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This study aims to investigate access to mobile money services and its relationship to financial planning for adults with mobile phones across different countries in different income groups.

Using new survey data from the Global Findex Database over the 2021–2022 time period, this study applies traditional cross-sectional regressions in investigating the relationship between access to mobile money accounts and the proportion of adults that save and borrow across different countries in different income groups.

This study provides findings on population dynamics, the percentage of adults who own mobile phones, the percentage of adults that own mobile money accounts, and the percentage of adults who save and borrow through mobile money accounts across different countries in different income groups. Results of the cross-sectional regressions indicate a positive relationship between saving and borrowing in relation to access to mobile money accounts across different countries in different income groups. The empirical results are robust after controlling for financial literacy, and moreover, suggest a relatively stronger effect for saving relative to borrowing.

This study proposes a novel approach toward examining the relationship between access to mobile money accounts and the proportion of adults that save and borrow. This study quantifies the aggregate impact of mobile money access on saving and borrowing based on a new cross-sectional data set for different countries in different income groups.

This study aims to investigate the variation in overvaluation proxies and volatility across industry sectors and time.

Using industry sector data from the S&P Capital IQ database, this study applies traditional cross-sectional regressions to investigate the relationship between overvaluation and volatility over the 2001–2020 time period.

This study finds that the most volatile industry sectors generally do not coincide with overvalued industry sectors in the cross-section, implying that there are limitations to price-multiple methods for forecasting future volatility. Rather, this study finds that historical volatility significantly increases the goodness-of-fit when modeling volatility in the cross section of industry sectors. The findings of this study imply that firms should increase disclosures and transparency about corporate practices to decrease downside risk that stems from bad news. In addition, the findings underline the consistency between market efficiency and high levels of volatility in periods of significant uncertainty.

This study proposes a novel approach to examining the cross section of volatility across time for industry sectors.

This study aims to investigate physical capital investments for Azerbaijan in the context of Sustainable Development Goals (SDGs) 6 and 7.

Drawing on the conceptual frameworks of Soto et al. (2020) and Gaspar et al. (2019), this study adopts peer analysis in quantifying investment policy recommendations for Azerbaijan based on data from the World Bank, International Monetary Fund, United Nations Population Fund, the State Statistical Committee of the Republic of Azerbaijan and the US Energy Information Administration.

This study estimates that Azerbaijan invests approximately $1.47bn in their energy sector for 2020–2030 and that total spending on water and sanitation infrastructure increases by 1.91 percentage points of GDP by 2030.

Investment decision-making for physical capital based on the United Nations SDGs is an underresearched yet important topic. This study fills this void for Azerbaijan through peer country analysis.