The impact of central bank independence and transparency on the cost of capital, equity home and foreign bias, and debt home and foreign bias

The independence and transparency of central banks have a substantial influence on investment holdings and financial decisions, as monetary policy affects macroeconomic fundamentals and the financial market. A Political government of a country may influence monetary policy as different political parties have different agendas and goals. Politicians are well aware of the importance of monetary policy issues such as price stability and market volatility; however, they are less inclined than the central bank's authority to prioritize monetary policy objectives over their political agenda and commitment to the public. Politicians and central bank personnel have diverse policy preferences and points of view, making central bank independence (CBI) and transparency (CBT) crucial for a country's financial market and competitiveness. Therefore, our main argument is that central bank independence and transparency may interact with macroeconomy and institutional quality to reduce information asymmetry and convey policy and institutional stability signals to foreign investors. As a result, more market participants lead to risk sharing, lower cost of capital, reduced home bias, and increased foreign bias in equity and debt portfolios. This study employed a panel dataset of 40 countries from 2001 to 2014, including 23 developed and 17 emerging countries. The first empirical study investigates the impact of central bank independence and transparency on the cost of capital. Following existing literature, we use four measures to proxy for the cost of capital. We find compelling evidence supporting the hypothesis that countries with a higher degree of central bank independence and transparency experience lower cost of capital. In the second empirical study, we examine the impact of central bank independence and transparency on equity home and equity foreign bias. Our findings, based on rigorous analysis, demonstrate that a lower degree of home bias is linked to a higher degree of central bank independence and transparency, and an equally higher degree of equity foreign bias is associated with an increased degree of central bank independence and transparency. Finally, in our third empirical study, we investigate whether various degrees of central bank independence and transparency affect debt home and debt foreign bias in the same way that equity home and foreign bias. Following extensive analysis, our findings demonstrate that a lower level of debt home bias is associated with a higher degree of central bank independence and transparency. Similarly, higher debt foreign bias is associated with increased central bank independence and transparency. The primary contribution to the knowledge of this research is its extension of the literature on central banking and international finance. As the independence and transparency of the central bank influence, the cost of capital is crucial for developing a country's financial market and economic growth. Therefore, this study would help policymakers develop a deeper understanding of monetary policy principles and international portfolio management. The independence and transparency of the central bank influence home bias and foreign bias in equity and debt portfolio by reducing the cost of capital and increasing risk sharing among investors. The fund manager and portfolio investors will find this study invaluable in making decisions regarding international portfolio investment allocation

Derivation of new design rainfall in Qatar using L-moment based index frequency approach

AbstractFor stormwater system design, flood estimation and many other environmental assessment tasks, design rainfall is an essential input. Estimation of design rainfall is generally made using a regionalization technique based on a regional database of observed rainfalls. Many countries have derived their own generalized design rainfall data, which are generally expressed in the form of intensity–duration–frequency (IDF) curves. In Qatar, situated in an arid region, the existing IDF data were developed in 1991 using a limited data set. This paper presents the development of new IDF data for the State of Qatar using the method of L-moments and the index regional frequency analysis approach. The daily rainfall data from 32 stations located in Qatar and nearby Gulf countries have been used to form a homogeneous region. It has been found that the Pearson Type 3 distribution best fits the 24-h duration annual maximum rainfall data in the Qatar region. For the ungauged case, a prediction equation is developed where mean annual maximum rainfall is expressed as a function of climatic and physiographic characteristics. From a leave-one-out validation, it has been found that the developed prediction equation can estimate mean annual maximum rainfall with a median relative error of about 5.5%. Finally, an approximate method is used to obtain design rainfalls for other durations due to the limitations of continuous pluviograph data in Qatar. The new set of IDF curves is based on a much bigger dataset than the existing 1991 IDF curves. It is expected that the new IDF curves will have wider application in Qatar and will provide a statistically sound basis for storm water design, flood and environmental studies. The method can be applied to other middle-eastern states and similar arid countries in the world

Table 2: Example applications of the use of remote sensing technologies to detect change in vegetation.

