The remaining projections are determined by assuming that long-term trends in Peru remain constant and by performing steady state calculations. The labor share in the non-resource sector N = 0.49 is calibrated by adjusting the aggregate labor share proportionally in relation to non-resource GDP (see Loayza et al. 2022).<sup>7</sup> Using the calibration of Loayza ββ et al. (2022), the capital share in the mining sector ( )=0.84 is calculated with the natural resource rents shares ( ) from the Global Trade Analysis Project (GTAP), and averaged over 2004, 2007, 2011, and ii 2014. The tax rate in the resource sector, = 0.621 −γγ , is calibrated using data on government natural ii γγ resource revenues and resource GDP from the IMF’s World Commodity Exporters Dataset (IMF-WCE). For Peru, the = 0.62 is set to match the historical average in the last 20 years of resource revenues as a ττ<sup>NN</sup> share of resource GDP. Following the standard model of the LTGM-NR, we calibrate the fiscal rule like a Balanced Budget-Hartwick Rule, which implies a marginal propensity to invest of ττ<sup>NN</sup> . GDP for 2021 is taken from World Bank’s World Development Indicators (WB-WDI), in constant 2015 U.S. θθ= 1 GDP for 2021 is taken from World Bank’s World Development Indicators (WB-WDI), in constant 2015 U.S. dollars. In the absence of comprehensive information on GDP at the copper sector level, we proxy GDP in the copper sector by the exports of copper. For Peru, GDP in the copper industry is set to match the value of exports as a share of GDP in 2021. The export data is taken from the UN-Comtrade Database (UN-CT), which provides information on export value for all 11 commodities and all 56 countries, with a time series that usually starts in 2002.

As in the standard LTGM, the initial stock of capital-to-GDP ratio of 3.6 is calculated using the most recent observation from PWT 10.01. The initial capital stock is split across activities to equalize the initial marginal revenue product of capital across the copper and non-resource sectors.<sup>8</sup> In the resource sector, the reserves are calibrated using the initial stock of reserves in industry is taken from the U.S. Geological Survey Database (USGS) for mining industries, such as copper, gold, and iron. As a stock variable, initial ii reserves are set to match the most recent observation (usually 2017).

The model requires the paths of exogenous variables from 2021 until 2050, and we assume that the variables will follow recent trends in the long-term. Discoveries of natural resources are calibrated using data on annual production and reserves of the resource good , taken from the USGS. The time series of discoveries of good in period is computed as the change in reserves from period to plus production in period . In the baseline, the trajectory of discoveries of good ii from 2021 to 2050 is set to ii tt tt− 1 tt match the historical average over the past 15 years of 6.5 million metric tons (mt). tt ii The trajectory of copper prices is from Chile’s Advisory Committee projections for the Copper Reference Price 2023, which is a survey of 20 experts that publishes their expected prices of copper until 2032. We use the average of the 20 responses and convert it to real prices of 2015 in US$/mt. For the trajectory of prices between 2032 and 2050 we assume copper prices are constant at their 2032 value.

> 7 N P × G /G 0 where P is the share of labor compensation in GDP in period , taken from Penn World Table 0 10.01 (PWT10), and PP G is non-resource GDP in period PP . 8 Following Loayza et al. (2022), the initial capital stock in activity ββtt = ββtt PPtt PPtt ββtt must satisfy the following tt equations, tt PP tt 2021 2021 = 0 )G jj 2jj021 f NN+ 1 jj iijj )G 2021 + ∑ii )G 2021 (1 −γγ II where G II2021jj ≡ ~~�~~ pp̅2015jjpp̅tjj �GKK PP2021ii /YY denotes real GDI in activity (1 −ββ<sup>N</sup> PP ii , year NNii=1(1 −γγtt ; γγ0 = ββii<sup>N</sup> IIii . ff ii= 0, ... , NN

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