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An Interview With Professor Dilip M Nachane

2020· article· en· W3152886293 sur OpenAlexaboutno aff
Grk Murty

Notice bibliographique

RevueSSRN Electronic Journal · 2020
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueSocial and Economic Development in India
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésSchools of economic thoughtManagementSociologyPolitical scienceEconomics
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Inspired by the Strumilin-Mahalanobis model of planning being implemented by the young independent India for laying a strong foundation for its economic growth, a young graduate who had just then passed BA Mathematics, securing first rank with distinction from Bombay University in 1965, in an unusual move decided to pursue another BA degree, this time in Economics as elective, hoping that with his knowledge of Mathematics and Statistics allied with economic theory, he could contribute his mite to the then ongoing India’s planning exercise and its overall economic welfare. After completing BA with Economics, he joined MA Economics at Bombay University and passed in 1968 with first rank. He obtained his PhD in 1973. That young scholar is none other than Dilip Madhukar Nachane, who in 1971 joining his alma mater as a lecturer, became a reader, then UGC Chair in Modern Quantitative Economics in 1978, before finally becoming the Director of the Department of Economics at Mumbai University in 1993. In 2003, Prof. Nachane joined the Indira Gandhi Institute of Development Research (IGIDR) as a Senior Professor, and later in 2007-10, he served as its Director-cum-Vice Chancellor. Since 2010, he has been working as Professor Emeritus at IGIDR. In 2011, he was also appointed the Chancellor of Central University of Manipur. When Prof. Nachane started teaching Mathematical Economics to the first batch of students in 1977-79, there was no tradition of teaching the subject with any of the expected rigor; nor were there any textbooks available like today. According to Romar Correa, the first batch student, their background in Mathematics education was limited to high-school algebra and geometry. Correa says that yet “Prof. Nachane rising to the occasion gamely”, skirting the likely pitfalls of either the sophistication dictated by the reading list that would have been completely incomprehensible to the students, or without trivializing math with chitchat substituting for proofs, “pitched his teaching high but not inaccessible to the outstretched hands”. Correa, Prof. Nachane’s doctoral student, who later became RBI Chair Professor of Monetary Economics, University of Mumbai, further states that Prof. Nachane “is a renaissance man. The history of economics and economic history, literature and philosophy, are part of his makeup and come to the fore in interactions.” No surprise, he was conferred with the UGC Swami Pranavananda Saraswathi National Award in 2004 for his lifelong contribution to the teaching of economics in India. Besides teaching economics for over five-and-a-half decades, Prof. Nachane also guided 40 scholars for PhD in several facets of economics. He has also carried out research into core econometrics, improving the testing tools for causal relationships, computational methods for TVP problems, etc. He has made significant contributions to several areas in economics by publishing more than 100 papers. He has also carried out extensive research in post-liberalization growth in India, impact of reforms on banks’ credit behavior and capital adequacy requirements, etc. It is in recognition of his outstanding contributions to econometric studies in India that he was elected President of the Indian Econometric Society in 2003. For Prof. Nachane, Monetary Economics remained his main research area for almost five decades. He did extensive research in the areas of monetary policy, its transmission to real economy, inflation estimation, exchange rate regimes, business cycles, international trade and balance of payments, etc. During 2005-11, he also served as a member of the Technical Advisory Committee on Monetary Policy of the Reserve Bank of India. His youthful ambition to work for the welfare of the Indian economy appeared to have been fulfilled when he was appointed Member of the Prime Minister’s Economic Advisory Council in 2013. He has recently been included in the International Biographical Center (Cambridge, UK) list of 2000 “Outstanding Intellectuals of the 21st Century.” He was a Visiting Professor at University of British Columbia, Canada (1988-89), University of Manchester, UK (1990), University of Ulster, UK (1991), University of Avigon, France (1997) and Otto von Guericke University, Germany (2002-2004). Once, I heard a Professor describing Monetary Economics as something akin to that of Uankara’s Advaita Vedânta, which apparently sounds simple but profoundly complex to comprehend as an integral whole. There is a certain mysticism encircling it, yet, at the hands of Prof. Nachane, you find monetary issues turning so obvious as he so lucidly articulates his way forward through the maze of issues raised in this interview. He simply makes everything look so very clear to every reader, for he speaks as a teacher but not as an economist. That is his depth of knowledge and his commitment as a teacher to make complex concepts obvious to students, and that is what you will enjoy in the following pages.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,012
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: aucune
Score de désaccord entre enseignants0,027
Score d'incertitude au seuil0,092

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,012
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,002
Études des sciences et des technologies0,0090,002
Communication savante0,0040,006
Science ouverte0,0010,004
Intégrité de la recherche0,0070,017
Charge utile insuffisante (le modèle a refusé de juger)0,0270,011

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.

Tête enseignante Opus0,030
Tête enseignante GPT0,288
Écart entre enseignants0,258 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2020
Routes d'admission1
Résumé présentoui

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