Learning to Import through Production Networks
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866909507144122368 |
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| author | Huremović, Kenan Nutarelli, Federico Serti, Francesco Vega-Redondo, Fernando |
| author_facet | Huremović, Kenan Nutarelli, Federico Serti, Francesco Vega-Redondo, Fernando |
| contents | Using administrative data on the universe of inter-firm transactions in Spain, we show that firms learn to import from their domestic suppliers and customers. Our identification strategy exploits the panel structure of the data, the firm-time variation across import origins, and the network structure. We find evidence of both upstream and downstream network effects, even after accounting for sectoral and spatial spillovers. We estimate that an increase of 10 percentage points in the share of suppliers (customers) that are importing from a given region increases the probability of starting importing from that region by 10.7\% (19.2\%). Connections with geographically distant domestic firms provide more useful information to start importing. Larger firms are more responsive to this information but less likely to disseminate it. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_13422 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Learning to Import through Production Networks Huremović, Kenan Nutarelli, Federico Serti, Francesco Vega-Redondo, Fernando General Economics Economics Using administrative data on the universe of inter-firm transactions in Spain, we show that firms learn to import from their domestic suppliers and customers. Our identification strategy exploits the panel structure of the data, the firm-time variation across import origins, and the network structure. We find evidence of both upstream and downstream network effects, even after accounting for sectoral and spatial spillovers. We estimate that an increase of 10 percentage points in the share of suppliers (customers) that are importing from a given region increases the probability of starting importing from that region by 10.7\% (19.2\%). Connections with geographically distant domestic firms provide more useful information to start importing. Larger firms are more responsive to this information but less likely to disseminate it. |
| title | Learning to Import through Production Networks |
| topic | General Economics Economics |
| url | https://arxiv.org/abs/2405.13422 |