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Despite the growing recognition of the complex interplay between macroeconomic shock indexes and stock market dynamics, there is a significant research gap concerning their interconnectedness and return spillovers in the context of the African stock market. This leaves much to be desired, given that the financial market in Africa is arguably one of the most preferred destinations for hedge and portfolio diversification (Alagidede, 2008; Anyikwa and Le Roux, 2020). Further, like other financial markets across the globe, the increased capital flow, coupled with declining information asymmetry in Africa, has deepened intra and inter-sectoral integration within and across national borders. This has, thus, increased the susceptibility of financial markets in Africa to spillover of shocks from other sectors and jurisdictions. Additionally, while previous studies have investigated these factors individually (Asafo-Adjei et al., 2020), with much emphasis on developed markets, an all-encompassing examination of spillovers and the connectedness between the aforementioned macroeconomic shock indexes and stock market returns remains largely unexplored. This study happens to be the first to consider the impact of each of the indexes on stock returns in Africa, with evidence spanning from May 2007 to April 2023, covering notable global crisis episodes such as the Global Financial Crisis (GFC), the COVID-19 pandemic and the Russia–Ukraine war.

This study employs the novel quantile vector autoregression (QVAR) model, making it the first of its kind in literature. By applying the QVAR, the study captures the potential nonlinear and asymmetric relationship between stock returns and the factors of interest across different quantiles, i.e. bearish, normal and bullish market conditions. Thus, the approach allows for a more accurate and nuanced examination of the tail dependence and extreme events, providing insights into the behaviour of the variables under extreme events.

The study revealed that connectedness and spillovers intensified under bearish and bullish market conditions. It was also observed that, among the macroeconomic shock indicators, FSI exerted the highest influence on stock returns in Africa in both bullish and normal market conditions. Across the various market regimes, the Egyptian Exchange (EGX) and the Nairobi Stock Exchange (NSE) were net receiver of shocks.

This study happens to be the first to consider the impact of each of the indexes on stock returns in Africa, with evidence spanning from May 2007 to April 2023, covering notable global crisis episodes such as the GFC, the COVID-19 pandemic and the Russia–Ukraine war. On the methodology front, this study employs the novel QVAR model, making it one of the few studies in recent literature to apply the said method.

In the digital age, the spread of online behavior and real-world information leads to social contagion. This study aims to investigate the contagion phenomenon of online physician choice and then discuss its potential influence on the sub-specialization process in the healthcare service industry. In specific, this study aims to propose the basic mechanism of infection and immunity as follows – exposure to antigen may lead to an immune response, and the success of the immune response may depend on the provision of appropriate immune signaling.

Data collected from haodf.com including 4 disease types and 247 physicians from 2008 to 2015 were used to test the proposed hypotheses. Panel vector autoregression method was utilized to analyze the panel data.

The obtained result shows that social contagion of physician choice over disease type is salient on e-consultation platforms, indicating that physicians associated with/on haodf.com are concentrating on an even narrower type of disease. Disclosing more simple signals (physician history orders) results in more disease concentration for that physician in the future. In contrast, disclosing more detailed signals (physician-contributed knowledge or physician reviews) leads to less disease concentration.

This finding implies that physician-contributed knowledge and physician reviews may act as immune signal which will tend to trigger a success immune response. This study not only suggests managers should be careful about the double-edged sword effect of online physician choice contagion but also provides the useful approaches to promote or restrain such a contagion in a flexible way.

The purpose of this study is to examine the impact of a recent innovation in the uranium market, the Global X Uranium Exchange-Traded Fund (URA), on the trading characteristics of constituent and non-constituent stocks.

The authors analyse bid-ask spread measures, relative effective spreads and adverse selection costs to assess changes in information asymmetry among uranium stocks. The authors also study abnormal returns to assess the impact of URA on the market.

Over a three-month period, following the introduction of URA, the authors find uranium stocks display decreased bid-ask spread measures, driven by reductions in information asymmetry. Relative effective spreads decrease by 36% after the introduction of URA, and adverse selection costs decline by 24% over the same period. Uranium stocks experience a significant positive abnormal return of 5.0% the day after the introduction of URA with subsequent price reversals. These suggest that the introduction of URA prompted uninformed traders to rebalance portfolios and migrate to the less information-sensitive Exchange-Traded Fund (ETF), causing temporary deviations in trading characteristics.

