the balancing item in australia's balance of payments accounts: an impressionistic view

Applied Economics, 1996, 28, 1303—1311

The balancing item in Australia’s balance ofpayments accounts: an impressionistic view

DIETRICH K. FAUSTEN and ROBERT D. BROOKS*

Department of Economics, Monash ºniversity, Clayton 3168 and *Departmentof Economics and Finance, Royal Melbourne Institute of ¹echnology, Melbourne,Australia

The balancing item in the Australian balance of payments has been increasing inmagnitude and volatility, violating with increasing frequency internationally agreedacceptability criteria of smallness. This investigation examines the temporal evolutionof the balancing item, identifying structural breaks that are plausible a priori. It alsoexplores alternative data-driven and structural approaches to the diagnosis of theerrors and omissions in the statistical record.

I . INTRODUCTION

As one indicator of economic performance and well-being,balance of payments statistics are deemed to provide signalsabout likely directions of economic policy. In the Australiancontext the sensitivity of official reactions to newly releasedbalance of payments data is particularly acute in view of theprominence in public debate of the current account deficitand the foreign debt. Whether such prominence is justified isa matter for debate. Nonetheless, the fact of political prom-inence reinforces legitimate concern about the fundamentalreliability of the information assembled in the balance ofpayments accounts. Difficulties and pitfalls associated withdata collection and processing are well-known. A parti-cularly instructive illustration of their impact is the reportedglobal trade surplus of some $80 billion.

Balance of payments outcomes are the aggregate conse-quence of individual choice. As such, they provide no causefor policy activism and intervention (for example, Pitch-ford 1990). Analytical warnings against precipitate policy ac-tivism are reinforced by the tentative nature of newly releaseddata. Along with other core national statistics, balance ofpayments data are revised considerably after initial publica-tion. This fact should counsel circumspection in the responseto the initial release of such figures. Just the same, releases ofnew data of known unreliability dominate the news and inspirecountless column inches of commentary. Insofar as policymakers do not invariably turn a deaf ear to exhortations by themedia, these journalistic expositions augment the politicalsignificance of the relatively coarse quantitative information.

0003—6846 ( 1996 Routledge

Clearly, balance of payments statistics, and their reliabil-ity, are matters of public interest. Their importance in thepublic and policy arena is, ipso facto, transmitted to thebalancing item because that statistic is generated by thefactual and systemic imperfections, the errors and omissions,that permeate the balance of payments statistics.

II . THE BALANCING ITEM

The logistics and complexities of data collection and pro-cessing imply that, in practice, transactions are recordedincorrectly (‘errors’) and some transactions are not recorded atall (‘omissions’). The net balance of errors and omissionsconstitutes the balancing item. Its particular value is generatedby the accounting conventions of double-entry bookkeeping.

The balancing item can be interpreted in different ways,and its analytical content and meaning vary accordingly.From the perspective of cross-border transactions activity,the equivalence-in-exchange constraint attributes theemergence of the balancing item essentially to the fact thatthe records of the financial and the real sides of any giventransaction are procured from fundamentally differentsources. Alternatively, recognition of the nexus between netnational saving, current account balance, and nationalwealth formation suggests that the balancing item may besymptomatic of mistakes in the documentation of the pro-cess of national wealth accumulation.

Non-zero entries for the balancing item illustrate theunsurprising fact that the ‘real world’ is not a perfect place.

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1304 D. K. Fausten and R. D. Brooks

Recognition of this condition presumably accounts for thecontinued allocation by national statisticians and interna-tional institutions of substantial resources to the refinementof national accounting concepts and systems. At issue, how-ever, is not the fact, but the degree, of imperfection. Insofaras ‘small’ balancing items1 document the manifest impreci-sion of national accounting systems, they are ‘acceptable’.By the same token, ‘small’ net errors are compatible withvery large absolute errors and omissions on each side of theledger. Since ‘small’ balancing items may disguise quitesubstantial mistakes, they are not invariably innocuous. Ifthe errors wash out largely, then the containment of themagnitude of the net distortion may justify a degree ofequanimity. But the fortuitous offset between misrepresen-tations on the credit side and on the debit side need not besystematic or structural. Random shocks can easily destroythe pattern of mutual offsets, and ‘small’ balancing items cansuddenly explode without any change in statistical proced-ure or economic behaviour.

