kydland zarazaga 1997 businesscyclearg

8/16/2019 Kydland Zarazaga 1997 BusinessCycleARG

http://slidepdf.com/reader/full/kydland-zarazaga-1997-businesscyclearg 1/16

FEDERAL RESERVE BANK OF DALLAS 21 ECONOMIC REVIEW FOURTH QUARTER 1997

Societies w ould prefer a steady grow th

path for their national incom e of, say, 3 p ercent

every year to one that delivers a 3 percent

grow th rate on average, but w ith zigzags from ,

say, 12 percent one year to –6 percent the next.

Consequently, they typically dem and that

policym akers elim inate undesired econom ic

fluctuations.1 It is not surprising, then, that the

understanding of business cycles has alw ayscaptured the interest of econom ists and has

inspired som e of their best w ork.

The w ork of John M aynard K eynes and

M ilton Friedm an w ent a long w ay in defining

the term s and identifying the issues that a suc-

cessful theory of econom ic fluctuations ought to

address. D espite the m uch-advertised difference

betw een the schools of thought inspired by

these scholars, their w ork agrees on som ething

very im portant: nom inal factors, such as the

m oney supply, interest rates, and price rigidi-

ties, play the m ost im portant role in explaining

econom ic fluctuations.As is w ell know n, the 1970s w ere not kind

to the K eynesian interpretation of business cycles.

This interpretation predicts that the rising in-

flation rates of that decade should have been

associated w ith declining unem ploym ent rates,

not w ith the rising rates actually observed.

Em pirical and theoretical research did not treat

the “rival”school m uch better. Sim s (1980), for

exam ple, show ed evidence that seem s to con-

tradict som e versions of the m onetarist theory.

Initially, the theoretical developm ents

inspired by these failures kept nom inal factors

as the param ount force behind econom ic fluc-

tuations. In fact, in Lucas (1972), the first and

perhaps m ost celebrated application of the

novel approach to m acroeconom ic analysis for

w hich Robert Lucas received the 1995 N obel

Prize, the m oney supply still plays a crucial role

for the business cycle. Thus, econom ists w ere

surprised w hen K ydland and Prescott (1982)

show ed that one could account for tw o-thirds of

the U .S. econom ic fluctuations w ith a dynam ic

stochastic general equilibrium m odel from

w hich nom inal variables w ere totally absent—

that is, a m odel w ithout any m oney in it.K ydland and Prescott obtained this result

using a variation of the sam e basic theoretical

m odel econom ists had been using tim e and

again to study econom ic grow th issues.

U nifying theories—that is, theories that can

sim ultaneously explain seem ingly unrelated

phenom ena—are usually w elcom e in science.

W hat m any econom ists found attractive about

the Real B usiness Cycle (RBC) theory proposed

by K ydland and Prescott w as that, for the first

Is the BusinessCycle of Argentina

“ Dif ferent” ?

Finn E. KydlandProfessor

Carnegie Mellon University

and

Research Associate

Federal Reserve Bank of Dallas

Carlos E. J. M. Zarazaga

Senior Economist and Executive Director

Center for Latin American Economics

Federal Reserve Bank of Dallas

Nominal factors do not seem

to be able to account for any

significant fraction of the

business cycles of Latin

American countries in general,

and of Argentina in particular.

Perhaps for this reason it is time

to give real factors their fair

chance to do the job.



22

tim e, a business-cycle theory pointed to the

possibility that the sam e analytical tools used to

address econom ic grow th issues could be used

to address business-cycle questions as w ell. This

m ay explain w hy these econom ists regarded

K ydland and Prescott’s findings persuasive

enough to b egin seriously exploring the

hypothesis that “real”factors, rather than nom i-

nal ones, are a prevalent driving force behindeconom ic fluctuations.2 Although real or supply-

side factors, such as the am ount of resources

used by the governm ent, tax p olicies, techno-

logical changes, governm ent regulations, m odi-

fications of financial interm ediation rules, and

even political shocks signaling p ossible changes

in property rights, m ay appear to be the obvi-

ous candidates to explain business cycles, this

w as not that clear a short w hile ago.

The process of verifying, sharpening, or

refuting the real-shock account of business

cycles has generated a large body of theoretical

and em pirical research concentrated, so far,on developed countries. This is unfortunate, be-

cause the evidence suggests that econom ic fluc-

tuations are particularly severe in developing

countries. U nderstanding w hy this occurs could

lead to w ays to m ake the business cycles of

these countries at least as sm ooth as those of

developed ones. W hat m akes the study of Latin

Am erican countries’business cycles p articularly

interesting is the claim that econom ic fluctua-

tions in those countries have been driven by

nom inal factors. Science m akes progress pre-

cisely w hen it encounters observations that the

prevailing paradigm cannot explain. Therefore,

there seem s to be a com pelling need to confirm

the alleged anom alies by answ ering the ques-

tion, Are business-cycle regularities in Latin

Am erica really all that different from those in

the U nited States and in O rganization for Eco-

nom ic Cooperation and D evelopm ent (O EC D )

and other European countries?

This article focuses this question on

Argentina, w ith the hope of m aking a m odest

contribution to the understanding of the busi-

ness cycles of Latin A m erican countries in

general. For exam ple, if Argentina’s business-cycle regularities are sim ilar to those of the

U nited States or Europe, then the business

cycles of all these countries m ay be m anifesta-

tions of essentially the sam e phenom enon.

Therefore, real factors could play an im portant

role in accounting for Argentina’s business

cycles, just as, according to recent research,

they do in the U nited States and Europe.

By contrast, if Argentina’s business cycles

show im portant anom alies w ith respect to the

evidence available for other countries, then the

possibility of real factors playing an im portan

role in its business cycle dim inishes. In this

case, existing interpretations em phasizing the

role of nom inal variables in Latin Am erica m ay

regain the prom inence they had in business

cycle theories until the 1970s. Allow ing for

com parisons w ith the em pirical evidence fo

other countries, this article exam ines theA rgentinean business-cycle regularities w ith

the sam e m ethodological approach used in

previous studies for the U nited States and sev

eral European countries.

In the follow ing section, w e present the

evidence other authors have used to support the

contention that nom inal factors have driven the

business cycles in Latin Am erica and provide

reasons to doubt the robustness of those find

ings. W e also suggest that the data require fur

ther system atic scrutiny before econom ists can

conclude w ith som e confidence that busines

cycles in Latin A m erican countries, and particularly in Argentina, differ in nature from those

observed in the U nited States and in O EC D and

other European countries. N ext, w e undertake

one such system atic study by presenting, as the

availability of data perm its, the A rgentinean

counterpart of the statistics researchers have

used to describe the business cycles of the

U nited States and several European countries

W e then com pare the statistics for Argentina

w ith those of other countries and state the

im plications that result from analysis of cross

country sim ilarities and differences. The las

section sum m arizes our conclusions.

The state of the business-cycledebate in Latin America

The understanding of the Latin A m erican

business cycles has not escaped the view tha

nom inal shocks are the predom inant cause o

econom ic fluctuations. This view still influences

the thinking on m any Latin A m erican econom ic

problem s. This thinking is particularly notice

able in the inflation stabilization literature.

O ne of the m ost serious econom ic prob

lem s m any Latin Am erican countries have facedin past decades has been persistent, high infla

tion.3 Therefore, the quest to find the best anti

inflation policies has inspired a large body o

research on this problem . The m onetarist influ

ence in that literature is evident in its contention

that nom inal factors (such as changes in the

nom inal exchange rate regim e) w ere the only

system atic force driving econom ic fluctuations

around the tim e the stabilization program s w ere

im plem ented. For exam ple, the conventiona




w isdom in Latin Am erica is that anti-inflation

program s using the exchange rate as a nom inal

anchor (exchange-rate-based stabilization, or

ER BS, program s) have been able to reduce the

inflation rate w ithout causing the initial output

losses associated w ith program s that use som e

m onetary aggregate as a nom inal anchor

(m oney-based stabilization program s).4

O f course, a theory for stabilization pro-gram s is not the sam e as a theory for the

business cycle. But there should be som e con-

sistency am ong them . For exam ple, a finding

that nom inal shocks do not have im portant real

effects during Latin Am erican stabilization pro-

gram s w ould m ake it harder to m aintain the

m onetarist view that such factors m ay have

been im portant at any other point of the busi-

ness cycle. A nd this is precisely w hat w e find

problem atic: a reexam ination of the evidence

on ERBS program s show s that it is far from clear

that the adoption of the exchange rate as a

nom inal anchor has been responsible, as theliterature claim s, for the econom ic fluctuations

observed during those program s.

