Search results

The purpose of this study is to empirically examine the extent to which volatility associated with corporate performance could be attributed to specific adverse macroeconomic conditions in a bivariate causality analysis.

The study uses the Toda–Yamamoto Wald test approach to Granger causality analysis in verifying significant causal interactions if any, between corporate performance volatility and seven macroeconomic conditions or variables.

This study finds that economic policy uncertainty and macroeconomic uncertainty tend to have bidirectional causal interaction with corporate performance volatility. In addition, estimated results further suggest significant unidirectional causal interaction between corporate performance volatility and inflation expectations, exchange rate volatility, inflation and inflation uncertainty, with direction of causality running from the macroeconomic variables toward corporate performance volatility. This study, however, found no significant causal interaction between corporate performance volatility and recessionary probability or likelihood of recession.

This study’s conclusions could have significant and critical policy implications for key corporate policymakers responsible for corporate performance strategy. Various causal interactions identified could inform policy framework and, subsequently, strategies geared toward minimizing volatility associated with performance during episodes of any of the various macroeconomic conditions examined in this study.

The uniqueness of this study stems from its focus on corporate performance volatility instead of corporate performance and potential causal interactions it might have with key adverse macroeconomic conditions, some of which have not been examined in previous studies according to reviewed literature.

This paper provides a review and synthesis of past research regarding financial disclosure management by nongovernmental nonprofit organizations and suggests directions for future study. The primary purpose of this review is to summarize the evidence on financial disclosure management to help regulators and other stakeholders understand why, how, and to what extent nonprofits engage in this behavior. The paper begins by defining disclosure management in nonprofit organizations and exploring the motivations for why it might occur. Next is a survey of the nongovernmental nonprofit financial reporting environment: objectives, common practices, and the informational needs of users of nonprofit financial reports. Research exploring the motives, methods, and consequences of disclosure management is summarized. The evidence suggests that nongovernmental nonprofit managers have a variety of incentives to manage reported numbers and that they do in fact alter spending decisions, choose accounting methods, and design cost allocations to achieve certain performance benchmarks. Furthermore, this review sheds light on the consequences of disclosure management and what can or should be done to limit it.

This study aims to analyze the long-run dynamic relationship between financial inclusion and economic growth for developing nations.

This study develops a comprehensive financial inclusion index based on the UNDP methodology for 53 developing nations. The authors use second-generation unit root tests, cointegration techniques and an advanced dynamic common correlated effects estimator model called cross-sectional augmented autoregressive distributed lags (CS-ARDL) to examine long-run dynamics among variables.

The tests confirm the presence of slope-heterogeneity and cross-sectional dependency. The second-generation panel unit root tests show the chosen variables are stationary at first difference. The bootstrap Westerlund cointegration result shows the variables are cointegrated in the long run. The CS-ARDL estimates conclude that financial inclusion positively enhances gross domestic product per capita in selected developing countries. The robustness check through augmented mean group estimation validates the findings.

The study makes three important contributions: first, it constructs a comprehensive financial inclusion index using 10 variables for a panel of 53 developing nations; second, the potential cross-section dependence and slope heterogeneity of panel data have been accounted for by applying the second-generation unit root tests; third, the study uses the dynamic common correlated effects estimator model (CS-ARDL) to examine long-run dynamics among variables.

Sustainable development calls for concerted efforts towards building an inclusive, sustainable and resilient future for people and planet. The approach that considers sustainable development as the fight against poverty, through the promotion of a sustainable and equitable economy, as the attempt to reduce polluting emissions to promote environmental protection and as the satisfaction of social goals to increase the well-being of populations is adopted. Sustainability development is therefore a complex and subjective concept, considering the three dimensions that define the phenomenon: economic, environmental and social.

The authors have chosen subjective variables, which provide information on the perception of the ‘sustainable development’ in the European countries. Data come from the database of ‘Eurofound’, the European Foundation for the Improvement of Living and Working Conditions. The authors applied a formative measurement model, according to which indicators are considered as the cause of the phenomenon analysed, unlike with the reflective model. To conduct the quantitative analysis, the authors have adopted a non-compensatory approach: Mazziotta and Pareto index which summarising a set of individual indicators that are assumed to be not fully substitutable. The authors place at the centre of the analysis, variables deriving from the perceptive state of the different European populations, offering new hints to measure sustainable development on the basis of subjective assumptions.

This paper aims to identify the economic stimulus measures that ensure stability of the Lithuanian housing market in the event of an economic shock.

The econometric analysis includes stationarity test, Granger causality test, correlation analysis, autoregressive distributed lag models and cointegration analysis using ARDL bounds testing.

The econometric modelling reveals that the housing price in Lithuania correlates with quarterly changes in the gross domestic product and approves that the cycles of the real estate market are related to the economic cycles. Economic stimulus measures should mainly focus on stabilizing the economics, preserving the cash and deposits of households, as well as consumer spending in the case of economic shock.

This study is beneficial for policy makers to make decisions to maintain stability in the housing market in the event of any economic shock.

Mexico is an OECD member country that historically has allocated less than half a per cent of its gross domestic product to spend on research and experimental development. The purpose of this paper is to evaluate the country’s science and technology policy through its main program, the National System of Researchers (SNI), an attempt made for the first time. The results obtained make it possible to see whether the SNI has succeeded in improving research in Mexico. The authors also look at whether the program provides ways of improving and strengthening the science policy model adopted by Mexico and whether it could be extended and/or introduced into other nearby countries with levels of development or characteristics similar to those of Mexico.

