the Structur- alist position as foreign price and exchange rate changes are substan- tially passed into domestic supply prices; a monetary contraction also raises supply prices except in Uganda. However, a rise in the official in- terest rate lowers supply prices in line with the McKinnon-Shaw prediction.

These findings emphasize the need to look carefully at the results of simulating the complete model country-by-country. The simulations show that tight monetary policy interpreted as a monetary contraction inhibits inflation only in Uganda and only if achieved by increased non-Central-Bank borrowing. Cuts in government spending that reduce money growth are stagflationary in all three countries. This effect can arise in our model because less money drives up curb-market interest rates and hence working capital costs thus driving up the supply price of output. an effect that can dominate more orthodox policy trans- mission channels. Thus, as long as the curb-market continues to play a key role in the economy, with official interest rates tightly regulated, orthodox policies may generatz unorthodox results. Tax rate changes are more mixed in their effects, possibly because of the difficulty of distinguishing empirically between changes in nominal rates and .hanges in coverage. However, for Kenya and Uganda, the results suggest that tax increases lnay not have the adverse inflationary effects that are sometimes feared. Foreign aid is found to have positive effects in Kenya and Uganda but to be stagflationary in Tanzania.

Finally. we turn to the general implications of our analysis. We find that the use of Zellner’s technique significantly improves the efficiency of the model estimates. Moreover, the data were able to accept a (to us) surprisingly large number of cross-country parameter equality re- strictions, thus offering further efficiency gains. In the aggregate supply schedules. almost one-third of the ‘economic’ parameters were thus restricted. Despite this. model simulations revealed that the remaining parameter diffcrenccs were capable of generating substantial q&irarive as well as yucu~titc~fi~~e differences in the responses of policy targets to policy instruments. ” Although, by no means all our results are supportive in detail of the Structuralist viewpoint, we would suggest that substantive qwlirt~ti~~e variations in the multipliers among our three

STABILIZATION POLICY 45-2

countries indicate that the Structuralist emphasis on individual country differences is not misplaced in East I\ ilica.

Perhaps the most important tinding of all concerns the overall re- sponse of output and prices to policy shocks. Neoclassical theory and empirical evidence in the industrial countries strongly suggest that output and prices are positively correlated in the economy as a whole.

innon-Show and Structuralist argument suggest that, in LDCs, output and prices may be negatively correlated offering, for example, in response to an interest rate reform, either a free lunch of higher outl:ut and lower prices (McKinnon-Shaw) or unpleasant stag- flationary consequences (Structuralism). Out of 2 1 system-wide policy multipliers reported in Table 6, no fewer than 18 exhibit such a negative correlation between prices and output. ” This appears to us to constitute a very strong warning that there are considerable dangers involved in mechanically applying orthodox stabilization policies to Kenya, Tan- zania, or Uganda, in particular, and, possibly, to the developing worId in general.

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Green. C.J.. and Murinde. V. (1992) Potency of Budgetary and Financial Policy Instruments in Uganda. In Polic,? Adjttstment in Afrku: Cuse Studies in Economic Development, Vol. 1. (C.R.Milner and A.J.Rayner. Eds.). London: Macmillan.

Greene. W.H. (1990) Ecuttomerric Attu/ysis. New York: Macmillan. Griffin. K., and Enos. J. ( 1970) Foreign Assistance, Objectives and Consequences. Erotromic

Devehpmettr uttd Ctthurul Change 18: 3 13-337.

Ize. A.. and Salas. J. ( 1985) Prices and Output in the Mexican Economy: Empirical Testing of Alternative Hypotheses. Jottrttal of Dewlopmettr Economics 17: 175-99.

Johnson, H.G. (1967) Economic Policies Tontard Less Developed Countries. Washington D.C.: The Brookings Institution.

Khan, M.S.. and Knight, M. i 13bi ; Stabilization Programmes in Developing Countries: A Formal Framework. /,MF Staff Papers 28( March): I-53.

Khan, M.S.. and Knight. M. (1982) Some Theoretical and Empirical Issues Relating to Economic Stabilization in Developing Countries. World Dewlopmettr 9: 709-730.

