Estimating the Trade and Welfare Effects of Brexit: A Panel Data Structural Gravity Model

Harald Oberhofer and Michael Pfaffermayr

Department of Economics Working Papers from Vienna University of Economics and Business, Department of Economics

Abstract: This paper proposes a new panel data structural gravity approach for estimating the trade and welfare effects of Brexit. The suggested Constrained Poisson Pseudo Maximum Likelihood Estimator exhibits some useful properties for trade policy analysis and allows to obtain estimates and confidence intervals which are consistent with structural trade theory. Assuming different counterfactual post-Brexit scenarios, our main findings suggest that UKs (EUs) exports of goods to the EU (UK) are likely to decline within a range between 7.2% and 45.7% (5.9% and 38.2%) six years after the Brexit has taken place. For the UK, the negative trade effects are only partially offset by an increase in domestic goods trade and trade with third countries, inducing a decline in UKs real income between 1.4% and 5.7% under the hard Brexit scenario. The estimated welfare effects for the EU are negligible in magnitude and statistically not different from zero.

Keywords: Constrained Poisson Pseudo Maximum Likelihood Estimation; Panel Data; International Trade; Structural Gravity Estimation; Trade Policy; Brexit (search for similar items in EconPapers)
JEL-codes: C13 C50 F10 F15 (search for similar items in EconPapers)
Date: 2018-01
New Economics Papers: this item is included in nep-eec and nep-int
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Citations: View citations in EconPapers (15)

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Related works:
Journal Article: Estimating the trade and welfare effects of Brexit: A panel data structural gravity model (2021)
Working Paper: Estimating the Trade and Welfare Effects of Brexit: A Panel Data Structural Gravity Model (2018)
Working Paper: Estimating the Trade and Welfare Effects of Brexit: A Panel Data Structural Gravity Model (2017)
Working Paper: Estimating the Trade and Welfare Effects of Brexit. A Panel Data Structural Gravity Model (2017)
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