In order to understand the distribution and prevalence of Ommatissus lybicus (Hemiptera: Tropiduchidae) as well as analyse their current biographical patterns and predict their future spread, comprehensive and detailed information on the environmental, climatic, and agricultural practices are essential. The spatial analytical techniques such as Remote Sensing and Spatial Statistics Tools, can help detect and model spatial links and correlations between the presence, absence and density of O. lybicus in response to climatic, environmental, and human factors. The main objective of this paper is to review remote sensing and relevant analytical techniques that can be applied in mapping and modelling the habitat and population density of O. lybicus. An exhaustive search of related literature revealed that there are very limited studies linking location-based infestation levels of pests like the O. lybicus with climatic, environmental, and human practice related variables. This review also highlights the accumulated knowledge and addresses the gaps in this area of research. Furthermore, it makes recommendations for future studies, and gives suggestions on monitoring and surveillance methods in designing both local and regional level integrated pest management strategies of palm tree and other affected cultivated crops

Flood Risk Assessment and Protection Guidelines for Infrastructure Planning in Qatar

This paper presents key features of "Flood Assessment and Protection Guidelines" (FAPG) prepared by the Ministry of Municipality and Environment (MME), Qatar. It is intended that the FAPG will provide guidance and assistance to a wide range of entities including government agencies, developers, engineers, planners and policy makers for locating flood prone areas across Qatar, assessing potential flood hazard and subsequent mitigation. A flood modelling was carried out using two-dimensional rain on grid (RoG) hydraulic modelling approach. A series of flood risk maps covering both rural and urban areas of Qatar were then prepared as per the degree of flood risk to people, property and infrastructure. These maps have been provided as digital flood inundation layers in an interactive GIS web-based flood mapping portal

Rainfall analysis under changing climate regime in Qatar

Rainfall data is needed in the planning and design of storm water infrastructure, hydraulic structures, flood management works and various environmental assessment tasks. Design rainfall is generally expressed by intensity-duration-frequency (IDF) curves. This thesis focuses on rainfall analysis, in particular, trends and variability in rainfall indices, selection of probability distributions in frequency analysis of rainfall data, uncertainty assessment and evaluation of climate change impact on design rainfall. In this research, Qatar, located in the arid region of the Gulf has been selected as the study area. Rainfall data from a total of 35 rainfall stations from Qatar and nearby Gulf countries including Kingdom of Saudi Arabia, Bahrain, Oman and United Arab Emirates have been used in this study. A comprehensive quality check has been carried out in collating these rainfall data. Any station failing the quality assurance test is excluded from the analysis. It should be noted that different subsets of these stations have been used in the analysis and modelling presented in different thesis chapters. This research identified trends in rainfall data in Qatar using fifteen different rainfall indices by applying a combination of Mann-Kendall and Spearman’s Rho tests. It has been found that rainfall indices in Qatar have mixed trends (both positive and negative trends) throughout the country. Stations showing increasing trend in annual total rainfall are mainly located in the central part of Qatar. However, no relationship between spatial location and the elevation of rain gauges is found with the identified trends. Examination of trends in annual total rainfall during dry and rainy seasons shows that seasonal rainfall in Qatar is changing. This study identifies the best fit probability distribution for Qatar for annual maximum rainfall data based on fourteen different probability distributions and three goodness-of-fit tests. Based on a relative scoring method, the Generalized Extreme Value distribution is found to be the best fit distribution for majority of the selected stations. A modelling framework is also developed to quantify uncertainty in design rainfall estimation arising from limited data length using Monte Carlo simulation and bootstrapping techniques. Results from bootstrapping on the observed annual maximum rainfall data show that the estimate of the mean rainfall is associated with the smallest degree of standard error, whilst skewness has the highest error level. The coefficient of variation (CV) of standard deviation estimate is found to be 12 times higher than that of the mean. Furthermore, the CV of skewness estimate is found to be 26 times higher than that of the mean. Based on the results of Monte Carlo simulation, it has been found that the confidence band (measure of uncertainty) increases with increasing “average recurrence interval” (ARI). The 100 year ARI design rainfall intensity has the highest degree of uncertainty among the six ARIs (2 to 100 years) considered in this study. This study assesses the impacts of climate change on the design rainfall estimation in Qatar based on Intergovernmental Panel on Climate Change’s most recent new generation of climate models. A total of 61 Global Circulation Models with 609 emission scenarios are considered for the assessment. The results indicate an increase of up to 50% for the 100-year rainfall event from current to the intermediate scenario (2040-2069). The rate-of-change of the far future (2070-2100) is at similar level as the intermediate period

