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This study aims to empirically examine the effects of smart cities on sustainable development for the period 1990–2019 for Türkiye.
Abstract
Purpose
This study aims to empirically examine the effects of smart cities on sustainable development for the period 1990–2019 for Türkiye.
Design/methodology/approach
The relationship between smart cities and sustainable development was analyzed with the help of the ARDL Bounds Test. In addition, the consistency of the model was tested with the FMOLS estimator. The indicators of the smart city were selected following the literature to represent smart cities, and the author created the smart city index. The study used other variables thought to impact sustainable development as secondary data.
Findings
The results show that smart cities positively and significantly impact sustainable development in Turkiye in both models during the sampling period. In addition, while real GDP, population density, and financial development variables positively affect sustainable development, population density has a negative effect on sustainable development, according to the results obtained from FMOLS estimators.
Originality/value
The first novelty of this study is the creation of the smart city index. The second novelty is that there are almost no studies on the effects of smart cities on sustainable development, especially for Türkiye.
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Kavita Kanyan and Shveta Singh
This study aims to examine the impact and contribution of priority and non-priority sectors, as well as their sub-sectors, on the gross non-performing assets of public, private…
Abstract
Purpose
This study aims to examine the impact and contribution of priority and non-priority sectors, as well as their sub-sectors, on the gross non-performing assets of public, private and foreign sector banks.
Design/methodology/approach
The Reserve Bank of India's database on the Indian economy is used to retrieve data over 13 years (2008–2021). Public sector (12), private sector (22) and foreign sector (44) banks are represented in the sample. Two-way ANOVA, multiple regression and panel regression statistical techniques are used in SPSS and EViews to examine the data. Further, the results are also validated by using robustness testing by applying the fully modified ordinary least square (FMOLS) and dynamic least square (DOLS) regression.
Findings
The results showed that, for private and foreign banks, the non-priority sector makes up the majority of the total gross non-performing assets, although both the priority and non-priority sectors are substantial for public sector banks. The largest contributors to the total gross non-performing assets in public, private and foreign banks are industries, agriculture and micro and small businesses. The FMOLS displays robustness results that are qualitatively similar to the baseline result.
Practical implications
Based on the study's findings about the patterns of non-performing assets originating from these specific industries, banks might improve the way in which these advanced loans are managed.
Originality/value
There has not been much research done on the subject of sub-sector-specific non-performing assets and how they affect total gross non-performing assets across the three sector banks. The study's primary focus will be on the issue of non-performing assets in the priority’s and non-priority’s sub-sectors, namely, agricultural, micro and small businesses, food credit, industries, services, retail loans and other priority and non-priority sectors.
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Yousra Trichilli, Mouna Boujelbène Abbes and Sabrine Zouari
This paper examines the impact of political instability on the investors' behavior, measured by Google search queries, and on the dynamics of stock market returns.
Abstract
Purpose
This paper examines the impact of political instability on the investors' behavior, measured by Google search queries, and on the dynamics of stock market returns.
Design/methodology/approach
First, by using the DCC-GARCH model, the authors examine the effect of investor sentiment on the Tunisian stock market return. Second, the authors employ the fully modified dynamic ordinary least square method (FMOL) to estimate the long-term relationship between investor sentiment and Tunisian stock market return. Finally, the authors use the wavelet coherence model to test the co-movement between investor sentiment measured by Google Trends and Tunisian stock market return.
Findings
Using the dynamic conditional correlation (DCC), the authors find that Google search queries index has the ability to reflect political events especially the Tunisian revolution. In addition, empirical results of fully modified ordinary least square (FMOLS) method reveal that Google search queries index has a slightly higher effect on Tunindex return after the Tunisian revolution than before this revolution. Furthermore, by employing wavelet coherence model, the authors find strong comovement between Google search queries index and return index during the period of the Tunisian revolution political instability. Moreover, in the frequency domain, strong coherence can be found in less than four months and in 16–32 months during the Tunisian revolution which show that the Google search queries measure was leading over Tunindex return. In fact, wavelet coherence analysis confirms the result of DCC that Google search queries index has the ability to detect the behavior of Tunisian investors especially during the period of political instability.
Research limitations/implications
This study provides empirical evidence to portfolio managers that may use Google search queries index as a robust measure of investor's sentiment to select a suitable investment and to make an optimal investments decisions.
