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This chapter reviews the econometric approaches typically used to deal with the spike of zeros when modelling non-negative outcomes such as expenditures, income, or consumption. Relying on the assumptions of selection on observables for evaluating a policy or treatment, this chapter discusses other issues that arise with spikes of zeros in the data, including the analyst's choice between full information versus quasi-likelihood methods, considering whether observed zeros are true or masking more complex behavioural decisions, and dealing with zeros that arise due to self-selection. This chapter ends with discussions of empirical strategies to deal with these behavioural assumptions and a brief review of the literature where such strategies were employed.

Introduction: Political stability is an essential source of stock market dynamics. Investors are confident about countries that have higher political stability. Political stability in an economy enables investors to develop their ability to predict the future and thus to tend towards longer-term and permanent economic and financial activities.

Purpose: The study aimed to investigate the impact of political instability in BRICS countries and Türkiye on their stock market volatilities.

Methodology: The study analysed the univariate exponential generalised autoregressive conditional heteroskedasticity (EGARCH) Model. The model employed the credit default swap (CDS) 5-year USD Bond data of the BRICS countries and Türkiye to represent political instability. The daily stock exchange index return data from 1 January 2015 to 15 January 2023 was used for model estimation.

Findings: The results of the EGARCH model indicate that political instability is a crucial factor in stock market volatility. The coefficients suggest that when CDS increases in BRICS countries and Türkiye, the volatility of stock returns also increases. The analysis shows that the impact of political instability on the stock market of BRICS countries and Türkiye is not uniform. However, the significant effect of political instability on volatility is higher for Türkiye than for BRICS countries. This indicates that investors perceive the political risk of Türkiye to be greater than that of BRICS countries when investing in the stock market of Türkiye.

This paper aims to examine the reaction of energy inflation to geopolitical risks in the European Economic Area between 1990 and 2015.

This study applies the nonparametric time-varying coefficient panel data model with fixed effects. In addition, to further reveal potential tail effects that may not have been captured by conditional mean-based regressions, the method of moments quantile regression was also used.

The findings of this study are as follows: first, as European countries get exposed to geopolitical tensions, it is expected that energy prices will surge. Second, the ability of geopolitical risk to trigger energy inflation in recent times is not as powerful as it used to be. Third, countries with a lower inflation rate, when exposed to geopolitical risks, experience smaller increases in energy inflation compared to countries with a higher inflation rate.

The findings of this study lead us to the conclusion that transitioning from nonrenewable to renewable energy use is one channel through which the sampled countries can battle the energy inflation, which geopolitical risks trigger. A sound macroeconomic policy for inflation control is a complementary channel through which the same goal can be achieved.

Given the increasing level of energy inflation and geopolitical risks in the world today, this study is an attempt to reveal the time-varying characteristics of the relationship between these variables in European countries using a nonparametric time-varying coefficient panel data model and method of moments quantile regression with fixed effects.

The purpose of this study is to examine institutional quality’s absorptive capacity in African countries’ remittances-finance nexus.

A balanced panel data set of thirty African countries between 2000 and 2022 is used for the study. The study adopts an augmented mean group (AMG), method of moment quantile regression (MMQR) and two-step system generalized method of moment (2SGMM) as the estimation techniques due to the nature of the data set.

The findings of the direct effect reveal that remittances do not constitute the growth of financial development, while institutional quality promotes the growth of financial development in the long. The moderating effect of institutional quality in the linkages shows that the interactive term of institutional quality and remittances has a significant positive effect on financial development in the region. Hence, institutional quality moderates the impact of remittances. These results are robust to different proxies of financial development and estimates obtained from MMQR and 2SGMM.

This study, therefore, suggests that institutional quality is essential in the linkages between remittances and financial development. Hence, remittances should be seen as one of the instruments that can be used to develop the financial sector rather than survival mechanisms for households.

This study contributes to the literature by unearthing the absorptive capacity of institutional quality in the nexus between remittances and financial development in African countries, which extant studies have neglected.

