Article
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The Determinants of U.S. Olive Oil Imports
Version 1
: Received: 16 December 2022 / Approved: 19 December 2022 / Online: 19 December 2022 (03:54:13 CET)
How to cite: Hammami, A. M.; Beghin, J. C. The Determinants of U.S. Olive Oil Imports. Preprints 2022, 2022120317. https://doi.org/10.20944/preprints202212.0317.v1 Hammami, A. M.; Beghin, J. C. The Determinants of U.S. Olive Oil Imports. Preprints 2022, 2022120317. https://doi.org/10.20944/preprints202212.0317.v1
Abstract
We investigate the determinants of U.S. bilateral imports of olive oil and their dynamics from shocks in foreign supplies and changes in U.S. olive oil demand, using an augmented gravity framework that leads to an equilibrium of bilateral trade flows from olive oil exporters to the U.S. market. The empirical specification is applied at the disaggregated HS-6 level in a panel dataset, and three estimation techniques (truncated OLS, PPML, Heckman), for which the latter two account for zero trade flows, the extensive margin of trade and the potential censored distribution of exports with zero trade flows. We run Reset and HPC tests to qualify our results. On the supply side, exporters’ capacity to exports, multilateral trade resistance, and immigrants’ networks into the US are strong determinants of the bilateral trade flows for both aggregate olive oil exports and for virgin olive oil exports, On the consumer side, U.S. GDP, the import unit value, and immigrant network effects are robust determinants of bilateral flows as well for aggregate and virgin olive oil trade flows. Migrants’ stock, exporters’ GDP and population, and total exports revenues increase the probability of an exporter entering the U.S. market. We could not find robust evidence of consumer behavior being influenced by popular press measures of the emergence of Mediterranean diet and olive oil, or measures of cultural globalization of U.S. consumers.
Keywords
olive oil; trade; gravity equation; migrant network
Subject
Business, Economics and Management, Economics
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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