Originality/value
The important research question of how political instability affects stock market dynamics has been neglected by scholars. This paper attempts principally to fill this void by investigating the time-varying interactions between market returns, volatility and Google search based index, especially during Tunisian revolution.
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The present study aims to examine the moderating impact of governance quality on the tourism poverty nexus using a panel of six South Asian Association for Regional Cooperation…
Abstract
Purpose
The present study aims to examine the moderating impact of governance quality on the tourism poverty nexus using a panel of six South Asian Association for Regional Cooperation (SAARC) countries during the period 2002 to 2019.
Design/methodology/approach
For the soundness of the results, fully modified ordinary least square (FMOLS) and dynamic ordinary least square (DOLS) econometric models were applied to determine the long-run relationship.
Findings
The findings confirmed the positive and significant impact of tourism development (international tourism arrival) and governance quality (effectiveness of governmental services) on poverty (per capita household consumption) reduction. Interestingly results confirm that governance quality and tourism development have complementary impacts on poverty reduction.
Originality/value
The present study has twofold contributions; First, despite the high potential of SAARC tourism, research remains limited in studies examining the role of tourism and governance quality on poverty reduction within the SAARC region. As a result, the present paper presents critical insights into the impact of tourism inflow and governance quality on poverty reduction in South Asian countries. Second, to the best of the author's knowledge, this is the first attempt to conduct an econometric analysis to examine the role of governance quality on the relationship between tourism inflow and poverty reduction in SAARC countries.
This study empirically assessed the influence of foreign direct investment on the manufacturing sector growth in the Middle East and North African region using panel data of 18…
Abstract
Purpose
This study empirically assessed the influence of foreign direct investment on the manufacturing sector growth in the Middle East and North African region using panel data of 18 countries covering the period of 1975–2017.
Design/methodology/approach
The study employed Levin et al. (2002) test (LLC) and Im et al. (2003) panel unit root test. Furthermore, Kao’s cointegration test was applied to examine the long-run relationship between the variables. Both the Dynamic OLS and Fully modified OLS were used in estimating the short-run relationship.
Findings
The results of the DOLS and FMOLS indicate that both inward and outward FDI influence the manufacturing sector growth positively. This shows that much of the manufacturing sector growth in the MENA region is driven by both inward and outward FDI. Our findings made a strong new proposition that aside from the negative influence proposed by Stevens and Lipsey (1992), outward FDI could also have a positive influence on the manufacturing sector of a country through effective utilization of domestic raw materials that are produced locally for production of goods in a foreign country.
Practical implications
MENA countries should concentrate more on making policies that will encourage the effective utilization of domestic resources for outward foreign direct investment in other countries of the world as it has the capacity to boost the manufacturing sector growth. Also, policies that will attract more inflows of FDI in the region should be encouraged. Both inward and outward FDI should be considered as an integral part of MENA economic policy in order to spur the manufacturing sector growth.
Originality/value
Previous empirical studies on the relationship between FDI and manufacturing sector growth have focused much on the influence of inward FDI. Thus, very little attention has been paid to the contribution that the outward FDI makes to the growth of the manufacturing sector of the host country. Our empirical study focused on the influence of both inward and outward FDI on the manufacturing sector growth with specific emphasis on the MENA region that remains the center of attraction of inward FDI and a source of inward FDI to most nonoil producing developing and developed countries given the oil-rich nature of the region.
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Chi Aloysius Ngong, Kesuh Jude Thaddeus, Lionel Tembi Asah, Godwin Imo Ibe and Josaphat Uchechukwu Joe Onwumere
This research investigates the bond between stock market development and agricultural growth in African emerging economies from 1990 to 2020.
Abstract
Purpose
This research investigates the bond between stock market development and agricultural growth in African emerging economies from 1990 to 2020.
Design/methodology/approach
Agricultural value added to the gross domestic product measures agricultural growth and market capitalization and stock value traded measure stock market development.
Findings
The findings disclose that market capitalization negatively affects agricultural growth while stock value traded positively affects agricultural growth in the fully modified and dynamic ordinary least square techniques. The findings unveil bidirectional causality between labour and agricultural value added with unidirectional causality flow from agricultural value added to market capitalization and stock value traded.
