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This paper aims at demonstrating the characteristics of the accommodations in the early period of the tourism development and determining the relationships between these characteristics and the price before it became a well-developed tourism destination focusing on Okinawa, Japan. Before Okinawa was returned to Japan, tourism markets were limited due to political reasons, though, tourism industries were developed and became a popular tourism site after the return of Okinawa. First, this paper conducted a principal component analysis (PCA) to identify the characteristics of the tourism accommodations. Two characteristics were obtained: one is for the characteristics of Western style hotels, the other is for Japanese-style accommodations which feature in traditional Japanese style rooms. Then a regression model was carried out to estimate the relationships between the price of accommodations and the characteristics obtained from the PCA. The estimation model showed that the characteristics of the Western style hotels more strongly influenced to the price, compared with those of the Japanese-style accommodations. Further, regional dummy variables were added to the model, which showed the price differences of accommodations between the cities and peripheral areas. Based on these results, Western style facilities were found to be more expensive before tourism development took off, and they were limited only in the part of areas in Okinawa. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper examines the impact of entrepreneurs' inventor identity and entrepreneur patent participation on enterprise performance using the panel data of 358 firms from the Science and Technology Innovation Board in China from 2014–2019. The methodology applied in this study is ordinary least square (OLS) regression. Inventor identity (a dummy variable) and patent participation (measured by Entrepreneur Degree Centrality and Entrepreneur Betweenness Centrality) are independent variables. The dependent variable enterprise performance is split into patent quantity, speed, and quality. The results show that an entrepreneur's inventor identity positively affects the patent quantity and quality but slows the patent speed. Entrepreneur Degree Centrality negatively affects the patent quantity and quality but increases the patent speed. Entrepreneur Betweenness Centrality positively affects the patent quantity and quality, and there is a U-shape association between Entrepreneur Betweenness Centrality and patent speed. The findings suggest that entrepreneurs who are inventors can actively improve the patent quantity and quality. Still, an entrepreneur's full participation in patent may negatively affect the patent quantity and quality. Entrepreneurs should participate in a patent in a direction-oriented or node-controlled way. [ABSTRACT FROM AUTHOR]

This paper investigates the economic development within the Guangdong-Hong Kong-Macao Greater Bay Area from two perspectives--spatial pattern and influencing factors--to promote coordinated development across the area. This paper employs Moran's I test and local Getis-Ord G statistic from spatial statistics. Furthermore, it constructs a hierarchical spatial econometric model to facilitate empirical investigation. It is found that the overall economic development of the Guangdong-Hong Kong-Macao Greater Bay Area exhibits a "mountain-shaped" spatial pattern of the high-level homogeneous regions with "high-high correlation" and the low-level homogeneous regions with "low-low correlation." The internal difference in economic density is moderate, with an obvious trend of decrease year by year. Economic density shows a significant spatial positive correlation, with the expansion of the scope of areas exhibiting "high-high correlation." The differences in economic density between hotspots and sub-hotspots have decreased, but the economic density of cold spots has failed to keep up with the development of other regions. The difference in factor input density among the influencing factors explains most of the differences in economic density among different regions. The results from the R&D capital investment coefficient indicate that in recent years, the effect of investments in urban scientific and technological innovation factors has been more extensive and uniform among the regions under its jurisdiction, but the spatial spillover effect of innovation factors at both layers is not significantly positive. Apart from the city's location within the Greater Bay Area, the relative location of the jurisdictions within the city equally influences the economic development configuration of the Greater Bay Area. Although economic density in regions adjacent to cities outside the Greater Bay Area is notably lower than in other regions, their growth rate and production efficiency remain on par with other regions. T-test and model results underscore the rapid development of the areas encircling the bay. The coefficient of location dummy variables in areas adjacent to cities in the Greater Bay Area varies among cities. At a particular factor input density, some cities have higher output efficiency in areas contiguous to cities in the Greater Bay Area. This study uniquely adopts low-level city jurisdictions and high-level cities to shape a two-tiered hierarchical dataset with nested geographic units. This innovative approach fully leverages insights from distinct layers, delving into spatial interdependence and interplay across layers. This paper aims to explore the spatial pattern and influencing factors steering economic development in the Guangdong-Hong Kong-Macao Greater Bay Area. In doing so, it aims to identify problems and present pertinent policy recommendations. [ABSTRACT FROM AUTHOR]

Purpose: This paper examines the role of institution in the combating crime in India. This study also assesses institutions for controlling property crime in India in the post-reform era. Design/methodology/approach: Crime and socio-economic data are taken from National Crime Record Bureau and the Reserve Bank of India, respectively. Twenty major Indian states are selected for the study purpose for the period of 1994–2019. Fixed effect panel data technique is used for analysis purpose. Findings: Property crime rate declines with economic growth, while it increases with financial development. Findings of fiscal policy instruments are different. Own tax is positively associated with property crime in India, while non-tax fiscal instruments such as fine, penalty, and so on, are inversely related to it. Property crime rate is inversely related to institutional factors like charge sheet and conviction rate. Research limitations/implications: Further research is needed for other crimes in India. State-level data are used here for analysis purpose; however, spatial or cluster analysis techniques might provide more insights for combating crimes in India. Practical implications: This study suggests that economic growth and fiscal instrument along with institutional development are essential to control property crime in India. Social implications: Government should take steps to improve the law-and-order system to control property crime across states. Originality/value: Impact of non-tax fiscal instrument reduces property crime while that of own tax is increases it in India. These findings are unique and added certain insight in the study. Institutional roles are captured its performances like charge sheet and convict rate, which are significantly reduce property crime in Indian states. Least square dummy variable model is applied to capture individual state effects. Peer review: The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-01-2023-0063 [ABSTRACT FROM AUTHOR]

