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The Effect of Financial and Non-financial Factors on the Productivity and Profitability of the Goat Industry: A Modelling Approach to Structural Equations Read chapter Read first chapter

2022 | OriginalPaper | Chapter

4. Countries’ Image and Agricultural Trade Volume

Authors : Christos Staboulis, Dimitrios Natos, Efthimia Tsakiridou, Konstadinos Mattas

Published in: Food Policy Modelling

Publisher: Springer International Publishing

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Abstract

The main focus of this paper is to demonstrate empirically that country of origin perceptions have an impact on actual agricultural trade volume. Moreover, a second aim is to compare these effects on agricultural trade volume with effects on the non-agricultural sectors (manufacture, machinery and transportation equipment as well as the chemicals sector). The study empirically tests these relationships using a bilateral measure of reputation as a determinant of export volume, utilizing one of the most successful models in the literature of international economics, the structural gravity model of international trade. Countries’ reputation measures are derived from a global survey, in which respondents in 20 countries rate the reputation for products and people of 50 other countries. As the results indicate, a better country reputation for products and people is associated with increased agricultural trade volume. It is worth noting that the effects of a country’s image concerning its products are minor in the agricultural sector in comparison with the three other investigated sectors.

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Appendix
Available only for authorised users
Footnotes
1
Several studies have proved the existence of a relationship between reputation and firms’ performance (Brown & Perry, 1994). Carmeli and Tishler (2005) stated that corporate reputation affects the performance of organizations. The authors examined the following measures of performance: growth, profitability, financial soundness, market share and future sales estimates, through the opinions of executives of the Kibbutz companies.
 
2
According to Hausman’s test, the null hypothesis is that the preferred model is the fixed effects vs. the alternative of the random effects.
 
3
The Stata command is “poisson dep_var exp_var, robust”.
 
4
Observations of import flows are classified by Standard International Trade Classification (SITC), revision 3 at the 2-digit level. Following that classification and according to the identification of four sectors in the current paper’s empirical research, the agricultural sector consists of bilateral import flows classified in SITC codes 0, 1, 4 and 22, the manufacturing sector consists of mutual import flows classified in code 6, machinery equipment and equipment of transport mutual import flows in code 7, and the chemical sector’s mutual import observations in code 5.
 
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Metadata
Title
Countries’ Image and Agricultural Trade Volume
Authors
Christos Staboulis
Dimitrios Natos
Efthimia Tsakiridou
Konstadinos Mattas
Copyright Year
2022
Book
Food Policy Modelling

Print ISBN: 978-3-031-08316-7

Electronic ISBN: 978-3-031-08317-4

Copyright Year: 2022

DOI
https://doi.org/10.1007/978-3-031-08317-4_4

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