Search results

This study aims to estimate the quality-adjusted changes in residential mobile consumer prices by controlling for the changes in the relevant service characteristics and quality, in a case study on Hungary between 2015 and 2021; compare the results with changes measured by the traditionally calculated official telecommunications price index of the Statistical Office; and discuss separating the hedonic price changes from the effect of a specific government intervention that occurred in Hungary, namely, the significant reduction in the value added tax rate (VAT) levied on internet services.

Since the price of commercial mobile offers does not directly reflect the continuous improvements in service characteristics and functionalities over time, the price changes need to be adjusted for changes in quality. The authors use hedonic regression analysis to address this issue.

The results show significant hedonic price changes over the observed seven-year period of over 30%, which turns out to be primarily driven by the significant developments in the comprising service characteristics and not the VAT policy change.

This paper contributes to the literature on hedonic price analyses on complex telecommunications service plans and enhances this methodology by using weights and analysing the content-related features of the mobile packages.

We seek to quantify the relationship between urbanization and economic growth in China using recent advances in econometric techniques.

This study adopts a smoothed instrumental variables quantile regression (SIVQR) estimator to obtain consistent estimates of the effects of urbanization on economic growth in China. Our approach accounts for the differential impacts of urbanization across the conditional distribution of economic growth while allowing for an identification strategy that addresses the endogeneity of urbanization. Our main findings reveal that ignoring urbanization endogeneity leads to inconsistent estimates of urbanization effects. Further, we find a positive relationship between urbanization and growth resembling an inverted U-shape. This supports the hypothesis that the beneficial effects of urbanization intensify at initial stages while diminishing beyond a certain threshold, due perhaps to weakening scale economies.

Our main results indicate that the individual productivity gains brought by urbanization outweigh the negative effects thereof that impede productivity, thus contributing to the economic growth in China. Further, we find that ignoring differential impacts of urbanization underestimates the beneficial effects of urbanization for provinces whose quality of governance is in the vicinity of the center of quality distribution. Ignoring the endogeneity of urbanization generates inconsistent estimates of the elasticity of economic growth with respect to urbanization. Finally, we estimate an inverted U-shape resembling relationship between urbanization and growth.

First, future studies would benefit from incorporating more data as provinces further east on the mainland become more urbanized and urbanization runs its course. Second, controlling the barriers to rural-urban mobility would contribute to the robustness of the estimated relationship between urbanization and growth once such data became available. Unveiling the impact of government-imposed barriers is key to designing optimal policies that help fuel economic growth in the country. Finally, future research could benefit from information on urbanization sources not considered here such as inter-provincial migration, as such data become publicly available.

Quantifying the beneficial effects of urbanization on economic growth can help guide the government in China to further fuel the growth through a set of relevant policy tools that promote urbanization.

Rural-urban migration in China lays the groundwork for economic advancement in recipient cities and economies, as it may induce scale economies. This can benefit both the economy at large and the migrants.

The SIVQR estimator accounts for potential heterogeneous effects of urbanization across the entire conditional distribution of growth while allowing for an identification strategy that addresses the endogeneity of urbanization. An additional distinguishing feature of the current study is our use of the most recent novel, provincial-level data obtained from the National Bureau of Statistics of China. Our focus on a single country allows sidestepping issues arising from the inconsistency of the definition of urban across different countries while accounting for intra-country urbanization drivers intrinsic to China, such as natural features and geographic characteristics. Therefore, our approach has the potential to sidestep the bias resulting from the differences in mechanisms behind urbanization-growth relationships across different countries.

This paper aims to analyse the influence of workforce diversity on the firm’s likelihood to develop organisational innovations. Operationalising human resources diversity is not straightforward, and its effect has been rather overlooked in the context of non-technological innovations. This study analyses the impact of task-related diversity among research and development (R&D) unit workers and women R&D workers, in particular.

To estimate the impact of task-related diversity on firm propensity to undertake organisational innovation, this study uses a generalised linear model (GLM) – with a binomial family and log–log extension. GLMs are used to control problems of over-dispersion, which, in models with binary response variables, could generate inaccurate standard error estimates and provide inconsistent results.

This paper provides three important results. Firstly, employee diversity increases the firm’s propensity to engage in organisational innovations. Secondly, the influence of each facet of task-related diversity varies depending on the type of organisational innovation considered. Thirdly, gender has an effect on the innovation process; this study shows that women play a different role in the production of non-technological innovations.

This paper makes several contributions to the literature. Firstly, it makes a theoretical contribution to research on innovation management by considering the influence of human resources diversity on the development of non-technological innovations. Secondly, this study analyses the role of workforce diversity in an R&D department context to clarify the contribution made by women R&D workers.

This study forecasts the government expenditure components in Nigeria, including recurrent and capital expenditures for 2021 and 2022, based on data from 1981 to 2020.

The study employs statistical/econometric problems using the Feasible Quasi Generalized Least Squares approach. Expenditure forecasts involve three simulation scenarios: (1) do nothing where the economy follows its natural path; (2) an optimistic scenario, where the economy grows by specific percentages and (3) a pessimistic scenario that defines specific economic contractions.