If errors and omissions are driven by a random process,then the time series of balancing items is characterized byalternating signs. Conversely, persistent overrecording ofdebits and underrecording of credits (and conversely) primafacie indicates systematic measurement and reportingerrors. In practice, size as well as sign of balancing item datacontain ample scope for ambiguous signalling. Hence, theproviso in the official assessment that ‘[t]he size of thebalancing item provides an objective but limited measure ofthe accuracy of the balance of payments accounts’ (ABS,1990, p. 10, emphasis added) is entirely apposite.

III . DESCRIPTIVE ANALYSIS OF THEBALANCING ITEM INTHE AUSTRALIAN BALANCEOF PAYMENTS

Plots

Casual inspection of the time series of the quarterly balanc-ing item in the Australian balance of payments (Fig. 1)reveals a notable increase in the late 1970s, and a large jumpin the mid-1980s, in the variability of the variable, as well asa preponderance of large negative values during the latterperiod.

The dominance of negative values of the balancing itemsuggests persistent underrecording of debit transactions oroverrecording of credits. This feature is consistent with a,presumably inadvertent, ‘guilding-of the-lily’ syndrome thatgenerates excessively favourable balances of recorded trans-actions.

1As a rule of thumb, contained in the IMF Balance of Payments Manutoo big if it exceeds 5% of the (absolute) sum of gross merchandise2Assuming that the various transactions categories are structurally

Fig. 1. BoP Australia: balancing item 1959:3—1992:3 ($m)

The apparent increase in variability of the balancing itemmay reflect a similar increase in the variability of the truebalance of payments data, as well as shifts in the importanceof different transactions categories,2 and may indeed becommon to all industrialized countries. The time pattern ofinstitutional changes adds weight to the intuitive plausibil-ity of these explanations: a gradual secular shift from cur-rent transactions (‘leads and lags’) to capital transactions(‘hot money’) in response to the liberalization throughoutthe 1970s of world financial markets, together with thederegulation of Australian financial markets in the mid-1980s. At the same time, country-specific traits and theparticular timing of financial deregulation in Australia, inturn, may contribute to an explanation of the noticeabledifference in the time pattern of the Australian balancingitem compared to corresponding time series for Germany,Japan, UK, and the USA (see Fig. 2).

A more informative perspective on the temporal evolu-tion of errors and omissions in international transactionsmay be gleaned from relating the balancing item to the twomajor categories of transactions. If errors and omissionsrepresent systematic errors in recording current or capitaltransactions, respectively, then the absolute size of the bal-ancing item would be expected to fluctuate with the volumeof either type of transactions. Deflating the balancing itemalternately by current account and by capital account trans-actions would smooth such volatility. A constant indexwould lend support to the conjecture that the dominantsource of the balancing item is sector-specific, involvig fac-tors such as collection and processing of data from eithersector, and systematic discrepancies between alternativesources of data. Importantly, such evidence would be

al and endorsed by the ABS (1988, 29), a balancing item is consideredimports and exports.stable but display different dynamic properties.

¹he balancing item in Australia’s balance of payments accounts 1305

Fig. 2. ¹he BoP balancing item in international perspective

compatible with structural stability in the various factorsthat contribute to the errors and omissions.

Fig. 3 plots current account and capital account indices ofthe balancing item. The current account balance (CA) andthe capital account balance (KA) are the deflators in panels(a and b, respectively). The balance on current or capitalaccount is not the appropriate deflator when the errors varywith the total volume of transactions. Hence, the remainingpanels plot alternative indices of the balancing item: inpanels (c) and (d) total transaction volumes on current andcapital accounts (CATT and KATT),3 while panel (e) relatesthe balancing item to total merchandise flows (CATM),noting the IMF’s 5% criterion of ‘smallness’.