Copyright of Forest Engineering is the property of Forest Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper constructs a unique dataset of clean energy and collects firm-level green innovation data that matches it with provinces and cities. Then, this paper executes quasi-natural experiments on green innovation to examine the effects of China's emission trading policy on green innovation. Further, this paper introduces the interactive terms of the pilot time and pilot area dummy variables into the spatial Durbin model (SDM) and spatial dynamic panel model (SDPM) to construct quasi-natural experiments to examine the spatial effect. The findings confirm a negative association between the 'policy treatment effect' and green innovation. The results also indicate a significant negative association between the emissions trading policy and clean energy. Besides, the empirical results reveal a positive correlation between clean energy and green innovation; clean energy promotes green innovation in the region and the surrounding areas. This paper complements existing research and provides empirical evidence and policy implications for developing clean energy, promoting green innovation, and improving the emission trading policy. [ABSTRACT FROM AUTHOR]

This paper investigates the threshold impact of government debt on economic growth in the presence of fiscal consolidation in South Africa from 1979 to 2022. The autoregressive threshold regime (TAR) model and two-stage least squares (2SLS) are used. The contribution of the paper is on the estimation of the threshold of government debt using the first difference, dummy variables, and the TAR in the presence of fiscal consolidation in South Africa. The TAR provides evidence with the consideration of fiscal consolidation, there is evidence of the U-shape impact of domestic government debt on gross domestic product per person. At a high threshold, there is evidence of an S-shape impact on gross domestic product per person when there is a range threshold. Overall high domestic government debt harms gross product per person and results in fiscal consolidation not being able to stimulate gross domestic product per person. It is recommended for fiscal authorities to not use fiscal consolidation when the domestic government debt is above 60% in South Africa. [ABSTRACT FROM AUTHOR]

This paper investigates the threshold of the cyclical adjusted primary balance (CAPB) that can be attributed to fiscal consolidation in South Africa. The CAPB framework is used in the threshold autoregressive regime (TAR) from 1979 to 2022. The contribution of the paper is the estimation of the CAPB in the context of South Africa to find fiscal consolidation episodes. Moreover, we identify the threshold of CAPB that can be attributed to fiscal consolidation, which the available literature is silent on. The TAR, first-order derivative and dummy variables are employed to find thresholds that can be attributed to fiscal consolidation episodes. By doing so, we provide valuable insights into the underlying dynamics of fiscal consolidation in the country, which can help policymakers develop more effective strategies for managing fiscal consolidation episodes. We estimated the success of fiscal consolidation on government debt in South Africa. There is a threshold of −1.28168%, 1.9182%, and 1.9270% for the CAPB of total government revenue increase, government expenditure cut, and the CAPB as a sum of both revenue and expenditure, respectively. These thresholds are different from the threshold of 1.5% advocated in the literature. It is recommended that a country-based threshold be used to find fiscal consolidation episodes. No or less fiscal consolidation is needed, as it results in less chance of reduction in government debt. Fiscal authorities must establish and execute a strategy for managing domestic government debt to avoid increasing its risk. [ABSTRACT FROM AUTHOR]

Copyright of Transformations in Business & Economics is the property of Vilnius University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Remittances are one of the major driving forces of economic growth in Bangladesh. The paper's main objective is to empirically investigate the effect of COVID-19 on the remittance inflow to Bangladesh using a gravity model framework. We have employed monthly data of remittance inflow to Bangladesh from January 2018 to September 2022 with its top twelve partners, namely the Kingdom of Saudi Arabia, the United Arab Emirates, Kuwait, Qatar, Oman, Bahrain, Libya, the United Kingdom, Italy, Malaysia, Singapore, and Japan. Using the gravity equation, we tapped the COVID-19 dummy as the critical variable of our interest, along with COVID transmission, mortality, and vaccination data at home and abroad. Using Poisson pseudo-maximum likelihood (PPML), fixed-effect (FE), and random-effect (RE) estimations, we find that during the COVID-19 pandemic, remittance inflow to Bangladesh increased significantly after controlling for other Gravity variables. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to investigate the moderating effect of sustainability reporting on the relationship between the independent variables of board diversity, and earnings management and the dependent variable of readability of financial statements. Design/methodology/approach: The study panel data regression analysis involved 36 Kenyan-listed companies from 2016 to 2020. Findings: Key findings were that increased board diversity was found to significantly improve the readability of financial statements. Discretionary earnings management was found to significantly reduce the readability of financial statements. Sustainability reporting was found to significantly increase the readability of financial statements, and it moderated the relationship between board diversity, earnings management and financial statements readability in Kenya. Research limitations/implications: The study sample of 36 non-financial listed in the Nairobi Securities Exchange was very small and was affected by the problem of thin trading; hence, caution should be adopted when interpreting the findings. Practical implications: The Capital Markets Authorities (CMA) as a policymaker should enforce sustainability reporting by Kenyan listed firms as there is evidence that the reporting enhances the readability of financial statements. The Institute of Certified Public Accountants as a policymaker should closely monitor the published financial statements of firms for earnings management and punish the perpetrators, as there is empirical evidence that the practice reduces the readability of financial statements. Social implications: Sustainability reporting is successful as a moderating variable between readability of financial statements and determinants of readability of financial statements. Originality/value: This study contributes to knowledge by studying sustainability reporting as a moderating variable between the independent variables of board diversity and earnings management and the dependent variable of readability of financial statements and measured sustainability reporting using a dummy variable for the period before and after the enactment and release of CMA code of 2016 on corporate governance that required sustainability reporting by Kenyan listed companies. [ABSTRACT FROM AUTHOR]

