Waste and organized crime in regional environments

D’Amato, Alessio; Mazzanti, Massimiliano; Nicolli, Francesco

doi:10.1016/j.reseneeco.2015.04.003

Cited by 81 publications

(10 citation statements)

References 45 publications

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“…In addition, the presence of first-order autocorrelation shows the need to establish a dynamic model. Furthermore, to acquire accurate and efficient parameter estimates, and to improve the robustness of our results, we eliminated cross-sectional dependence among errors by creating a year-dummy control variable [43][44][45][46]. The abovementioned conditions lead us to establish a dynamic panel vector autoregressive (VAR) model of first differences to test the relationships between the variables in question.…”

Section: Empirical Testmentioning

confidence: 99%

Causal Dynamic Relationships between Political–Economic Factors and Export Performance in the Renewable Energy Technologies Market

Sung

Chen

2018

Energies

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This study explores how political-economic forces could affect export performance in the renewable energy technologies market. We conduct panel framework analyses to verify the characteristics of panel data for 19 countries before establishing the panel estimator meant to test the effects of political-economic forces on export specialization. We consider the results of the panel framework analyses and develop an empirical model to test casual dynamic relationships between political-economic forces and export performance. The results from the least squares dummy variable-corrected estimation indicate that the major factors promoting the export specialization of renewable energy technologies are, in order of decreasing importance, public pressure, market size, and government demand-pull policy. However, the traditional energy industry has no significant effect on export performance. Finally, this study finds that dynamic effects exist in all estimations.

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Section: Empirical Testmentioning

confidence: 99%

Causal Dynamic Relationships between Political–Economic Factors and Export Performance in the Renewable Energy Technologies Market

Sung

Chen

2018

Energies

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“…So, checking the cross-sectional dependence is key to finding consistent and reliable results using the GMM parameter. Notably, creating the year-dummy control variable can check cross-individual correlation (D'Amato et al. , 2015; Roodman, 2009a,b; Sarafidis et al.…”

Section: Methodsmentioning

confidence: 99%

Does infrastructural development allure foreign direct investment? The role of Belt and Road Initiatives

Rehman

Islam

Sohag

2022

IJOEM

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PurposeChina's Belt and Road Initiative (BRI) is the most ambitious investment strategy for infrastructural development belonging to the significant potential for stimulating regional economic growth in Asia, Europe and Africa. This study aims to investigate the impact of infrastructure on spurring inward foreign direct investment (FDI) within the purview of human capital, GDP per capita, foreign aid, trade, domestic investment, population and institutional quality in BRI countries.Design/methodology/approachIn doing so, the authors analyze panel data from 2000 to 2019 within the framework of the system generalized method of movement (GMM) approach for 66 BRI countries from Europe, Asia, Africa and the Middle East.FindingsThe investigated results demonstrate that aggregate and disaggregate infrastructure indices, e.g. transport, telecommunications, financial and energy infrastructures, are the driving forces in attracting foreign direct investment (FDI) in the BRI countries. In addition, control variables (i.e. institutional quality, human capital, trade, domestic investment, foreign aid and GDP per capita) play an essential role in spurring FDI inflows.Originality/valueThe authors’ study uniquely investigates both the pre- (2000–2012) and post- (2013–2019) BRI scenarios using the aggregate and disaggregate infrastructural components from the perspectives of full and clustered sample regions, such as Asia, Europe, Africa and the Middle East. The study provides several policy implications.

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“…Hence, we employ a dependent variable in the previous period as an independent variable to control for autocorrelation. To control for cross-individual correlation, we create year dummy control variables following Sarafidis et al [61] and Roodman [65] to improve the robustness of our results [66]. The presence of unit roots demonstrates that the first-differenced variables should be used to estimate an empirical model.…”

Section: Empirical Analysismentioning

confidence: 99%

How Knowledge Assets Affect the Learning-by-Exporting Effect: Evidence Using Panel Data for Manufacturing Firms

Kim

Sung

2020

Sustainability

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Using panel data from Korean manufacturing firms, this study empirically investigates how knowledge assets impact the relationship between exports and productivity. We consider a scenario in which firms are situated in a globally competitive, knowledge-based environment. We establish a dynamic panel vector autoregressive model by considering the outcomes of various panel framework tests. A generalized method of moments estimator is employed to test the dynamic relationships among the variables, and a post-estimation test, Granger causality test, and impulse response test are performed. Our findings indicate the existence of a learning-by-exporting effect on the enhancement of total factor productivity (TFP). The result show that TFP can be improved by interacting with exports and knowledge assets, and that firms’ knowledge assets significantly and positively affect their exports. However, industry competition, as an external force, does not contribute to boosting firms’ productivity. We highlight the importance of continuously upgrading productivity, exports, knowledge assets, and industry competition by demonstrating that the present levels of these elements serve as the main source of their own future values. Finally, the implications of our results are outlined.

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Waste and organized crime in regional environments

Cited by 81 publications

References 45 publications

Causal Dynamic Relationships between Political–Economic Factors and Export Performance in the Renewable Energy Technologies Market

Causal Dynamic Relationships between Political–Economic Factors and Export Performance in the Renewable Energy Technologies Market

Does infrastructural development allure foreign direct investment? The role of Belt and Road Initiatives

How Knowledge Assets Affect the Learning-by-Exporting Effect: Evidence Using Panel Data for Manufacturing Firms

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