Study on the thermal performance of a multi-layer structural green roof panel / Abdullah-Al-Mamoon

The indoor condition of a building is one of the most important concerns for the occupants which is affected by climatic conditions. During a typical summer day, solar radiation heats up a building through the windows, walls, doors and especially the roof. To maintain indoor comfort during the summer, the heat gained must be removed by a cooling system. The energy is used for cooling purposes to make indoor comfort for the building’s occupants. As a result, energy savings is a major focus in building design and requires systematic investigations. It is suggested to make a proper roof design to ensure a comfortable temperature inside a building. The main aim of this research is to demonstrate the effectiveness of the design concept on the impact of air gaps driven by forced ventilation effects to reduce the attic temperature. This temperature reduction contributes to the enhancement of the comfort of the residents. In this study, eight different indoor roof models were designed and experiments were carried out by using solar simulator. Their performances were evaluated among the roof designs regarding the attic temperature reduction. The main feature of the roof model is an Aluminum and PVC tubes (which act as a moving-air path), placed on the underside of the roof. The roof inclination angle was 30º to the horizontal. An insulation layer and ventilation fans were integrated with the roof. These ventilation fans can help to remove the hot air to the surroundings. The thermal performances of the roof models were evaluated by measuring the reduction in attic temperature for each of the roof designs compared with a standard Design-A as a baseline. Among all the designs, it was found that Design-H is 8.99 % more efficient in attic temperature reduction than the standard roof Design-A due to metal roof, insulation, MAP (moving-air path) and ventilation fan which contribute to the decrease in the heat flow. The Design-H which consisted of an insulation layer, fans (airflow in moving-air path, Vair = 1 – 1.9 m/s) and PVC tubes showed a significant improvement in the reduction in attic temperature of 3.2 ºC compared with the conventional roof model (33.7 ºC in the attic). The theoretical calculation showed that the annual energy savings can be as high as 37.35 kWh/m2 by using optimum conditions in roof design. The annual cost saving of energy per unit of area is increased by up to US$ 2.24/m2 by using roof Design-H. Furthermore, Adaptive Neuro Fuzzy Inference System (ANFIS) is applied as a soft-computing method to determine the predominant variables that affect the thermal comfort in the building. Five input parameters were used to compute the output parameter which is the attic temperature. The outcome of this method showed that the combination of mass flow rate and ambient temperature is the primary factor and has the best predictor accuracy for thermal comfort in the building. All of these significant findings indicate that the cooling system in the roof provides a new design paradigm with greater temperature reduction and reduces the annual energy consumption

