Stack, M.M. ORCID: 0000-0002-9213-7607, Pentecost, E.J. and Ravishankar, G. ORCID: 0000-0002-9281-7207, 2018. A stochastic frontier analysis of trade efficiency for the new EU member states: implications of Brexit. Economic Issues, 23 (1), pp. 35-53. ISSN 1363-7029
|
Text
10795_Stack.pdf - Post-print Download (417kB) | Preview |
Abstract
Examining the trade performance for the new European Union (EU) member states is an important issue in the context of the enlargement process – and in a new era of membership contraction with the likely exit of the United Kingdom from the EU. Typically, the degree of trade integration is assessed by comparing actual trade volumes with potential trade volumes projected from the gravity model parameters estimated for a reference group of countries that best represent normal trade relations. This approach, however, does not compare trade levels against a maximum level of trade defined by a stochastic frontier. In this paper, a stochastic frontier specification of the gravity model is used to identify the efficiency of trade integration relative to maximum trade levels. The findings, based on a panel dataset of bilateral exports from 18 Western European countries to the 13 new member states over the 1995-2022 period, indicate a high degree of trade integration close to two-thirds of frontier estimates. Using forecast data for 2017-2022, trade efficiency should remain broadly stable and even increase for the larger countries in the likely post-Brexit phase.
Item Type: | Journal article |
---|---|
Publication Title: | Economic Issues |
Creators: | Stack, M.M., Pentecost, E.J. and Ravishankar, G. |
Publisher: | Economic Issues Education Fund |
Date: | March 2018 |
Volume: | 23 |
Number: | 1 |
ISSN: | 1363-7029 |
Divisions: | Schools > Nottingham Business School |
Record created by: | Jonathan Gallacher |
Date Added: | 09 May 2018 09:26 |
Last Modified: | 31 Mar 2019 03:00 |
URI: | https://irep.ntu.ac.uk/id/eprint/33468 |
Actions (login required)
Edit View |
Views
Views per month over past year
Downloads
Downloads per month over past year