This paper is an attempt to assess the impact of climate on wheat yield in the Indo-Gangetic Plain (IGP) region of India by using panel data analysis. Five IGP states namely Punjab, Haryana, Uttar Pradesh, Bihar, and West Bengal have been considered to frame a panel. The study used the data of climatic and non-climatic variables from 1990 to 2022 to achieve the objective of the study. The Im-Pesaran-Shin unit-root test was applied to check the stationarity of data. The results of the panel least square dummy variable model indicated that all the climatic variables had non significant influence. Among non-climatic variables that help increase wheat yield, fertilizer consumption and mechanization in agriculture were found to have a significant positive impact on wheat yield in the IGP region of India. [ABSTRACT FROM AUTHOR]

This paper investigates the evolution of the Ukrainian stock market through an analysis of various data properties, including persistence, volatility, normality, and resistance to anomalies for the case of daily returns from the PFTS stock index spanning 1995–2022. Segmented into sub-periods, it aims to test the hypothesis that the market's efficiency has increased over time. To do this different statistical techniques and methods are used, including R/S analysis, ANOVA analysis, regression analysis with dummy variables, t-tests, and others. The findings present a mixed picture: while volatility and persistence demonstrate a general decreasing trend, indicating a potential shift towards a more efficient market, normality tests reveal no discernible differences between analyzed periods. Similarly, the analysis of anomalies shows no specific trends in the market's resilience to the day-of-the-week effect. Overall, the results suggest a lack of systematic changes in data properties in the Ukrainian stock market over time, possibly due to the country's volatile conditions, including two revolutions, economic crises, the annexation of territories, and a Russian invasion leading to the largest war in Europe since WWII. The limited impact of reforms and changes justifies the need for continued market reform and evolution post-war. [ABSTRACT FROM AUTHOR]

There is a vast literature that seeks to define and identify spatial submarkets in metropolitan housing systems. These tend to use one of three methods to delineate submarkets: a priori geographies, ad hoc subdivision and data-driven approaches to grouping units. Recently, analysts have increasingly used multilevel modelling strategies to analyse spatial segmentation in the housing market. Despite the increasing prevalence of multilevel approaches, there is no existing systematic analysis of which of these three main approaches to submarket definition has the greatest effectiveness when employed in a multilevel modelling framework. This paper addresses the gap in the literature by comparing the utility of these main approaches to submarket definition. It develops and evaluates three separate, distinct multilevel models of submarkets to a data set comprising 2175 transactions in the Istanbul housing market of Turkey, an emergent market context. The results show that multilevel models with a priori submarket dummy variable can predict price more accurately than the models with ad hoc subdivision or data-driven stratified submarkets. Similarly, test results indicate that multilevel models with neighbourhood submarket dummy variables (a priori) perform better than other models. These test results show that granular definition of submarkets tend to perform better in terms of predictive accuracy than less spatially granular models. The paper also suggests that real estate agents' views of submarket structures might be particularly useful as inputs into micro-modelling processes in contexts where datasets are thin. [ABSTRACT FROM AUTHOR]

Exploring the relationship between International Financial Reporting Standards (IFRS) and Foreign Direct Investment (FDI) inflows is the main objective of this paper. Although IFRS is identified as a determinant of FDI, a few studies have examined the impact of IFRS on FDI inflows, and it is unexplored as to whether IFRS impacts CIS countries. This paper covers ten (10) IFRS adopted CIS countries from 2000 to 2019 using Ordinary Least Square (OLS) and bias-corrected Least Square Dummy Variable (LSDVC). OLS estimator shows that IFRS positively impacts FDI inflows. However, according to the results of LSDVC, there is a negative relationship between IFRS adoption and FDI inflows. Generally, in developing countries implementing IFRS would lead to FDI enhancement. The negative relationship between IFRS adoption and FDI inflows in CIS countries shows that IFRS is not an essential factor of FDI inflows. [ABSTRACT FROM AUTHOR]

The aim of the paper is to explore the factors impacting export intensity of SMEs in India. It examines the influence of various firm level variables on export intensity. The sample considered for the study includes 50 SME firms from different industries ranging from equipment and manufacturing to textile. Data for ten years (2011–2020) has been analyzed for drawing relevant results. For regression, Least Square Dummy Variable corrected (LSDVC) estimates have been used to address the issue of heteroskedasticity and autocorrelation issue present in the data. The results arrived at indicate that the expenditure incurred on research and development, selling and distribution acts as an investment which provides returns in terms of better export performance. Also, top managers having international experience can be an important asset for a firm looking for expanding in international market. These results have substantial implications for the management of SME firms. [ABSTRACT FROM AUTHOR]

