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This study aims to test the validity of the Rajan theory in South Africa and other selected emerging markets (Chile, Peru and Brazil) during the period 1975–2019.

In this study, the researchers used time-series data to estimate a Bayesian Vector Autoregression (BVAR) model with hierarchical priors. The BVAR technique has the advantage of being able to accommodate a wide cross-section of variables without running out of degrees of freedom. It is also able to deal with dense parameterization by imposing structure on model coefficients via prior information and optimal choice of the degree of formativeness.

The results for all countries except Peru confirmed the Rajan hypotheses, indicating that inequality contributes to high indebtedness, resulting in financial fragility. However, for Peru, this study finds it contradicts the theory. This study controlled for monetary policy shock and found the results differing country-specific.

The findings suggest that an escalating level of inequality leads to financial fragility, which implies that policymakers ought to be cautious of excessive inequality when endeavouring to contain the risk of financial fragility, by implementing sound structural reform policies that aim to attract investments consistent with job creation, development and growth in these countries. Policymakers should also be cautious when implementing policy tools (redistributive policies, a sound monetary policy), as they seem to increase the risk of excessive credit growth and financial fragility, and they need to treat income inequality as an important factor relevant to macroeconomic aggregates and financial fragility.

In service, the periodic clashes of wheel flat against the rail result in large wheel/rail impact force and high-frequency vibration, leading to severe damage on the wheelset, rail and track structure. This study aims to analyze characteristics and dynamic impact law of wheel and rail caused by wheel flat of high-speed trains.

A full-scale high-speed wheel/rail interface test rig was used for the test of the dynamic impact of wheel/rail caused by wheel flat of high-speed train. With wheel flats of different lengths, widths and depths manually set around the rolling circle of the wheel tread, and wheel/rail dynamic impact tests to the flats in the speed range of 0–400 km/h on the rig were conducted.

As the speed goes up, the flat induced the maximum of the wheel/rail dynamic impact force increases rapidly before it reaches its limit at the speed of around 35 km/h. It then goes down gradually as the speed continues to grow. The impact of flat wheel on rail leads to 100–500 Hz middle-frequency vibration, and around 2,000 Hz and 6,000 Hz high-frequency vibration. In case of any wheel flat found during operation, the train speed shall be controlled according to the status of the flat and avoid the running speed of 20 km/h–80 km/h as much as possible.

The research can provide a new method to obtain the dynamic impact of wheel/rail caused by wheel flat by a full-scale high-speed wheel/rail interface test rig. The relations among the flat size, the running speed and the dynamic impact are hopefully of reference to the building of speed limits for HSR wheel flat of different degrees.

Though an accumulating body of study has analysed monetary policy transmission in India, there are few studies examining the differential impact of monetary policy action. Against this backdrop, this study aims to analyse the differential impact of monetary policy on aggregate demand, aggregate supply and their components along with the general price level in India.

The study develops a structural macroeconometric model, which is primarily aggregate and eclectic in nature. The generalized method of movements is used for estimation of behavioural equations, while a Gauss–Seidel algorithm is used for model simulation purposes.

The paper presents the results of two policy simulations from the estimated model that highlight the differential impact of monetary policy. The first one, hike in the policy rate by 5% and second is a reduction in bank credit to the commercial sector by 10%. The results from the first policy simulation experiment reveal that interest hike has a significant negative impact on aggregate demand, aggregate supply and general price level. However, the maximum impact is borne by investment demand and imports followed by private consumption. While as among the components of aggregate supply maximum impact is born by infrastructure output followed by the manufacturing and services sector with the agriculture sector found to be insensitive in nature. The results from the second policy simulation experiment revealed that pure monetary shocks have a significant negative impact on aggregate demand, aggregate supply and general price level. However, the maximum impact is born by private consumption and imports followed by investment demand. While as among components of aggregate supply maximum impact is borne by infrastructure followed by the manufacturing and services sector with the agriculture sector found to be insensitive in nature. From both policy simulation experiments, the study highlighted the relative importance of the income absorption approach as opposed to the expenditure switching effect.

The results obtained in this study provides a strong framework for design the monetary policy framework. The results are in a view of the differential impact of monetary policy action among the components of both aggregate demand and aggregate supply. This reflection of differential impact has immense significance for the macroeconomic stabilization as the central bank will have to weigh the varying repercussion of its actions on different sectors. For instance, the decline in output after monetary tightening might be conceived as mild from an overall perspective, but it can be appreciable for some sectors. This differential influence will have an implication for policy design to care for distributional aspects, which otherwise could be neglected/disregarded. Similarly, the output decline may be as a result of either consumption postponement or a temporary slowdown in investment. However, the one emanating due to investment decline will have lasting growth implications compared to a decline in consumer demand. In addition, the relative strength of expenditure changing or expenditure switching policies of trade balance stabilization may have varying consequences in the aftermath of monetary policy shock. Accordingly information on the relative sensitiveness/insensitiveness of different sectors/ components of aggregate demand towards monetary policy actions furnish valuable insights to monetary authorities in framing appropriate policy.