Figure 1 illustrates the consum ption

grow th rates for the ten ERBS program s studied

by V égh (1992). The vertical line indicates the

year or quarter in w hich the ERBS program

started.5 Casual inspection of the plots suggests

that only in the first four cases did consum ption

exp erience the upw ard jum p that theory pre-

dicts should occur upon announcem ent of ERBS

program s.6 H ow ever, this theoretical prediction

did not m aterialize in the rem aining six cases. In

particular, in none of these six did consum ption

grow faster than in the im m ediately preceding

period. Instead, in four of the six cases, con-

sum ption grow th w as basically the sam e im m e-

diately before and im m ediately after the

announcem ent of the corresponding ERBS pro-

gram . In tw o of the four, the so-called con-

sum ption boom preceded the announcem ent.

In the other tw o, there w as no consum ption

boom w hatsoever: consum ption continued

falling at approxim ately the sam e rate as before

the ERB S program s began. Furtherm ore, in the

last tw o cases, the ERB S program w as follow edinstead by a consum ption bust.

Therefore, the tim ing, intensity, or direc-

tion of consum ption grow th for the countries in

Végh’s study, after m ost ERBS program s began,

appears to differ from that im plied by the ERBS

theory.

In this sense, at least four of the p lots in

Figure 1 (Chile, February 1978; Argentina, D e-

cem ber 1978; Argentina, June 1985; and Israel,

July 1985) could be interpreted using the non-

m onetarist approach: the dynam ics of output

im m ediately after the announcem ent of an ERB S

program w ere m ere continuations of upsw ings or

dow nturns that had begun earlier. In these four

cases, forces other than the adoption of a fixed

or pegged exchange rate w ere already driving

the business cycle w hen the ERBS program s

began. But such conclusions from the casual

reading of tw o-dim ensional plots w ould be pre-m ature.7 W e are m ore persuaded, instead, by

the m ore thorough em pirical effort of Rebelo

and V égh (1995), w ho conclude that m onetarist-

inspired theoretical m odels of ERBS program s

are quantitatively incapable of rep licating any

significant fraction of the econom ic fluctuations

associated w ith such program s.

The evidence on ERBS program s, both

from casual plot readings and from the w ork of

Rebelo and Végh, poses a serious challenge to

m onetarist theories of Latin Am erican business

cycles: if nom inal exchange rate shocks in Latin

Am erica seem to have failed to produce thenoticeable and consistent effects on consum p-

tion and other real variables predicted by m one-

tarist-inspired theories precisely w hen they

w ere given the best shot at it, how could they

have significant real effects at other tim es?8

A natural next step in the research agenda

is to pay m ore attention to real shocks as a

potentially im portant source of the econom ic

fluctuations observed in Latin A m erican coun-

tries, including fluctuations observed during

inflation stabilization program s.9 In principle,

there is no reason the assessm ent of the quanti-

tative im portance of such shocks in Latin

Am erica could not be accom plished w ith the

sam e kind of dynam ic stochastic general equi-

librium m odels the RB C tradition has used to

that effect for the U nited States and other devel-

oped countries.

But such a research program m ust start by

describing the data w ith a system atic, atheoreti-

cal m ethodology.10 The rem aining sections of

this article m ake a m odest attem pt in that direc-

tion by describing the business-cycle regularities

of Argentina w ithout im posing theoretical priors

to the data.11

Business-cycle regular it ies f or Argenti naSome caveats about the data. N ational

account data in Latin Am erica are not as reliable

as their U .S. and O ECD counterparts.12 In fact,

because of frequent m ethodological changes

and corrections of previous errors, the reported

series m ay change substantially from one

national account estim ate to the next. This is

indeed the case for Argentina. For exam ple,



24

Figure 1

ERBS Programs

Argentina, March 1967 Uruguay, June 1968

–20

–15

–10

–5

0

5

10

15

’83:1’82:1’81:1’80:1’79:1’78:1

Uruguay, October 1978 Brazil, February 1986

SOURCE: Table 10 in Végh (1992). SOURCE: Table 12 in Végh (1992).


Argentina, June 1985 Israel, July 1985

Brazil, March 1964 Mexico, December 1987


Chile, February 1978 Argentina, December 1978



–6

12

10

8

6

4

2

0

–2

–4

’62 ’63 ’64 ’65 ’66 ’67 ’68 ’69 ’70 ’71 ’72

–4

10

8

6

4

2

0

–2

’67 ’68 ’69 ’70 ’71 ’72 ’73

–10

20

15

10

5

0

–5

’84:1 ’85:1 ’86:1 ’87:1

–20

20

15

10

5

0

–5

–10

–15

’77:1 ’78:1 ’79:1 ’80:1 ’81:1 ’82:1 ’83:1

–15

–10

–5

0

5

10

15

20

’84:1 ’85:1 ’86:1 ’87:1 ’88:1

–20

20

15

10

5

0

–5

–10

–15

’78:1 ’79:1 ’80:1 ’81:1 ’82:1

–15

25

20

15

10

5

0

–5

–10

’84:1 ’85:1 ’86:1 ’87:1 ’88:1 ’89:1 ’90:1

–10

20

15

10

5

0

–5

’62 ’63 ’64 ’65 ’66 ’67 ’68 ’69 ’70 –4

8

6

4

2

0

–2

’87:1 ’88:1 ’89:1 ’90:1 ’91:1

R e a l p r i v a t e c o n s u m p t i o n *


R e a l p r i v a t e c o n s u m

p t i o n *

R e a l t o t a l c o n s u m p t i o n *

R e a l G D P *


R e a l t o t a l c o n s u m p t i o n *

R e a l p r i v a t e c o n s u m

p t i o n *



* Growth in percent with respect to the same per iod of the previous year.




volatility of consum ption relative to output is

substantially low er in the national accounts esti-

m ate at 1986 prices (released at the end of 1996)

than in the previous estim ates at 1970 prices.

The exam ple above em phasizes that in

dealing w ith countries such as A rgentina,

researchers should heed the usual w arning to

appropriately w eigh the quality of the data

before taking for puzzles anom alies that inreality m ay be m ere statistical artifacts. For that

reason, w e report the business-cycle regularities

obtained from using tw o different estim ates of

G D P and its com ponents. The com parison of

the results from each data set w ill eventually

give som e idea of the confidence one should

place on the business-cycle regularities of Argen-

tina reported here or elsew here (for exam ples,

see K aufm an and Sturzenegger 1996 and C arrera,

Féliz, and Panigo 1996).

O ne estim ate (the “old”estim ate), in con-

stant prices of 1970, covers the 1970:1–90:4

period and w as prepared by the Central Bank ofArgentina. W e obtained this estim ate from the

FIEL (Fundación de Investigaciones Económ icas

Latinoam ericanas) data bank. The other esti-

m ate (the “new ”estim ate), in constant prices of

1986, covers the 1980:1–95:4 period. The figures

for this estim ate w ere taken from the publica-

tion Oferta y Demanda Global es, 1980 –1995 ,

prepared by the D irección N acional de Cuentas

N acionales. N otice that these tw o estim ates

overlap only during the 1980:1–90:4 period.13

Methodology. W e characterize the busi-

ness-cycle regularities of A rgen tina u sing

K ydland and Prescott (1990) as a guide. Their

procedure is inspired by Lucas (1977), w ho

defines the business-cycle com ponent of a vari-

able as its deviation from trend. K ydland and

Prescott define the trend of a variable as that

w hich results from applying the H odrick–

Prescott filter (H P filter) to the raw data.

