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Enregistrement W2513688966 · doi:10.11588/heidok.00005744

Industrial Sickness in Indian Manufacturing

2005· dissertation· en· W2513688966 sur OpenAlexaboutno aff
Rahel Falk

Notice bibliographique

RevueheiDOK (Heidelberg University) · 2005
Typedissertation
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueFirm Innovation and Growth
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésLegislationSubsidyDeregulationIndustrial policyBusinessPublic sectorEconomic policyGovernment (linguistics)Quarter (Canadian coin)Promotion (chess)Market economyEconomyEngineeringEconomicsPoliticsInternational tradePolitical scienceGeography

Résumé

récupéré en direct d'OpenAlex

In India, the term ‘sick units’ refers to economically unviable firms which are kept alive ‘in the public interest’ by means of subsidies of various kinds. Since this practice is common, and large parts of the industrial sector are affected, this phenomenon is referred to as industrial sickness. As of March 2001, the Reserve Bank of India counted over a quarter of a million of sick units with outstanding credit worth more than a quarter of a trillion of Indian Rupees, i.e. about 1.2 percent of Indian GDP. Recognizing that scarce resources are wasted on a great scale, the Government of India enacted special legislation to tackle the problem, namely, the Sick Industrial Companies Act. Based on a rich panel data set of some 4,400 manufacturing companies covering the 1988-1999 period, this thesis investigates the causes of sickness and the responses of firms to the policies that are supposed to remedy it. Chapter 1 motivates the topic, briefly summarizes existing contributions and introduces the dataset. Chapter 2 deals with Indian industrial policy, much of which is still a legacy of the attempt at planning a so-called mixed economy, with the state supposedly ‘occupying the commanding heights’. Until the deregulation process of the early 1990s dismantled discrete barriers to entry, the economic environment involved a labyrinthine system of industrial licensing, the promotion of priority sectors, the regulation of foreign trade, capital flows and investment, protection of jobs in the regulated sector, and directed credit provided by public financial institutions. Chapter 3 first discusses various concepts of sickness. In the following several descriptive statistics from the given firm-level dataset are presented to provide a picture of the dimensions of sickness and its patterns over industries, time, location (state), form of ownership, firm-size and firm-age. The ‘stylized facts’ section is rounded out with an investigation of the relation between a firm’s health status and measures of its profitability, single-factor productivity and liabilities, with firms classified by ten manufacturing sectors. Decreasing sickness rates in the early days of reforms stand vis-à-vis erratic rises in industrial sickness from the mid 1990s onwards. This finding raises two questions: (i) have the reforms ultimately failed to foster productive efficiency? or (ii) is increased sickness in the mid and late 90s just a reflection of the New Economic Policy (NEP) and its attempt to harden budgets? Chapter 4 draws on the former by analyzing productivity and efficiency in 10 separate Indian manufacturing industries over 3 important sub-periods, viz. pre-reform (1989-‘91), transition phase (1992-‘96), and post-reform (1997-‘99). The results corroborate previous results on the general downturn of aggregate manufacturing performance after 1991. Moreover it is shown that sectoral downturns in productivity and mean efficiency went with greater variation in firm performance. Diverging firm-wise efficiency scores combined with increasing failure rates lead to the supposition that NEP reforms have not been generally unsuccessful, but that economically viable firms have considerably benefited from the changes in policy. The key hypothesis of chapter 5 is that prior to the 1991 reforms preferential treatment irrespective of economic viability established systematic disincentives to perform well, and once these were withdrawn, then firms fell into sickness. This hypothesis is tested by running a panel probit model, wherein observed health status in the late nineties is regressed against (i) dummy variables that capture the effect of the policy shock on formerly protected types of firms, (ii) pre-reform measures of budget softness, and (iii) pre-reform measures of economic distress. In a second part, it is investigated whether measures that lowered barriers to entry, and so sharpened competition, affected the dispersion of efficiency levels among firms and the incidence of sickness. While chapter 5 concentrates on reductions in barriers to entry, chapter 6 is more concerned with the remaining barriers to exit (of labor and firms). The starting point is the notion that the status of sickness entails great advantages to the incumbent management and the shareholders (exemptions from debt repayment or other obligations and generous financial assistance) as well as to politicians: once a company has fallen sick, the old management is replaced by a government appointed director. An agency model is tested, the core of which states that the politician-manager rescues the firm, because employment guarantees increase his popularity and his chances of getting re-elected. Inference from single-equation estimation mostly supports the model, but a simultaneous systems approach (a particular choice of the capital structure and the sickness status) would reject it.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,915
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0020,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,001

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 Opus0,031
Tête enseignante GPT0,194
Écart entre enseignants0,163 · 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

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
Publié2005
Routes d'admission1
Résumé présentoui

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