The authors demonstrate that the introduction of new financial securities to the market can have a significant impact on the trading characteristics of related equities. As URA is the only ETF in the uranium sector, the authors thereby avoid the influence of multiple ETFs that may have impacted previous studies.

Because of growing demand for slim, thin and cheap handheld devices, reduced-volume solder interconnects like land grid array (LGA) are becoming attractive and popular choices over the traditional ball grid array (BGA) packages. This study aims to investigate the mechanical shock and impact reliability of various solder alloys and BGA/LGA interconnect configurations.

Therefore, this paper uses drop testing experiments and numerical finite element simulations to evaluate and compare the reliability performance of both LGA and BGA components when exposed to drop and impact loadings. Additionally, three common solder alloys, including 63Sn37Pb, SAC305 and Innolot, are discussed.

The results of this study showed that electronic packages’ drop and impact reliability is strongly driven by the solder configuration and the alloy type. Particularly, the combination of stiff solder alloy and shorter joint, LGA’s assembled with SAC305, results in highly improved drop reliability. Moreover, the BGA packages’ performance can be considerably enhanced by using ductile and compliant solder alloys, that is, 63Sn37Pb. Finally, this paper discussed the failure mode of the various solder configurations and used simulation results to explain the crack and failure situations.

In literature, there is a lack of published work on the drop and impact reliability evaluation and comparison of LGA and BGA solders. This paper provides quantitative analysis on the reliability of lead-based and lead-free solders when assembled with LGA and BGA interconnects.

With the outbreak of COVID-19 at the beginning of 2020, many countries attempted to control the spread of the virus by implementing a lockdown policy. This study investigates the impact of the lockdown in Jakarta in 2020 on the economy. The database used the Input–Output (IO) 2015. We employed a bottom-up approach by selecting Jakarta to generate the shock on the economy since only Jakarta constantly applied the lockdown policy named Large-Scale Social Restriction (PSBB) policy in 2020. We earned some useful information on whether the shock in Jakarta significantly impacted the national economy as well as other provinces. Our empirical results revealed that the PSBB policy reduced output in Jakarta by 7.20%, value-added declined by about 8.04%, income waned by 8.08%, and labour shrank by 7.68%. We also found that national output decreased by 1.30% in other provinces, especially those depending on the agricultural sector.

This study aims to explore the impact of oil prices on housing prices using Pakistani annual data from 1973 to 2021.

The Augmented Dickey–Fuller (ADF) and Phillips–Perron (PP) tests were used for unit-root testing, whereas the johansen-juselius test was used for cointegration. For the short-run, the error correction model is used and the robustness of the model is checked using the dynamic ordinary least squares (DOLS) and fully modified OLS (FMOLS). The cumulative sum (CUSUM) and CUSUM of Squares tests were used to check the stability of the model, while parameter instability was confirmed by the Chow breakpoint test. Finally, the impulse response function was used for causality.

According to the findings, rising oil prices, among other things, have an impact on housing prices. Inflation is the single most important factor affecting not only the housing sector but also the entire economy. Lending and exchange rates have a significant impact on housing prices as well. The FMOLS and DOLS results suggest that the OLS results are robust. According to the variance decomposition model, housing prices and oil prices are bidirectionally related. The Government of Pakistan must develop a housing policy on a regular basis to develop the country’s urban housing supply and demand.

It is suggested that in Pakistan, the rising oil prices is a problem for the housing prices as well as many other sectors. The government needs to explore alternative ways of energy generation rather than the heavy reliance on imported oil.

Pakistan has been experiencing rising oil prices and housing prices with the rapid urbanisation and rural–urban migration. The contribution to the literature is that neither attempt (as to the best of the authors’ knowledge) has been made to check the impact of rising oil prices on housing sector development in Pakistan.

The aim of this study is to understand a family firm's choice of related-party transaction (RPT) types and analyze their value impacts to separate the abusive from benign RPTs.

It uses a 10-year panel of BSE-listed 378 family (and 200 non-family) firms. The fixed effects, logit and difference-in-difference (DID) models help examine value effects, propensity and persistence of harmful RPTs.

