Estimation of gross refining margin of Indian petroleum refineries using Driscoll-Kraay standard error estimator

Joshi, Jignesh M.; Dalei, Narendra N.; Mehta, Pratik

doi:10.1016/j.enpol.2021.112148

Cited by 28 publications

(14 citation statements)

References 8 publications

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“…According to Joshi et al ( 68 ), preliminary analyzes should be made about what the panel data model will be to be selected among the pooled model, fixed model and random model. F-test is conducted to select between the fixed-effect model and the pooled ordinary least square model in panel data analysis.…”

Section: Methodsmentioning

confidence: 99%

“…F-test is conducted to select between the fixed-effect model and the pooled ordinary least square model in panel data analysis. Then, the Hausman test is used to determine the final model between fixed and random effect models ( 68 ).…”

Section: Methodsmentioning

confidence: 99%

“…The inferences drawn from the panel data are not conclusive and the statistical result is completely biased if the presence of cross-sectional dependence in the model. Therefore, diagnostic controls about the problems of the cross-sectional dependence, heteroscedasticity and serial correlation in the model should made to check the model's validity ( 68 ). Tests applied for diagnostic controls in this study are Bhargava et al Durbin-Watson and Baltagi-Wu LBI tests for autocorrelation, Modified Wald Test for heteroscedasticity, Breusch-Pagan LM Pesaran Scaled LM and Pesaran CD test for cross-sectional dependence.…”

Section: Methodsmentioning

confidence: 99%

“…In the case of autocorrelation, heteroscedasticity (changing variance), and cross-section dependence in a panel data analysis model, robust estimators should be used to overcome these problems. Joshi et al ( 68 ) states that the White (1980) estimator, the Rogers (1993) estimator and the Driscoll and Kraay ( 69 ) estimator can be considered as the appropriate estimators to draw a conclusive result. However, as stated by Joshi, et al ( 68 ) the Driscoll and Kraay estimator gives strong conclusive empirical results, and removes the deficits of the White and Rogers approach which produces inappropriate estimation when the cross-sectional dependence is present in the panel data set.…”

Section: Methodsmentioning

confidence: 99%

Section: Estimation Strategymentioning

confidence: 99%

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The relationship between health expenditure indicators and economic growth in OECD countries: A Driscoll-Kraay approach

Beylik¹,

Çıraklı

Çetin

et al. 2022

Front. Public Health

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IntroductionThe main purpose of the study is to examine the relationship between health expenditure indicators and economic growth in OECD countries.MethodsIn this context, health expenditures and economic indicators data of 21 OECD countries were analyzed by the Driscoll-Kraay standard error approach within the scope of panel data analysis. While Gross Domestic Product (GDP) and income per capita were used as dependent variables, the amount of out-of-pocket health spending, per capita health expenditure, the amount of public health expenditure, the ratio of drug expenditures to gross domestic product, the share of current health expenditures in GDP were used as independent variables.ResultsAccording to the results, in the model (Model 1) where real GDP level was used as the dependent variable, all health expenditure indicators were positively related to the economic growth. When the estimation results of Model 1 are examined, it is predicted that there will be an increase of 0.09% in GDP in case of a 1% increase in the share allocated to health services from GDP. In case of a 1% increase in the amount of out-of-pocket spending on healthcare, it is foreseen that there may be an increase of 0.04% in the real GDP. In the model (Model 2) where the per capita income variable is the dependent variable, it is seen that the increase in out- of-pocket health spending has a decreasing effect on the per capita income level, while the increase in public expenditures has an increasing effect on the per capita income level. From the findings of Model 2, it was found that if a 1% increase in the share of current health expenditures in GDP, there may be an increase of 0.06% in the amount of per capita income.DiscussionConcludingly, it is possible to say that that public resources allocated to health services play an important role in the economic growth.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Estimation Strategymentioning

confidence: 99%

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The relationship between health expenditure indicators and economic growth in OECD countries: A Driscoll-Kraay approach

Beylik¹,

Çıraklı

Çetin

et al. 2022

Front. Public Health

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Toward sustainable development: Does digitalization narrow the gender gap in the labor market?

Yin

Zhang

Choi

2023

Sustainable Development

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The direct and moderating impact of digitalization on the gender gap in the labor force participation rate is explored in this study. By analyzing the panel data of the G20 countries for the period of 2006–2021, we find that (1) the rising level of digitalization tends to narrow the gender gap in the labor force participation rate, with a greater gender gap‐narrowing effect in high‐income countries than in upper‐middle and lower‐middle income countries. (2) The interaction between digitalization and globalization has a small impact on the gender gap in the labor force participation rate in the full sample of the G20 countries, but the results are significantly different in countries divided by income level: the interaction is more likely to narrow the gender gap in the high‐income countries but widen the gender gap in upper‐middle and lower‐middle income countries. The gender gap‐widening effect is greater in upper‐middle income than in lower‐middle income countries. (3) Digitalization is more likely to increase the female employment rate and reduce the female unemployment rate, while it has the opposite effect on males; the female employment improvement effect is observed in the services sector.

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Roadmap to achieving sustainable development: Does digital economy matter in industrial green transformation?

Yang,

Xu,

Razzaq

et al. 2023

Sustainable Development

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The rapid advancements in the digital economy have created numerous opportunities and solutions for industrial green transformation. However, the complex relationship between these two has received relatively less attention. Therefore, this study analyses how the digital economy impacts industrial green transformation across 30 Chinese provinces. The empirical findings highlight the digital economy's significant role in driving industrial green transformation. Within this dynamic framework, two crucial operational mechanisms have been identified: heightened public awareness of environmental issues and the vigorous innovation of green technologies. It becomes evident that the digital economy can energize and sustain the momentum of industrial green transformation. Notably, this influence is most pronounced in eastern‐central China. However, its impact in western China appears relatively weaker, especially at higher quantiles. We observe a strong correlation between the evolution of the digital economy and industrial green transformation in terms of space and time. Higher spatiotemporal regression coefficients are primarily found in areas south of the Hu line, while lower values are more common in the northern regions. These findings provide insights into how the digital economy can be strategically applied to drive industrial green transformation.

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Estimation of gross refining margin of Indian petroleum refineries using Driscoll-Kraay standard error estimator

Cited by 28 publications

References 8 publications

The relationship between health expenditure indicators and economic growth in OECD countries: A Driscoll-Kraay approach

The relationship between health expenditure indicators and economic growth in OECD countries: A Driscoll-Kraay approach

Toward sustainable development: Does digitalization narrow the gender gap in the labor market?

Roadmap to achieving sustainable development: Does digital economy matter in industrial green transformation?

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