The estimation model is informed by Wagner's law specifying a positive link between economic activities and public spending. Model estimation affirms the expected positive relationship and is relevant for generating forecasts. The out-of-sample results show that a higher proportion of the total government expenditure (7.6% in 2021 and 15.6% in 2022) is required to achieve a predefined growth target (5%).

This study offers empirical evidence that specifically requires Nigeria to invest a ratio of 3 to 1 or more in capital expenditure to recurrent expenditure for the economy to be guided on growth.

This study aims to explore the effects of intellectual capital (IC) on the occurrence of a modified audit opinion decision. The authors expect that high IC intensive firms are positively associated with the occurrence of a modified audit opinion since they are associated with an increased business risk and are more likely to exhibit issues concerning their financial health and stability.

Using a data sample of 423 listed firms from Greece, Italy, Spain and Portugal over a 10-year period, the authors estimated a logistic regression model to examine the effects of IC on the probability that a modified audit opinion is issued. The authors used organizational capital as a measure of a firm’s intensity on IC.

Empirical findings indicate a significant and positive relationship between the IC and the likelihood of a firm receiving a modified audit opinion decision.

This study expands prior literature by exploring the predictive ability of IC on the likelihood of a firm receiving a modified audit opinion decision.

Trade can be severely impacted by economic crisis whatever might have been the trigger. Protectionist tendencies are also normally on the rise during such times having further impact on trade and associated variables. In this chapter, an attempt has been made to assess the impact of economic crisis on international trade. Three episodes of crisis have been picked up for the same, the oil crisis of early 1970s, the global financial crisis (GFC) of 2007–2008, and the COVID-19 crisis of 2019. Each episode is triggered by different factors. Do the differing triggers ultimately lead to different impact on trade? This chapter first tries to answer this question at aggregate trade level and then across country groups and product groups. Interesting trends are observed. Across product groups, both agricultural and manufacturing goods exports were more impacted during the GFC, whereas for services exports, the impact was severe during the COVID-19 pandemic. Across country groups, the high-income countries were more impacted during the first two episodes, whereas the less-developed countries (LDCs) were more impacted during the pandemic. Further, a gravity model estimation was attempted to empirically measure the effects of crisis for the world as a whole and for India and China separately. All country bilateral trades were significantly impacted by the three episodes. After controlling for the relevant factors for India and China, certain differences in impact are observed. China seems to be less impacted by destination country factors.

The aim of this paper is to explore the possibility of using the Define-Measure-Analyze-Improve-Control (DMAIC) cycle, process mining (PM) and multi-criteria decision methods in an integrated way so that these three elements combined result in a methodology called the Agile DMAIC cycle, which brings more agility and reliability in the execution of the Six Sigma process.

The approach taken by the authors in this study was to analyze the studies arising from this union of concepts and to focus on using PM tools where appropriate to accelerate the DMAIC cycle by improving the first two steps, and to test using the AHP as a decision-making process, to bring more excellent reliability in the definition of indicators.

It was indicated that there was a gain with acquiring indicators and process maps generated by PM. And through the AHP, there was a greater accuracy in determining the importance of the indicators.

Through the results and findings of this study, more organizations can understand the potential of integrating Six Sigma and PM. It was just developed for the first two steps of the DMAIC cycle, and it is also a replicable method for any Six Sigma project where data acquisition through mining is possible.

The authors develop a fully applicable and understandable methodology which can be replicated in other settings and expanded in future research.

In the context of sustainable development goal 5 of the United Nations 2030 Agenda: “Achieve gender equality and women’s empowerment”, where gender equality is not only a matter of justice but also essential to achieve sustainable development, this paper aims to examine the gender pay gap in executive director compensation and the influence of female board representation and participation in nomination and remuneration committee (NRC) on this gap in Spanish listed firms over the period 2012–2022.

The analysis is conducted using a data set created by the authors, which includes executive director compensation data for 164 unique firms. This data set comprises 128 distinct observations for a given firm and year for women, and 2,333 observations for men. The authors estimate ordinary least squares models, clustering standard errors by executive. The authors use Oaxaca-Blinder decomposition to decompose gender differences in compensation into differences in the characteristics of men and women and differences in the return on the same characteristics.

The authors find evidence of pay penalty for female executive directors compared to male counterparts. After controlling for firm, board and executive characteristics, the authors find that women earn 27% less than comparable men. The penalty is lower in companies with a higher share of women on the compensation committee, suggesting that women’s participation plays a role in setting a more equal remuneration policy. The gender gap in executive compensation narrows over time due to a substantial reduction of the differences between men and women in both characteristics and the return on these characteristics.

This study is one of the few analysing the gender gap in executive director compensation and its evolution in Spain. It specifically explores how gender diversity on both the board and the NRC impacts this gap. The analysis is focused on the most recent period characterized by important efforts to promote gender diversity.