Nondiscretionary residential water use: the impact of habits and water‐efficient technologies

Several studies published in the last few decades have demonstrated a low price‐elasticity for residential water use. In particular, it has been shown that there is a quantity of water demanded that remains constant regardless of prices and other economic factors. In this research, we characterise residential water demand based on a Stone‐Geary utility function. This specification is not only theory‐compatible but can also explicitly model a minimum level of consumption not dependent on prices or income. This is described as minimum threshold or nondiscretionary water use. Additionally, the Stone‐Geary framework is used to model the subsistence level of water consumption that is dependent on the temporal evolution of consumer habits and stock of physical capital. The main aim of this study is to analyse the impact of water‐saving habits and water‐efficient technologies on residential water demand, while additionally focusing attention on nondiscretionary uses. This is informed by an empirical application using data from a survey conducted among residents of Brisbane City Council, Australia. The results will be especially useful in the design of water tariffs and other water‐saving policies.     

Portfolio Optimization under Solvency Constraints: A Dynamical Approach

We develop portfolio optimization problems for a nonlife insurance company seeking to find the minimum capital required that simultaneously satisfies solvency and portfolio performance constraints. Motivated by standard insurance regulations, we consider solvency capital requirements based on three criteria: ruin probability, conditional Value-at-Risk, and expected policyholder deficit ratio. We propose a novel semiparametric formulation for each problem and explore the advantages of implementing this methodology over other potential approaches. When liabilities follow a Lognormal distribution, we provide sufficient conditions for convexity for each problem. Using different expected return on capital target levels, we construct efficient frontiers when portfolio assets are modeled with a special class of multivariate GARCH models. We find that the correlation between asset returns plays an important role in the behavior of the optimal capital required and the portfolio structure. The stability and out-of-sample performance of our optimal solutions are empirically tested with respect to both the solvency requirement and portfolio performance, through a double rolling window estimation exercise.     

A framework for text mining on Twitter: a case study on joint comprehensive plan of action (JCPOA)- between 2015 and 2019

Quality & Quantity - In the big data era, there is a necessity for effective frameworks to collect, retrieve, and manage data. As not all tweets are hashtagged by users, retrieving them is a...     

Analysis of quality of services for checkout operation in Refah chain stores using queuing theory

As the last serving unit in each store, the checkout operation unit has a very important role in determining customers’ satisfaction level for the received services. The objective of this study was to analyze the quality of services in checkout operation units in Refah chain stores in Tehran Province using queuing theory. The required data were gathered through a questionnaire. The quality of the performance of Refah chain stores’ checkout operation units was evaluated and the overall system utilization was estimated at 73.97%. Weekdays, day time, and the location of the store are some factors that influence the efficiency of services.     

Optimal Risk Transfer: A Numerical Optimization Approach

Capital efficiency and asset/liability management are part of the Enterprise Risk Management Process of any insurance/reinsurance conglomerate and serve as quantitative methods to fulfill the strategic planning within an insurance organization. A considerable amount of work has been done in this ample research field, but invariably one of the last questions is whether or not, numerically, the method is practically implementable, which is our main interest. The numerical issues are dependent on the traits of the optimization problem, and therefore we plan to focus on the optimal reinsurance design, which has been a very dynamic topic in the last decade. The existing literature is focused on finding closed-form solutions that are usually possible when economic, solvency, and other constraints are not included in the model. Including these constraints, the optimal contract can be found only numerically. The efficiency of these methods is extremely good for some well-behaved convex problems, such as Second-Order Conic Problems. Specific numerical solutions are provided to better explain the advantages of appropriate numerical optimization methods chosen to solve various risk transfer problems. The stability issues are also investigated together with a case study performed for an insurance group that aims capital efficiency across the entire organization.     

Analysing rationing policies: drought and its effects on urban users’ welfare (Analysing rationing policies during drought)

The aim of this paper is to study the impact on consumers of rationing policies implemented during water shortages. Water scarcity gives rise to the need for rationing, and various methods, including supply cutoffs, can be used. A model is devised to quantify the welfare losses associated with qualitive and quantitive restrictions. Based on virtual prices and using the consumer surplus as a welfare measurement, welfare variations for different users have been calculated. To achieve the aim, information relative to Seville (Spain) has been used, analysing the drought period that took place in the first half of the 1990s. It has been possible to observe the main source that led to welfare losses for each kind of user.     

Deriving the Trace of Optimal Output for a Noncompetitive Firm

A Monopolist or monopolistic competitive firm has no supply curve independent of the demand curve for its product. The intention of this paper is to utilize this dependency and show that under a generally accepted and practiced assumption about changes in the market demand curve facing a noncompetitive firm, it is possible to derive its locus of supply points or its trace of optimal output.     

An efficient approach to quantile capital allocation and sensitivity analysis

In various fields of applications such as capital allocation, sensitivity analysis, and systemic risk evaluation, one often needs to compute or estimate the expectation of a random variable, given that another random variable is equal to its quantile at some prespecified probability level. A primary example of such an application is the Euler capital allocation formula for the quantile (often called the value‐at‐risk), which is of crucial importance in financial risk management. It is well known that classic nonparametric estimation for the above quantile allocation problem has a slower rate of convergence than the standard rate. In this paper, we propose an alternative approach to the quantile allocation problem via adjusting the probability level in connection with an expected shortfall. The asymptotic distribution of the proposed nonparametric estimator of the new capital allocation is derived for dependent data under the setup of a mixing sequence. In order to assess the performance of the proposed nonparametric estimator, AR‐GARCH models are proposed to fit each risk variable, and further, a bootstrap method based on residuals is employed to quantify the estimation uncertainty. A simulation study is conducted to examine the finite sample performance of the proposed inference. Finally, the proposed methodology of quantile capital allocation is illustrated for a financial data set.     

The measurement of technical efficiency: a neural network approach

The main purpose of this paper is to provide an introduction to artificial neural networks (ANNs) and to review their applications in efficiency analysis. Finally, a comparison of efficiency techniques in a non-linear production function is carried out. The results suggest that ANNs are a promising alternative to traditional approaches, econometric models and non-parametric methods such as data envelopment analysis, to fit production functions and measure efficiency under non-linear contexts.     

Extremes on the discounted aggregate claims in a time dependent risk model

This paper presents an extension of the classical compound Poisson risk model for which the inter-claim time and the forthcoming claim amount are no longer independent random variables (rv's). Asymptotic tail probabilities for the discounted aggregate claims are presented when the force of interest is constant and the claim amounts are heavy tail distributed rv's. Furthermore, we derive asymptotic finite time ruin probabilities, as well as asymptotic approximations for some common risk measures associated with the discounted aggregate claims. A simulation study is performed in order to validate the results obtained in the free interest risk model.