A Balance-of-Payments-Constrained Growth Model for a Small Commodity Exporting Country: Argentina Between 1971 and 2016

ABSTRACT

We study the balance of payments (BOP) as a constraint on economic growth, focusing on Argentina’s economy between 1971 and 2016. The data show that Thirlwall’s balance-of-payments-constrained growth model cannot explain Argentina’s average growth during this period, which witnessed high growth in the terms of trade. We expand Thirlwall’s model based on recent empirical indications that exporters set their prices in foreign currencies. Thus, we show new ways in which the terms of trade and real exchange rate impact the growth rate compatible with the BOP equilibrium. While prices affect the growth rate compatible with the BOP equilibrium mainly through changes in the original model’s quantities, the proposed extension finds a stronger direct effect of the terms of trade. Through the extended model, we find that the weak and strong tests of Thirlwall’s Law are not rejected. Further, we show the consistency of the results regardless of the assumed country size or presence of structural economic breaks. Consequently, we argue that prior literature was inconclusive for Argentina as it did not consider invoicing of international trade in foreign currency, thus disregarding the full effect of the terms of trade and real exchange rate on growth compatible with the BOP equilibrium.

KEYWORDS:

• Balance-of-payments-constrained growth
• thirlwall’s law
• terms of trade
• Argentina
• real exchange rate
• currency invoice

Disclosure statement

No potential conflict of interest was reported by the author(s).

D ata a vailability s tatement: The data used in this study are openly available from

Arklems + LAND Project Database. 2020 [in Spanish]. https://arklems.org/. Accessed 25 April 2020.

Argentina’s National Institute of Statistics and Censuses (INDEC) [in Spanish]. https://www.indec.gob.ar/. Accessed 21 August 2018.

Board of Statistics of the Province of San Luis. http://admin.estadistica.sanluis.gov.ar/estadisticaasp/Paginas/Pagina.asp?PaginaId=76 Accessed: 21 August 2018.

Bruegel Datasets. 2020. ‘Real Effective Exchange Rates for 178 Countries: A New Database’ (dataset). Bruegel. Accessed 5 December 2020. https://www.bruegel.org/publications/datasets/real-effective-exchange-rates-for-178-countries-a-new-database/

Central Bank of the Republic of Argentina (BCRA). ‘Índices de Tipo de Cambio Multilateral’ (dataset) [in Spanish]. BCRA. Accessed 5 December 2020. http://www.bcra.gob.ar/PublicacionesEstadisticas/Indices_tipo_cambio_multilateral.asp

Maddison Project Database. 2018. Bolt, J., R. Inklaar, H. de Jong and J. Luiten van Zanden (2018). ‘Rebasing “Maddison”: new income comparisons and the shape of long-run economic development’, Maddison Project Working Paper 10. https://www.rug.nl/ggdc/historicaldevelopment/maddison/releases/maddison-project-database-2018. Accessed 28 November 2018.

Ministry of Economy of the Republic of Argentina Database. https://www.economia.gob.ar/datos/. Accessed 20 August 2019.

Notes

1. For empirical purposes, Perraton (2003) suggested two ways to test Thirlwall’s Law: first, the supposed weak version (Eq. 8) where exports are treated as exogenous variables using observed data; and second, the strong version in which the exports function must be estimated and is used as an endogenous variable to the realization of other variables. We discuss this topic deeper in the empirical analysis.

2. Following Dávila-Fernández and Amado (2015), the model can be considered as a three-sector small-country model (non-tradable sector, export sector, and import sector). In this framework, domestic, export, and import prices can differ.

3. We estimate this equation in levels using co-integration techniques. We do so to properly estimate the long-run relationship between the variables described in equation (21) and to be consistent with similar papers estimating the import demand function for Argentina, as in Ahumada and Cornejo (2015).

4. In addition, in Table 10, we present comparative BPCG estimates using both RER, in its two versions, and REER.

5. We use the same elasticities to calibrate each model.