Many countries have been facing the problem of how to represent the economic downtime, economic crashing or economic recession in order to make appropriate decision or policy intervention. For this purpose, the paper estimates mobile telecommunication demand for 10 years of 27 countries using Ordinary Least-Square (OLS) method with qualitative information as dummy variable. The dummy variable examines the economic crashing time in South Korea during 1997. The paper uses price of mobile (mobile cellular monthly subscription) in telecommunication industry, income of consumers and investment as three independent variables, while the number of mobile cellular telephone subscribers per 100 inhabitants is used as dependent variable. The results indicate that the higher the income, the higher would be the demand for mobile cellular telephone subscribers per 100 inhabitants and investment has no effect as t-statistic is less than 2. In the same manner, the dummy variable has no statistical significance at 5% level on the demand for mobile telecommunication during economic crashes. This implies that the effect of economic crash or economic downtime in South Korea in 1997 is statistically insignificant in relation to demand for mobile telecommunication. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the effect of geopolitical risks on financial development (measured by domestic credit to the private sector) in a panel dataset of 18 emerging markets over the period 1985-2018. The results from the fixed-effects estimations indicate that an increase in geopolitical risks leads to a lower level of domestic credit to the private sector. The findings from the bias-corrected least-squares dummy variable estimations also confirm that geopolitical risks impacts negatively on domestic credit to the private sector. In terms of controls, we have found that per capita income and broad money are positively associated with domestic lending. Further, external imbalances were found to suppress domestic credit in emerging markets. Various additional controls were then included to address potential omitted variable bias. Moreover, we utilized multiple robustness checks, such as excluding countries from different continents as well as extracting outlier observations. According to the findings from these robustness checks, the negative impact of geopolitical risks on domestic lending is statistically and economically robust. To the best of the author's knowledge, this paper is the first to provide evidence for the negative impact of geopolitical risks on financial development in emerging markets, the economic performance of which can slow down as competitiveness deceases due to concomitant threats. [ABSTRACT FROM AUTHOR]

The paper uses the data of digital tax burden calculator of Russia’s Federal Tax Service to study the determinants of the total tax burden and average salary on the example of St. Petersburg for year 2020 with enterprises broken down by size and types of economic activity and with the focus on top-priority and socially important industries. Therefore, this study aims to provide a mathematical substantiation for the need to improve state support measures provided for top-priority or socially important types of activities in the region using taxation means and methods. The objectives set were achieved using simulation modeling. The dependent variables that characterize the state support of the top-priority and socially important types of activities are the rate of tax burden (excluding mineral tax and excise taxes) and the size of the average salary. Moreover, two analyses were conducted sequentially to achieve the objectives. The first was a two-way analysis of variance of the relationship between the average salary and the size of the organization or industry as well as the dependence of tax burden on the same factors. The second was a one-way analysis of the variance of the tax burden and average salary depending on different types of activities as well as the scale of the enterprise. The results of the one-way analysis were refined through regression methods based on dummy variables. It was observed that there were no considerable differences between the average salary and total tax burden in top-priority or socially important sectors compared to the other industries in the economy. The trend was the evidence of insufficient support provided by the state and the need to introduce additional preferences. [ABSTRACT FROM AUTHOR]

Based on the empirical literature of the payments for environmental services (PES) projects for the environmental improvement and poverty reduction, this paper uses a meta-regression analysis method to study whether PES can achieve the effects of improving environmental quality and reducing poverty levels. For the meta-regression analysis, the literature was mainly searched by the Web of Science core journal database. The explanatory variables of meta-regression analysis are the hypothesis and related features of the models in the original literature by generally taking the binary dummy variables or categorical variables. The dependent variables used in this paper are environmental improvement and poverty reduction. The results show that PES projects based on private ownership rights are more conducive to poverty reduction and environmental improvement. If the country is a buyer of a PES project, it is more likely to achieve the effects of environmental enhancement and poverty alleviation. PES projects based on local conditions can also achieve a win–win situation for the two effects. The effects are more effective as policy implementation time is extended. The findings suggest that in developing countries, the government should set different PES projects according to different regions conditions, to promote project implementation through individual voluntary participation, and to achieve the dual purpose of environmental governance and poverty alleviation based on the expectation of long-term implementation of participant projects. [ABSTRACT FROM AUTHOR]

This paper uses the World Bank survey database of Chinese enterprises to investigate the impact of information and communication technologies (ICTs) on Chinese enterprises' innovation performance and the internal mechanism at the micro‐level. The results show that ICTs have significantly improved the innovation performance of Chinese enterprises. This conclusion does not change with the addition of other control variables and dummy variables, showing strong robustness. This study also finds that the impact of ICTs on enterprise innovation performance shows obvious heterogeneity across different industries and regions. We should enhance the transmission effect of ICTs on enterprise innovation performance. [ABSTRACT FROM AUTHOR]

Purpose: Despite the existing conceptual analysis on the impact of trade unions on employees' welfare and the wider economy, the mediating effect of political party orientation (i.e., right, centre and left) on income inequality remains under researched. In this paper, the authors empirically explore the relationship between the nature of political party orientation, trade unions and income inequality. Design/methodology/approach: The authors use three different measures of income inequality and dummy variables that capture government party orientation with respect to economic policy for a panel of 17 OECD economies over the period 2000–2016. The authors employ a panel fixed effects approach and the Driscoll and Kraay's (1998) nonparametric covariance matrix estimator. Findings: The empirical evidence indicates that strong unions and, to some extent, left party governance, are fundamental institutional elements to combat rising levels of income inequality whilst countries dominated by right-wing political parties appear to exacerbate income inequality. The results pertaining to the impact of centrist parties on income inequality are ambiguous suggesting that a potential fragmentation may exist in their political approach. Originality/value: The evidence generated can have significant policy ramifications in alleviating rising levels of income inequality as well in relation to the declining unionization rates observed across advanced economies. [ABSTRACT FROM AUTHOR]