Sea outfall assessment in Qatar : lessons for Bangladesh

Pollution in coastal waters is a major concern in the Arabian Gulf countries. In Qatar, the untreated water mainly consisting of stormwater is discharged into the Doha coastline via several surface/shoreline type outfalls. This may cause adverse impacts to the sea environment of a fragile ecosystem of the coastal zone in Qatar. The Ministry of Municipality and Environment (MME), Qatar has carried out a comprehensive sea outfall study to identify existing outfalls and assess theirs impacts on planning, regulation, design and implementation of environment friendly outfall schemes. Direct discharge of large quantity of domestic and industrial wastewater, pesticides and agricultural chemicals into the rivers and the Bay of Bengal is a major concern in Bangladesh. The pollution levels in the Bay of Bengal affect fish and other living things. In addition to the biological and chemical pollutants, heavy metals pollution has also been reported in coastal and riverine waters of Bangladesh which presents an enormous challenge of monitoring, environmental management and conservation efforts. The recommendations and outcome of Qatar sea outfall study could provide government stakeholders in Bangladesh with adequate information for a sustainable coastal management and the proper tools for planning, maintenance, and monitoring of sea outfalls as discussed in this paper

Rainfall in Qatar : is it changing?

In this paper, we investigate the spatial and temporal distributions of rainfall in Qatar, which falls in the arid region of the middle-east. We use rainfall data from 29 rain gauges covering the period of 1962–2010. Fifteen different rainfall indices are used in the assessment. A combination of Mann–Kendall and Spearman’s Rho tests is adopted to identify trends in the rainfall data. The average annual rainfall values are found to be in the range of 55.5–99 mm. A sharp gradient in average annual rainfall is noticed, with north having much higher values than the south. A mixed trend, both increasing (upward) and decreasing (downward) for most of the rainfall indices, is identified. Annual total and maximum daily rainfalls show mixed trends, while rainy days show an increasing trend. For the rainy seasons, the total rainfall during the months of December–January–February shows an increasing trend and March–April rainfall shows a decreasing trend, reflecting that seasonal rainfall in Qatar is changing. The findings of this study provide important insights into the nature of rainfall variability in Qatar, which will be useful in water resources planning tasks in Qatar and nearby countries

Uncertainty in design rainfall estimation : a review

Design rainfall is an essential input to a hydrologic model, which is used to estimate design discharge that is needed in the planning and design of many engineering infrastructure projects. Design rainfall estimation is made using recorded rainfall data over many stations in a given region. Uncertainties in design rainfall estimates arise from various sources such as data error, sampling error, regionalization error, model error and error due to climate change. This paper reviews various sources of uncertainties in design rainfall estimation. It has been found that uncertainty in design rainfall estimates are hardly considered in design applications. Uncertainty in design rainfall estimation can be assessed using Monte Carlo simulation and bootstrapping techniques. These techniques require significant computer power, which however is not a problem now a days. The biggest challenge in uncertainty estimation lies in the assessment of the impacts of non-stationarity in the rainfall data on design rainfall estimates. The findings of this paper would be useful to future studies on design rainfall estimation

Qatar Rainfall and Runoff Characteristics : a new direction of engineering education and practice in Qatar

Prompted by a rapid infrastructure development in recent years, the State of Qatar has developed a comprehensive national guideline titled Qatar Rainfall and Runoff Characteristics (QRRC) for estimation of design rainfall in Qatar. This guideline introduces more accurate rainfall characteristics that will be used as the bases to new world-class drainage standards that will contribute to a more resilient and safe storm water infrastructure for Qatar under a changing climate regime. QRRC was developed using rainfall data from over 30 stations located in Qatar and nearby Gulf countries. The method of L-moments was employed for derivation of new set of Intensity-duration-frequency (IDF) data for Qatar. This approach reduces the impacts of sampling variability on the analysis. It is intended that the QRRC will provide guidance and assistance to a wide range of entities including government agencies, developers, engineers, planners and policy makers. It is therefore of paramount importance that the recommended approaches and guidelines presented in QRRC be introduced in the undergraduate and graduate courses at the universities, including research and training centers in Qatar. This will assist in the preparation and training of young professionals for solving engineering problems in civil infrastructure, storm water design and hydrology. This paper presents important features of QRRC and how this can be used in tertiary education in Qatar