In his article, 'Publication bias in export promotion impact on export market entry: Evidence from a meta-regression analysis', Dr Binyam Afewerk Demana argues that selective focus on export promotions policies and programmes may be providing a skewed picture of their effectiveness.
Export promotion policies and programmes (EPPs) are important tools used by governments to encourage businesses to start selling goods and services overseas. These policies help companies overcome challenges in foreign markets and begin exporting. To understand how effective these government-supported measures are, researchers have looked at lots of studies on how EPPs affect the likelihood of businesses entering export markets.
The authors reviewed many of these studies up to 2020 and found 479 reported estimates. Using advanced analyses, they discovered something important: there's strong evidence that the reported effects of EPPs on getting into export markets are often exaggerated. This means that the impact of these policies is not as big as it seems in the research.
Interestingly, this exaggeration seems to be mostly due to researchers holding back negative results rather than journal reviewers or editors rejecting them. This means that the evidence we have might be giving policymakers and scientists a skewed picture of how effective EPPs really are in helping businesses start exporting.
Read the article online
The full article is available for download from the publisher's website - 'Publication bias in export promotion impact on export market entry: Evidence from a meta-regression analysis', Applied Economics Letters, January 2024.
What is publication bias?
Publication bias occurs when research findings are chosen for publication based on their statistical significance or alignment with pre-existing theoretical expectations.
This bias can lead to an overemphasis on studies showing significant results while overlooking or underrepresenting those with smaller effects or insignificant outcomes. If such bias exists, it has the potential to distort empirical research inferences, impacting both scientific conclusions and policymakers' decisions.
- Assistant professor
