Chapter 8 Growth Econometrics

Durlauf, Steven N.; Johnson, Paul A.; Temple, Jonathan

doi:10.1016/s1574-0684(05)01008-7

Cited by 804 publications

(638 citation statements)

References 280 publications

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“…First, data on both mortality and government health expenditure are unlikely to be comparable across countries. Second, the estimates in these studies are subject to bias on account of unobserved heterogeneity that might be correlated with the variable of interest (see Durlauf et al 2005). The present study addresses the first problem by using sub-national data, and the second problem by using panel data on state health expenditure and income.…”

Section: Related Literaturementioning

confidence: 99%

Spending to save? State health expenditure and infant mortality in India

Bhalotra

2007

Health Economics

105

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in Spending to Save? State Health Expenditure and Infant Mortality in IndiaSonia Bhalotra D I S C U S S I O N P A P E R S E R I E S ABSTRACT Spending to Save? State Health Expenditure and Infant Mortality in India *There are severe inequalities in health in the world, poor health being concentrated amongst poor people in poor countries. Poor countries spend a much smaller share of national income on health expenditure than do richer countries. What potential lies in political or growth processes that raise this share? This depends upon how effective government health spending in developing countries is. Existing research presents little evidence of an impact on childhood mortality. Using specifications similar to those in the existing literature, this paper finds a similar result for India, which is that state health spending saves no lives. However, upon allowing lagged effects, controlling in a flexible way for trended unobservables and restricting the sample to rural households, a significant effect of health expenditure on infant mortality emerges, the long run elasticity being about -0.24. There are striking differences in the impact by social group. Slicing the data by gender, birth-order, religion, maternal and paternal education and maternal age at birth, I find the weakest effects in the most vulnerable groups (with the exception of a large effect for scheduled tribes). JEL Classification:I18, I38, O15, O12

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Section: Related Literaturementioning

confidence: 99%

Spending to save? State health expenditure and infant mortality in India

Bhalotra

2007

Health Economics

105

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“…However, a concern is that the data is subject to large outliers; see Temple (1999) and Durlauf, Johnson & Temple (2005 …”

Section: Economic Growth Modelmentioning

confidence: 99%

“…For example, a higher mean population growth rate will generally lead to a lower mean growth rate. This type of correlation between explanatory variables x i,t and countryspecific effects µ i is unaccounted for in random effects models and leads to biased parameter estimates; see Durlauf et al (2005) for a discussion of this issue in the context of economic growth. To overcome this issue we standardize the explanatory variables to have mean zero and unit variance for each country.…”

Section: Student's T Dynamic Panel Data Modelmentioning

confidence: 99%

Generalized dynamic panel data models with random effects for cross-section and time

Mesters¹,

Koopman²

2014

Journal of Econometrics

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“…2 Using a worldwide sample of countries from 1960 to 2009, our analysis on the role of natural capital on economic growth is based on the augmented Solow model with a set of new growth theories (Solow, 1956and Durlauf et al, 2005, 2008a.…”

Section: Natural Capital and Macroeconomic Frameworkmentioning

confidence: 99%

“…The lack of agreed theoretical bases for empirical work and for a reduced form to apply in empirical analyses, has led researchers to abandon any a priori models and to let the data show which variables are correlated with economic growth through model uncertainty (Capolupo, 2009). In order to estimate accurately the role of the so-called new growth theories such as natural capital in determining economic growth, Durlauf et al (2005Durlauf et al ( , 2008a and Sala-i- Martin et al (2004) propose the Bayesian Model Averaging (BMA) methodology. 4 There is indeed a problem of model uncertainty when performing economic growth estimations that account for new growth theories Durlauf, 2001, Brock et al, 2003).…”

Section: Natural Capital and Macroeconomic Frameworkmentioning

confidence: 99%

Essays on marine resources conservation : macroeconomics and national accounting

Virto¹

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Chapter 8 Growth Econometrics

Cited by 804 publications

References 280 publications

Spending to save? State health expenditure and infant mortality in India

Spending to save? State health expenditure and infant mortality in India

Generalized dynamic panel data models with random effects for cross-section and time

Essays on marine resources conservation : macroeconomics and national accounting

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