Rossi-Hansberg 2015; Caliendo, Monte and Rossi-Hansberg 2017; Spanos 2016), Danish data (Friedrich 2016), Swedish data (Tag 2013), and Portuguese data (Caliendo, Mion, Opromolla and Rossi-Hansberg 2016). The only application for developing countries is Cruz, Bussolo, and Iacovone (2016), who study internal firm reorganization and export performance in Brazil. While Chile is at the low spectrum of developed countries, and it is therefore not a developing country, this experience and the evidence gathered here illustrate the possibilities that export opportunities offer for the demand of skills and tasks for developing countries down the road. Our paper is thus a contribution to this incipient empirical literature.

The rest of the paper is organized as follows. In section 2, we introduce the data, we present a set of stylized facts on exports and the demand for skilled tasks and we perform a detailed formal regression analysis. In section 3, we discuss our results in terms of the theoretical literature. Section 4 discusses extensions and concludes.

# **2 Exporting Firms and The Demand for Skilled Tasks**

In this section, we study the most salient facts concerning the link between exporting firms and the demand for skilled tasks in Chile. We first describe the data and present the basic correlations between skills, tasks, and exports. Next, we turn to a detailed causal empirical analysis based on instrumental variables regressions.

We use two sources of data, firm-level data and customs records. The firm-level data come from the Encuesta Nacional Industrial Anual (ENIA), an annual industrial census run by Chile’s Instituto Nacional de Estad ́ıstica that interviews all manufacturing plants with 10 workers or more. The ENIA is a panel. The customs data provide administrative records on firm exports by destination. We manually matched both databases for the period 2001–2005. As a result, we built a 5-year panel database of Chilean manufacturing firms.

The data have several modules. The main module contains information on industry affiliation, ownership type, sales, exports, input use, imports of materials, workers and wages. Industry affiliation is defined at the 4-digit ISIC Revision 3 level, which totals 113 industries.

We are mostly interested in the employment information. The data on workers are presented at detailed categories, which allows us to explore the demand for different skills and tasks. To do this, we base our empirical analysis on recent models of international trade where goods are produced with tasks using assignment rules (Acemoglu and Zilibotti 2001; Acemoglu and Autor 2011; Costinot and Vogel 2010). Production involves many different tasks, such as managing, accounting, clerical activities, design, packaging, logistics, sales representation, operational production, input control, monitoring, supervision, services. Tasks can be executed by workers with different skills. We argue that the most skill-intensive tasks, such as managing or directing, are typically filled with skilled workers. In turn, the most unskill-intensive tasks, such as cleaning services, are instead performed by unskilled workers. The remaining tasks, mostly involving production and design, can be done by either skilled or unskilled workers. This depends on factor prices as well as on firm characteristics such as productivity. Because of this, exporters and non-exporters may choose different skill employment composition even for similar tasks. For instance, a machine at an exporting firm may be operated by a skilled engineer, while the same task could instead be performed 3