Search results

Robots are widely used in industrial manufacturing and service industries around the world. However, most of the previous studies on industrial robots use data at the national or industry level in the context of developed countries. This study examines the impact of imported industrial robots on firm innovation at the firm level in China.

Drawing on a large dataset of more than three million records in China, including non-publicly traded small and medium firms, the authors adopt a difference-in-differences method to investigate the impact and channels of industrial robots on firm innovation.

The authors find that the application of industrial robots increases firm innovation. Two possible channels are identified through which robots promote innovation: alleviation of financial constraints and the improvement of human capital. Further analysis shows that the effect of robots on innovation is more pronounced for firms that are highly dependent on external financing, belong to high-tech industries, import high-end robots, have insufficient supply of skilled labor and private firms (non-SOEs). The authors also find that industrial robots increase the firms' innovation quality and the marginal contribution of innovation to firms' total factor productivity.

This study provides big data evidence of the unintended positive consequences of industrial robots on firm innovation. The results are helpful to clarify the controversy of industrial robots. It also has important implications for government industrial policy making, firm innovation and human resource management.

The main objective of this research is to investigate if there is a long-term relationship between “terrorism” and sustainable “economic growth” in Big Ten Countries.

The data was tested via Panel ARDL Analysis. The growth rate (GR) is the dependent variable, and the “Global Terror Index (GTI)” is the independent variable as the terror indicator. The ratio of Foreign Direct Investment (FDI) to the Gross Domestic Product (GDP), and the ratio of External Balance (EB) to Gross Domestic Product (GDP) are included in the model as the control variables due to their effect on the growth rate. A Panel ARDL analysis is conducted to examine the existence of long-term co-integration between terror and the economy. The planning of the study, the formation of its theoretical and conceptual framework, and the literature research were carried out in 2 months, and the collection of data, the creation of the methodology and the analysis of the analyzes were carried out in 2 months, the interpretation of the findings and the development of policy recommendations were carried out within a period of 1 month. The entire study was completed in a total of 5 months.

Results showed that “Terror” has a negative impact on “Growth Rate” in the long term while “External Balance” and “Foreign Direct Investment” positively affect the Growth Rate. The coefficients for the short term are not statistically significant.

The sample is only limited to Big Ten including China, India, Indonesia, South Korea, Argentina, Brazil, Mexico, Turkey, Poland and South Africa. The period for annual data collection covers the years between 2002 and 2019 and due to the unavailability of data.

Considering the risks and the mutual negative effect that turns into a vicious circle between terrorism and the economy, it is necessary to eliminate the problems that cause terrorism in the mentioned countries, on the one hand, and to develop policies that will improve economic performance on the other.

Trustful law enforcement bodies have to be established and supported by all technological means to prevent terror. The conditions causing terror have to be investigated carefully and the problems causing terror or internal conflict have to be solved. International cooperation against terrorism has to be strengthened and partnerships, information, experience sharing have to be supported at the maximum levels.

It is certain that terror might have a negative influence on the performance of economies. But the limited number of studies within this vein and the small size of their sample groups mostly including single-country case studies require conducting a study by using a larger sample group of countries. Big Ten here represents at least half of the population of the world and different regions of the Globe.

The main objective of this article is to analyze the role of governance quality in influencing the economic growth of 22 selected Sub-Saharan African Countries.

The study applied the panel dynamic Generalized Method of Moments (GMM) to analyze the data obtained from the World Bank database over the period from 2002 to 2020.

The overall finding indicated that the composite governance index has a positive significant effect on the economic growth of the countries; where a unit improvement in the aggregate governance index leads to a 3.05% increase in GDP. The disaggregated result has shown that corruption control and government effectiveness have a negative significant effect on growth performance, whereas, the rule of law and regulatory quality showed a positive significant effect. Political stability and voice and accountability have an insignificant effect on economic growth.

Due to data limitations, this study could not address the whole members of Sub Sahara African Countries and could not see the causal relationship.