On first impression, Fig. 3 does not project the samesecular increase in the variability of the balancing item thatdominated Fig. 1. To that extent it supports the hypothesisthat there is some systematic misrecording of the size oftransactions. Casual inspection of panel (a) reveals a more

3CATT and KATT represent the absolute sums of total credit and d

stable pattern of the balancing item as a proportion of thecurrent account balance, abstracting from the handful ofmajor outliers, than the raw balancing item did. At the sametime, it provides instructive insight into the quantitativesignificance of the balancing item in terms of the currentaccount balance. Values of Balitem/CA((!1) imply thatthe correction of errors and omissions, presuming they areassociated with current transactions, would transform a re-ported current account deficit into a surplus, and converse-ly. Eight observations in the sample provide scope for suchpotential ‘inversions’ or switches. The most significant casesare 1964:1 and 1975:2 when the balancing item was of theorder of four times the current account balance (!4.25 and!3.96, respectively).

Deflating the balancing item by the balance on capitalaccount (panel b) does not provide much useful incrementalinformation. The time series is dominated by two largeoutliers (1980:1, 1986:4). Both are associated with atypically

ebit transactions on current and on capital accounts, respectively.


Fig. 3. BoP Australia: balancing item deflated by balances on current and capital accounts (panels a and b), total transactions on current andcapital accounts (panels c and d), and by total merchandise flows (panel e)

small net balances on capital account. Indeed, these outliersdisappear if the balancing item is deflated by the totaltransactions volume on capital account (panel d), only to bereplaced by another two dominant outliers (1960:3 and1990:2). Their removal generates a plot (Fig. 4.a) that looks

very similar to the (negative) pattern of the current accountindex in panel (3.a). This apparent complementarity of cur-rent and capital account transactions does not transpirewhen the series is deflated by total transactions volume(compare Fig. 4.b with Fig. 3.c). A notable difference is


Fig. 4.

Table 1. First four moments for the data

Mean »ariance Skewness Kurtosis

BI 37.362 987.219 1.143 10.714BI/CA !0.148 0.739 !2.697 12.863BI/CATT 0.056 0.001 !0.034 3.585BI/CATM 0.007 0.003 !0.067 3.978BI/KA !1.137 11.337 !8.633 78.141BI/KA* 0.011 1.769 !0.578 8.985(outliers removed)BI/KATT !0.033 1.537 !5.320 41.207BI/KATT* 0.033 0.946 !5.532 57.331(outliers removed)

that the latter series contains more absolutely large observa-tions.

The information depicted in Fig. 3 resounds with warningbells about the magnitude of the balancing item. The ratioof Balitem to total transactions on current account (CATT)fluctuates between 0.11 and !0.09. These values signifi-cantly exceed the IMF’s ‘rule of thumb’ which places thecritical value at 5% of total merchandise transactions. Thedeflator in panel (c) constitutes a substantially weaker cri-terion. Just the same, in more than 20% of the observationsthe recorded balancing item assumes a value larger than 5%of total current account transactions. The default rate jumpsto 38% when the IMF criterion (0.05 of CATM) is adopted.The balancing item as a proportion of total merchandisetransactions is plotted in panel (e), together with the $5%‘acceptability’ band. As many as 51 observations fall outsidethis band, with values ranging from !0.14 to #0.18.

Descriptive statistics

An additional method of descriptive analysis emphasizesstatistical properties of the data set. The first four momentsof the distribution of the balancing item for the raw and thedeflated series are reported in Table 1, and the first twelveautocorrelations for each of the series in Table 2.

The data shows a large degree of non-normality, largelyin the form of excess Kurtosis. Some residual autocorrela-tions (with values greater than 0.17) are statistically signifi-cant. However, the Q statistics indicate that the full sets ofautocorrelations for each series are not statistically signifi-cant. The spikes in the autocorrelation function at whichsignificant values occur constrain the feasibility of con-structing a parsimonious model. Furthermore, the nature ofthe model would tend to vary with the alternative specifica-tions of the dependent variable. Such a lack of robustness


Table 2. Autocorrelations for the data

BI BI/CA BI/CATT BI/CATM BI/KA BI/KATT(outliersremoved)