Khan, M . S., et al. ( I99 I ) Macrqeronomic Models for Adjustment in Developittg Cowtrries.

Washington D.C.: IMF.

“We view the ywdikh~c~ multiplier differences as important. WC suspect that most economists

would be astonished if we did not find substantial quanrirurive differences of multiplier values

among different countries. ‘hThe exceptions are loans in Tanzania and direct taxes in Kenya and Tanzania.

4% C. Gram and V. Murinde

kugman. P., and Taylor. L. ( 1978) Contractionary Effec!s of Devaluation. J~~wrwl of her-

naricmcd Ecwnnmic~s 8( Novemtxrb: 44S-4%. McKinnon, R, I. ( 197.3) Monc,v and CqGral in Ecrmomic~ ikrr~/opmcnf. Washangton. DC: The

Brookings Institution.

Murinde. V. ( 1990) The Stabilization Potency of Budgetary and Financial Policies in Dev*.;o~inp

Economies: Evidence on Uganda. Kenya. and Tanr.ania. Unpl~blished PhD The&. Um-

venity of Wales. Murinde. V. f 19911 Application of Stochastic Simulation and Policy Sensitivity Technique5 to

a Macroeconomic Model of CJganda. Applitd E~wnomics 21: I - 17.

Murindc, V. (1993) Budgetary and Financial Policy Potency Amdisl Structural Bottlenechs.

Worlc1 I)n~l~/wrw ( forthcomin~~. Papanel.. G. ( 1’17.31 Aid. Foreign Pnvate Investment. Saving%. and Growth in 1~44 Devclopd

Countries. Jourtrol oj’ Politicul Ecorum~,v X I : I 10- 130.

Shaw. E.S. ( 1973) FinarrcBl Drcpcnin~ ill Ec*r)flot?tic* Dc~~+~rn~rtr. New York: Oxford Um- versity Press.

Snowden. P.N. ( 19X7) Financial Market Liberalisation in LDCs: The Incidence of Risk Allocation

Effects of Interest Rate Increases. Jour& c$ D~rvk~pmcnr Smdics 24 I I: 83-94. Struthers. 3. ( 1981) Inflation in Ghana (1966-78): A Perspective on tile Monetarist vs Structuralist

r:“-‘- 1.T ILLld,C. l%&r~““‘.“i un,: i irtrngt I L. K-_ . r. ?:3

?‘a4 icri , i. i i 983) S~ruc?wulis~ ~lnt~roc~c~r~?ronli~~.~: App/iplicwhlc Modt~ls /or tlw Third W&d. New

York, Basic Books. :nc.

van Wijnbcr_rcn. S’. (19H3hl Credi: Policy. Inflation and Growth in a Financially Repressed Economy. Joltrfwl (4 D~~~~f~lqmuvif Et~otz~m~i~~s 13: 4545.

van Wijnbergen. S. ( I9861 Exchange Rate Management and Stabilization Policies in Developing Countries. Jnunrul of Dt~r~&prntvtr Ecmomicx 23: 137-838.

Zellner. A. ( I9621 An Efficient Method of Estimating Seemingly Unrelated Regression Equations and Tests of Aggregation Bias. Jourr~~l of Atncricm Smrisricul Assoriurion 57: 348-368.

Zellner. A. ( 19633 Estimators for Seemingly Unrelated Regression Equations: Some Exact Finite Sample Results. Journal of Anwricwr S~cl~i.~~ir~crl As.wc~icr;icw 58: 977-993.

Wcissbopf. T. ( 1970) The Impact of Foreign Capital Flows on Domestic Savings in Underde-

vclopcd Countries. Jmtrrrcd of hut nr~r~io~~l Ecottontic.s 2: 2 I -3X

Govrmmrnt Finxtcr St;ltistics ( l%O-86) IFS Ya-lwok~. line YYh (lY60-X6)

IFS YrtiwR\. line 60 t 1962-X6)

IFS Yur!~~~ks. lrnr 64. UK. (1960-X71

IFS Ytxhx~k. line rd (UK) f 196tklWh)

As abow for E iShs per SDR I ).

IFS Yrarhwhs. Ilnc I4 ( 1967-1986,

SW Lxrbcw 3.