The study suggested a strong commitment to the implementation of policy and reform measures on all governance factors. This may add to the need to devise participatory corruption control mechanisms; to closely look at the proper implementation of policies and reforms that constitute the government effectiveness factors, and properly implement the rule of law at all levels of the government with a strong commitment to realizing it so that citizens at all levels can have full confidence in and abide by the rules of society.

Even though there are some studies conducted using conventional methods of panel data analysis such as random effect or fixed effects, this empirical study used more advanced panel dynamic generalized moment of methods to examine the role of improvement in governance quality on economic growth.

This study examines the effect of social media marketing on voting intention applying a combination of fuzzy logic methodology and a multidimensional panel data model.

The study adopts a multidimensional panel data method that includes several fixed effects. The dependent variable is a multifaceted construct that measures the participants’ intention to vote. The independent variables are electronic word of mouth (eWOM), customisation (CUS), entertainment (ENT), interaction (INT), trendiness (TRD), candidate’s perceived image (CPI), religious beliefs (RB), gender and age. The grouping variables that signify fixed effects are employment status, level of education, mostly used social media and religion. First, the significance of said fixed effects was tested through an ANOVA process. Then, the main model was estimated, including the significant grouping variables as fixed effects.

Employment status and level of education were significant fixed effects. Also, eWOM, ENT, INT, CPI, RB and gender significantly affected participants’ voting intention.

Being based on a questionnaire that asked participants about how they perceive different aspects of social media, the present study is limited to their perceptions. Therefore, further studies covering the voters’ behaviour in action could be efficient complements to the present study.

The findings could guide the political parties into prioritizing the aspects of social media in forming an effective campaign resulting in being elected.

The findings have the potential to help the public in making better informed decisions when voting. Furthermore, the results of this study indicate applications for social media which are beyond leisure time fillers.

Fuzzy logic and multidimensional panel data estimates are this study’s novelty and originality. Structural equation modelling and crisp linguistic values have been used in previous studies on social media’s effect on voting intent. The former refines the data gathered from a questionnaire, and the latter considers the possibility of including different grouping factors to achieve a more efficient and less biased estimation.

The purpose of this research is to systematically scrutinize the influence of macroeconomic determinants on trade openness, through the lens of various trade theories, with a particular focus on the economies of the GIPSI countries – Greece, Ireland, Portugal, Spain and Italy.

This study investigates the macroeconomic factors influencing trade openness in the GIPSI economies from 1995 to 2020. Methods include stepwise regression (SR) for model selection, Pedroni panel cointegration test and panel regression results. The analysis uses advanced panel regressions, including FMOLS, Panel OLS and FEM. The long-term dynamics were tested using Pedroni cointegration, while Granger causality testing was used to examine the causal direction between the trade openness ratio and trade determinant.

The results show both long-term and short-term relationships between trade openness and (1) foreign direct investment, (2) labor force participation rate, (3) trade reserves and (4) trade balance. The researchers also detected unidirectional and bidirectional causality relationships between trade openness and these four factors. The study also revealed that trade reserves (TR) emerge as the most influential determinant of trade openness, and per capita income does not exhibit economic significance concerning the trade openness of GIPSI economies.

This research is conducted within the context of the GIPSI nations (Greece, Ireland, Portugal, Spain and Italy). As such, the outcomes may not be universally applicable to other economic systems due to the distinct institutional settings and governance structures across different economic groups. Future investigations may explore the relationship between trade openness and its determinants by incorporating different variables.

To the best of the authors' knowledge, this is the first study investigating the theory that suggested trade drivers drive the trade openness of GIPSI countries context. By focusing on GIPSI countries, the study offers a unique perspective on the dynamics of trade openness in economies that have experienced financial crises and stringent austerity measures.

Despite the importance of tax policy in reducing energy consumption and carbon emissions, there is a dearth of research on the environmental impact of indirect taxes. This paper examines the impact of indirect taxes on carbon dioxide (CO₂) emissions, with an emphasis on institutional quality.