Inform ally, this filter produces trends that are

“close to the one that students of business

cycles and grow th w ould draw through a tim e

plot”(K ydland and Prescott 1990).14 Application

of the H P filter to Argentinean G D P, for ex-

am ple, produces the trend represented by thesm oother curves in Figure 2.15,16

Except for net exports, all variables in the

tables of this article are expressed in natural

logarithm s, as is standard in the business-cycle

literature.17 Since it is not possible to com pute

the logarithm of negative values, variables that

can take on such negative values, such as net

exports, w ere exp ressed instead as ratios to

G D P. All the variables w ere seasonally adjusted

using the X -11 procedure.

The tables rep ort statistics that m easure (1)the direction of the m ovem ents of a variable

com pared w ith that of real G D P (procyclical , in

the sam e direction;countercyclical , in the oppo-

site direction; acyclical , w hen there is no clear

pattern); (2) the degree to w hich the variable

follow s the m ovem ents of real G D P (contem po-

raneous correlation); (3) the am plitude of fluc-

tuations (volatility or relative volatility); and (4)

the phase shift—that is, w hether a variable

changes before or after real G D P does (leads or

lags the cycle, respectively.)

The statisticsvolatility

corresponds to the

standard deviation of the percentage by w hich

the cyclical com ponent of a variable deviates

from trend. The statistics r elati ve volatili ty is the

ratio betw een the volatility of the variable of ref-

erence and the volatility of real G D P.

Real f acts f or Argentina Output and its components: GDP. Table 1

rep orts statistics for real G D P and its m ajor

com ponents. The first striking feature of the

table is the high vo latility of real G D P.

According to the new national account esti-

m ates, the percentage standard deviation fromtrend of Argentina’s real G D P is roughly 2.5

tim es larger than for the U nited States. Real G D P

volatility is also high in the old national account

estim ates, but w ithin the range observed in

European countries such as G reece (2.85),

Portugal (3.05), and Luxem bourg (3.2).18,19

Total consumpti on. An im portant caveat in

interpreting the consum ption evidence is that in

Argentina’s national account, consum ption is

com puted as a residual, w hich casts consider-

Figure 2

Real GDP, Old and New EstimatesThousands of 1986 pesos (log scale)*

8.9

9.5

9.4

9.3

9.2

9.1

9

’94:1’92:1’90:1’88:1’86:1’84:1’82:1’80:1’78:1’76:1’74:1’72:1’70:1

Trend real GDP new

Real GDP new

Trend real GDP old

Real GDP old

* For visual effect, the old estimates have been rescaled so that

their level is the same as for the new estimates in 1980:1.

SOURCES: Dirección Nacional de Cuentas Nacionales for new

estimates; FIEL for old ones; authors’ calculations for

trends.



26

able doubt on the nature of the anom alous

behavior of consum ption that w e discuss below .

The volatility of real G D P and the relative

one for consum ption im ply that the volatility of

this real G D P com ponent is higher than that for

the U nited States or European countries. But

this anom aly is not all that rem arkable becauseit results directly from the reported high vola-

tility of real G D P and the fact that consum ption

and G D P are highly correlated.

Perhaps w hat is rem arkable is that the

volatility of consum ption is larger than that of

output. A lthough theoretically the opposite

should hold, this excess relative consum ption

volatility is w ithin the ranges observed in Japan

and som e European countries.20 M ore specifi-

cally, according to the new national account

estim ates in Table 1, A rgentinean consum ption

is 19 p ercent m ore volatile than G D P. This is no

uncom m on by international standards. Backus

K ehoe, and K ydland (1995) report that the cor

responding figure is 14 percent for Austria and

15 p ercent for Japan. A ccording to Christo

doulakis, D im elis, and K ollintzas (1995), it is ashigh as 46 percent for the N etherlands.21

By contrast, relative consum ption volatility

does exceed international standards for the old

national account estim ates. A consum ption

volatility 70 percent larger than that of outpu

is indeed hard to explain. Som e studies have

attributed this excess volatility to the presence

of credit constraints.22 H ow ever, there are rea

sons to be skeptical about this explanation

because in m odels w ith credit constraints, con

Table 1

Cycl ic al Behavior of Real GDP and Its M ain Components in Argentina and Other Countries

Argentina Argentina OECD, G–7,

(new national (old national and other

account estimates) account estimates) United European

1980:1– 95:4 1970:1– 90:4 States1 countries2

Real GDP volatility3 4.59 3.06 1.71 .90 to 3.20

Total consumption Procyclical Procyclical Procyclical Procyclical

Contemporaneous correlation .96 .84 .82 .1 to .83

Relative volatility 4 1.19 1.69 .73 .66 to 1.46

Phase shift Coincidental Coincidental Coincidental Coincidental5

Gross fixed investment Procyclical Procyclical Procyclical Procyclical

Contemporaneous correlation .94 .71 .90 .15 to .90

Relative volatility 4 2.90 3.44 3.15 2.30 to 5.63

Phase shift Coincidental Coincidental Coincidental Coincidental

Government consumption indicator Acyclical6 Acyclical7 Acyclical Acyclical

Contemporaneous correlation .206 .247 .05 –.23 to .27

Relative volatility 4 3.196 4.437 1.21 .36 to 1.28

Phase shift Lagging6 Lagging7 Lagging —

Net exports8 Countercyclical Countercyclical Acyclical Acyclical/countercyclical

Contemporaneous correlation –.84 –.62 –.28 –.01 to –.68

Volatility3 2.28 3.27 .45 .5 to 1.33

Phase shift Coincidental Coincidental Leading —

Imports Procyclical Procyclical Procyclical —

Contemporaneous correlation .81 .71 .71 —

Relative volatility 4 4.05 5.61 2.88 —

Phase shift Coincidental Coincidental Coincidental —

Exports Countercyclical Countercyclical Procyclical —

Contemporaneous correlation –.61 –.21 .34 —


Phase shift Coincidental Coincidental Lagging —

1 Statistics are from Kydland and Prescott (1990).2 Statistics are from Backus, Kehoe, and Kydland (1995) and Christodoulakis, Dimelis, and Kollintzas (1995).3 Percent standard deviation from trend.4 Ratio of volatility of the variable and the volatility of real GDP.5 Except in France, where, according to Christodoulakis, Dimelis, and Kollintzas (1995), it leads the cycle.6 For the period 1980:1–89:4.

7 For the period 1970:1–89:4.8 Trade balance as percentage of GDP.

NOTE: Seemingly anomalous statistics are in bold type.

SOURCES: Authors’ calculations, using the sources reported in the text.




sum ption is not as sm ooth as it w ould be

otherw ise, but it is still typ ically sm oother than

incom e.23

In considering the correlation betw een

output and consum ption, it is the figure for the

old national account estim ates that is norm al

and the one for the new national account esti-

m ates that is abnorm al. The correlation of 0.84

for the old national account estim ates is aboutthe sam e as the 0.83 correlation reported for

Canada—the highest correlation am ong the

countries reported in B ackus, K ehoe, and

K ydland (1995) and Christodoulakis, D im elis,

and K ollintzas (1995). This m eans that the 0.96

correlation betw een deviations from trend of

consum ption and G D P reported for the new

national account estim ates is unusually high by

international standards. It seem s to be high even

by Latin Am erican standards, as that correlation

is 0.91 for M exico (our ow n estim ates for the

1980:1–95:4 period) and 0.88 for U ruguay (for

the 1976:1–93:4 period; see K am il Saúl 1997).Theory predicts that such correlation

should be higher the m ore perm anent the

shocks are to incom e. Therefore, the high cor-

relation observed for Argentina m ight be an

indication that its business cycle is indeed dif-

ferent in the sense that shocks are m ore perm a-

nent there than in other countries. W e suspect,

how ever, that m ost business-cycle m odels,

m onetarist or real, w ill have a hard tim e

accounting for this high correlation w ithout, at

the sam e tim e, failing to accom m odate other

key regularities of the Argentinean business

cycle. N onetheless, there are reasons to be

cautious about the m agnitude of the contem po-

raneous correlation betw een detrended con-

sum ption and G D P in A rgentina. O ne reason, of

course, is that the significant discrepancy

betw een the correlations obtained w ith the tw o

national account estim ates points to the possi-

bility of im portant m easurem ent errors. This

possibility becom es even m ore apparent w hen

w e recall that consum ption in Argentina, as in

m any developing countries, is calculated as

a residual. This residual includes governm ent

consum ption —for w hich Argentina producesno separate quarterly estim ates—and, in the

case of the new national accounts estim ate,

changes in inventories, for w hich there also is

no separate estim ate.

