Human capital and state-level economic growth: what is the contribution of schooling?

Yamarik, Steven

doi:10.1007/s00168-010-0365-9

Cited by 17 publications

(12 citation statements)

References 48 publications

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“…Conversely, its individual components—when assessed in isolation—are not necessarily good predictors for innovative performance. In particular, only human capital is positively and significantly associated with innovation in line with existing literature on the impact of human capital on regional growth and innovation in the U.S. (Fallah and Partridge ; Rupasingha, Goetz, and Freshwater ; Yamarik , ; Hoyman and Faricy ).…”

Section: Resultssupporting

confidence: 86%

R&D, Socio‐Economic Conditions, and Regional Innovation in the U.S

Crescenzi

Rodríguez‐Pose

2013

Growth and Change

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This paper looks at the genesis of innovation in the U.S. from a territorial perspective. The analysis aims to disentangle the impact of local research and development (R&D) expenditure from other contextual conditions supportive of the process of innovation. Particular emphasis is devoted to the role of socio-economic factors and systems of innovation (“social filter” conditions) and to their impact on the returns of R&D expenditure in different territorial contexts. The empirical analysis is based on a regional knowledge production function approach, leading to an empirical model estimated by means of panel data analysis for the period between 1994 and 2007 at the U.S. Bureau of Economic Analysis-Economic Area level. The results unveil the complexity of the territorial dynamics of innovation of the U.S. Local R&D investments are important predictors for regional innovative performance and their impact is highly localised. However, social filter conditions are fundamental for the productivity of innovation efforts

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Section: Resultssupporting

confidence: 86%

R&D, Socio‐Economic Conditions, and Regional Innovation in the U.S

Crescenzi

Rodríguez‐Pose

2013

Growth and Change

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“…Although, education was positive it was not significant. This was contrary to studies in other places such as those of Benhabib and Soiegel (1994), Yamarik (2011), Chanda and Panda (2016) and Panda (2017) all of which emphasized the importance of human capital (education and health) to economic growth.…”

Section: System Gmm Estimation To Determine the Effect Of Health On Economic Growthcontrasting

confidence: 93%

Effect of health outcome on economic growth in sub-Saharan Africa: a system generalized method of moment approach

Akinbode

Dipeolu

Bolarinwa

et al. 2021

JED

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PurposeSome progress have been made over time in improving health conditions in Sub-Saharan Africa (SSA). There are, however, contradicting reports on the relationship between health outcomes and economic growth in the region. The paper aimed at assessing the effect of health outcome on economic growth in SSA.Design/methodology/approachData for 41 countries from 2000 to 2018 were obtained from WDI and WGI and analyzed using system generalized method of moment (sGMM) which is appropriate for the present scenario. AR(1) and AR(2) tests were used to assess the validity of the model while Sargan and Hansen tests were adopted to examine the validity of the instrumental variables. The robustness of the estimation was confirmed using the pooled OLS and fixed effect regression.FindingsHealth outcome (proxied by life expectancy), lagged GDP per capita, capital formation, labor force (LF), health expenditure (HE), foreign direct investment (FDI) and trade openness (TOP) significantly affected economic growth emphasizing the importance of health in the process of economic growth in the region. AR(1) and AR(2) tests for serial correlation and Sargan/Hansen tests confirmed the validity of the estimated model and the instrumental variables respectively. Robustness of the GMM results was established from the pooled OLS and the fixed effect model results.Social implicationsImprovement in the national health system possibly through the widespread adoption of National Health Insurance, increase government spending on healthcare alongside increased beneficial trade and ease of doing business to facilitate investment were recommended to enhance.Originality/valueThe study used up-to-date data with appropriate methodology.

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“…This technique is extensively used in panel-data growth studies to allow for unobserved panel heterogeneity and simultaneously control for endogeneity bias arising from the possibility that one or more of the explanatory variables in growth regressions may not be strictly exogenous (see e.g. Aisen and Veiga, 2013;Bond et al, 2001;Christiansen et al, 2013;Guariglia and Poncet, 2008;Hoeffler, 2002;Rooth and Stenberg, 2012;Saidi and Aloui, 2010;Yamarik, 2010). Indeed, a common feature of most empirical growth models is that causation between the dependent and the right-hand-side variables may run in both directions, leading to endogeneity bias.…”

Section: Description Of the Data And Estimation Resultsmentioning

confidence: 99%