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This study examines the effect of digitalization on poverty and income inequality in developing countries. The study answers the question of whether digitalization is a way for developing countries to get out of poverty and income inequality.

The study uses data from 17 developing countries with data from 2005 to 2021. The study employs fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS), with an augmented mean group (AMG) for robustness. Digitalization, as the variable of interest, is proxied by the digitalization index (DI), constructed using principal component analysis (PCA). The dependent variables are poverty and income inequality, which are used in different models.

The evidence indicates that digitalization decreases poverty and income inequality in developing countries. These findings are justified when we use the AMG estimator, but the strength of the coefficients and significance levels are higher in the FMOLS and DOLS estimators. The results of the control variables also show that human development (LHDI), CO2 emissions and foreign direct investment (FDI) have decreasing effects on poverty and income inequality. Thus, digitalization is a good option for developing countries to get out of poverty and income inequality to achieve sustainable development goals (1&10).

This study provides rigorous empirical evidence on the effect of digitalization on poverty and income inequality in developing countries. Unlike the previous studies on developing countries, this study used a DI to proxy digitalization. In addition, the authors use FMOLS and DOLS estimators, with an AMG estimator for robustness, to provide long-run coefficients.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-08-2023-0586

The vast amounts of waste generated today threaten economies and societies due to high environmental and management costs. The aim is to investigate the short- and long-term patterns of municipal waste generation (MWG) in response to socio-economic and demographic growth variables at national and regional levels.

A panel data approach employing ordinary least squares (OLS), fixed effects (FE), random effects (RE), fully modified least squares (FMOLS) and error correction model (ECM) techniques. A sample of 28 European countries (2000–2020) and 44 European Union (EU) regions (2000–2018) were selected.

During periods of economic growth and higher employment rates, consumer confidence tends to increase, leading to elevated levels of consumer spending and consumption. Intensification in the production factors, specifically capital and employment, results in an upsurge in MWG, thereby creating a cycle where waste generation becomes deeply entrenched in the economic system in both the short and long terms. Rapid population growth, attributed to higher fertility rates, is associated with increased MWG. At the regional level, a double-aging process and a shift toward an aging population exert less pressure on MWG in both the short and long term. Promoting higher levels of environment-oriented human development yields various benefits, including the generation of greater knowledge spillovers, enhanced environmental literacy, a shift toward circular thinking and the promotion of greener entrepreneurship. Increased R&D expenditures facilitate the development of innovative waste reduction technologies, fostering improvements in waste management techniques, recycling processes and the utilization of sustainable materials.

The research examines the short- and long-term adjustments of MWG in response to changes in macroeconomic variables from low aggregation (countries) to high aggregation (regions). By analyzing the relationship between economic growth, urbanization, healthcare system quality, labor market functioning, demographic trends, educational level, technological advancement and MWG, the study fills a research gap and enhances understanding of waste management interventions. However, data availability and waste statistics accuracy should be considered. Future research could explore the relationship between macroeconomic variables and waste generation in sectors beyond MWG, such as industrial or construction waste, for a more comprehensive understanding of waste generation as a whole.

The positive correlation between economic activity levels and waste generation in both the short and long terms, emphasizes the criticality of investing in waste reduction and recycling infrastructure to mitigate landfill waste. The negative correlation between population density and waste generation stresses the importance of strategic waste facility placement in low-density areas. To effectively manage higher MWG, tailored waste collection systems and initiatives promoting healthy lifestyles are of immense importance. The positive relationship between employment rates and waste generation underscores the necessity of waste reduction programs that generate employment opportunities. The positive correlation between fertility rates and waste generation emphasizes the need for the expansion of extended producer responsibility programs to include products and materials specifically associated with families and child-rearing. Education campaigns and governmental support for research and development (R&D) in waste reduction technologies are also integral components of an effective waste management strategy.

The short- and long-term adjustments of MWG reacts to shifts in macroeconomic variables from low aggregation (countries) to high aggregation (regions). Previous research has neglected the long-term information contained in variables by not incorporating the lagged error correction term (ETM). Neglecting this aspect could result in imprecise estimates of the elasticities.

The purpose of this study is to reveal the dynamics of house prices and sales in spatial and temporal dimensions across British regions.

This paper incorporates two empirical approaches to describe the behaviour of property prices across British regions. The models are applied to two different data sets. The first empirical approach is to apply the price diffusion model proposed by Holly et al. (2011) to the UK house price index data set. The second empirical approach is to apply a bivariate global vector autoregression model without a time trend to house prices and transaction volumes retrieved from the nationwide building society.

Identifying shocks to London house prices in the GVAR model, based on the generalized impulse response functions framework, I find some heterogeneity in responses to house price changes; for example, South East England responds stronger than the remaining provincial regions. The main pattern detected in responses and characteristic for each region is the fairly rapid fading of the shock. The spatial-temporal diffusion model demonstrates the presence of a ripple effect: a shock emanating from London is dispersed contemporaneously and spatially to other regions, affecting prices in nondominant regions with a delay.

The main contribution of this work is the betterment in understanding how house price changes move across regions and time within a UK context.

To estimate the volatility of exchange and stock markets and examine its spillover within and across the member countries of BRICS during COVID-19 and the conflict between Russia and Ukraine.

The study utilizes the “dynamic conditional correlation-generalized autoregressive conditional heteroskedasticity (DCC-GARCH)” approach of Gabauer (2020). The volatility of the markets is calculated following the approach of Parkinson (1980). The sample dataset comprises the daily volatility of the stock and exchange markets for 35 months, from November 2019 to September 2022.

The study confirms the existence of contagion effects among member countries. Volatility spillover between exchange and stock markets is low within the country but substantial across borders. Russian contribution increased significantly during the conflict with Ukraine, and other countries also witnessed a surge in the spillover index during the pandemic and war.

It adds to the body of literature by emphasizing the necessity of comprehending the economies' behavior and interdependence. Offers insightful information to decision-makers who must be more watchful regarding the financial crisis and its regional spillover.

The study is the first to explore the contagion of volatility among the BRICS countries during the two biggest crisis periods of the decade.