An additional m ethodological source of

spurious correlation betw een consum ption and

output is the w ay output in Argentina is allo-

cated betw een consum ption and investm ent.

M any goods—such as autom obiles, electronics,

furniture, com puters, and telecom m unications

equipm ent—m ay be used for consum ption or

investm ent purposes. U nfortunately, Argentina

does not have the inform ation necessary to

determ ine the categories in w hich these goods

are being applied. To circum vent this problem ,

the production of m any item s is im puted to

both consum ption and investm ent according to

fixed coefficients constructed w ith inform ation

available only for the base year. For exam ple, 80percent of autom obile production is alw ays

im puted to consum ption and 20 percent to

investm ent. The sam e p rocedure is applied to

im ports and to the output of m any other indus-

tries that produce goods that can be used for

both investm ent and consum ption purposes.24

O f course, the proportions in w hich m any

goods are purchased for consum ption or invest-

m ent purposes change over the cycle. As a

result, the fixed-proportion m ethodology used

for Argentina’s national account estim ates w ill

distort the true underlying features of the busi-

ness cycles. In particular, w ith this im putationm ethod, part of the investm ent boom s w ill

show up m isleadingly in the data as consum p-

tion boom s.25 Because investm ent is highly cor-

related w ith output, the fixed coefficients

m ethod of im putation can artificially increase

the m easured correlation betw een consum ption

and G D P. This problem could be especially

serious in the new national account estim ates

that include the unusual investm ent boom of

the 1990s (Figure 3 ).

In sum m ary, there are reasons to be cau-

tious about the interpretation of the high cor-

relation betw een consum ption and output for

Figure 3

Real Gross Fixed Investment,Old and New EstimatesThousands of 1986 pesos (log scale)*

Trend real investment new

Real investment new

Trend real investment old

Real investment old

6.5

8.1

7.9

7.7

7.5

7.3

7.1

6.9

6.7

’94:1’92:1’90:1’88:1’86:1’84:1’82:1’80:1’78:1’76:1’74:1’72:1’70:1

* For visual effect, the old estimates have been rescaled so that

their level is the same as for the new estimates in 1980:1.

SOURCES: Dirección Nacional de Cuentas Nacionales for new

estimates; FIEL for old ones; authors’ calculations for

trends.



28

the new national account estim ates reported in

Table 1. Better data are needed before one can

confidently establish that this unusually high

correlation is indeed an anom aly by interna-

tional standards.

Gross fixed domestic investment. The m ag-

nitude and sign of the statistics for this com -

ponent (plotted in Figure 3) are in line w ith

those observed in other countries. It is particu-

larly notew orthy that the relative volatility of

this real G D P com ponent is close to that for the

U nited States.

Government consumption. As stated, Argen-tina does not have separate quarterly national

account estim ates for governm ent consum ption.

The disorganization of public accounts in com -

bination w ith the high inflation rates that pre-

vailed during the period have m ade estim ation

of such a series very difficult.

H ow ever, the sam e high inflation that pre-

vents the construction of reliable governm ent

consum ption estim ates also suggests that fiscal

policies m ay have played an im portant role in

the A rgentinean econom y. Therefore, w e believe

it is im portant to report statistics—albeit par

tial—for an indicator that show s the govern

m ent consum ption contribution to G D P a

quarterly frequencies. Figures for treasury pay

roll paym ents are available on a m onthly basis

for the 1970–89 period, so w e choose this vari

able as a potential indicator of fiscal policy. W e

m ust em phasize, how ever, that these disburse

m ents represent only a fraction of all such pay

m ents in the Argentinean public adm inistration

The statistics in Table 1 show that the

relative volatility of our real governm ent consum ption indicator is w ell above internationa

standards. It is also acyclical, a feature tha

characterizes governm ent purchases in the

U nited States as w ell. This acyclicality seem s

to be anom alous by Latin Am erican standards

(see Talvi and V égh 1996).

Trade balance. Som e of the statistics fo

Argentinean net exports (trade balance as a per

centage of G D P) are in line w ith the interna

tional evidence: net exports are countercyclical

Table 2

Cycl ic al Behavior of Argenti nean and U.S. Labor Inputs and Product ivi ty

Argentina Argentina

(new national (old national

account estimates) account estimates) United

1980:1– 90:4 1970:1– 90:4 States1

Industrial real GDP volatility 2 5.57 5.84 4.18

Real GDP Procyclical Procyclical Procyclical

Contemporaneous correlation .95 .90 .86

Relative volatility 3 .69 .52 .36

Phase shift Coincidental Coincidental Coincidental

Total hours Procyclical Procyclical Procyclical




Employment Procyclical Procyclical Procyclical



Phase shift Lagging Lagging Lagging

Hours per worker Procyclical Procyclical Procyclical




Productivity Procyclical Procyclical ProcyclicalContemporaneous correlation .48 .72 .71



1 The statistics correspond to the 1959:3–94:4 period and were constructed by the authors using a series of value added by the

manufacturing sector and a corresponding series of employment and hours worked in that sector published by the Bureau of Labor

Statistics (BLS) until 1994. The quarterly measure of industrial value added was taken from CITIBASE and corresponds to the

“fixed-weighted gross product originating” series for manufacturing produced by the BLS (see Gullickson 1995 for details).2 Percent standard deviation from trend.3 Ratio of volatility of the variable and the volatility of real industrial GDP.


SOURCES: Authors’ calculations based on sources in the text for national account estimates and on FIEL for labor market data.




as in several O ECD countries, although the

Argentinean contem poraneous correlation w ith

output is on the high end of the range. By con-

trast, the volatility of this com ponent seem s to

be abnorm ally high by international standards.

A sim ilar situation arises w ith im ports: they are

procyclical, as in the U nited States, but exhibit a

m uch higher volatility relative to output. Finally,

alm ost all of the statistics for exports are out ofline w ith those for the U nited States.

O ne caveat in analyzing the trade balance

com ponents of G D P is that Argentinean im ports

and exports are subject to considerable m eas-

urem ent errors because A rgentina used open

or hidden form s of exchange rate controls dur-

ing substantial portions of the period under

analysis. D uring these p eriods, the private

sector had incentives to understate exports and

overstate im ports in order to exploit the differ-

ential (w hich eventually becam e large) betw een

the often m ultiple official exchange rates and

the higher exchange rate usually prevailing inthe black m arket.

Labor inputs. Table 2 presents facts on

aggregate p roduction and labor input for the

old and new national account estim ates.

Because w e are trying to follow the m ethod-

ological approach in K ydland and Prescott

(1990) as closely as possible, w e w ould like to

replicate in our Table 2 all the statistics those

authors rep ort in their Table 1. U nfortunately,

lack of data has prevented us from achieving

the sam e results so far: there are no reliable

quarterly estim ates of capital input. And infor-

m ation on em ploym ent and hours w orked is

available only for the m anufacturing sector,

w hose value added represents a 25 percent

average of total G D P in the 1980–95 period.

For these reasons, w e report in Table 2 the

correlation and relative volatility of labor inputs

w ith respect to real industrial G D P, rather than

aggregate overall real G D P, used in Tables 1 and

3. W e also construct sim ilar m easures for the

U nited States. To give som e idea of how w ell

these series eventually approxim ate the rela-

tionship betw een labor inputs and real G D P for

the w hole A rgentinean econom y, w e report thecorrelation and relative volatility of aggregate

and real industrial G D P.

Another serious lim itation of the data is

that there are no reliable estim ates of average

w orker com pensation. Also, the relevant series

for labor m arkets have not been updated since

1990. Thus, these series overlap the new G D P

estim ates only during the 1980:1–90:4 period.