Economic evaluations often utilise individual-patient data (IPD) to calculate probabilities of events based on observed proportions. However, this approach is limited when interest is in the likelihood of extreme biomarker values that vary by observable characteristics such as blood glucose in gestational diabetes mellitus (GDM). Here, instead of directly calculating probabilities using the IPD, we utilised flexible parametric models that estimate the full conditional distribution, capturing the non-normal characteristics of biomarkers and enabling the derivation of tail probabilities for specific populations. In the case study, we used data from the Born in Bradford study (N = 10,353) to model two non-normally distributed GDM biomarkers (2-hours post-load and fasting glucose). First, we applied fully parametric maximum likelihood to estimate alternative flexible models and information criteria for model selection. We then integrated the chosen distributions in a probabilistic decision model that estimates the cost-effective diagnostic thresholds and the expected costs and quality-adjusted life years (QALYs) of the alternative strategies (‘Testing and Treating’, ‘Treat all’, ‘Do Nothing’). The model adopts the ‘payer’ perspective and expresses results in net monetary benefits (NMB). The log-logistic and Singh-Maddala distributions offered the optimal fit for the 2-hours post-load and fasting glucose biomarkers, respectively. At £13,000 per QALY, maximum NMB with ‘Test and Treat’ (−£330) was achieved for a diagnostic threshold of fasting glucose >6.6 mmol/L, 2-hours post-load glucose >9 mmol/L, identifying 2.9% of women as GDM positive. The case study demonstrated that fully parametric approaches can be implemented in healthcare modelling when interest lies in extreme biomarker values.

The current research aims to investigate the impact of coronavirus 2019 (COVID-19) evolution, government stringency measures and economic resilience on stock market volatility in the Middle East and North African (MENA) emerging markets. Other macroeconomic factors were also taken into account.

Based on financial data from 10 selected MENA countries, we tested an integrated framework that has not yet been explored in prior research. The exponential generalized autoregressive conditional heteroskedasticity (E-GARCH) was adopted to analyze data from March 2020 to February 2022.

Our research illustrates the direct and indirect effects of the virus outbreak on stock market stability and reports that economic resilience could alleviate the volatility shock. This finding is robust across the various proxies of economic resilience used in this study. We also argue that the negative impact of the pandemic on equity market variation gets more pronounced in countries with higher level of stringency scores.

Policymakers ought to strengthen their economic structures and reinforce the economic governance at the national level to gain existing and potential investors’ trust and ensure lower stock market volatilities in times of crisis. Our study also recommends some key economic factors to consider while establishing efficient policies to tackle unexpected shocks and prevent financial meltdowns.

Our findings add to the evolving literature on the reaction of economic and financial markets to the sanitary crisis, particularly in developing countries where research is still scarce. This study is the first of its kind to investigate the stock market reaction to stringency measures in the understudied MENA region.

We seek to quantify the relationship between urbanization and economic growth in China using recent advances in econometric techniques.

This study adopts a smoothed instrumental variables quantile regression (SIVQR) estimator to obtain consistent estimates of the effects of urbanization on economic growth in China. Our approach accounts for the differential impacts of urbanization across the conditional distribution of economic growth while allowing for an identification strategy that addresses the endogeneity of urbanization. Our main findings reveal that ignoring urbanization endogeneity leads to inconsistent estimates of urbanization effects. Further, we find a positive relationship between urbanization and growth resembling an inverted U-shape. This supports the hypothesis that the beneficial effects of urbanization intensify at initial stages while diminishing beyond a certain threshold, due perhaps to weakening scale economies.

Our main results indicate that the individual productivity gains brought by urbanization outweigh the negative effects thereof that impede productivity, thus contributing to the economic growth in China. Further, we find that ignoring differential impacts of urbanization underestimates the beneficial effects of urbanization for provinces whose quality of governance is in the vicinity of the center of quality distribution. Ignoring the endogeneity of urbanization generates inconsistent estimates of the elasticity of economic growth with respect to urbanization. Finally, we estimate an inverted U-shape resembling relationship between urbanization and growth.