(outliersremoved)

o1

!0.239 !0.216 !0.113 !0.113 0.026 0.166o2

0.045 !0.101 0.022 0.017 !0.056 !0.015o3

0.018 0.079 !0.011 !0.013 !0.076 !0.014o4

0.247 0.307 0.133 0.138 0.058 !0.008o5

!0.338 !0.361 !0.109 !0.138 !0.019 0.032o6

0.215 0.123 !0.001 0.000 !0.489 0.030o7

!0.425 !0.337 !0.170 !0.176 0.032 !0.009o8

0.084 0.084 0.104 0.086 0.094 0.000o9

!0.151 !0.135 !0.056 !0.068 0.024 !0.002o10

0.083 0.085 0.172 0.178 !0.005 0.002o11

!0.223 !0.244 !0.021 !0.025 0.000 !0.001o12

0.038 0.061 0.037 0.050 0.058 !0.005Q

1219.0 17.7 16.7 18.4 9.0 4.6

(Box-Pearce)

would conflict with the presumption that the data are drivenby a stable process. Specifically, it suggests the possibilitythat errors and omissions are difficult to model as a functionof their own past history.

There is little prospect of fitting a simple parsimonioustime series model to the balancing item. At the same time,the statistical data do show some apparent structure. Analternative, more complex, modelling strategy appears to berequired for the exploration of that structure.

This descriptive investigation shows the existence ofprima facie grounds for review and for systematic modellingof the balancing item in the Australian balance of payments.Identification of the relevant structural characteristics of theincidence of errors and omissions would usefully inform andguide the review process.

IV. ANALYTICAL INVESTIGATION OFTHE BALANCING ITEM: SOMETENTATIVE STEPS

Since the raison d’eL tre of the balancing item is to validateprior accounting constraints by offsetting any discrepanciesbetween the balances on current and capital accounts, thereis no analytical presumption about its sectoral origin.The errors and omissions may equally be generated by cur-rent account transactions as well as by capital accounttransactions. One relevant task is to ascertain whether oneor the other type of transaction systematically exerts a pre-ponderant influence on the balancing item. Such informa-tion could be helpful, not only in improving the quality ofthe statistics but also in informing the design of economicpolicy. Given the acceptance of policy activism, the design ofpolicy measures must take into account the disparate natureof the dominant influences over, and determinants of, cur-

rent transactions and capital transactions. The balancingitem has been shown to attain magnitudes sufficient toswitch the sign of component account imbalances. Offend-ing imbalances can, in principle, turn out to be fictitious, theproduct of errors and omissions. Hence, policies designed tocorrect such phantom imbalances could be severely de-stabilizing.

A fairly widespread, but largely untested, workinghypothesis is that the ‘nature’ of the balancing item hasundergone secular change. It has traditionally been domin-ated by the attempts of traders to squeeze out profits from‘leading or lagging’ cross-border payments for goods andservices, whereas in the contemporary setting the balancingitem is dominated by deficiencies in the recording of capitalaccount transactions. With the progressive deregulation ofexchange controls and the integration of world capital mar-kets, fungible funds have become the dominant vehicle forsqueezing out profits. Retrospectively, these make the re-turns to ‘leads and lags’ look rather modest by comparison.Deficiencies in the recording of transactions are com-pounded, if not dominated, by widening gaps in the report-ing of transactions. Portfolio transactions increasingly tendto elude statisticians because of the continually evolvingnature of transactions arrangements in the direction ofsecuritization, derivatives, and other less tractable off-balance sheet positions.

Analytical exploration of the sectoral origin of the balanc-ing item can follow various different routes. One possibilityis a ‘data-driven’ approach that constitutes an analyticallymore rigorous extension of the descriptive investigationpursued above. It emphasizes the data itself, and attempts toexplain, with the help of regression-based methods, thebalancing item in terms of other balance of payments statis-tics. Appropriate manipulations and diagnostic tests shouldshed some (illuminating) light on the fundamental nature


and determinants of the balancing item and, thus, provideguidance for attempts to improve the quantitative reportingof external transactions. Preliminary experiments (reportedbelow) have provided some useful cues and encouragementfor further analysis.

An alternative approach focuses on analytical priors andtests these against the data. Suitable models of economicstructure can be derived from the micro or macro domain.They might emphasize the role of relative prices and otherincentives for transactors to vary their behaviour, or facetsof macro-structure such as the national savings-investmentrelation or the process of wealth accumulation. Method-ologically, this approach also utilizes regression methods,but it tests behavioural variables embedded in a structuralmodel instead of the statistics as explanators.