W ith these caveats about the data in m ind,

Table 2 suggests that total hours w orked,

em ploym ent, and hours per w orker are strongly

procyclical. The statistics for those variables aresim ilar across the different national account esti-

m ates. Except for em ploym ent, this sim ilarity

extends also to the correlations for the U nited

States for both periods.

The correlation of em ploym ent in the

industrial sector w ith real industrial G D P is

low er in Argentina than in the U nited States.

This finding is not surprising given the m uch

m ore stringent labor m arket regulations in

Argentina. Because of high firing costs, firm s

w ill postpone hiring and firing decisions. So

changes in em ploym ent w ill not trace changes

in output as closely as they w ould in the

absence of labor m arket restrictions.

Relative volatilities are rem arkably sim ilar

across the countries, although volatility tends to

be higher in Argentina for the num ber of hours

per w orker. This finding, again, likely reflects

the labor m arket restrictions: w hen confronted

w ith the high costs of firing w orkers, firm s tend

to expand or contract the labor hours of those

already em ployed, rather than hire or lay off

m ore w orkers.

Finally, it is w orth noting that productivity

in the A rgentinean industrial sector is procycli-cal (Figure 4 ), w ith correlations and relative

volatilities on the sam e order of m agnitude as

those for the U nited States.

O verall, the business-cycle features of

Argentinean labor inputs are reasonably sim ilar

to those in the U nited States.

Nominal facts for Argentina Table 3 sum m arizes the statistical proper-

ties of the business-cycle com ponent of several

Figure 4

Argentina, Productivit y Is Procycli calPercent standard deviation from trend

–15

–12

–9

–6

–3

0

3

6

9

’90:1’89:1’88:1’87:1’86:1’85:1’84:1’83:1’82:1’81:1’80:1

Deviationsindustrial

productivity

Deviationsreal industrial GDP

SOURCES: Authors' calculations using new national account

estimates from Dirección Nacional de Cuentas

Nacionales and index of total hours worked in the

manufacturing sector from FIEL.



30

nom inal and m onetary aggregate series. This

table presents inform ation analogous to that in

Table 4 of K ydland and Prescott (1990), w ith the

necessary m odifications to incorporate som e

idiosyncracies of the Argentinean econom y.

First, w e do not report statistics for the

m onetary base. Because of the frequent and

cum bersom e changes in financial regim e thatArgentina experienced in the period under

analysis, the concept of m onetary base does not

have the m eaning it has in the U nited States or

in the O EC D and European countries w e use for

com parison in this article.26

Second, the im plem entation of different

form s of price controls during the analysis

period m ay have distorted the true business-

cycle price features. Therefore, as proxy for the

true underlying nom inal price level, w e also

report statistics for the exchange rate in the

black m arket.

The intense inflationary process tha

Argentina experienced in the 1970s and 1980s

is responsible for the unusual high volatility o

all variables in Table 3. H ow ever, to correctly

interpret this volatility and other statistics in the

table, it is im portant to stress that m onetarypolicy in A rgentina during m ost of the 1970–95

period w as not m onetary policy in the sense

that it is in the U nited States, but rather a form

of im plem enting fiscal policies financed w ith

m oney creation.27

O ne striking sim ilarity w ith internationa

evidence stands out from the table: w hether

m easured by the consum er price index or the

black m arket exchange rate, the p rice level has

been countercyclical (Figure 5 ), as it is in the

Table 3

Cycl ic al Behavior of M onetary Aggregates and Pric e Level Indic es in Argentina and Other Countri es

Argentina Argentina

(new national (old national

account estimates) account estimates) United OECD, G–7, and other

1980:1– 95:3 1970:1– 90:4 States1 European countries2

M1 Countercyclical Acyclical Procyclical Acyclical/procyclical

Contemporaneous correlation –.36 –.09 .31 –.06 to .42

Relative volatility 3 15.13 15.68 1.00 .49 to 2.93

Phase shift Lagging No clear pattern Leading Leading (when countercyclical)

M2 Countercyclical Acyclical Procyclical Acyclical/procyclicalContemporaneous correlation –.40 –.07 .46 –.034 to .39


Phase shift Lagging No clear pattern Leading No clear pattern

M2–M1 Acyclical Acyclical Procyclical —

Contemporaneous correlation –.23 .01 .40 —


Phase shift No clear pattern Leading No clear pattern —

Velocity M1 Countercyclical Countercyclical Procyclical —

Contemporaneous correlation –.46 –.26 .31 —


Phase shift Leading Leading Coincidental —

Velocity M2 Countercyclical Acyclical Acyclical —

Contemporaneous correlation –.37 –.24 .24 —Relative volatility 3 5.06 7.08 1.08 —

Phase shift Lagging Lagging Lagging —

CPI Countercyclical Acyclical Countercyclical Acyclical/countercyclical

Contemporaneous correlation –.47 –.20 –.57 –.55 to –.03


Phase shift Lagging No clear pattern Leading Leading

ER Countercyclical Countercyclical — —

Contemporaneous correlation –.61 –.49 — —

Relative volatility 3 16.04 18.29 — —

Phase shift Lagging Lagging — —

1 From Kydland and Prescott (1990).2 From Christodoulakis, Dimelis, and Kollintzas (1995).3 Ratio of volatility of the variable and the volatility of real GDP reported in Table 1.

4 Only Spain exhibits a large negative correlation (–.30).


SOURCES: Authors’ calculations, based on sources reported in the text for national accounts and on FIEL for monetary aggregates and price level indices.




U nited States and in m ost European countries

(Christodoulakis, D im elis, and K ollintzas 1995).

The countercyclicality of prices for the U nited

States w as pointed out in K ydland and Prescott

(1990) at a tim e w hen econom ists com m only

held the opposite view . N ot surprisingly, this

finding created considerable debate because it

w ent against the predictions of m ost K eynesian

or m onetarist-inspired theories of businesscycles.28

For nom inal M 1, how ever, the com parison

w ith other countries is not that clear cut. The

pattern of correlation for this m onetary aggre-

gate depends in an im portant w ay on the

national account estim ates used. For the old

estim ates, M 1 is acyclical and all correlations

are sim ilar in sign and m agnitude to those

reported for the N etherlands in Christodoulakis,

D im elis, and K ollintzas (1995). By contrast,

according to the new national account esti-

m ates, M 1 is countercyclical, w hereas in the

U nited States and the European countries inChristodoulakis, D im elis, and K ollintzas (1995),

it is acyclical or procyclical.

The differences betw een the tw o national

account estim ates should serve as a note of

caution to researchers w orking w ith nom inal

m onetary aggregates for Argentina. It is possible

that som e of the regularities taken for granted in

the p ast w ere derived using the old estim ates,

but now those regularities have disappeared or

becom e less obvious w ith the new national

account estim ates.

In any case, both national account esti-

m ates suggest that the m onetary aggregate of

savings accounts and tim e deposits (M 2–M 1) is

acyclical. This is in contrast w ith the U nited

States, w here, according to K ydland and

Prescott (1990), this m onetary aggregate is pro-

cyclical and leads the cycle. But it w ould be

w rong to conclude that this evidence suggests

that credit arrangem ents could play a m ore sig-

nificant role in U .S. business cycles than in

those of A rgentina, because during m ost of the

analysis period, there w as a considerabledegree of financial repression in the latter

country. As a result, part of the credit m arket

w as channeled through the inform al financial

sector, w hose transactions by its very nature are

not cap tured by the official m onetary statistics.

Finally, velocity of all m onetary aggre-

gates, w hether using the consum er price index

(reported in Table 3) or the exchange rate

(not reported) as a deflator, is countercyclical,

w hereas K ydland and Prescott (1990) reported it

is procyclical for the U nited States.

ConclusionIs the business cycle of Argentina really

different from that of other countries? W e hope

this article show s other researchers how difficult

it is to answ er this sim ple question. O ne reason

for this difficulty is that the business-cycle fea-

tures of Argentina can change substantially from

one national account estim ate to the next. A s

w e indicate, the com m only held view that

absolute volatility of output is abnorm ally high

in Argentina is a m yth by the old national

account estim ates but a fact by the new ones.

