05630oam 22012854 450 991096111630332120250426110149.097866128421469781462377985146237798X978145278640714527864029781451871210145187121X97812828421441282842145(CKB)3170000000055160(EBL)1608096(SSID)ssj0001488723(PQKBManifestationID)11842762(PQKBTitleCode)TC0001488723(PQKBWorkID)11445320(PQKB)11175823(OCoLC)465449025(IMF)WPIEE2008263(MiAaPQ)EBC1608096(IMF)WPIEA2008263WPIEA2008263(EXLCZ)99317000000005516020020129d2008 uf 0engur|n|---|||||txtccrWhat is Really Good for Long-Term Growth? Lessons from a Binary Classification Tree (BCT) Approach /Rupa Duttagupta, Montfort Mlachila1st ed.Washington, D.C. :International Monetary Fund,2008.1 online resource (29 p.)IMF Working PapersIMF working paper ;WP/08/263Description based upon print version of record.9781451915747 1451915748 Includes bibliographical references.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 Checks3. 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; ReferencesAlthough 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.IMF Working Papers; Working Paper ;No. 2008/263Economic developmentCross-cultural studiesEconomic developmentRegional disparitiesDemographic Economics: GeneralimfDemographyimfEconomic policyimfEducationimfEducation: GeneralimfEmpirical Studies of TradeimfExports and ImportsimfHealth economicsimfHealthimfHealth: GeneralimfHuman CapitalimfHuman capitalimfIncome economicsimfInternational economicsimfLabor ProductivityimfLaborimfLabourimfNternational cooperationimfOccupational ChoiceimfPopulation & demographyimfPopulation and demographicsimfPopulationimfSkillsimfTerms of tradeimfUnited StatesimfEconomic developmentEconomic developmentRegional disparities.Demographic Economics: GeneralDemographyEconomic policyEducationEducation: GeneralEmpirical Studies of TradeExports and ImportsHealth economicsHealthHealth: GeneralHuman CapitalHuman capitalIncome economicsInternational economicsLabor ProductivityLaborLabourNternational cooperationOccupational ChoicePopulation & demographyPopulation and demographicsPopulationSkillsTerms of trade338.9Duttagupta Rupa1815725Mlachila Montfort1815726DcWaIMFBOOK9910961116303321What is Really Good for Long-Term Growth? Lessons from a Binary Classification Tree (BCT) Approach4371236UNINA