The third approach utilizes pertinent existing findingsfrom different contexts and objectives, and explores theirimplications in the present setting. Relevant research effortsinclude the supranational investigations into the ‘black hole’that appears to absorb each year some 80 billion dollarsworth of global transactions in goods and services. TheIMF-sponsored inquiry (IMF, 1987) identified prominentirregularities in the recording of particular types of transac-tions that include, most importantly, cross-border incomeflows. Other error-prone transaction classes are unrequitedtransfers, portfolio investments, and services. In the presentcontext the object would be to examine the significance andexplanatory power of the IMF-identified transactions typesfor the temporal behaviour of the Australian balancing item.As a side-benefit, such an investigation might throw somelight on the contribution to the global export surplus oftransactions involving Australia.

Analytical statistics: data-driven regressions

Difficulties with this type of approach are illustrated in thecontext of the following experiment. Using quarterly dataover the period 1959:4 to 1992:3, a preliminary regressionwas run of the balancing item (BI) on the gross transactionsflows of the main components of the balance of payments.The results are reported in Equation 1:

BI"!99.916#0.307GDS!1.451SER(0.518) (2.593) (2.813)

#1.283INC!0.784ºR¹!0.064GG(5.455) (0.611) (2.691)

#0.250RB!0.351POR¹!0.018DIR(2.267) (5.048) (1.409)

RM 2"0.301 (1)

4Where z5"CA2 or z

5"KA2, the balances on current and on capit

The definitions of the variables are as follows: GDS — mer-chandise trade; SER — services; INC — income payments;ºR¹ — unrequited transfers; GG — general government; RB— Reserve Bank; DIR — direct investment; POR¹ — portfolioinvestment. t-statistics for the hypothesis that the coeffi-cients equals zero are given in parentheses below eachcoefficient estimate.

Tests for the joint significance of the determinants werecarried out by means of F-tests. These tests suggested thatthe current account variables (GDS, SER, INC, ºR¹)have a role to play in the determination of the balancingitem. Furthermore, those tests indicate that the capitalaccount variables (GG, RB, POR¹, DIR) also affectthe balancing item. Given the relevance of the currentaccount variables it seemed plausible to assimilate theseinto an ‘omnibus’ variable that represents the entirecurrent account effect. For instance, the componentmerchandise trade and services variables were aggregatedinto an amalgam ‘goods’n services’ (GNS). On the capitalaccount the official components (GG and RB) and thenon-official components (DIR and POR¹) were aggregatedinto separate composites. Pushing aggregation stillfurther, an examination was undertaken of comprehensiveaggregates such as all current account transactions(CA¹¹), all capital account transactions (KA¹¹), and,finally, all transactions (on the primitive assumption thatthe incidence of errors and omissions is distributed insome stable pattern across all entries in the balance ofpayments accounts). These amalgams imply sets of linearrestrictions of the coefficients in Equation 1. Examination ofthe validity of these restrictions yielded overwhelminglynegative results. In all instances, F tests rejected the restric-tions, suggesting that these various aggregates are inappro-priate explanators.

While Equation 1 has a reasonable fit (RM 2"0.301) itsdiagnostics are unsatisfactory. Autocorrelation is indicatedby the highly significant Ljung—Box test statistic (Q

4"

33.437). Heteroscedasticity and non-normality also appearto be present in the data set. Breusch—Pagan LM tests of theform4 p2

t(1#jz

t) proved significant, and a highly significant

value of 518.129 was obtained for the Jarque—Bera teststatistic.

In an attempt to neutralize the autocorrelation problemthe dependent variables were lagged. These specificationsdid not produce any useful results because the lagged depen-dent variables generally were not significant. As an alterna-tive strategy to adjust for heteroscedasticity the data wasscaled by the current account balance (dividing through byCA). The results from the Breusch—Pagan tests providedsome justification for this procedure. Equation 2 reportsthose regression results where all variables are expressed asa proportion of the current account balance (the ‘ratio-

al accounts, respectively.


variables’ are identified by the suffix ‘R’):

BIR"76.330!0.267GDSR#0.792SERR(3.223) (4.352) (2.784)

#0.504INCR!0.476ºR¹R!0.116GGR(2.003) (0.878) (3.035)