The work carried out in the present paper is motivated by the fact that although a number of studies have examined the monetary transmission mechanism in India, a very few studies examining the differential impact of monetary policy action. However, to the best of the knowledge, there is no such studies, which have examined the differential impact of monetary policy in the structural macro-econometric framework. The paper will enrich the existing literature by providing a detailed account of the differential impact of monetary policy among the components of both aggregate demand and aggregate supply in response to an interest rate hike, as well as a decrease in the money supply.

The objective of this study is to investigate the impact of longitudinal forces on extreme-long heavy-haul trains, providing new insights and methods for their design and operation, thereby enhancing safety, operational efficiency and track system design.

A longitudinal dynamics simulation model of the super long heavy haul train was established and verified by the braking test data of 30,000 t heavy-haul combination train on the long and steep down grade of Daqing Line. The simulation model was used to analyze the influence of factors on the longitudinal force of super long heavy haul train.

Under normal conditions, the formation length of extreme-long heavy-haul combined train has a small effect on the maximum longitudinal coupler force under full service braking and emergency braking on the straight line. The slope difference of the long and steep down grade has a great impact on the maximum longitudinal coupler force of the extreme-long heavy-haul trains. Under the condition that the longitudinal force does not exceed the safety limit of 2,250 kN under full service braking at the speed of 60 km/h the maximum allowable slope difference of long and steep down grade for 40,000 t super long heavy-haul combined trains is 13‰, and that of 100,000 t is only 5‰.

The results will provide important theoretical basis and practical guidance for further improving the transportation efficiency and safety of extreme-long heavy-haul trains.

Background: Fear has been a common response to the coronavirus disease 2019 (COVID-19) pandemic throughout the world. In Mauritius, the outbreak of COVID-19 has been an exceptional occurrence requiring stringent confinement of the population. In this study, we have explored people’s reactions to COVID-19 during confinement, with emphasis on fear and the impact of news on the level of fear.

Methods: An anonymized online survey was carried out during confinement. Participation was voluntary. Participants reported fear level on a scale from 1-10, where no fear scored 1 and maximum fear scored 10. Participants reported the impact of news on their fear level on a scale of 1-10, where 1 represented no impact and 10 represented maximum impact. Participants reported the status of information received about COVID-19 on a scale of 1-10 where 1 represented no information on COVID-19 and 10 represented maximum information on COVID-19.

Results: The self-rated level of fear during confinement had a mean of 5.09 with 95%CI [4.70, 5.47]. This increased to a mean of 6.39 with 95%CI [6.00-6.78] at the prospect of confinement being lifted. The difference was statistically significant (paired-sample T-test, p<0.001). With regard to the impact of news on fear of COVID-19, the mean for local news was 5.97 with 95%CI [5.59, 6.34] whereas that of worldwide news was 6.86 with 95%CI [6.50, 7.23]. Worldwide news had a more significant impact (paired-sample T-test, p<0.001). The information score about COVID-19 had a mean of 5.12 with 95%CI [4.71, 5.53].

Conclusions: Participants experienced a moderate level of fear of COVID-19 during confinement which increased at the prospect of confinement being lifted, implying that people felt safer during confinement. Their fear was influenced more by international news than by local news. Overall participants reported that they were moderately well informed about the COVID-19 pandemic.

Occupational Safety and Health Administration (OSHA) of the U.S. government ensures that all health and safety regulations, protecting the workers, are enforced. OSHA officers conduct inspections and assess fines for non-compliance and regulatory violations. Literature discussion on the economic impact of OSHA inspections with COVID-19 related citations for the construction sector is lacking. This study aims to investigate the relationships between the number of COVID-19 cases, construction employment and OSHA citations and it further evaluates the total and monthly predicted cost impact of OSHA citations associated with COVID-19 violations.

An application of multiple regression analysis, a supervised machine learning linear regression model, based on K-fold cross validation sampling and a probabilistic risk-based cost estimate Monte Carlo simulation were utilized to evaluate the data. The data were collected from numerous websites including OSHA, Centers for Disease Control and the World Health Organization.

The results show that as the monthly construction employment increased, there was a decrease in OSHA citations. Conversely, the cost impact of OSHA citations had a positive relationship with the number of COVID-19 cases. In addition, the monthly cost impact of OSHA COVID-19 related citations along with the total cost impact of citations were predicted and analyzed.

The application of the two models on cost analysis provides a thorough comparison of predicted and overall cost impact, which can assist the contractors to better understand the possible cost ramifications. Based on the findings, it is suggested that the contractors include contingency fees within their contracts, hire safety managers to implement specific safety protocols related to COVID-19 and request a safety action plan when qualifying their subcontractors to avoid potential fines and citations.