Loans/guarantees (irrespective of counterparties) destroy firm value. Capital asset RPTs decrease the firm value but enhance value when undertaken with holding parties. Operating RPTs increase firm value and profitability. They improve asset utilization and reduce discretionary expenses (especially when made with controlled entities). Family firms have larger loans/guarantees and capital asset volumes but have smaller operating RPTs than non-family firms. They are less likely to undertake loans/guarantees (and even operating RPTs) and more capital RPTs vis-à-vis non-family firms. Family firms persist with dubious loans/guarantees but hold back beneficial operating RPTs, despite RPTs being in investor cross-hairs amid the Satyam scam.

Rent extractability and counterparty incentives supplement each other. (1) The higher extractability of related-party loans and guarantees (RPLGs) dominates the lower extraction incentives of controlled parties. (2) Holding parties' bringing assets, providing a growth engine and adding value dominate their higher extraction incentives (3) The big gains to the operational efficiency come from operating RPTs with controlled parties, generally operating companies in the family house. (4) Dubious RPTs seem more integral to family firms' choices than non-family firms. (5) Counterparty incentives behind the divergent use of RPTs deserve more research attention. Future studies can give more attention to how family characteristics affect divergent motives behind RPTs.

First, the study does not single out family firms for dubious use of all RPTs. Second, investors, auditors or creditors must pay close attention to RPLGs as a special expropriation mechanism. Third, operating RPTs (and capital RPTs with holding parties) benefit family firms. However, solid procedural safeguards are necessary. Overall, results may help clarify the dilemma Indian regulators face in balancing the abusive and business sides of RPTs.

The study fills the gap by arguing why some RPTs may be dubious or benign and then shows how RPTs' misuse depends on counterparty types. It shows operating RPTs enhance operating efficiencies on several dimensions and that benefits may vary with counterparty types. It also presents the first evidence that family firms favor dubious RPTs more and efficient RPTs less than non-family firms.

This paper models the benefits of Islamic banking on the efficiency of the banking sector and on societal happiness. This paper aims to examine how the adoption of Islamic banking to various degrees affects economics outcomes.

This study uses machine-learning tools to build a happiness function and integrate it in an agent-based model to test for the direct and indirect welfare effects of implementing Islamic banking principles.

This study shows that even though Islamic banking systems tend to reduce economic activity, financial stability and societal happiness is improved. Additionally, a banking sector using Islamic principles across all its members is better equipped to handle banking crises because contagion to both economic activity and societal welfare is greatly reduced. At the same time, adoption of the profit-and-loss sharing (PLS) paradigm by banks may also slow down economic growth.

The findings extend existing literature on the advantages of Islamic banking, by quantifying the welfare benefits of the PLS paradigm on happiness and financial stability.

To the best of the authors’ knowledge, this paper is the first to combine agent-based modelling with machine learning tools to examine the benefits of the Islamic banking model on financial stability, social welfare and unemployment.

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.

The main purpose of this paper is to investigate the dynamic effects of the oil price shocks on Iran’s inflation in the period 1993:2–2018:2

The main purpose of this paper is to investigate the dynamic effects of the oil price shocks on Iran’s inflation in the period 1993:2–2018:2 using the time-varying parameter vector autoregressive (TVP-VAR) model. The dynamics of the results enable us to study the amount and severity of the impact of the oil price shocks on inflation with the distinction of the sanctioned and non-sanctioned periods. The volume of oil export is used to identify the effective oil sanctions. The period is divided into sanctioned and non-sanctioned periods by Markov switching model.

The results show that the pass-through of oil price shocks into Iran’s inflation are time-varying, and there are significant differences at sanction period from other time horizons. An increase in oil price has a positive effect on inflation and its effects are stronger during the sanctions period. It is also observed that the producer price index is more sensitive to changes in the oil price than the consumer price index. The necessity of the government’s earnest efforts to improve international relations to lift the sanctions, along with diversification of exports, and making the economy of Iran independent of oil revenues is obvious.

In addition to the exogenous oil price shocks, Iran’s economy faces numerous restrictions for its oil exports due to the sanctions. The main purpose of this paper is to investigate the dynamics effects of the oil price shocks on Iran’s inflation in the period 1993:2–2018:2 using the time-varying parameter vector autoregressive (TVP-VAR) model. The dynamics of the results enable us to study the amount and severity of the impact of the oil price shocks on inflation with the distinction of the sanctioned and non-sanctioned periods. The volume of oil export is used to identify the effective oil sanctions.