#0.059RBR!0.044POR¹R(1.464) (0.471)

#0.045DIRR(1.632)

RM 2"0.268 (2)

Scaling causes deterioration in the fit of the estimatingequation, compared to the raw balancing item regression inEquation 1, but it improves its diagnostics: corrected RM 2declines to the value of 0.268; autocorrelation is virtuallyeliminated (Ljung—Box Q

4test statistic declines to 8.462);

heteroscedasticity also appears to be solved since theBreusch—Pagan test is no longer significant; but non-nor-mality persists as indicated by the continuingly significantvalue of the Jarque—Bera test statistic (130.418). Non-nor-mality is known to affect the size and power properties ofstandard econometric tests in a variety of ways. This, inturn, increases the complexity of interpreting test results,and compromises confidence in any particular interpreta-tion pari passu.

Instead, the search was continued for some analyticallyrobust insights into the nature of the balancing item byconsidering a major source of distortion that may be pro-vided by structural instability. Obvious structural shifts inthe balancing item could be associated with the systemicchanges in the global monetary order, as well as with de-regulation and liberalization by Australia of its trade andpayments in the home market and across borders. ChowF tests and Ashley Stabilogram tests provided support forthis conjecture by identifying three possible sub-periods:1959.4—1971.3, 1971.4—1983.3, and 1983.4—1992.3. This tem-poral decomposition tailors nicely with the a priori hypo-thesis about the structural significance of changes inthe global monetary order and financial deregulation inAustralia. Estimation results for the first subperiod showvery little explanatory power. This may be simply the conse-quence of the lack of variation in the dependent variableduring this time period (as evidenced in Fig. 1). For the twolater subperiods useful results were obtained for both theraw version and the scaled specification of the estimatingequation (BI and BIR, respectively). The results are parti-cularly strong for the middle period (Equations 3 and 4), butdeteriorate again for the final post-financial-deregulationsubperiod. The empirical support for structural shifts ex-poses the limitations of the statistical approach because itsuggests that exclusive reliance on statistical properties isunlikely to generate robust explanations of the balancing

item.

BI"!0.364#0.159GDS!0.632SER(2.444) (1.556) (1.428)

!0.955INC#3.564ºR¹!0.185GG(2.270) (3.108) (1.126)

#0.226RB!0.324POR¹#0.063DIR(2.176) (3.816) (0.998)

R1 2"0.369 (3)

BIR"0.180#0.008GDSR#0.104SERR(2.187) (0.075) (0.285)

!1.119INCR#1.370ºR¹R!0.822GGR(2.603) (1.291) (4.945)

!0.054RBR#0.027POR¹R#0.324DIRR(0.625) (0.180) (3.293)

R1 2"0.638 (4)

As a concrete illustration, consider the results for the sub-period 1971:4—1983:3. These show no evidence of autocorre-lation in the regression of the raw balancing item (Equation3), and its residuals are normally distributed. Similarly,positive diagnostics are generated by the scaled estimate(Equation 4): absence of autocorrelation and heteroscedas-ticity, and normally distributed residuals. However, therobustness of these results is not confirmed in the sub-sequent period. The fit of this specification deterioratedduring the following decade.

The ‘impermanence’ of the imputed structure reinforcesreservations about the general applicability of the specifica-tion and the associated results that were obtained for thetumultuous subperiod. That subperiod is bounded, approxi-mately, at the beginning by the Smithsonian agreement andat the end by the anticipated decision to float the Australiandollar. From this perspective, it is not entirely surprisingthat results obtained for such a period are short on secularstability and, therefore, may lack general validity over time.What is surprising, however, is that the investigation didsucceed in revealing any systematic patterns during thisperiod that stand up to the scrutiny of reasonably exactingdiagnostic tests and criteria.

