2015
DOI: 10.3386/w21583
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What Drives Home Market Advantage?

Abstract: In the automobile industry, as in many tradable goods markets, firms usually earn their highest market share within their domestic market. The goal of this paper is to disentangle the supplyand demand-driven sources of the home market advantage. While trade costs, foreign production costs, and taste heterogeneity all matter for market outcomes, we find that a preference for home brands is the single most important driver of home market advantage -even after controlling for brand histories and dealer networks. … Show more

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Cited by 8 publications
(9 citation statements)
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References 18 publications
(19 reference statements)
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“…(2018) report in their Table 11 average firm-market markups ranging from 6 percent (Peugeot in Brazil) to 12.4 percent (Peugeot in France). 31 Among the determinants of marketing frictions, consumers are more than twice as likely to select a home brand, corroborating the large home bias found by Coşar et al (2018). In addition, we estimate that increasing consumer distance from headquarters sharply lowers market shares, even controlling for distance from the consumer to the assembly location, which is captured by C bn in the same regression.…”
Section: A Baseline Estimatessupporting
confidence: 68%
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“…(2018) report in their Table 11 average firm-market markups ranging from 6 percent (Peugeot in Brazil) to 12.4 percent (Peugeot in France). 31 Among the determinants of marketing frictions, consumers are more than twice as likely to select a home brand, corroborating the large home bias found by Coşar et al (2018). In addition, we estimate that increasing consumer distance from headquarters sharply lowers market shares, even controlling for distance from the consumer to the assembly location, which is captured by C bn in the same regression.…”
Section: A Baseline Estimatessupporting
confidence: 68%
“…TheCoşar et al (2018) dataset has 9 markets and 60 brands compared to the 76 markets and 138 brands in our estimating sample 6 Grigolon and Verboven (2014). show that nested logit can match fairly closely the cross-price elasticities of a random coefficients model.…”
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confidence: 77%
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