Climate variability and extremes adversely affect the livestock sector directly and indirectly by aggravating the prevalence of livestock diseases, distorting production system and the sector profitability. This paper aims to examine climate variability and its impact on livestock system and livestock disease among pastoralists in Borana, Southern Ethiopia.

Data were collected through a combination of quantitative and qualitative methods using household questionnaire, field observations, focus group discussions and key informant interviews. Areal grid dikadal rainfall and temperatures data from 1985 to 2014 were collected from national meteorological agency. The quantitative and qualitative data were analyzed and interpreted using appropriate analytical tools and procedures.

The result revealed that the study area is hard hit by moisture stress, due to the late onset of rainy seasons, decrease in the number of rainy days and volume of rainfall. The rainfall distribution behavior coupled with the parallel increase in minimum and maximum temperature exacerbated the impact on livestock system and livestock health. Majority of the pastoralists are found to have rightly perceived the very occurrence and manifestations of climate variability and its consequences. Pastoralists are hardly coping with the challenges of climate variability, mainly due to cultural prejudice, poor service delivery and the socio-economic and demographic challenges.

Pastoralists are vulnerable to the adverse impact of climate variability and extreme events.

The finding of the study provides baseline information for practitioners, researchers and policymakers.

This paper provided detailed insights about the rainfall and temperature trend and variability for the past three decades. The finding pointed that pastoralists’ livelihood is under climate variability stress, and it has implications to food insecurity.

Fewer researchers have investigated the climatic and economic drivers of land-use change simultaneously and the interplay between drivers. This paper aims to investigate the nonlinear and interaction effects of price and climate variables on the rice acreage in high-latitude regions of China.

This study applies a multivariate adaptive regression spline to characterize the effects of price and climate expectations on rice acreage in high-latitude regions of China from 1992 to 2017. Then, yield expectation is added into the model to investigate the mechanism of climate effects on rice area allocation.

The results of importance assessment suggest that rice price, climate and total agricultural area play an important role in rice area allocation, and the importance of temperature is always higher than that of precipitation, especially for minimum temperature. Based on the estimated hinge functions and coefficients, it is found that total agricultural area has strong nonlinear and interaction effects with climate and price as forms of third-order interaction. However, the order of interaction terms reduces to second order after absorbing the expected yield. Additionally, the marginal effects of driven factors are calculated at different quantiles. The total area shows a positive and increasing marginal effect with the increase of total area. But the positive impact of price on the rice area can only be observed when price reached 50% or higher quantiles. Climate variables also show strong nonlinear marginal effects, and most climatic effects would disappear or be weakened once absorbing the expected rice yield. Expected yield is an efficient mechanism to explain the correlation between crop area and climate variables, but the impact of minimum temperature cannot be completely modeled by the yield expectation.

To the best of the authors’ knowledge, this is the first study to examine the nonlinear response of land-use change to climate and economic in high-latitude regions of China using the machine learning method.

The purpose of this paper is to analyze the supply chain's resilience in crowd networks from both static and dynamic perspectives.

This paper first defines the supply chain’s resilience, then proposes a graphical and game-theoretic framework to evaluate the resilience.

In this framework, an equilibrium with high resilience will be achieved after the iterated prisoner's dilemma in the supply chain. The two-stage update mechanism contributes to higher profits, higher stability and stronger risk resistance capability. The reputation-based tit-for-tat strategy in the second stage helps to realize society cooperation.

This work pays more attention to the dynamic evolution of interactions between organizations in the supply chain. It provides an important theoretical basis for future work such as how to effectively control and guide the evolution of events in the intelligence network and how to stand sudden changes and avoid collapse.

This paper aims to examine the complexity of the relationship between human capital management (HCM) and the performance of community-based health planning and services (CHPS) from an emerging market perspective. It further explores the mediating role of community orientation; institutional intervention and capability of resources in the hypothesized relationship between HCM and the performance of CHPS.

Quantitative data was collected (through a survey) from 210 health volunteers using a systematic random sampling technique. A 95% response rate was realized and the data was analyzed using exploratory and confirmatory factor analysis and hierarchical multiple regression.

HCM has a direct relationship with the performance of the CHPS model. It also emerged that institutional intervention and capability of resources partially mediate the relationship between HCM and CHPS performance; while community orientation fully mediates the same relationship.

Capacity building for staff must be wired into the workings of the CHPS model to yield the maximum impact. This points to the need for training packages that focus on building both social and cultural competence for staff working among locals under the CHPS model. Effective planning is, thus, needed to ensure a seamless allocation of adequate resources to boost performance. Also, community engagement is critical to the success of the CHPS model as it could serve as a platform for awareness creation among locals.

This paper introduces community orientation, institutional intervention and capability of resources as mediating variables to investigate the hypothesized relationships. It offers a developing country insight into how HCM-related factors might be impacting the performance of community-based health programs.