Purpose: The paper aims to examine the corporate social responsibility (CSR) activity of audit firms. Design/methodology/approach: Using hand-collected data on all Chinese audit firms' CSR activities from 2007 to 2020, this study constructs two measures to proxy for audit firms' CSR engagement: a dummy variable to indicate whether an auditor engages in CSR activities in year t and the frequency with which auditors conduct CSR activities in year t. The authors use ordinary least squares regression as a baseline methodology, along with the entropy balancing method and instrumental variable approach to alleviate potential endogeneity concerns. Findings: The baseline results show that socially responsible audit firms provide higher quality audit services than their counterparts. In particular, the authors find that clients audited by socially responsible audit firms are less likely to receive an aggressively clean opinion. Moreover, the findings suggest that CSR activities related to community and employees are more relevant in improving audit quality compared with those related to other dimensions of CSR. Further analyses show that capital markets and audit clients react positively to audit-firm CSR activity. Audit firms engaging in CSR increase their audit inputs in response to risky clients, as compared with their counterparts. Finally, cross-sectional analyses show that the positive relationship is more pronounced for non-Big 4 and non-industry experts and is attenuated by within-firm geographic dispersion. In terms of client characteristics, the positive effect of audit-firm CSR is stronger when their clients face the higher financial risk or have lower CSR awareness than others. Taken together, these findings are consistent with the ethical view of audit-firm CSR engagement. Practical implications: The study advances investors' understanding of audit-firm CSR engagement and helps them evaluate the credibility of audited financial reports. Besides, the findings may also help guide the audit firms to conduct more CSR activities and help guide the audit clients to choose CSR audit firms. Originality/value: To the best of the authors' knowledge, this study provides the first large-sample evidence by empirically examining the association between audit-firm CSR activity and audit service performance. Besides, this paper also explores audit-firm CSR activity from two competing perspectives, thereby providing a comprehensive understanding of this issue. Finally, this work responds to the call for more CSR research in emerging markets. [ABSTRACT FROM AUTHOR]

Copyright of Financial & Credit Activity: Problems of Theory & Practice is the property of University of Banking of the National Bank of Ukraine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Efficient decisions by various stakeholders depend on how business organizations communicate their operational and financial information. Financial reporting is a means to disseminate information on various operational and non-operational affairs of business organization; it is done through financial statements, notes to accounts and narrative section in the annual reports. Due to risks in business environment, stakeholders expect enhanced information on various multidimensional aspects of business. Therefore, business organizations are required to disseminate enhanced information so as to assist in decision making by them. This is possible only with the help of an enhanced business reporting model. Such a model can be successfully implemented through the application of extensible business reporting language (XBRL). The present paper analyzes the impact of XBRL on the quality of financial reporting based on the financial reporting patterns of 23 selected NSE listed companies from 2005 to 2020, using statistical tools such as Tukey test and dummy variable regression analysis. The study finds that XBRL had a significant impact on the quality of financial reporting of the selected companies. [ABSTRACT FROM AUTHOR]

This paper assesses the impact of constitutional changes on foreign direct investment (FDI) in 49 African countries during the period 1980–2020. The paper uses a dummy variable related to the year of the constitutional change and the number of changes during the study period to capture the frequency of constitutional changes. The results reveal that an increase in the frequency of constitutional changes negatively affects FDI. The negative relationship between constitutional change and FDI is consistent across different measures of constitutional change and FDI and is robust to alternative empirical approaches. These results suggest that frequent constitutional changes may create uncertainty and instability in the investment climate, which may discourage foreign investors from investing in these African countries. The study provides evidence for policymakers that a stable constitutional framework may attract FDI in African countries. [ABSTRACT FROM AUTHOR]

Copyright of EURE is the property of Pontificia Universidad Catolica de Chile and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, we investigate the effect of inter-country wage differentials on textile and garment (T&G) exports of Bangladesh and present an account of the important issue of why textile and garment exports are directed from developing countries to developed countries. Our empirical results imply that the wage differentials between developed and developing countries constitute one of the main drivers of T&G exports. In addition, we checked other factors such as the Multi-Fiber Arrangement (MFA) and the Generalized System of Preferences (GSP) by including dummy variables representing the MFA quota withdrawal and the GSP. We found that removal of the MFA had a significant negative effect, as expected. Our study confirms the positive correlation between GSP and exports. After phasing out the MFA and its quota system, the wage differentials not only boost the T&G exports from Bangladesh, but also increase the effectiveness of GSP. Given such findings, we discuss relevant policy implications. [ABSTRACT FROM AUTHOR]

This paper investigates the determinants of medium to long‐run real exchange rate volatility in South Africa over the period 1986–2015. The main objective of the paper is to analyse the impact of trade openness on real exchange rate volatility following conflicting results offered by empirical studies. Employing the Autoregressive Distributed Lag (ARDL) cointegration approach and using a variety of specifications and robustness tests, results show that trade openness has an impact on real exchange rate volatility. The interaction term of trade openness and the dummy variable for capital account liberalisation leads to a significant negative impact on real exchange rate volatility. Furthermore, findings indicate that volatility of output, commodity prices, money supply and government consumption, and the exchange rate regime significantly influence rand volatility. [ABSTRACT FROM AUTHOR]

This paper addresses the following question: can satisfactory residential property price indexes be constructed using hedonic regression techniques where location effects are modeled using local neighborhood dummy variables or is it necessary to use spatial coordinates to model location effects. Hill and Scholz (2018) addressed this question and found, using their hedonic regression model, that it was not necessary to use spatial coordinates to obtain satisfactory property price indexes for Sydney. However, their hedonic regression model did not estimate separate land and structure price indexes for residential properties. To construct national balance sheet estimates, it is necessary to have separate land and structure price indexes. The present paper addresses the Hill and Scholz question in the context of providing satisfactory residential land price indexes. The spatial coordinate model used in the present paper is a modification of Colwell's (1998) spatial interpolation method. The modification can be viewed as a general nonparametric method for estimating a function of two variables. [ABSTRACT FROM AUTHOR]

