Robust Causality Test of Infinite Variance Processes

Author(s):  
Fumiya Akashi ◽  
Masanobu Taniguchi ◽  
Anna Clara Monti ◽  
Tomoyuki Amano
2020 ◽  
Vol 216 (1) ◽  
pp. 235-245
Author(s):  
Fumiya Akashi ◽  
Masanobu Taniguchi ◽  
Anna Clara Monti

2020 ◽  
Vol 7 (54) ◽  
pp. 205-217
Author(s):  
Mnaku Honest Maganya

AbstractTanzania, like most other developing countries, faces numerous economic challenges in striving to achieve sustainable economic growth and development through taxation. In the literature, the debate on how effective taxes are as a tool for promoting economic growth and economic development remains inconclusive, as various research have reported mixed effects of tax on economic growth. This article investigates the effect of taxation on economic growth in Tanzania using the recently developed technique of autoregressive distributed lag model (ARDL) bounds testing procedure for the period from 1996 to 2019. Various preliminary tests were conducted including stationary tests as well as the pair-wise Granger causality test. According to the results obtained, domestic goods and services (TGS) taxes are positively related to GDP growth and are statistically significant at 1% level. Income taxes, on the other hand, were found to be negatively related to GDP growth and to be statistically significant at 5% level. The pair-wise Granger causality results indicated that there is bidirectional Granger causality between TGS and GDP growth at 1 % significance level. The government should aim at growing, nurturing and sustaining tax base to positively drive economic growth even further.


2020 ◽  
Vol 8 (10) ◽  
pp. 105-111
Author(s):  
Khujan Singh ◽  
Anil Kumar

The present study is an attempt to examine long run relationship among India’s GDP, Exports and Imports for which yearly time series data from 1995 to 2018 has been collected. Data for India’s GDP has been collected from RBI website and India’s export and import data has been collected form Ministry of Commerce and Industry website. The Augmented Dickey-Fuller unit root test for stationarity found that studied variables become stationary at first order of difference. While, Johnson cointegration test revealed long run cointegration between India’s GDP, exports and imports. The results of VECM Granger causality test exhibited bi-directional relationship between India’s GDP and India’s exports, whereas uni-directional relation has been found between India’s GDP and India’s imports. These results have significant implication for India’s export import policy and to achieve a target of $5 trillion economy till 2024-2025.


2020 ◽  
Author(s):  
Karar Zunaid Ahsan ◽  
Rashida Ijdi ◽  
Peter Kim Streatfield

UNSTRUCTURED Given the low Covid-19 testing coverage in the country, this study tested whether the daily change in the number of new Covid-19 cases is due to increase (or decrease) in the number of tests done daily. We performed Granger causality test based on vector autoregressive models on Bangladesh case and test numbers between 8 March and 5 June 2020, using publicly available data. The test results show that the daily number of tests Granger-cause the number of new cases (p <0.001), meaning the daily number of new cases is perhaps due to an increase in test capacity rather than a change in the infection rates. From the results of this test we can infer that if the number of daily tests does not increase substantially, data on new infections will not give much information for understanding covid-19 infection dynamics in Bangladesh.


2020 ◽  
Vol 8 (7) ◽  
pp. 530
Author(s):  
Jeho Hwang ◽  
Sihyun Kim

Local residents living adjacent to ports are directly affected by the fine dust generated from the port operations. There is a need to prepare detailed measures according to cargo type given the high correlation between the types of dust-producing cargo primarily managed at ports and local industries. This study attempts to establish the attributes of the cargo handled at ports and the relationship between supply chains built for local key industries and the air quality of the local community. It aims to ascertain which cargo needs managing preemptively at the local level, based on the major cargo types handled in a port. A correlation analysis and Granger causality test were performed to investigate the causality between the factor of cargo and fine dust concentrations. The results in this study indicate the necessity for intensive management of scrap metal cargo among the major cargo handled at the target port, which confirms the large effect of management on fine dust reduction, as well as on reduction efficiency. The results suggest requirements to expand the regulations on the emissions of supply chains by cargo type, not by industry type. Additionally, it is required to minimize the blind spots of management and form an eco-friendly supply chain by introducing green technology. The preparation of emission control measures is also necessary. The findings provide useful insights for the sustainable operations of the local supply chain around the target port and will help the strategic agenda for future improvement.


2021 ◽  
Vol 13 (6) ◽  
pp. 3039
Author(s):  
Tomiwa Sunday Adebayo ◽  
Sema Yılmaz Genç ◽  
Rui Alexandre Castanho ◽  
Dervis Kirikkaleli

Environmental sustainability is an important issue for current scholars and policymakers in the East Asian and Pacific region. The causal and long-run effects of technological innovation, public–private partnership investment in energy, and renewable energy consumption on environmental sustainability in the East Asian and Pacific regions have not been comprehensively explored while taking into account the role of economic growth using quarterly data for the period 1992–2015. Therefore, the present study aims to close this literature gap using econometric approaches, namely Bayer–Hanck cointegration, autoregressive distributed lag (ARDL), dynamic ordinary least square (DOLS), and fully modified ordinary least square (FMOLS) tests. Furthermore, the study utilizes the frequency domain causality test to capture the causal impact of public–private partnership investment in energy, renewable energy consumption, technological innovation, and economic growth on CO2 emissions. The advantage of the frequency domain causality test is that it can capture the causality between short-term, medium-term, and long-term variables. The outcomes of the ARDL, FMOLS and DOLS show that renewable energy consumption and technological innovation mitigate CO2 emissions, while public–private partnership investment in energy and economic growth increase CO2 emissions. Moreover, the frequency causality test outcomes reveal that technological innovation, public–private partnership investment in energy, and renewable energy consumption cause CO2 emissions, particularly in the long-term. Thus, as a policy recommendation, the present study recommends promoting renewable energy consumption by focusing more on technological innovation in the East Asia and Pacific regions.


2021 ◽  
Vol 16 (1) ◽  
pp. 130-151
Author(s):  
Fernanda Andrade de Xavier ◽  
Aparna P. Lolayekar ◽  
Pranab Mukhopadhyay

We study the effect of revenue decentralization (RD) and expenditure decentralization (ED) on sub-national growth in India from 1981–1982 to 2015–2016 for 14 large (non-special-category) states. Our study provides evidence that both RD and ED play a defining role in India’s sub-national growth in this three-and-a-half-decade period. We use a panel data model with fixed effects (FE) and Driscoll and Kraay standard errors that control for heteroscedasticity, autocorrelation and cross-sectional dependence. To test for causality between growth and decentralization, we use the Granger non-causality test. The regression analysis is supplemented with the distribution dynamics approach. We find that: (a) While decentralization Granger-caused economic growth, the reverse causality effect of growth on decentralization was not significant; (b) Economic growth increased significantly after liberalization; (c) Decentralization, capital expenditure and social expenditure had significant positive impacts on economic growth; and (d) States that had high levels of decentralization also had high levels of per capita income, while states that had low decentralization also exhibited low per capita income.


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