The study uses the Government Revenue Dataset (2021), comprising 143 countries, dividing into 114 developing and 29 developed countries, during the period between 1996 and 2019. The author adopts panel data techniques, with Driscoll–Kraay standard errors to account for the issue of cross-sectional dependence (CSD).

The results indicate that indirect tax revenues have a negative and significant impact on CO₂ emissions for the total sample. The subsample analysis revealed that while indirect taxes reduce carbon emissions in developing countries, opposed results are reported for developed countries. This finding implies that most of the advanced countries have already reached a high level of taxes, at which carbon emissions increase as indirect tax increases further. Interestingly, the results revealed that institutional quality enhances the role of indirect taxes in mitigating carbon emissions for both developing and developed countries.

To the best of the authors' knowledge, this is the sole study using the newly developed tax data by the United Nations University, World Institute for Development Research (UNU-WIDER) to investigate the impact of indirect taxes on carbon emissions, with an emphasis on institutional quality. The existing literature focuses on specific taxes, like carbon taxes, with no comprehensive research on the link between indirect taxes and carbon emissions.

Entrepreneurial activity is a phenomenon that increases the economic growth of countries and improves their social welfare. The economic development levels of countries have significant effects on these entrepreneurial activities. This research examines which institutional and macroeconomic variables explain early-stage entrepreneurship activities in developed and developing economies.

The authors conducted panel data analysis on the data from the Global Entrepreneurship Monitor (GEM) and International Monetary Fund (IMF) surveys covering the years 2009–2018.

First, the authors' results reveal that cognitive, normative and regulatory institutions and macroeconomic factors affect early-stage entrepreneurial activity in developed and developing countries differently. Second, the authors' findings indicate that cognitive, normative and regulatory institutions affect early-stage entrepreneurship more positively in developed than developing countries. Finally, the authors' results report that macroeconomic factors are more effective in early-stage entrepreneurial activity in developing countries than in developed countries.

This study provides a better understanding of the components that help explain the differences in entrepreneurship between developed and developing countries regarding institutions and macroeconomic factors. In this way, it contributes to developing entrepreneurship literature with the theoretical achievements of combining institutional theory and macroeconomic indicators with entrepreneurship literature.

This article investigates the long-run impact of remittance inflows on agricultural productivity (AGP) in emerging Asian economies (Bangladesh, Sri Lanka, Malaysia, India, Nepal, Philippines, Pakistan, and Vietnam), employing a panel dataset from 2000 to 2018.

This study initially applies cross-sectional dependence (CSD), second-generation unit root, Pedroni, and Westerlund panel co-integration techniques. Next, it uses the augmented mean group (AMG) and common correlated effect mean group (CCEMG) methods to investigate the long-term impact of remittance inflows on AGP while controlling for several other important determinants of agricultural growth, such as cultivated area, fertilizers, temperature change, credit, and labor force.

The empirical findings are as follows: The results first revealed the existence of CSD and long-term co-integration between AGP and its determinants. Second, remittance inflows significantly boosted AGP, indicating that remittance inflows played a crucial role in improving AGP. Third, global warming (changes in temperature) negatively impacts AGP. Finally, additional critical elements, for instance, cultivated area, fertilizers, credit, and labor force, positively affect AGP.

This study suggests that policymakers of emerging Asian economies should develop an exclusive remittance-receiving system and introduce remittance investment products to utilize foreign funds and mitigate agricultural production risks effectively.

This is the first empirical examination of the long-term impact of remittance flows on agricultural output in emerging Asian economies. This study utilized robust estimation methods for panel data sets, such as the Pedroni, Westerlund, AMG, and CCEMG tests.

The purpose of this study is to examine the impact of anti-money laundering (AML) regulations on accrual earnings management (AEM) and real earnings management (REM) in Iran’s emerging capital market.

The panel data regression is used to testing hypotheses. The sample includes 2,020 data and 202 companies listed on the Tehran Stock Exchange (TSE) over a period of ten years from 2012 to 2021. Also, the companies covered in this study include financial and nonfinancial companies. Furthermore, the data related to the research variables were extracted from the annual financial statements and the TSE database.

