# **5. General Performance Premia for Importers in Peru**

The results so far show very clear evidence of premia in the export performance of exporter-importers in Peru. As discussed in Section 1, imported intermediate inputs are important because they embody variety and higher quality and thus increase productivity for users, as microevidence has shown for several countries. In this section, we discuss some complementary evidence obtained for Peru on the importance of imported inputs for productivity based on firmlevel data from the Encuesta Economica Annual (EEA).<sup>8</sup> The EEA data is a useful complement to our main analysis using the panel exporter-level/importer-level customs data because it allows us to calculate more general measures of firm performance than those focusing just on the export market, for example firm productivity. But in addition to not providing nearly as much detail as our customs data does on exports and imports by Peruvian firms, the EEA data has other caveats which explain why we do not use it as our main data source. In particular, the EEA is not a panel data set covering all manufacturing firms in Peru, rather it has a census component for the largest firms and a sample component for the smaller firms which implies that firms are sampled randomly as discussed in Iacovone et al. (2015). As a result, it is not possible to trace firm performance over time, which is fundamental to answering the questions raised in this paper, for any but the largest manufacturing firms.

First, we estimate a variant of Eq. (1) for the cross-sections of manufacturing firms in Peru covered by the EEA over the 2008-2012 period where the dependent variable is a firm outcome measure, either employment, real output (domestic output plus exports), real capital, real capitallabor ratio, or labor productivity (all in logarithms).<sup>9</sup> In the case of labor productivity, the regression also controls for the real capital-labor ratio hence the results are proximate to those that would be obtained for a total factor productivity measure.<sup>10</sup> The corresponding regression results are shown in Table 4, focusing on all manufacturing firms and separately on firms in the agribusiness and apparel sectors.

> 8 Details on the cleaning and preparation of the EEA are provided in Iacovone et al. (2015).

> 9 Real output is measured as total output sold by the firm deflated by a 4-digit industry price deflator, real capital is constructed according to the perpetual inventory method and labor productivity is measured as value added reported in the EEA (total production minus costs of intermediate inputs (goods + services)) per employee, all defined as in Iacovone et al. (2015). Appendix Tables 3 and 4 show summary statistics for all the dependent and independent variables from the EEA data used in the analysis. 10 Given that the EEA data that we use consists of cross-sections of firms it is not possible to obtain firm-level total factor productivity measures based on production function estimation techniques such as those by Olley and Pakes (1996) or Levinsohn and Petrin (2003). Thus, the use of a labor productivity measure while controlling for the capital-labor ratio is the best possible alternative.

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