What is Really Good for Long-Term Growth? Lessons from a Binary Classification Tree (BCT) Approach / / Rupa Duttagupta, Montfort Mlachila

• Autore: Duttagupta Rupa
• Pubblicazione: Washington, D.C. : , : International Monetary Fund, , 2008
• Descrizione fisica: 1 online resource (29 p.)
• Disciplina: 338.9
• Soggetto topico: Economic development; Economic development - Regional disparities; Exports and Imports; Labor; Demography; Demographic Economics: General; Empirical Studies of Trade; Health: General; Human Capital; Skills; Occupational Choice; Labor Productivity; Education: General; Population & demography; International economics; Health economics; Labour; income economics; Education; Population and demographics; Terms of trade; Health; Human capital; Population; Economic policy; nternational cooperation
• Soggetto geografico: United States
• Altri autori: MlachilaMontfort
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references.
• Nota di contenuto: Contents; I. Introduction; II. A Few Notes on the Growth Literature; Tables; 1. Most Significant Variables in Selected Growth Studies; III. The Binary Classification Tree (BCT) Approach; IV. Properties of the Data; 2. Definition of Variables; V. The Results; A. Baseline Model: What is Good for Strong Growth?; Figures; 1. Distribution of Growth; 3. Growth Rate for Top Quartile; 4. What is Really Good for Growth: Ranking of Indicators; 2. Baseline Model; 5. Median Values of Key Indicators in Baseline Model; B. Alternative Specifications and Robustness Checks ; 3. Out of Sample Forecast (I)-Advanced Economies4. Out of Sample Forecast (II)-Highly Indebted Poor Countries; 6. The Do's and Don'ts of Growth; VI. Concluding Remarks; Appendix; I. Description of the Database; References
• Sommario/riassunto: Although the economic growth literature has come a long way since the Solow-Swan model of the fifties, there is still considerable debate on the "real' or "deep" determinants of growth. This paper revisits the question of what is really important for strong long-term growth by using a Binary Classification Tree approach, a nonparametric statistical technique that is not commonly used in the growth literature. A key strength of the method is that it recognizes that a combination of conditions can be instrumental in leading to a particular outcome, in this case strong growth. The paper finds that strong growth is a result of a complex set of interacting factors, rather than a particular set of variables such as institutions or geography, as is often cited in the literature. In particular, geographical luck and a favorable external environment, combined with trade openness and strong human capital are conducive to growth.
• Titolo autorizzato: What is Really Good for Long-Term Growth? Lessons from a Binary Classification Tree (BCT) Approach
• ISBN: 1-4623-7798-X; 1-4527-8640-2; 1-4518-7121-X; 9786612842146; 1-282-84214-5
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910788341203321
• Lo trovi qui: Univ. Federico II
• Serie: IMF Working Papers; Working Paper ; ; No. 2008/263