After that, the authors will analyze the scientific productivity of SNI members in comparison to Mexican researchers as a whole so as to assess both whether the SNI selects the best researchers and whether these researchers carry out more research and of a higher quality. Finally, the authors will check whether the selection criteria of the assessment committees are internally consistent. To do this, the authors will carry out a bibliometric analysis of Mexican scientific production (overall and specifically of SNI members) and an analysis of the groups of researchers belonging to the SNI.

The aim of this paper is to discover the impact and importance of the best program in Mexico as regards research policy, known as the SNI. Analyzing it will, in short, enable the authors to detect whether the program has been of use in improving the investigation potential and capacity for science and technology transfer of the research elite in Mexico; check whether the levels assigned to these researchers within the SNI are justified, based on research indicators (inputs and outputs); and assess the pros and cons of the SNI program with an eye to reviewing it in Mexico.

A limitation of using cross-sectional data is that information is not the same in each period analyzed. However, the SNI of Mexico has used the same information in all its evaluations. Therefore, the authors believe that using longitudinal data allows us to compare the evolution of SNI for various periods. This certainly is helpful for making decisions and, above all, provides first-hand information to the authorities who, in turn, should strengthen and make more efficient remedial measures regarding public policies on science and technology in Mexico.

SNI assessment program will know the science and technology of Mexico and whether it is advisable to implement this program of science policy in similar economies or the same level of development as Mexico.

The contributions of this study are relevant to the extent that the evaluation system of researchers from Mexico is the basis for allocating research resources, making proposals to help improve the system for evaluating researchers and contributing to efficiency in the allocation of resources for research.

This paper has also applied different techniques that have made it possible to look more thoroughly into the classification of all the researchers who were assessed positively by the SNI for period 1996-2003. These techniques have enabled us to obtain alternative classifications based on statistical algorithms and to gauge the level of internal consistency of the classifications made by the SNI, based strictly on the quantitative information supplied.

The purpose of this research is to examine the validity of the agriculture-induced environmental Kuznets curve (EKC) hypothesis with evidence from an autoregressive distributed lag (ARDL) approach with a structural break including real income and energy consumption in the model for Ghana over the period 1980–2014.

The ARDL approach with a structural break was used to analyze the agriculture-induced EKC model which has not been studied in Ghana. The dynamic ordinary least squares (DOLS), canonical cointegration regression (CCR) and fully modified ordinary least squares (FMOLS) econometric methods were further used to validate the robustness of the estimates, and the direction of the relationship between the study variables was also clarified using the Toda–Yamamoto Granger causality test.

The ARDL results revealed that GDP, energy consumption and agricultural value added have significant positive effects on CO₂ emissions, while GDP² reduces CO₂ emissions. The Toda-Yamamoto causality test results show a bidirectional causality running from GDP and energy consumption to CO₂ emissions whereas a unidirectional long-term causality runs from GDP² and agriculture value-added to CO₂ emissions.

This finding validated the presence of the agriculture-induced EKC hypothesis in Ghana in both the short run and long run, and the important role of agriculture and energy consumption in economic growth was confirmed by the respective bidirectional and unidirectional causal relationships between the two variables and GDP. Thus, a reduction in unsustainable agricultural practices is recommended through specific policies to strengthen institutional quality in Ghana for a paradigm shift from rudimentary technology to modern sustainable agrarian technologies.

This study is novel in the EKC literature in Ghana, as no study has yet been done on agriculture-induced EKC in Ghana, and the other EKC studies also failed to account for structural breaks which have been done by this study. This study further includes a causality analysis to examine the direction of the relationship which the few EKC studies in Ghana failed to address. Finally, dynamic ordinary least squares (DOLS), canonical cointegration regression (CCR) and fully modified ordinary least squares (FMOLS) methods are used for robustness check, unlike other studies with single methodologies.

The purpose of this study is to analyze short- and long-run market-sensitive drivers of housing affordability. The study highlights an ongoing housing affordability crisis in an emerging market context by also providing an empirical tool to combat the crisis.

To investigate determinants of uniquely constructed effective housing affordability index and house price to income ratio index, the author uses a bound testing approach to cointegration and error correction models, besides causality tests, variance decompositions and impulse response functions. This study uses Turkish data for the period of 2007 M06 and 2017 M12.

The evidence suggests that the housing affordability crisis is mainly driven by credit expansion, rent and construction costs. A sensible housing policy response would target these variables. This evidence suggests that housing affordability mostly depends on housing market dynamics rather than policies because of the exogeneous/cyclical natures of the drivers.

Data constraints shape the study. A regional or an aggregate-level panel study cannot be developed because of a lack of data. This limitation inevitably results in the exclusion of relevant socio-economic/political factors and is also the main reason for the lack of comparative analysis in a cross-country setting.

This study argues that dependency on neoliberal housing market practices seems the underlying reason for the lack of efficient policy answers and the ongoing affordability crisis. From a policymaking perspective, the study suggests that necessary policy measures to resolve the housing affordability crisis may give a specific emphasis on housing rent, housing credit volume and construction costs as the major components of the crisis.

This study develops a novel measure and presents a new conceptual framework by combining quantitative research methods and policymaking in housing affordability. In this respect, to the best of the author’s knowledge, this is the first work to comparatively investigate the determinants of uniquely developed monthly housing affordability measurements.

The purpose of this paper is to provide a literature review of elasticity-based techniques for the estimation of the degree of operating leverage (DOL) and the degree of financial leverage (DFL) in empirical corporate finance research.

This paper describes the specific details of the estimation of DOL and DFL coefficients under both of the primary estimation techniques and documents the econometric properties of the estimates derived from each techniques.

There are tradeoffs between the two techniques, as each technique has both appealing and limiting features.

This paper indicates how each of the two techniques possesses limitations and suggests that future research should attempt to develop estimation techniques that overcome those limitations.