The results show that compliance with AML regulations leads to a reduction in AEM and REM. In other words, companies with higher money laundering (ML) tend to manage their earnings, which is in line with agency theory.

This study has implication for policymakers and regulators, auditors and managers. Considering the negative impact of AML regulations on earnings management (EM), Iranian auditing firms need to emphasize on the full implementation of AML regulations in TSE. Also, the results of this research may aid policymakers and regulators to detect financial crimes through accounting signals.

To the best of the authors’ knowledge, this is the first study in an Iran capital market to examine the impact of AML regulations on EM in financial and nonfinancial companies. Previous research has not controlled for the effects of financial companies. Prior studies have not examined the effects of financial companies. In addition, this study differentiates itself from previous studies by introducing a new method for measuring the independent ML variable based on auditor opinions. The obtained data can aid international bodies to better understand compliance with ML regulations in Iran and can reduce their concerns in negotiations.

In this study the authors aim to comprehensively investigate the determinants of voting behavior in Turkey, with a specific focus on the dynamics of the center-periphery debate. Mainly, the authors focus on regional voting patterns during the period that is dominated by the Justice and Development Party (JDP/AKP) in the elections. The authors apply the random effects generalized least squares (GLS) methodology, and analyze electoral data covering four pivotal parliamentary elections (2007, 2011, 2015 and 2018) across all 81 provinces (NUTS III regions). The authors individually examine voting dynamics of the four major parties in parliament: the JDP/AKP, the Republican People's Party (RPP/CHP), the Nationalist Movement Party (NMP/MHP) and the Peoples' Democratic Party (PDP/HDP). The authors contribute to a comprehensive understanding of how socioeconomic cleavages, economic performance, party alignment and social dynamics shape voter preferences in the Turkish context, thereby addressing gaps in the existing literature.

This research employs an ecological study of Turkish NUTS III sub-regions, covering national elections from 2007 to 2018. The authors utilize the random effects GLS method to account for heteroscedasticity and time effects. The inclusion of the June and November 2015 elections enables a comprehensive analysis of the evolving dynamics in Turkish voting behavior. The results remain robust when applying pooled OLS and fixed effect OLS techniques for control.

The study's findings reveal that economic performance, specifically economic growth, plays a pivotal role in the sustained dominance of the JDP/AKP party. Voters closely associate JDP preference with economic growth, resulting in higher voting shares during periods of economic prosperity. Along with economic growth; share of agriculture in regions' GDP, female illiteracy rate, old population rate, net domestic migration, terrorism and party alignment are also influential factors in the Turkish case. Furthermore, differences among sociocultural groups, and East–West dichotomy seem to be important factors that reveal the impact of social cleavages to understand electoral choice in Turkey.

This study contributes to the existing literature by offering a comprehensive multidimensional analysis of electoral behavior in Turkey, focusing on the JDP/AKP dominance period. The main contribution of this study is its multidimensional perspective on the power bases of all main parties, considering key voter choice theories (cleavages, party alignment and retrospective economic performance voting) that have not been systematically analyzed in prior research. The main research question of this study is to examine which factors affect voting behavior in Turkey and how the dynamics of center-periphery or eastern-western region voting behavior under the JDP hegemony can be explained. The contribution of this study consists not only in its empirical testing of panel data approaches but also in its comprehensive analysis of four major political parties. Building upon existing studies in the literature, this research seeks to extend the understanding of voting dynamics for the four main parties in the parliament — JDP/AKP, RPP/CHP, NMP/MHP and PPDP/HDP — by delving into their dynamics individually, thereby expanding the scope of previous studies. This study aims to make a contribution by not only empirically testing panel data approaches but also conducting a comprehensive analysis of four major political parties. Furthermore, the separate inclusion of the 2015 elections and utilization of a panel data approach enrich the analysis by capturing the evolving dynamics of Turkish voting behavior. The study underscores the significance of socioeconomic factors, economic performance and social cleavages for voters' choices within the context of a dominant party rule.