First, future studies would benefit from incorporating more data as provinces further east on the mainland become more urbanized and urbanization runs its course. Second, controlling the barriers to rural-urban mobility would contribute to the robustness of the estimated relationship between urbanization and growth once such data became available. Unveiling the impact of government-imposed barriers is key to designing optimal policies that help fuel economic growth in the country. Finally, future research could benefit from information on urbanization sources not considered here such as inter-provincial migration, as such data become publicly available.

Quantifying the beneficial effects of urbanization on economic growth can help guide the government in China to further fuel the growth through a set of relevant policy tools that promote urbanization.

Rural-urban migration in China lays the groundwork for economic advancement in recipient cities and economies, as it may induce scale economies. This can benefit both the economy at large and the migrants.

The SIVQR estimator accounts for potential heterogeneous effects of urbanization across the entire conditional distribution of growth while allowing for an identification strategy that addresses the endogeneity of urbanization. An additional distinguishing feature of the current study is our use of the most recent novel, provincial-level data obtained from the National Bureau of Statistics of China. Our focus on a single country allows sidestepping issues arising from the inconsistency of the definition of urban across different countries while accounting for intra-country urbanization drivers intrinsic to China, such as natural features and geographic characteristics. Therefore, our approach has the potential to sidestep the bias resulting from the differences in mechanisms behind urbanization-growth relationships across different countries.

This study investigates the reasons behind the very high net interest margins in the Greek banking industry compared to the euro-area, focussing on the association between bank competition and recapitalisations.

The author conducts a dynamic panel analysis covering the period from the early 2000s to 2021, that controls for possible endogeneity and treats for heterogeneity. The author also employs local projections impulse response functions that control for structural changes in Greek banking.

The author finds that low bank competition has contributed to high net interest margins in Greece. Interestingly, the impact of recapitalisations conditional to low bank competition has had a significant further impact on increasing net interest margins, which is a noteworthy case due to several Greek bank recapitalisations in the last ten years. The author’s findings are supported by local projections impulse response functions.

To mitigate distortions in bank competition, the author argues to accelerate steps toward the direction of the banking union and a common bank regulation framework in the euro-area.

The purpose of this study is to investigate the role of ethical obligation and environmental concern in young consumers’ green purchase behaviour using Ajzen’s (1991) theory of planned behaviour as underpinning theoretical model.

Data collected from 253 college students of a major higher education institution in Northern India were analysed by using structural equation modelling and moderated mediation analysis in AMOS 22.0 and SPSS 20.0.

Investigating why environmental concern does not significantly translate into green purchase intention, the study demonstrates that the effect of environmental concern was mediated through attitude and ethical obligation. In addition, the study also found that the effect of environmental concern on attitude was positively moderated by ethical obligation. Moreover, subjective norms were found to exhibit no direct effect on green purchase intention; rather, this effect was indirect and mediated through attitude and perceived behavioural control. The results of moderated mediation analysis further demonstrated that the indirect effect of subjective norms on green purchase intention through attitude was found conditional on the values of perceived behavioural control.

The study offers a valuable contribution by signifying the moderating role of ethical obligation in green purchase behaviour. It also contributes to the existing knowledge by assessing the conditional indirect effect of subjective norms on green purchase intention which is rarely examined in the literature.

The adoption and usage of information and communication technology (ICT) has introduced transformation in the tourism arena with ICT applications extensively used in tourism industry. In addition to ICT, an advanced infrastructure is essential for the development of tourism industry. Thus, the goal of present research is to probe the impact of ICT and infrastructure on tourism development (TD) in 28 Asian economies using method of moments panel quantile regression (MM-QR) model introduced by Machado and Silva (2019) applied to a panel data from 2008 to 2020. Empirical findings demonstrate that there is an asymmetric non-linear effect of ICT and infrastructure through all quantile range. This indicates that ICT has negative effect on TD in poor countries while positive impact in rich countries. Negative impact in poor countries may be due to higher establishment cost and information technology (IT) productivity paradox. However, results confirm the importance of ICT and infrastructure in endorsing the development of tourism sector in Asian nations by lessening time and money costs and facilitating travelers.