V. CONCLUSION: WHERE TO NEXT?

The basic message of the descriptive investigation of errorsand omissions in the Australian balance of payments statis-tics is positive: the balancing item is not a trifling issue thatcan be classified as ‘small’ on the basis of generally acceptedcriteria. Whatever the factors that are responsible for itsoccurrence, they do exert a nontrivial influence on thecompilation of an important set of national statistics. Thepotential significance of this influence is magnified by thesensitivity of economic policy to quantitative informationabout Australia’s external economic performance. A casual


investigation indicates that errors in the reported data have,at times, been sufficiently large to invert the sign of theimbalance on current account. Such episodes are not re-assuring because they may impose unnecessary welfare costsif they cause policies to move in the ‘wrong’ direction. At thesame time, appeals to the virtues of benign neglect arepreempted by the fact that the IMF’s internationally en-dorsed rule-of-thumb for ‘acceptable’ balancing items hasbeen transgressed on average in more than one out of everythree quarters of the 33-year period of investigation.

One relatively compelling empirical result of this prelimi-nary investigation is that purely statistical explanations,such as simple time series modelling, are unlikely to providea satisfactory explanation of the behaviour over time of thebalancing item. This result is entirely consistent with a prioriexpectation. At the same time, it does point towardsa methodological approach that is more comprehensivethan purely data-driven explorations. For instance, we in-vestigated whether the recorded time pattern of the maincomponent accounts of the balance of payments was likelyto provide an explanation. A positive finding would beconsistent with the hypothesis that recording mistake con-stitute a major source of the balancing item. The resultsclearly show this not to be the case.

Accordingly, we investigated the potential role of eco-nomic influences on the time pattern of the balancing item.Such influences include the exchange rate, as a relative pricethat affects all cross-border transactions, and the extent ofeconomic openness. To the extent that the degree or natureof economic interaction between the domestic economy andthe rest of the world changes, shifts or breaks would beexpected in the behaviour of the balancing item. This con-jecture is consistent with the earlier discussion of volatilityin the balancing item. Growth from the early 1980s in thevolatility of the balancing items for Australia, Japan, theUK, and the US occurred at a time of acceleration in thepace of global integration of financial markets. In an at-tempt systematically to model economic influences, someprimitive experiments were conducted. By way of capturingsome of these factors, we included among the regressors thesquared difference of the TWI, as a measure of exchangerate volatility, and the ratio of total trade to GDP, as anindex of the degree of economic openness. These particularproxies are experimental. No claims are made for theirintrinsic validity or superiority over alternative specifica-tions. Either way, the experiments were inconclusive.

An alternative direction of the investigation focused onthe specification of the dependent variable. While scalingthe balancing item appears to be useful, it is not clear thatthe current account balance is the most appropriate scalar.Balance of payments statistics are assembled as part of anintegrated programme of compilation of national economicstatistics. The balancing item, consequently, does not reflectsolely the errors and omissions of a strictly segregated set ofstatistics of cross-border transactions. Rather, it constitutesa composite of imprecisions that originate in the variousregions of the statistical data set. Accordingly, it might beappropriate to scale the balancing item by GDP on thebasis of the simplistic rationale that statistical mistakes arecorrelated with the numerical magnitude of the relevantvariables. None of these experiments, however, generatedany significant improvement in the results.

The manifest statistical ‘problem’ remains immune to theobstacles encountered in the preliminary investigations. Thepersistence of the problem sustains and, indeed, consoli-dates the prima facie case for the need for constructiveinvestigation. The main, albeit so far elusive, prize of theexercise is improvement in the quality of the statistics and,consequently, in the quality of policy formulation that isbased on those improved statistics.

ACKNOWLEDGEMENTS

Financial support from the Australian Research Council,constructive research assistance from Ken Anderson andSanchia Templar, and helpful comments by an anonymousreferee are gratefully acknowledged.

REFERENCES

Ashley, R. (1984) A simple test for regression parameter instability,Economic Inquiry, 22, 253—68.

Australian Bureau of Statistics (1988) Balance of Payments: Sum-mary of Concepts, Sources, and Methods, Cat. No. 5351.0.

Australian Bureau of Statistics (1990) Balance of Payments Austra-lia, June Quarter (1990), Cat. No. 5302.

International Monetary Fund (1987) Report on the ¼orld CurrentAccount Discrepancy (Washington, DC, September).

Maddala, G. S. (1992) Introduction to Econometrics, 2nd ed,Macmillan, New York.

Pitchford, J. (1990) Australia’s Foreign Debt: Myths and Realities,Allen & Unwin, Sydney.

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the balancing item in australia's balance of payments accounts: an impressionistic view

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