360 C. Green and V. Murinde

Table ia2: Restricted ZIV Eslirnati:m of Real Growth Rate Equarion.

Fixed Exchange Rates M&l Variant

Economy

Macrwconomic target Model variable Uganda Kenya Tanzania

Kcul growth rate

(In Y,- In Y, ,I Constant

InQt 2 lnQ*E, , Inl, _.

In I, ,

InL , In F,

R, In 6,

InG, , TY,

TY, t xi,

lnW ,

lnY, , Dummy ( 1980)

0.906

-0.339 0.2’97

- O.oJ98

o.!I607 - 0.0129

-- 0.056 0.0067

- 0.0747*

0.0513* 0.0126

-0.0118

-0.0017 0.966

0.0316** 0.0545

2.705 9.129

- 0.1025* 0.2167

- 0.069 -0.128

-0.183 0.115

0.171 -0.181 - 0.0407 0.009**

0.0534 0.00072** 0.0067 0. I68 0.368 0.065*

0.087 0.0513* 0.0032** - 0.0053**

- 0.0048* 0.0437

0.0131** 0.048 0.0131** 0.048

-0.514 -0.514 -0.104 0.0545

Nore: All coefficients are significant at the 95%- level (I 2 1.96) except those that arc marked

*. which are +niticant at the 90% level (t r> I .6-U) and those marked **. which are significant

at Icwer levels hut lxx tbc prcdiclcd pz;lmelL’r sipn.

Economy

Macroeconomic target Model variable Uganda Kenya Tanzania

Inflation rate

(In Q- In 9, ,I Constanl

In L, In Q*E,

InQ*E, ,

InY, I InI, , In I;,

InG, , TY,

TY, , XT XT I In F,

InF! , R

InQ, I In M, I

- 2.49

0.0192*

0.3198 0.38

0.6074 0.01 I**

- 0.665

o.ON5 * * 0.0059* *

- 0.0096

0.0014 O.OI22

-0.149

0.0108**

- 0.00085* - 0.727

0. I16

- 3.678

0.04105

0. I06 - 0.00307**

0.2282**

0. I z7* - 0.341

0.19s

.- O.U098*

-0.0153 - 0.052

- 0.0357

- 0.084

- 0.00585** - 0.0227

0.144** - 0.056

- 8.556

0.0092

0.3198

0.1006 0.6074

-0.2099

- 0.0694

O.i315 -0.1’2

- 0.0303

0.0014 -~0.014s

- 0.0295

-0.0519

- 0.088 - 0.623

- 0.019

Nope: All coefticients are significant at the 95% level (t 2 I .96) except those that are marked

*. which are significant at the 90% level (t 2 I .645) and those marked **, which are significant

at lower levels hug bear the predicted parameter sign.

462 C. Green and V. Murinde

Table A4: Restricd ZIV Estimation of BOP (I~orcign RCSCITLY) Equation.

Fixed Exchange Rates Mdcl Vximt

Economy -.

Macroeconomic target Model variable Uganda Iienya Tanzania

BOP: Foreign rcservch

(In F,- In F, ,) Constanl

in Y,

InF, , InF, : In V’E,

In Q, In 1, , R, In G,

InG , TY, In K,

XT, , In L , In M ,

\h.-ll7 - 1.143**

-O.S114 -0.173 0.632 0.2.V** \: 'I;** _*.

-~O.(\lS34** 0.303Y**

- 0.44* 0.04 1.35, 0.0526**

-0.00547* -0.06106" - 0.179

- “) .31

- 0.0373**

-0.7,' --0.273 0.633

-2.6S-t I.408

-0.137 - I.YYh 1.451

-0.08757 - 0.1997 -0.2133 0.042s** 0.344

11.056 -Y.ZW -1.447 -0.~73 I.833

- II.278 o.q'.3** _a I.317

- l.YYh -0.44" - I.688 0.03si7**

-0.2123 -0.1079** -1.277

NCJW: All codticicnts are sipificm~ at the s).C% level (I 2 I .96) except those that art’ marked

*, which arc’ significant at the 90% level (I 2 I .tiS) and those marked **, which are signiticant 31 lower levels but lxar the predicted paran.zter sign.