The Degree of Consensus among Economic Educators in a Transition Economy
Notice bibliographique
Résumé
ABSTRACT The question of regarding important economic issues among economists has been studied for over 30 years in many countries with established market economies. The authors investigate the degree of agreement about such issues among economic educators in Belarus by adapting the survey previously used by American and Western European economists. The study specifically analyzes the differences in the views of the former participants of retraining programs vs. non-participants while also comparing them to a survey of U.S. economists. Several statistical measures designed to identify consensus are applied to analyze the results. The authors generally find disagreement within the economics profession in Belarus although they conclude that training in market economics principles results in a greater degree of consensus. KEYWORDS: consensus, economists' views, change of opinions, transition economy. JEL Code: A11 INTRODUCTION How much do economists disagree? Various researchers have explored this question over the years (Kearl, Pope, Whiting, & Wimmer, 1979; Frey, Pommerehne, Schneider, & Gilbert, 1984; Block & Walker, 1988; Frey & Eichenberger 1992; Ricketts & Shoesmith, 1992; Alston, Kearl, & Vaughan, 1992; Becker, Walstad, & Watts, 1994; Fuller & Geide-Stevenson, 2003). In a profession with different theoretical and ideological approaches and competing schools of thought some disagreement is inevitable, however, while disagreement among economists is a part of economic tradition, many studies have found that there is more agreement than disagreement among economists in Northern American and Western European countries. This paper adds another dimension to the existing research by examining whether economists from the countries that are in the process of establishing market economies have achieved a similar level of agreement. By replicating the survey of opinions from Alston et al. (1992) in Belarus, this paper attempts to answer the following research questions: What is the degree of on economic issues among Belarusian economic educators? Did retraining programs in market economic principles shift these opinions? How do the results of the survey conducted in Belarus differ from the findings of the same survey among American economists? PREVIOUS RESEARCH ON CONSENSUS AMONG ECONOMISTS Over the last 30 years a number of studies have examined the areas of agreement and disagreement among economists over time and across countries. The first survey examined economic on 30 propositions. Kearl, Pope, Whiting, and Wimmer (1979) used the criterion of relative entropy. They concluded that there is among economists on most economic issues and found that 211 members of American Economic Association (AEA) tend to agree on textbook microeconomic and positively stated issues, but disagree about statements that involve macroeconomic concepts and have value judgments. Another study (F rey et al., 1984) analyzed the results of similar surveys conducted in France, Germany, Austria, and Switzerland and compared the responses to those from the USA. Although the results from each of the four European countries were different, the researchers found the least disagreement among economists regarding issues concerning the effectiveness of the price mechanism and the market system and that American, German, and Swiss economists tended to support typical textbook neoclassical propositions, while Austrian and French economists were more inclined to agree with broader government presence in the economy. Frey et al argued that possible causes for this disagreement could be different historical and cultural backgrounds. Canadian economists Block and Walker (1988) found that Canadian and U.S. economists have similar views on most propositions. In general, Canadian economists also tend to support the idea of effectiveness of the price mechanism in allocation, but they are less supportive of any interventionist policy by government than their American colleagues except in areas of government's redistributive role. …
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,017 | 0,053 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,004 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,003 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».