This paper examines the impact of the Indonesia double tax treaties (DTTs) network with developed countries on Indonesia's inward foreign direct investment (FDI) for the period 2005-2017 and investigates the causes of the result. Using Indonesia DTTs as a dummy variable and other data under the Capability Maturity Model (CMM) framework over 41 sample countries, this paper finds that the Indonesia DTTs network with developed countries does not have any statistically significant correlation with the inward FDI. When the analysis is extended to examine the effect of the DTTs in three and six years after the implementation of the DTTs, the results remain the same. This paper finds also that, in the case of Indonesia, DTTs do not affect the inward FDI because foreign investors consider more on the non-tax factors and most of Indonesia's DTTs were not negotiated for economic reasons. [ABSTRACT FROM AUTHOR]

In this paper, we reassess the impact of inequality on growth. The majority of previous papers have employed (system) GMM estimation. However, recent simulation studies indicate that the problems of GMM when using non‐stationary data such as GDP have been grossly underestimated in applied research. Concerning predetermined regressors such as inequality, GMM is outperformed by a simple least‐squares dummy variable estimator. Additionally, new data have recently become available that not only double the sample size compared to most previous studies, but also address the substantial measurement issues that have plagued past research. Using these new data and an LSDV estimator, we provide an analysis that both accounts for the conditions where inequality is beneficial or detrimental to growth and distinguishes between market‐driven inequality and redistribution. We show that there are situations where market inequality affects growth positively while redistribution is simultaneously beneficial. [ABSTRACT FROM AUTHOR]

With the growing cyber-infrastructure of smart grids, the threat of cyber-attacks has intensified, posing an increased risk of compromised communication links. Of particular concern is the false data injection (FDI) attack, which has emerged as a highly dangerous cyber-attack targeting smart grids. This paper addresses the limitations of the variable dummy value model proposed in the authors previous work and presents a novel defense methodology called the nonlinear function-based variable dummy value model for the AC power flow network. The proposed model is evaluated using the IEEE 14-bus test system, demonstrating its effectiveness in detecting FDI attacks. It has been shown that previous detection techniques are unable to detect FDI attacks, whereas the proposed method is shown to be successful in the detection of such attacks, guaranteeing the security of the smart grid's measurement infrastructure. [ABSTRACT FROM AUTHOR]

Economic crisis and uncertainty in global status quo affect stock markets around the world. This fact imposes improvement in the development of volatility models. However, the comparison among volatility models cannot be made based on a single‐error measure as a model can perform better in one‐error measure and worst in another. In this paper, we propose a two‐stage approach for prioritizing volatility models, where in the first stage we develop a novel slack‐based data envelopment analysis to rank volatility models. The robustness of the proposed approach has also been investigated using cluster analysis. In the second‐stage analysis, it is investigated whether the efficiency scores depend on model characteristics. These attributes concern the time needed in order to estimate the model, the value of Akaike Information Criterion, the number of models' significant parameters, groups and bias terms, and the error sum of squares (ESS). Further, dummy variables have been introduced to the regression model in order to find whether the employed model includes an in‐mean effect, whether the assumed distribution is skewed, and whether the employed model belongs to the generalized autoregressive conditional heteroskedasticity (GARCH) family. The main findings of this research show that the number of models' statistically significant coefficients, ESS, and in‐mean effects tend to increase the efficiency scores, while time elapsed, the number of statistically significant bias terms, and skewed error distributions tend to decrease the efficiency score. [ABSTRACT FROM AUTHOR]

Copyright of Arid Land Geography is the property of Chinese Academy of Sciences, Xinjiang Institute of Ecology & Geography and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: This paper aims to examine the relationship between knowledge-economy and economic growth in 16 Asia-Pacific (AP) countries during the period 2011–2018. The study also aims to investigate a diversity of knowledge-economy pillars, including tertiary education, domestic innovation, foreign innovation, economic incentives and institutional regime and information and communications technologies (ICTs) and their relation to economic growth. Design/methodology/approach: The study applies a comparative empirical analysis using pooled ordinary least squares (OLS), one-step difference generalised methods of moments (GMM) and bias-corrected least-squares dummy variables (LSDVc) estimators to test this relationship. Findings: Pooled OLS estimators deemed suboptimal to the panel data under study, while GMM results reveal a significant relationship between tertiary education, domestic and foreign innovation, government expenditure and investments with economic growth. Of these results, domestic innovation, investments and government consumption are positively correlated with economic growth, whereas tertiary education and foreign innovation show a negative relation. Meanwhile, institutions and ICT have insignificant relationships with economic growth. LSDVc results coincide with GMM results with respect to tertiary education, whereas institutions is the only additional significant and negatively correlated variable with economic growth. Research limitations/implications: The main limitation of this research lies in the unavailability of proxy data for knowledge economy pillars in monetary terms, and hence, the paper relies on indices. Originality/value: The novelty of the study lies in its aim to investigate economic growth in the AP region that is enhanced by domestic innovation, foreign innovation or both – an area which is empirically understudied in the knowledge-economy context. Further, the paper's novelty lies in its application of a comparative empirical analysis between the most popular dynamic panel estimators – dynamic GMM and bias-corrected LSDVc for AP countries. [ABSTRACT FROM AUTHOR]

