Search results

The COVID-19 pandemic and the onset of the conflict in Ukraine led to a sustained downturn in tourist arrivals (TA) in Russia. This paper aims to explore the influence of geopolitical risk (GPR) and other indices on TA over 1995–2023.

We employ a nonlinear autoregressive distributed lag (NARDL) model to analyze the effects, capturing both the positive and negative shocks of these variables on TA.

Our research demonstrates that the NARDL model is more effective in elucidating the complex dynamics between macroeconomic factors and TA. Both an increase and a decrease in GPR lead to an increase in TA. A 1% negative shock in GPR leads to an increase in TA by 1.68%, whereas a 1% positive shock in GPR also leads to an increase in TA by 0.5%. In other words, despite the increase in GPR, the number of tourists coming to Russia increases by 0.5% for every 1% increase in that risk. Several explanations could account for this phenomenon: (1) risk-tolerant tourists: some tourists might be less sensitive to GPR or they might find the associated risks acceptable; (2) economic incentives: increased risk might lead to a depreciation in the local currency and lower costs, making travel to Russia more affordable for international tourists; (3) niche tourism: some tourists might be attracted to destinations experiencing turmoil, either for the thrill or to gain firsthand experience of the situation; (4) lagged effects: there might be a time lag between the increase in risk and the actual impact on tourist behavior, meaning the effects might be observed differently over a longer period.

Our study, employing the NARDL model and utilizing a dataset spanning from 1995 to 2023, investigates the impact of GPR, gross domestic product (GDP), real effective exchange rate (REER) and economic policy uncertainty (EPU) on TA in Russia. This research is unique because the dataset was compiled by the authors. The results show a complex relationship between GPR and TA, indicating that factors influencing TA can be multifaceted and not always intuitive.

The purpose of this study is to examine the association between carbon emissions and earnings management (EM). This study also considers the effect of female CEOs on the association between carbon emissions and EM.

This study uses the carbon disclosure project (CDP) for carbon emissions data, the Compustat database for financial information and the ExecuComp database for female CEOs. The empirical sample of this study consists of 1,692 firm-year observations in the USA that voluntarily participated in the CDP survey from 2007 to 2015. Regression analysis and robustness tests are conducted for this study and both accrual and real EM are considered.

This study provides evidence that firms with female CEOs who voluntarily disclose their carbon emissions information engage in less real EM. Thus, the presence of female CEOs moderates the association between carbon emissions and EM. This study/paper also finds a positive association between carbon emissions and real EM, although there is an insignificant association between carbon emissions and accruals EM.

The association between carbon emissions and EM has important implications for investors, regulators and policymakers. This study suggests that policymakers should improve the conditions that promote inclusion of females in the top management positions to constrain EM.

This study focuses on the USA, which is one of the major contributors to carbon emissions in the world. The presence of female CEOs moderates the association between carbon emissions and EM and firms with female CEOs show a greater impact on EM.