Sim ilarly, the correlation of the cyclical

com ponent of real total consum ption w ith that

of real G D P is w ithin the range observed in

other countries, according to the old national

account estim ates, but unusually high by the

new ones. W e have given reasons, how ever, to

consider this last feature as partly a figm ent of

the data.

The statistics related to production inputs

(labor and investm ent), w hich play a crucial

role in R BC m odels, display rem arkable sim i-

larities w ith the international evidence. In par-

ticular, except for absolute volatilities, all the

statistics for investm ent, labor inputs, and pro-ductivity are w ithin the range observed in the

U nited States or European countries.

Based on these statistics, the only chal-

lenge for an RBC m odel of A rgentina w ould be

to explain the larger volatility of output. But a

study by M endoza (1995) suggests that an RBC

m odel could accom plish that if properly

adapted to deal w ith the idiosyncracies of the

Argentinean econom ic environm ent. By that, w e

do not m ean a m odel that incorporates only

Figure 5

Argentina, Pr ices Are Countercyclic alPercent standard deviation from trend

–200

–150

–100

–50

0

50

100

150

200

’94:1’92:1’90:1’88:1’86:1’84:1’82:1’80:1 –12

–10

–8

–6

–4

–20

2

4

6

8

10

12Price index deviations

Real GDPdeviations

SOURCES: Authors' calculations using new national account

estimates from Dirección Nacional de Cuentas

Nacionales and the consumer price index from

Instituto Nacional de Estadísticas y Censos (INDEC)

as reported by FIEL.



32

technology shocks, but one that uses other real

factors or econom ic policies w hose effects can

be captured through the aggregate p roduction

function of the econom y. M ore specifically,

M endoza’s study adds term s-of-trade shocks to

an RBC m odel w ith technology shocks and

show s that such a m odel can replicate about the

sam e proportion of G D P variability—50 percent

for G –7 and developing countries—even if theabsolute volatility of G D P is substantially larger

in the developing countries. Interestingly,

according to the M endoza study, the variability

of Argentina’s term s of trade is tw ice that for the

U nited States, w hich is the order of m agnitude

by w hich the variability of Argentina’s G D P

exceeds that of U .S. G D P (using the new

national account estim ates).29

A host of other em pirical studies confirm

the potential of RBC m odels to m im ic a large

fraction of the econom ic fluctuations observed

in Latin Am erican countries. For exam ple, using

a structural vector autoregression m odel (VAR),H offm aister and Roldós (1997) find that supply

shocks are, even in the short run, the m ain

source of the output fluctuations in these

countries. Sturzenegger (1989) also reports VA R

estim ates, according to w hich supply shocks

account for 90 percent of the A rgentinean out-

put fluctuations.

The results in Table 3 are unfavorable to

the hypothesis that nom inal factors play the

m ost im portant role in econom ic fluctuations. In

particular, the price level is countercyclical.

M onetary theories of business cycles have had a

hard tim e accom m odating this em pirical regu-

larity w ithin an em pirically successful (by som e

m easure) dynam ic stochastic general equilib-

rium m odel. Furtherm ore, the A rgentinean

m onetary aggregates display, in general, a very

different cyclical (countercyclical) pattern than

those of the U nited States and Europe (pro-

cyclical). Yet, these differences do not seem to

translate to the relative volatilities and other fea-

tures of real variables, w hich behave m ore sim i-

larly in Argentina and these other countries.30

In addition, our analysis of the business-

cycle debate in Latin Am erica suggests thatnom inal exchange rate shocks, even during

ERBS program s, do not seem to have had the

clear real effects the literature has alleged. In

fact, the evidence w e have presented—circum -

stantial as it m ay be—and the few available

studies that have attem pted to analyze it in a

m ore system atic w ay all point in the sam e direc-

tion: nom inal factors do not seem to be able

to account for any significant fraction of the

business cycles of Latin Am erican countries in

general, and of Argentina in particular. Perhaps

for this reason it is tim e to give real factors thei

fair chance to do the job. Therefore, it is essen

tial that a research agenda first specify the

em pirical regularities that real factors m us

account for.

To that end, w e have presented the facts

about the A rgentinean business cycle, follow ing

a w ell-defined, system atic ap proach that doesnot im pose on the data any strong a prior

belief on a particular theory of business cycles

W e hope that our atheoretical description o

em pirical regularities w ill m otivate further em

pirical and theoretical w ork that w ill ultim ately

lead to a better understanding of the econom ic

fluctuations and of the real effects of inflation

stabilization program s in Latin Am erican coun

tries in general, and in A rgentina in particular.

NotesThe authors are grateful to D avid G ould, C arlos Vég h,

and M ark W ynne for substantive and useful com -

m ents. W e are also thankful to A nne C oursey, w hose

editorial suggestions contributed to a clearer exp osi-

tion of our ideas.1 This distaste for econom ic fluctuations is im plied by

the assum ption that econom ic ag ents have concave

preferences. A n old joke illustrates the m eaning of this

econom ic jargon. A n econom ist is inform ed that a

fellow citizen, w ith one leg freezing in ice and the

other boiling in hot w ater, is in pain. “W hy?”the

econom ist asks. “O n average, he is O K .”A ctually,

this joke doesn’t do justice to the econom ics profes-

sion, w hose m em bers know very w ell that the citizen

has concave preferences: he w ould p refer to have

both feet in lukew arm w ater. Likew ise, econom ists

know that consum ers w ould prefer an econom y in

w hich output and consum ption g row at the sam e

steady rate, quarter after quarter, to one w hose grow th

is the sam e on average but varies from high (a hot

econom y) in som e quarters to slow (a cold econom y)

in others.2 So m uch so that a p rom inent m onetarist like Lucas

him self recently asserted, “M onetary shocks just aren’t

that im portant. That’s the view I’ve been driven to….

There’s no question, that’s a retreat in m y view s.”

(The N ew Yorker , D ecem ber 1996, 55.)3 For an excellent sum m ary, see Vég h (1992).4 For details, see K iguel and Liviatan (1992), Vég h

(1992), C alvo and Vég h (1993), and citations therein.5 The vertical line is d raw n on the tick corresponding

to the p eriod in w hich the p rog ram w as announced,

unless the announcem ent w as m ad e in the first third

of the period. In this case, the vertical line is draw n on

the tick corresponding to the im m ed iately preced ing

period. The im plicit assum ption is that the real effects

of ER B S p rog ram s did not have tim e to show up in the




period of the announcem ent if it cam e too late in the

period .6 This p rediction arises from the intertem poral substitu-

tion effect originally em phasized by C alvo (1986): the

tem porary (by assum ption) red uction of the devalua-

tion rate translates into a tem porary reduction in the

nom inal interest rate that increases the dem and of cur-

rent trad able g oods relative to future tradab le g oods.

The em pirical relevance of this m echanism , how ever,has b een questioned by R einhart and Végh (1995a).

7 “W itty”analysis of plots is a valid and w idely used

m ethod of analyzing econom ic evidence, esp ecially in

the early stag es of a theoretical develop m ent. H ow -

ever, this casual em piricism presents serious prob lem s

(see E asterly 1996). To avoid am biguities and im pre-

cisions, plot analysis should b e com plem ented w ith

m ore form al quantitative m ethods w henever possible.

In our case, it w ould be im portant to construct m eas-

ures estab lishing w hether the consum ption grow th

rate im m ed iately after the announcem ent of ER B S

prog ram s w as significantly d ifferent (by som e criteria)

than im m ed iately before. The ER B S literature has yet

to p rovide such a m easure. The few form al quantitative

studies in that literature that have attem pted to go

beyond the plot analysis (R einhart and V ég h 1994,

1995b, and H offm aister and Végh 1996) are con-

cerned, instead, w ith the dynam ics of real variab les

w ithin different inflation stab ilization program s.8 It is true that nom inal factors d eliver im portant real

effects in the nom inal w age rigidity version of the

m onetarist-inspired m od els exam ined by R ebelo

and V ég h (1995). H ow ever, that success is achieved

at the expense of generating countercyclical real

w ag es, w hich goes ag ainst the availab le evidence.