This paper serves to examine whether the growth in labour productivity (LP) in South Africa's manufacturing sector, following policy reforms after 1994, can be attributed to ICT use. To achieve this, we examine the link between ICT intensity and LP growth of 23 manufacturing industries for the period 1970–2016 and sub-periods 1970–1995 and 1996–2016. The industries are disaggregated into two groups, which are 'more ICT-intensive' and 'less ICT-intensive', using the ICT intensity index. Four dummy variable regression models are applied to test for the relationship between ICT intensity of industries and LP growth. The findings suggest that LP of the more ICT-intensive industries accelerated more than that of their counterparts. The results underscore the need for policy measures to increase ICT use with the aim of improving LP performance of industries. [ABSTRACT FROM AUTHOR]

Copyright of Transformations in Business & Economics is the property of Vilnius University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: This research paper uses a novel methodological approach to investigate the spillover effects among the key sectors of the US economy. Design/methodology/approach: The paper links the US sectors via a node theoretic scheme based on a general equilibrium framework, whereas it estimates the general equilibrium equation as a Global Vector Autoregressive process, taking into consideration the potential existence of dominant units. Findings: Based on our findings, the dominant sector in the US economy, for the period 1992–2015, is the sector of information technology, finance and communications, a fact that gives credence to the view that the US economy is a service-driven economy. In addition, the US economy seems to benefit by the increased labour mobility across knowledge-intensive sectors, thus avoiding the 'employment trap' which in turn enabled the US economy to overcome the financial crisis of 2007. Originality/value: Firstly, the paper models by means of a network approach which is based on a general equilibrium framework, the linkages between the US sectors while treating the sector of information, technology, communications and finance as dominant, as dictated by its degree of centrality in the network structure. Secondly, the paper offers a robustness analysis regarding both the existence and the identification of dominant sectors (nodes) in the US economy. Thirdly, the paper studies a wide period, namely 1992–2015, fully capturing the recent global recession, while acknowledging the impact of the global crisis through the introduction of the relevant exogenous dummy variables; Lastly and most importantly, it is the first study to apply the GVAR approach in a network general equilibrium framework at the sectoral level. [ABSTRACT FROM AUTHOR]

This paper deals with the spatial analysis of the educational performance measured by the average percentage Maths scores achieved in individual districts of Slovakia in Testing 9 during the school year 2018/2019. Besides identification of the spatial patterns in test scores achievements, the paper tries to investigate the impact of selected socio-economic variables (average nominal monthly wage and unemployment rate) onto the test scores achievements. Since we suppose the significant impact of the socially disadvantaged background onto the test results, corresponding dummy variable was taken into consideration as well. The ordinary least squares (OLS) estimation of the global linear regression model was followed by the local spatial approach using the geographically weighted regression (GWR) to capture the geographical variability of estimated parameters. Spatial variations in the relationship among the educational performance and the selected socio-economic variables were confirmed. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to investigate the endogeneity effect of state ownership on firm value in Indonesia. Design/methodology/approach: Using a sample of 139 Indonesian non-financial listed companies from 2009 to 2013, this study uses two-stage least square (2SLS) methods. Findings: The results of 2SLS show that state ownership as "continuous measure, dummy variable and after adjusting the outliers" are negatively and significantly influenced firm value, implying that state ownership tends to lower firm value. Moreover, the results also show that U-shaped effect of state ownership with firm value, implying that the size of shareholders by state increases, firm value initially decreases and then increases. Practical implications: The study intends to provide the shareholders, managers and investors with clear guidance before their investment decisions. Social implications: This paper provides evidence that the agency costs may increase in firms with state ownership share. Originality/value: This is the first paper contributes to the corporate governance literature by investigating the endogeneity effect between state ownership and firm value using 2SLS method in Indonesia. [ABSTRACT FROM AUTHOR]

Research background: The issues undertaken in the paper include the specification of an econometric model in real estate mass appraisal. Advantages and disadvantages of using econometric models in real estate mass appraisal are discussed. Purpose: The issue of aiding the valuation process with an econometric model based on the Szczecin algorithm of real estate mass appraisal is discussed in the paper. Such problems like multicollinearity, lack of coincidence and nonmonotonic influence of attributes are pointed out. Also, potential solutions to these problems are mentioned. Moreover, the paper features a discussion of cases in which econometric appraisal is not sufficient. Research methodology: The base for constructing an econometric model is the so-called Szczecin algorithm of real estate mass appraisal. Based on the algorithm, the econometric model was created to enable determining the impact of real estate attributes and location on their value. Results: problems related with specification, estimation and verification of the real estate mass appraisal econometric model are discussed in an empirical example. Novelty: A non-linear model is proposed, which features explanatory variables introduced into the model, and by taking into consideration the scale of their measurement. The proposed model, by introducing dummy variables, also account for the impact of a location, which significantly improves the fit to empirical values. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to reflect on the corpus of gender research in accounting journals, with the overall aim of evaluating the extent to which it has contributed to the understanding of the organization of accounting and its social and organizational functions.Design/methodology/approach Gender articles have been critically analyzed. The selection included all gender papers published between the years 2000 and 2014, in 58 journals ranked A*, A and B from the Australian Business Deans Council (ABDC) journal ranking list. Patterns within the publishing norms of those journals were identified and critically reflected upon.Findings Gender research has been grouped into three categories, namely, gender as a dummy (or control) variable, gender as giving voice and gender as a process and organizing principle. Of these three categories, it can be contended that using gender as a dummy variable is very common, and it proved to be the least fruitful in explicating the roles of gender in accounting. Moreover, many published papers confuse sex with gender.Research limitations/implications This paper discusses future avenues and approaches for research gender in accounting without, however, expanding on recent changes in gender research.Originality/value This paper is the first to systematically review gender research in the accounting field over the past three decades. Its key insight is to identify two persistent pitfalls within the current gender research practice, namely, the use of gender as a control variable only and the confusion of sex with gender. These pitfalls diminish the value of gender research overall and render it less relevant to the broader accounting literature. By using the term gender either as an add-on or, mistakenly, as a biological rather than cultural marker, the totality of those articles helps marginalize gender as an accounting research area because they fail to bring about the reconceptualization of accounting as a discipline. This stands in marked contrast to the achievements of gender approaches in other disciplines, such as sociology, history or work and employment. Articles that frequently decry the status of gender in accounting research turn out to be also reinforcing the marginalization of gender in accounting. [ABSTRACT FROM AUTHOR]

