Geography and intra-national home bias: U.S. domestic trade in 1949 and 2007

Crafts, Nicholas; Klein, Alexander

doi:10.1093/jeg/lbu008

Cited by 14 publications

(8 citation statements)

References 26 publications

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“…In all 22 industries, we estimate a negative border coefficient, and in 21 industries it is statistically significant at the 1% level (the average coefficient value is

- 1.42

with an average standard error of 0.21 ). This evidence is consistent with Crafts and Klein (2015) who also find statistically significant domestic border dummy coefficients.…”

Section: Resultssupporting

confidence: 90%

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Estimating Border Effects: The Impact of Spatial Aggregation

Coughlin

Novy

2021

Int Economic Review

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Trade data are typically reported at the level of regions or countries and are therefore aggregates across space. In this paper, we investigate the sensitivity of standard gravity estimation to spatial aggregation. We build a model in which initially symmetric micro regions are combined to form aggregated macro regions. We then apply the model to the large literature on border effects in domestic and international trade. Our theory shows that larger countries are systematically associated with smaller border effects. The reason is that due to spatial frictions, aggregation across space increases the relative cost of trading within borders. The cost of trading across borders therefore appears relatively smaller. This mechanism leads to border effect heterogeneity and is independent of multilateral resistance effects in general equilibrium. Even if no border frictions exist at the micro level, gravity estimation on aggregate data can still produce large border effects. We test our theory on domestic and international trade flows at the level of U.S. states. Our results confirm the model's predictions, with quantitatively large effects.

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“…In all 22 industries, we estimate a negative border coefficient, and in 21 industries it is statistically significant at the 1% level (the average coefficient value is

- 1.42

with an average standard error of 0.21 ). This evidence is consistent with Crafts and Klein (2015) who also find statistically significant domestic border dummy coefficients.…”

Section: Resultssupporting

confidence: 90%

“…For this purpose, we examine trade flows at the industry level from Crafts and Klein (2015) for the year 2007, sourced from the Commodity Flow Survey. By “industry,” we mean “commodity” in Commodity Flow Survey terminology.…”

Section: Resultsmentioning

confidence: 99%

Estimating Border Effects: The Impact of Spatial Aggregation

Coughlin

Novy

2021

Int Economic Review

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“…Wolf (2000), as one of the earlier studies using the trade‐related approach, postulates that excessive intra‐state trade or intra‐home trade bias can be explained due to geographic clusters of vertically linked industries, which particularly promote large volumes of intra‐state trade. This is confirmed empirically by Crafts and Klein (2015) who find geographical industrial location to be a significantly important explanation of intra‐state bias in the US. Of other factors, Xu and Fan (2012) show that a better business environment positively facilitates domestic trade between Chinese regions.…”

Section: Discussionsupporting

confidence: 65%

The economics of domestic market integration

Gunessee

Zhang

2021

Journal of Economic Surveys

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This paper reviews the literature that evidences the extent of the integration and fragmentation of domestic markets from measuring internal border effects. The empirical evidence from three main approaches—trade flows‐related, capital flows‐related, and price‐related—are reviewed. They are evaluated with emphasis on the role of recent methodological developments that adequately deals with the spatial and data aggregation problems and use disaggregated (micro) data, refined distance measures, and fine‐grained geographical areas. In particular, it enables distinguishing trade costs due to informal administrative impediments (border effects) and geographical barriers (distance effect). These allow for better inferences about internal border effects and domestic market integration to be drawn. They reveal that traditional approaches, which fail to tackle these inadequacies, have over‐estimated the size of the internal border effects and in effect domestic markets are more integrated than earlier documented. This addresses the reported mixed evidence found in earlier studies.

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“…4 Whether the home bias could ever be fully eliminated is another matter entirely. In fact, there is evidence that there are substantial border effects between US states (Crafts and Klein, 2014), even though they belong to the same cultural, legislative, economic, currency, and infrastructure framework.…”

Section: Literature Reviewmentioning

confidence: 99%

Home Sweet Home: The Home Bias in Trade in the European Union

Mika

2017

SSRN Journal

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Geography and intra-national home bias: U.S. domestic trade in 1949 and 2007

Cited by 14 publications

References 26 publications

Estimating Border Effects: The Impact of Spatial Aggregation

Estimating Border Effects: The Impact of Spatial Aggregation

The economics of domestic market integration

Home Sweet Home: The Home Bias in Trade in the European Union

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