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We thank without implicating Martin Grandes, Paul Masson, Nadina Mezza, Pablo Nicholson, and Thomas Reichmann for comments on an earlier draft of this paper, and Norma Caño at INDEC for providing us with Argentina’s foreign trade data. Groundwork for this paper was done while Ms. Falcetti was a summer intern at the IMF.
There exist remarkably few systematic studies on the estimation of foreign trade equations for Argentina. Besides earlier work by Diaz-Alejandro (1970), recent studies by Ahumada (1994), Reinhart (1995), and Senhadji (1998) have estimated standard long-run demand functions for Argentina’s exports using cointegration methods. The latter two authors, however, use panel data covering a large number of countries and devote little attention to the Argentine case.
These account for nearly 40 percent of Argentina’s exports. Other primary and agro-industrial products account for an additional 30 percent.
Note, however, that primary commodity exports to Brazil are left as part of this first group.
Although Argentina is a relatively large world producer of wheat and beef, for instance, in none of these markets is Argentina a price setter.
For a discussion of the pros and cons of distinct external competitiveness indicators, see Lipschitz and McDonald (1991).
A question arises as to the appropriate choice of the frequency of observations (daily, monthly or quarterly) and temporal window period (one quarter, a year or several years). For instance, under certain circumstances it can be argued that quarterly export performance is significantly affected by weekly or daily changes in the exchange rate (Gonzaga and Terra, 1997). In our case, however, since we are mainly concerned with medium-term fluctuations in exports and base the remainder of the analysis on quarterly observations, the use of quarterly changes in the RER over a one-year window appeared as a fair compromise.
I(1) variables can only be rendered stationary when first differenced in logs (or equivalently expressed in terms of percentage change). This is because the univariate autoregressive representation of such variable contains a unit root, which can only be eliminated by the first difference operator.
The procedure allows for the existence of up to n such vectors, where n is the number of I(1) variables in the system
Under the null hypothesis of no-cointegration, the distribution of such an F-statistic is nonstandard; so the usual critical values employed in classical statistical inference do not apply. The relevant critical bounds have been tabulated by Pesaran et al. (1996) and are provided in Table 3.
The optimal number of lags of the first-differenced variables can be determined by standard maximum log-likelihood based tests, such as the Akaike information criterion or the Schwarz Bayesian criterion.
In principle, this could be due to a simultaneity bias stemming from an inverse causality running from exports to the exchange rate. In other words, higher exports could lead to higher consumer prices or labor costs expressed in US dollar terms and hence to a negative association between exports and the relative price variable px/pc. Using instrumental variables, Ahumada (1994) concludes that such a simultaneity bias does not appear to be significant, and thus cannot account for the lack of statistical significance of current levels of the real exchange rate in the export equation.
The estimated coefficient on the kinked time trend for the 1990s yielded a rather low t-ratio while taking on the “wrong” sign, and was thus dropped from the reported regressions.
Because regression (A. 2) contains an intercept dummy defined as zero between 1980 and 1990, this test can only be computed for the post-1991:q1 period. Thus, we only report the results of the CUSUM test on (A. 1).
Not reported but available from the authors upon request.
Since Brazil has accounted for 85 to 90 percent of Argentina’s manufacturing exports to MERCOSUR, Brazil’s real GDP and consumer price index will be used as proxies for y* and p*, respectively. Quarterly figures for t* were obtained by interpolation from annual data on Brazil’s average external tariff as provided in Garriga and Sanguinetti (1995).
In contrast with the exports of traditional staples such as wheat and beef, domestic consumption tends to have a less significant bearing on manufacturing exports to MERCOSUR due to a variety of tax and tariff exemptions which lower the relative cost of exporting to neighboring countries relative to selling in the domestic market. Indeed, the inclusion of aggregate consumption yielded statistically insignificant coefficients in all the equations on Argentina’s manufacturing exports to Brazil.
As already noted, this will be proxied by Argentina’s real exchange rate with Brazil.
For a thorough discussion on the specification and statistical properties of VECMs, see Hamilton (1996).
It is possible that this reflects the inadequacy of our proxy to productive capacity in manufacturing which here is taken to be the aggregate capital stock.
It lacked statistical significant for both the level and first-difference equations. Indeed, inclusion of this variable in the error correction supply equation yielded a positive (though statistically insignificant at any conventional level) coefficient, contrary to the theory.
The statistical insignificance of the exchange rate volatility term in the equation on manufacturing exports to MERCOSUR, albeit surprising, echoes the findings of other empirical studies. Gonzaga and Terra (1997) find that the effect of real exchange volatility on Brazilian exports—a large share of which consist of manufacturing goods—is also statistically significant. Evidence for the European Union covering mostly manufacturing trade indicates that the effects of exchange rate volatility on trade are statistically significant but small (Dell’Ariccia, 1999).
Not reported here but available upon request from the authors.
Here it is important to note the difference between the theoretical concept of steady-state where an income elasticity of imports significantly above unity is ruled out by assumption (as it would entail explosive behavior of the share of imports in GDP), and the working definition of “long-run” underlying this paper. In the latter, long-run is simply defined as a time span covering nearly two decades (the 1980s and the 1990s). In the case of Argentina, this definition is not only more relevant for the purpose of current policy analysis, but also avoids the pitfalls of estimating steady-state relations on the basis of a data sample spanning over several decades which are subject to uneven data quality and the existence of major structural breaks.
Here we measure average import tariff rate as the ratio of total tariff revenues by total imports. Although this can be an inacurate proxy of the “true” protection costs (specially when certain import items are subject to quantitative restrictions as was the case in Argentina until the late 1980s), it has the advantage of being derived from observed data and appears to be the only measure of protection costs for which a consistent series is available on a quarterly basis over the entire 1980-98 period. For a discussion of different measures of tariff protection and evidence on the correlation between actual tariff revenues and official (or ex-ante) tariff rates, see Pritchett and Sethi (1994).
In the high inflation environment of the 1980s nominal interest rate were quoted on a monthly basis; so, the respective real rate was obtained by deflating the nominal figure by the one-month ahead actual inflation and the annualized. With the advent of macroeconomic stabilization in the 1990s, domestic lending institutions resumed quoting interest rates on an annual basis which were then deflated by the 12-month ahead inflation. Quarterly real interest rates were computed as arithmetic averages of the monthly rates.
Lags of the variables in levels were included in the regressors so as to reproduce the ARDL representation underlying the long-run estimates of Table 5. The autoregressive structure, selected by the Schwartz Bayesian criterion, added one lag of the (log) level of the dependent variable, two lags of the (log) level of real GDP and two lags of the real interest rate.
Consistent with the hypothesis of a fixed nominal exchange rate, zero inflation at home, and a trade basket weighted foreign inflation of 2 percent.
Which is not trivial given Argentina’s previous experiences with hyperinflation and high degree of real wage resistance.