The emerging markets like Pakistan stock exchange experience high volatility and high return after introducing liberalization policies and deregulation. The paper tries to explore the impact of deregulation on size and value premiums in the Pakistan Stock Exchange (PSX) using daily stock price data of 305 companies from 2004 to 2018 listed at Pakistan Stock Exchange. The main aim is to probe the time-varying behaviour of stock returns after the deregulation in the Pakistan Stock Exchange (PSX). From the policy makers view point, the study is significant to perceive costbenefit analysis of deregulation and different liberalization policies while contributing in pricing risk in the context of an emerging market of Pakistan. The findings show that various effects including size, value, and market are significant. The GARCH-in-Mean model exhibits significant relation of return and risk. As a result of deregulation, volatility in returns appears persistently significant. The coefficient of the dummy variable appears significant indicating the significant impact of regulatory developments in the PSX. The implications of deregulation in the PSX are to open up the stock market of Pakistan to foreign investors, protecting investors and relaxing regulations for investment, banking/financial as well as non-financial sectors. [ABSTRACT FROM AUTHOR]

Purpose: The paper examines the differential effect of liquidity constraints on corporate growth using unbalanced panel data for 457 Pakistani firms over the period 2010–2017. Design/methodology/approach: The study uses the probability of a financial unconstrained index constructed by estimating the endogenous regression model. This approach provides a time-varying measure of financial position for all firm-year observations and takes into account the different degrees of liquidity constraints that a company faces in attaining funds from external markets. It is derived from a multivariate selection equation that simultaneously accounts for all-important features of the underlying company identified in the literature. The cash flow variable has then interacted with various groups of dummy variables for financial constraint, which allows the coefficient of cash flow to vary across firm-year observations in the different liquidity constraint categories. The two-step system-GMM estimator is applied to estimate the main empirical model. Findings: The results of the study provide evidence of the heterogeneity in firms' growth sensitivity to internal funds, depending on the degree of liquidity constraints. Financing growth through internal funds is found to be essential for both liquidity unconstrained and constrained corporates. However, it is observed that the coefficient of cash flow is greater for firms that do not have access to external financing and it eventually decreases with reductions in the magnitude of liquidity constraints, making the least constrained corporates' growth less responsive to internal funds. The results further indicate that smaller and younger firms show higher responsiveness of growth to internal funds. This finding is mainly attributed to financial market imperfections that make external funding difficult for them. Practical implications: The results suggest that financially constrained firms should expand their corporate size more than the magnitude of positive income shocks they encounter. The study also suggests important policy implications for liquidity-constrained firms to carefully concentrate on their financing strategies to enhance their growth. By improving the corporate's capacity for production, corporates can achieve a faster effect of a potential positive income shock on their growth. Originality/value: This paper contributes to the literature by constructing a financial constraint index by running the endogenous regression model. It also contributes by investigating the differential impact of credit constraints on firms' growth in Pakistan and how corporate size and age affect firm growth when financial constraints and investment opportunities are controlled. [ABSTRACT FROM AUTHOR]

Given the significant oil price changes during the past two decades, this paper examines the effect of oil price uncertainty on the sovereign credit risk of four Gulf Cooperation Council (GCC) countries (United Arab Emirates, Qatar, Bahrain, and Saudi Arabia). By utilizing the nonparametric local linear dummy variable estimates (LLDVE), we unveil a significant effect of oil uncertainty on the credit risk mainly during the oil price crash of 2014–2015 and to a lesser extent during the early period of the COVID-19 pandemic. This effect, however, is heterogeneous across the GCC countries. Unlike previous studies, our study controls for structural shifts, nonlinearities, and long-term trends in the relationship between oil price uncertainty and credit risk. Our findings hold important policy implications for policymakers and investors. [ABSTRACT FROM AUTHOR]

Measuring inequalities in political participation across social groups is a challenging task as participation is typically coded in dummy variables. For instance, social scientists record whether their respondents have voted in the previous elections (1) or not (0). In this paper, we identify a list of desirable criteria that an inequality index used for empirical comparative studies should meet. Existing inequality indices fail to satisfy one or more of these criteria. Building on our list, we define a new Gini-type index, the Political Inequality in Participation Index (PIPI), suitable for cross-country comparisons. We show that inequalities measured by the PIPI are correlated to, but are qualitatively different from the best-known measurements. In particular, using data simulation techniques, we demonstrate that this correlation is decreasing in the complexity of societies' structure. Moreover, by replicating an existing study, we further demonstrate that when working with real-world data, the PIPI provides new empirical results. [ABSTRACT FROM AUTHOR]