series that are known to be cointegrated. We then ensure that signs are consistent with theoretical predictions.

The set of fundamentals found to be driving the long-run exchange rate for Argentina includes: the terms of trade, productivity differential, trade openness, and foreign exchange reserves. The indicators are defined as follows:

- **REER:** data for the REER ( _reer_ ) is taken from the BIS (1994-2015) and appended using data from the IMF (1980-1993), where both series are based on a trade-weighted nominal effective exchange rate (foreign currency units per unit of domestic currency) and relative CPI price indices. For the period December 2007-October 2015, we adjust the REER ( _reer_adj_ ) to correct the domestic price level for cumulative inflation discrepancies between (lower) official statistics and (higher) inflation figures produced by PriceStats.

- **Terms of trade:** in the monthly analysis, IFS data on the world price of soybeans deflated by CPI in advanced economies ( _psoy_ )<sup>14</sup> is used as a proxy for terms of trade, stipulating a ‘commodity currency’ property of the peso based on soybean exports. In our annual analysis, we use a terms of trade index ( _tot_ ) that measures the ratio of export-to-import prices obtained from the WDI database.<sup>15</sup>

- **Productivity differential:** this variable captures the Balassa-Samuelson effect based on the divergence of productivity levels in the country’s nontradable and tradable goods sectors. In the monthly analysis we two simplistic measures: the ratio of consumer-to-producer prices relative to main trade partners<sup>16</sup> ( _cpi/ppi_ , potentially underestimated) and industrial production relative to Brazil ( _ip_rel_ , potentially overestimated), Argentina’s main trade partner.<sup>17</sup> To correct for potential mismeasurement, we also make adjustments that increase CPI/PPI (increasing the ratio by 30% over 2008-2015)<sup>18</sup> and decrease industrial production (using OJF estimated growth rates). In the annual analysis we use trade-weighted measures<sup>19</sup> of: (i) GDP per capita ( _ypc_ and _ypc_adj_ , adjusted for mismeasurement by applying PriceStats CPI index as a deflator) and (ii) a more refined measure of tradables-to-nontradables labor productivity differentials ( _tnt_ ) along the lines of Ricci et al. (2008).

> 14 This is also used in Tashu (2015) and MacDonald and Ricci (2003). We alternatively use world CPI as a deflator.

> 15 An export-to-import price index is not available at monthly frequency for the length of our sample. 16 The main trade partners considered are Brazil, the United States, and Germany, where weights are computed using time-varying trade shares.

> 17 We consider the internal price ratio as a measure of the relative price of tradables-to-nontradables, defined as the ratio of the consumer price index to domestic wholesale or producer price index (as suggested in the literature by Alberola et al., 1999). Other studies, as a rough measure in the presence of widespread price controls, have used either GDP per capita (Wang et al., 2007) or real GDP per capita at PPP (MacDonald and Ricci, 2003) relative to main trading-partner countries. At monthly frequency, industrial production is a good proxy for GDP per capita.

> 18 To the extent that CPI figures are underreported by more than PPI, we adjust the CPI/PPI ratio upwards over 2008-201, in line with an estimated long-run relationship between the two price indices.

19 Trade-weighted measures consider the trade share represented by Argentina’s five main trade partners over 1980-2014: averaging 19% for Brazil, 13% for the United States, 5% for Germany, 5% for China (5%), 4% for Chile. Whereas Brazil and China grew in terms of trade importance over the period, we see a decline in the trade share of the US and Germany. See Appendix Figure 1.

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