Search results

Higher economic output as measured in gross national product (GNP) may not always imply a higher quality of living. It has been the outcome of the long debate between growth and development of a nation. The aims of economic growth should be reconsidered because it has polluted the environment, wasted natural resources, harmed people’s quality of life, and failed to alleviate socioeconomic problems. It is also a common phenomenon to the economies of the South Asian region. The study is thus conducted to show the existence of long-run relationship and short-run interplays between output efficiency of energy use (GEU) and carbon efficiency of energy use (CEU) in the panel of countries in the South Asian region for the period of 1971–2014. The results show that there is a long-run and short-run association between energy efficiency in output and carbon emission as respectively measured in GEU and CEU. This means that in South Asia, energy consumption leads to an increase in both gross domestic product and carbon emissions. When GEU is used as the independent variable in vector error correction model (VECM), the result reveals that any short-run disequilibrium from the long-run stable connection will be adjusted over time, and the long-run stable relationship will be restored.

There are many channels through which terrorism can influence macroeconomic variables, such as economic growth and international trade. However, the intensity of the consequences of terrorist events on the economy may be varied across countries based on the economic structure. Therefore, it is not unusual for the impacts of terrorism to vary across the developed and developing nations. Against this backdrop, this study assesses the influences of conflicts and terrorist activities on the growth of per capita gross domestic product (GDP) in 21 developed and 23 developing countries from 1970 to 2015. The stochastic properties of the variables are looked into by carrying out panel-specific Augmented Dicky-Fuller (ADF) and Phillips-Peron (PP) unit root test followed by estimating the dynamic regressions equations in structured balanced panel frameworks for selected developed and developing economies separately. This study draws on data from various sources namely, Global Terrorism Database (GTD) and World Development Indicators (WDI; World Bank). Our empirical findings imply that terrorist activities have a significant growth-limiting effect, and the extent and significance of impacts are higher in case of developing economies.

This chapter uses fully modified OLS principles to develop new methods for estimating and testing hypotheses for cointegrating vectors in dynamic panels in a manner that is consistent with the degree of cross sectional heterogeneity that has been permitted in recent panel unit root and panel cointegration studies. The asymptotic properties of various estimators are compared based on pooling along the ‘within’ and ‘between’ dimensions of the panel. By using Monte Carlo simulations to study the small sample properties, the group mean estimator is shown to behave well even in relatively small samples under a variety of scenarios.

This paper develops methods of Bayesian inference in a cointegrating panel data model. This model involves each cross-sectional unit having a vector error correction representation. It is flexible in the sense that different cross-sectional units can have different cointegration ranks and cointegration spaces. Furthermore, the parameters that characterize short-run dynamics and deterministic components are allowed to vary over cross-sectional units. In addition to a noninformative prior, we introduce an informative prior which allows for information about the likely location of the cointegration space and about the degree of similarity in coefficients in different cross-sectional units. A collapsed Gibbs sampling algorithm is developed which allows for efficient posterior inference. Our methods are illustrated using real and artificial data.

The aim of this chapter is to provide equilibrium exchange rates values for a large set of currencies and to study the adjustment process of observed exchange rates toward these levels by paying special attention to emerging Asian countries. Relying on panel smooth transition regression models, we show that real exchange rate dynamics in the long run are nonlinear for emerging Asian countries, and linear for the G7 currencies. Especially, there exists an asymmetric behavior of the real exchange rate when facing an over- or undervaluation, the adjustment speed being higher in the case of undervaluation in Asia. Although this result may be explained by the international pressure to limit undervaluation, the undervaluation may still persist over time, as has been observed since the beginning of 1990s.

Introduction: One of the main goals of the 2030 Agenda for Sustainable Development is to represent gender equality due to its essential role in sustainable progress. At the same time, the balance between women and men in management is explicitly mentioned as a desideratum, given that more women in leadership roles positively impact business performance and sustainability.

Purpose: The study investigates the dynamic relationship between gender inequalities in management positions and sustainable competitiveness. Our contribution is twofold: we examine this interrelationship and its causality.

Methodology: We used panel data of 350 observations for 2012–2021, and we employ a Vector Auto-Regression model and Granger causality method to examine the relationship between the gender gap in management and sustainable competitiveness. The panel VAR for analysing the impulse response function was enriched using Monte Carlo simulations with 5% and 95%.

Findings: The results highlighted that a bidirectional causality between the gender gap in management and sustainable competitiveness is manifested in the European countries. Our results are similar to other studies found in the literature, with gender equality and sustainability positively associated. As an element of originality, our study demonstrates that gender equality in management contributes to sustainable performance, and, on the other hand, a more competitive and sustainable environment contributes to eliminating the gap between men and women in management.

This chapter provides an overview of topics in nonstationary panels: panel unit root tests, panel cointegration tests, and estimation of panel cointegration models. In addition it surveys recent developments in dynamic panel data models.