Research limitations/implications
The governments should promote agricultural growth initiatives which stimulate stock market development. Effective methods required to encourage credit flow to the agricultural enterprises through the stock markets' intermediation should be promoted using aggressive policies which eliminate credit flow bottlenecks. Policy makers and regulatory authorities should implement policies which attract investors to the agricultural sector and encourage companies' listing in the stock markets. The capital market funding should be expanded to boost economic growth through agricultural value added.
Originality/value
Literature reveals divergent results on the relationship between stock market development and agricultural growth. Earlier studies provide conflicting findings on the bond between stock market development and agricultural growth. Some findings indicate positive link between stock market development and agricultural growth, while others show a negative association. Studies' results reveal opposing directions of causality between stock market development and agricultural growth.
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Yogeeswari Subramaniam, Tajul Ariffin Masron and Nanthakumar Loganathan
Tourism has grown to be one of the world's largest and fastest-growing economic industries. Tourism development is viewed as a tool to improve income distribution as it allows…
Abstract
Purpose
Tourism has grown to be one of the world's largest and fastest-growing economic industries. Tourism development is viewed as a tool to improve income distribution as it allows people at the bottom of the pyramid to get involved in the industry. This study aims to examine the impact of tourism on income inequality in the top income equality countries.
Design/methodology/approach
The paper employs fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares techniques to investigate the dynamic impact of tourism on income inequality in the world's most income equality countries, from 2001 to 2016.
Findings
The result shows that tourism is one of the major drivers of income equality. Thus, tourism can be used to reduce a country's income disparity.
Practical implications
As a result, policymakers should support the tourism industry to reduce income disparity and enhance income distribution.
Originality/value
Given the conflicting findings in the literature, this study reexamines this link and attempts to backwardly assess if the top equal-income countries in the world are heavily dependent on tourism.
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Nazife Özge Beşer, Asiye Tütüncü, Murat Beşer and Cosimo Magazzino
This paper aims to investigate the influence of air and rail transportation on pollution in Turkey from 1970 to 2020.
Abstract
Purpose
This paper aims to investigate the influence of air and rail transportation on pollution in Turkey from 1970 to 2020.
Design/methodology/approach
Fourier Autoregressive Distributive Lags (ADL) and Fourier Fractional ADL cointegration tests (Banerjee et al., 2017; Ilkay et al., 2021) are employed to analyze the relationship be-tween the variables. Cointegration tests that take into account soft transitions under structural changes are implemented. Structural change issues are crucial for this topic since the changes in countries’ environmental policies and transportation habits are shaped by the decisions taken in relation to environmental regulations. Finally, for robustness purposes, we tested the estimated equation with a completely different methodology. Thus, a Machine Learning (ML) analysis is conducted, through a Ridge Regression (RR).
Findings
The findings obtained by applying Fourier Autoregressive Distributive Lags (FADL) and Fourier Fractional ADL cointegration tests, which can control for structural changes, reveal the existence of a long-term relationship between the variables. In addition, FMOLS estimates emphasize that economic growth and air transport can lead to increased pollution in the long run, while rail transport reduces it. Moreover, the statistically significant trigonometric terms indicate the existence of a smooth structural change among the variables. Robustness checks are performed through a Machine Learning (ML) analysis, which roughly confirms the previous results.
Originality/value
To our knowledge, existing research in Turkey focuses mainly on road transport, while the impact of rail and air transport on pollution has not yet been investigated. As such, this study will be a significant addition to the academic literature.
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Clifford Odame, Kingsley Opoku Appiah and Prince Gyimah
This paper examines the nexus between financial inclusion and the economic growth of an emerging market.
Abstract
Purpose
This paper examines the nexus between financial inclusion and the economic growth of an emerging market.
Design/methodology/approach
We use dataset from the World Bank and Heritage Foundations over the period 2005–2016 and fully modified least squares (FMOLS) and dynamic OLS (DOLS) to examine the financial inclusion–economic growth nexus in Ghana.
Findings
We document a negative relationship between financial inclusion and economic growth, and the causal nexus is unidirectional from financial access to GDP. Financial penetration, however, causes GDP growth, and GDP growth also causes financial penetration. We also document that IT infrastructure, the depth of financial services, employment and inflation drive economic growth in an emerging market.
Practical implications
The findings support international calls to prioritize financial penetration policies geared toward greater economic growth.
Originality/value
The paper adds to extant literature by highlighting new empirical insights on the financial inclusion–economic growth nexus from a sub-Saharan Africa market perspective.
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