For exam ple, C arrera, Féliz, and Panigo (1996) rep ort

that real w ages in A rgentina and B razil are procyclical.9 In fact, none of the stabilization program s reported in

the literature has been a “pure”m onetary experim ent.

They w ere alw ays associated w ith other policy m eas-

ures, such as financial liberalization, changes in taxes

and tariffs, and so on, all factors that w ould fall in

the category of “real”in the analytical fram ew ork of

real-business-cycle theory. The om ission of these

factors from the analysis m ay lead to serious m isinter-

pretations of the evidence on stab ilization prog ram s.

For exam ple, as pointed out by C alvo (1986), “…if

expected to be tem porary, a banking liberalizationpolicy w ill tend to have effects sim ilar to the typ e of

exchange rate policies analyzed above [in reference

to E R B S program s].”10 In this sense, w e enthusiastically agree w ith C alvo

and Végh (forthcom ing, 14) that “too little em pirical

w ork—relative to theoretical w ork—has been done

in the area.”11 This m ethodology is “theory free”in the sense that it

does not take any stand w ith resp ect to the causes of

econom ic fluctuations.

12 H eston (1994) provides a very thorough d iscussion of

all the m easurem ent prob lem s typical of the national

accounts of develop ing countries like A rgentina.13 The chang e in the base year is not the only difference

betw een the tw o series. There w ere also im portant

m ethodolog ical m od ifications and other ad justm ents in

the new estim ates. The m ag nitud e of the corrections

should be ap parent from the fact that the level of

annual real G D P for 1980 is 36 percent higher in thenew estim ates than in the old estim ates. Jum ps of this

size in the level of G D P betw een subseq uent national

account estim ates are not unusual in Europ ean coun-

tries as w ell (see M ad dison 1995, 124).14 A technical presentation of the H P filter can b e found

in H od rick and Prescott (1997).15 B ecause w e are d ealing w ith q uarterly data, w e follow

K ydland and Prescott (1990) in setting the “sm oothing

param eter”λ = 1600.16 W e acknow led ge that the statistical prop erties of the

detrended com ponents m easured w ith the H P filter

rem ain som ew hat controversial (see, for exam ple, King

and R eb elo 1993). B ut it is im portant to keep in m ind

that our m ain goal is to com pare the business-cycle

regularities of A rgentina w ith those of the U nited States

and Europe. Several recent stud ies for such countries

have ind eed detrended the data w ith the H P filter as

w ell. M oreover, no d etrending technique is free from

criticism .17 The reason for this transform ation of the data is that

the business-cycle literature is concerned w ith p er-

centage (rather than absolute) deviations from trend in

grow ing series.18 A s an exercise, w e extend ed the G D P series from

each national account estim ate to the entire 1970:1–95:4

period by applying to each estim ate the grow th rates

of the other during the nonoverlap ping period . The

cyclical volatility of G D P from the series constructed

this w ay is 3.9 for the new estim ates and 3.65 for the

old ones.19 See tab le A 2 in C hristod oulakis, D im elis, and

K ollintzas (1995).20 A ccording to the p erm anent incom e hypothesis, the

series for consum ption should be sm oother than that

for incom e (or G D P). H ow ever, this pred iction is valid

only for consum ption of nond urable goods, and the

series for consum ption typ ically includes d urable

goods.21 The conjecture that the excess volatility of consum p-

tion relative to that of output m ost likely reflects a m is-

m easurem ent prob lem , as hypothesized in note 20,

is reinforced by the find ing in B ackus, K ehoe, and

K yd land (1995) that consum ption volatility is indeed

low er than that of G D P in the U .K . once exp enditures

on consum ption d urab les are exclud ed from aggre-

gate consum ption.22 See, for exam ple, “O vercom ing Volatility,”Inter-A m erican

D evelopm ent B ank (1995, 191).



34

23 Intuitively, in an econom y incapable of transferring

w ealth betw een period s, econom ic ag ents w ill use up

all they prod uce in every period —that is, consum ption

w ill be exactly equal to incom e period after period .

A lthoug h there is absolutely no credit in this econom y,

the volatility of consum ption cannot exceed that of

output (or incom e).24 H eston (1994, 43) discusses a concrete case in w hich

allocating im ports betw een consum ption and invest-m ent, w ith proced ures analog ous to the one outlined

ab ove, m ay lead to significant errors in consum ption.

The new national account estim ates used inform ation

from the N ational Econom ic C ensus of 1985 to im pute

im ports as consum ption or investm ent goods, and

data from the N ational Econom ic C ensus of 1973 for

the sam e im putation of dom estically prod uced good s.

For m ore d etails, see C EPA L/EC LA , final rep ort, 1991.

The p articular exam ple in the text about the allocation

of autom ob iles betw een consum ption and investm ent

w as p rovided in an interview w ith staff m em bers from

the S ub secretaría de Prog ram ación E conóm ica d el

M inisterio de Econom ía of A rgentina.25 This m ay have serious im plications for the prolific

literature inspired by rep orted consum ption boom s in

Latin A m erican countries: it m ay w ell be the case that

these boom s, or at least a part of them , are in reality

cap turing m ism easured investm ent boom s.26 For exam ple, in July 1982 all A rgentinean dep osits

w ere “nationalized”—that is, from that m onth on, all

deposits in financial institutions w ere considered

dep osits at the central bank. Since these dep osits are

by d efinition part of the m oney base, this b ase

becam e alm ost identical to M 2 and therefore experi-

enced an increase equal to the difference betw een

these tw o m onetary aggreg ates p revious to the reform .

A lm ost all of the resulting jum p in the m oney b ase that

m onth w as, then, an artifact of accounting proced ures

rather than the result of a chang e in m onetary policy.

For these and other details on the institutional features

of the A rgentinean financial system over the 1900 –95

period , see Zarazaga (1996).27 M onetary policy in the U nited States is closer to w hat

econom ists w ould reg ard as “pure”m onetary policy. In

particular, U .S. m onetary p olicy is carried out through

op en-m arket op erations that exchang e one form of

governm ent deb t (fiat m oney) for another (governm ent

bonds), leaving the overall level of outstand ing gov-ernm ent deb t unchanged . In A rgentina, by contrast,

the typical m onetary policy consisted of hand ing over

fiat m oney directly to the treasury, w hich used it to

finance its deficit and not to retire other form s of gov-

ernm ent deb t as in the U nited States. Thus, m onetary

policy in A rgentina has typ ically increased the overall

governm ent debt by expand ing the m oney base. It is

in this sense that A rgentina’s m onetary p olicy has

really b een a hidden form of fiscal policy.28 A bel and B ernanke (1992) provide an excellent, bal-

anced discussion of the business-cycle facts and their

consistency w ith R B C or K eynesian theories (see

especially S ections 11.2, 12.4, and 12.5).29 A recent paper by C rucini and K ahn (1996) show s

that tariffs can have a larger im pact on G D P than

generally b elieved. This is relevant in the light that

substantial im plicit or explicit changes in tariffs w ere

a usual ing red ient of the m any stab ilization prog ram s

im plem ented in A rgentina d uring the sam ple period .30 G avin and K ydland (1996) have recently rep orted a

related finding for the U nited States. They found that

real variab les in that country seem ed to have been

invariant to the changes in the cyclical behavior

ob served in the nom inal variab les after 1979. They

show ed that these ob servations can be g enerated by

a business-cycle m od el w ith im pulses to technolog y in

w hich m onetary policy affects the cyclical behavior of

nom inal variables b ut not that of real variables.

ReferencesA bel, A ndrew B ., and B en B ernanke (1992),M acro-

econom ics (R eading , M ass.: A ddison-W esley P ub lishing

C om pany).

B ackus, D avid, Patrick K ehoe, and Finn E. K ydland

(1995), “International B usiness C ycles: Theory and

Evidence,”in Frontiers of B usiness C ycle R esearch ,

ed . Thom as F. C ooley (Princeton, N J: Princeton

U niversity Press), 331–56.

C alvo, G uillerm o (1986), “Tem porary Stab ilization:

Pred eterm ined E xchang e Rates,”Journal of Political

Econom y 94 (June): 1319–29.

———, and C arlos A . Vég h (1993), “Exchange R ate-

B ased Stabilisation under Im perfect C redibility,”in O pen-

Econom y M acroeconom ics , ed . H . Frisch and A .

W orgotter (Lond on: M acM illan Press), 3–28.

———, and ——— (forthcom ing), “Inflation Stabilization

in C hronic Inflation C ountries,”in H andb ook of M acro-

econom ics , ed . John Taylor and M ichael W ood ford (N ew

York: N orth H olland).

C arrera, Jorge, M ariano Féliz, and D em ian Panigo

(1996), “C iclo Económ ico en A rgentina y B rasil,”in

A nales d e la A sociación A rgentina de E conom ía P olítica,XXXI R eunión A nual Vol. 6,(Salta, A rgentina).

C EPA L /EC LA—C om isión Económ ica para A m érica

Latina/Econom ic C om m ission for Latin A m erica (1991),

“Proyecto R evisión de las C uentas N acionales y de la

D istribución del Ing reso,”final report, D ecem ber.

C hristod oulakis, N icos, Sop hia D im elis, and Tryphon

K ollintzas (1995), “C om parisons of Business C ycles in

the E urop ean C om m unity: Idiosyncracies and R eg ulari-




ties,”Econom ica 62 (February): 1–27.

C rucini, M ario, and J. K ahn (1996), “Tariffs and A ggre-

gate E conom ic A ctivity: Lessons from the G reat D ep res-

sion,”Journal of M onetary Econom ics 38 (D ecem ber):

425 –67.

D irección N acional de C uentas N acionales (1996),

O ferta y D em and a G lob ales, 1980 –1995 , Secretaría deProg ram ación Económ ica, M inisterio de E conom ía y

O bras y S ervicios P úb licos (B uenos A ires, Sep tem ber).

Easterly, W . (1996), “W hen Is S tabilization Expansionary?

Evidence from H igh Inflation,”Econom ic P olicy 22

( A pril): 65–107.

FIEL—Fundación de Investigaciones Económ icas

Latinoam ericanas,D ATAFIEL (B uenos A ires, various

series from data b ank service).

G avin, W illiam T., and Finn E. K ydland (1996), “End og e-

nous M oney Supply and the B usiness C ycle,”Fed eral

R eserve B ank of C leveland W orking Pap er no. 96-05

(C leveland, July).

G ullickson, W illiam (1995), “M easurem ent of Productivity

G row th in U .S. M anufacturing ,”M onthly Labor R eview ,

(W ashington, D .C .: B ureau of Labor Statistics, July).

H eston, A lan (1994), “N ational A ccounts: A B rief R eview

of Som e P rob lem s in U sing N ational A ccounts D ata in

Level of O utput C om parisons and G row th S tud ies,”

Journal of Econom ic D evelopm ent 44 (June): 29 –52.

H od rick, R ob ert J., and E dw ard Prescott (1997),“Postw ar

U .S. B usiness C ycles: A n Em pirical Investigation,”

Journal of M oney, C red it, and B anking 29 (February):

1–16.

H offm aister, A lexander, and Jorge R oldós (1997), “Are

B usiness C ycles D ifferent in A sia and Latin A m erica?”

IM F W orking Pap er no. 97/9 (W ashing ton, D .C .: Inter-

national M onetary Fund , January).

———, and C arlos A . Vég h (1996), “D isinflation and the

R ecession-N ow -Versus-Recession-Later H ypothesis:

Evidence from U ruguay,”IM F S taff Pap ers 43 (June):355 –94.

Inter-A m erican D evelop m ent B ank (1995), “O vercom ing

Volatility,”in R ep ort on Econom ic and Social Prog ress in

Latin A m erica: 1995 (W ashing ton, D . C .: Johns H op kins

U niversity P ress for Inter-A m erican D evelop m ent B ank)

189 –256.

K am il Saúl, H erm an (1997), “C aracterización de las

Fluctuaciones C íclicas: U na A plicación al C aso

U rug uayo”(M ontevideo, U niversidad de la R ep úb lica,

U np ub lished dissertation).

K aufm an, M artin, and Fed erico S turzeneg ger (1996),

“Algunas R eg ularidad es d el C iclo E conóm ico A rgentino”

(B anco C entral de la R ep úb lica A rgentina, U np ub lished

m anuscript).

K iguel, M iguel, and N issan Liviatan (1992), “TheB usiness C ycle A ssociated w ith Exchang e R ate-B ased

Stabilizations,”The W orld B ank Econom ic R eview 6

(M ay): 279–305.

K ing , R ob ert, and Sergio R eb elo (1993), “Low Freq uency

Filtering and R eal B usiness C ycles,”Journal of Econom ic

D ynam ics and C ontrol17 (January–M arch): 207–31.

K ydland, Finn E., and Edw ard C . Prescott (1990),

“Business C ycles: R eal Facts and a M onetary M yth,”

Fed eral R eserve B ank of M inneapolis Q uarterly R eview

14:2, 3–18.

———, and ——— (1982), “Tim e to B uild and A ggreg ate

Fluctuations,”Econom etrica 50 (N ovem ber): 1345–70.

Lucas, R ob ert E. Jr. (1977), “U nd erstanding B usiness

C ycles,”C arnegie-R ochester C onference Series on

Public Policy 5, 7–29.

——— (1972),”Exp ectations and the N eutrality of

M oney,”Journal of Econom ic Theory 4 (A pril): 103–24.

M addison, A ngus (1995),M onitoring the W orld E conom y,

1820–1922 (Paris: D evelop m ent C entre Stud ies, O rgani-

zation for Econom ic C oop eration and D evelopm ent).

M endoza, Enrique (1995), “The Term s of Trad e, the R eal

Exchang e R ate, and Econom ic Fluctuations,”Interna-

tional Econom ic R eview 36 (February): 101–37.

R ebelo, Sergio, and C arlos. A . Vég h (1995), “Real Effects

of Exchang e R ate-B ased Stab ilization: A n A nalysis of

C om peting Theories,”N B ER M acroeconom ics A nnual,

125–74.

R einhart, C arm en M ., and C arlos A . Vég h (1995a),

"N om inal Interest R ates, C onsum ption B oom s and Lackof C redibility: A Q uantitative Exam ination,"Journal of

D evelopm ent Econom ics 46 (A pril): 357–78.

———, and ——— (1995b ), “D o E xchang e R ate-B ased

Stab ilizations C arry the Seeds of Their O w n D estruction?”

(U np ub lished m anuscript presented at the A m erican

Econom ic A ssociation m eeting , San Francisco, January

5–7, 1996).

———, and ——— (1994), “Estabilización en P aíses de



Inflación C rónica: La Evidencia Em pírica”(U np ub lished

m anuscript presented at the conference “Inflation

Stab ilization: The R ecent Experience in Latin A m erica,”

M ontevideo, U rug uay, A ug ust 8–9).

Sim s, C hristop her A . (1980), “C om parison of Interw ar

and Postw ar B usiness C ycles: M onetarism R econsid-

ered ,”A m erican Econom ic R eview 70 (M ay): 250–57.

Sturzenegger, Federico (1989), “Explicando las fluctua-

ciones del prod ucto en A rgentina,”Econom ica 35,

101–52.

Talvi, Ernesto, and C arlos A . Vég h (1996), “C an O ptim al

Fiscal Policy B e P rocyclical?”(U np ub lished m anuscript

presented at the S egund as Jornad as de Econom ia

M onetaria e Internacional, La Plata, Argentina, M ay 8–9,

1997).

Vég h, C arlos A . (1992), “Stop ping H igh Inflation: An

A nalytical O verview ,”IM F Staff Pap ers 39 (Septem ber):

626 –95.

Zarazaga, C arlos E. J. M . (1996), “Liberalization andR eg ulation B ack and Forth: A H istory of the Financial

System of A rgentina in the 20th C entury”(Federal

R eserve B ank of D allas, U np ub lished m anuscript).

kydland zarazaga 1997 businesscyclearg

Documents