Non-conventional Measures Research Articles

A Novel Class of Ratio Estimators Incorporating Auxiliary Variables in Simple Random Sampling for Estimating Population Mean: An Application to Real-Life Data

This paper presents a novel class of ratio estimators using non-conventional measures as auxiliary information to estimate the population mean of the study variable under simple random sampling without replacement. Three special cases are discussed, utilizing the coefficient of variation, median, and quartile deviation as auxiliary variables. The bias and mean square error (MSE) of the proposed estimators are derived up to the first order of approximation. Furthermore, theoretical conditions are established to compare the proposed class with existing estimators, supported by real-life data. Numerical results demonstrate that the proposed class of estimators is more efficient than traditional and other ratio-type estimators.

Facilitators and barriers to integrated malaria prevention in Wakiso district, Uganda: A photovoice study.

Malaria continues to cause significant morbidity and mortality globally, particularly in sub-Saharan Africa. Appropriate combinations of non-chemical and chemical methods of malaria vector control in the context of integrated vector management have been recommended by the World Health Organization. The aim of the study was to explore facilitators and barriers to using integrated malaria prevention in Wakiso district, Uganda. This qualitative study employed photovoice among 20 community members in Kasanje Town Council, Wakiso District. The photos taken by participants for 5 months using smartphones were discussed during monthly meetings with the researchers. The discussions were audio-recorded, and resulting data analysed using thematic analysis with the support of NVivo (2020) QSR International. Findings indicated that various conventional and non-conventional measures were being used for preventing malaria such as: insecticide treated nets; clearing overgrown vegetation; draining stagnant water; mosquito coils; smouldering of cow dung; spraying insecticides; plant repellents near houses; eating of prophylactic herbs; as well as closing doors and windows on houses early in the evening. Facilitators supporting the use of several malaria prevention methods holistically included: low cost and accessibility of some methods such as slashing overgrown vegetation; and support provided for certain methods such as receiving free mosquito nets from the government. Barriers to using several malaria prevention methods holistically included: inadequate knowledge of some methods such as housing improvement; allergic reactions to chemical-based methods such as insecticide treated nets; unaffordability of some methods such as insecticide sprays; and inaccessibility of certain methods such as body repellents. These barriers to integrated malaria prevention need to be addressed to achieve greater impact from the combination of methods in endemic communities.

STRUCTURAL DEPTH IN REFORMS INDUCED BY IMF PROGRAMS: INSIGHTS FROM THE FUND’S MAJOR DEBTORS

This paper investigates the evolution of IMF structural conditionality, with a specific focus on non-core policy areas, across the Fund’s top debtors from 1984 to 2023. The author builds on the concept of structural depth as defined by the IMF’s Independent Evaluation Office (IEO), categorizing it into high, medium, and low levels, guided by legal-economic perspectives. Analysing 1,233 conditions, she reveals nuanced patterns. The biggest borrowers often faced more policy prescriptions with significant share of non- core areas, while conditionality depth varies across countries and periods. Argentina’s unique case exhibits fewer and shallower conditions, despite significant challenges. Greece and Ukraine stand out with deep programs, attributed to the European influence. Recent agreements blend Washington Consensus-inspired and non-conventional measures, including social buffers and transparency. These developments, while positive, raise questions about their ability to transform borrowers into more resilient welfare states.

Особливості забезпечення якості та тарифного регулювання послуг теплопостачання

The article deals with studying the state of providing heat supply services. The quality indica-tors of centralized heat supply services have been categorized. The evaluation of the quality of cen-tralized heat supply services hinges on principal benchmarks such as punctuality in starting and fin-ishing the heating season, uninterrupted service provision, and adherence to current regulations. Having analysed the heat energy supply, its pricing was divided into two components – condi-tionally permanent and conditionally variable. Such division allows us to mitigate the adverse effects of the seasonality of this housing and communal services category. It's noteworthy that this tariff formation developed with the 'cost plus' method (which also includes heat energy losses), is assumed imperfect according to European standards. It provides only a minimal level of profitability, which neither fosters equipment development nor encourages cost savings nor motivates employees. The study on the quality of heat supply services revealed that the assessment was primarily based on the minimum technical requirements and consumer relations. The article states that the principal challenge in providing high-quality heat supply services is the lack of competition in this sector. Heat supply enterprises do not have enough incentives to enhance their efficiency and seek opportunities for implementing investment programmes to ensure a more cost-effective service sup-ply. To improve quality and resolve current issues the authors propose to adopt non-conventional measures, to investigate changes in the quality of heat supply services and how they are evaluated by consumers, to inform the regulatory housing and communal services authorities and local self-government bodies about the existing problems of heat supply services and their quality so that they can make effective management decisions. For the purpose of enhancing the quality of heat supply services, it has been recommended to use monitoring based on the integrated quality index calculation. This index comprises elements such as commercial service quality, service reliability, service accessibility, and technical quality.

Modified robust regression-type estimators with multi-auxiliary variables using non-conventional measures of dispersion

Auxiliary variables correlated with the study variables have been identified to be useful in improving the efficiency of ratio, product and regression estimators both at planning and estimation stages. The existing regression-based estimators are functions of auxiliary variables which are sensitive to outliers. In this paper, a modified class of estimators is proposed using robust non-conventional measures of dispersion which are robust against outliers or extreme values. The properties (Biases and Mean Squared Errors (MSEs)) of the modified class of estimator were derived up to the first order of approximation using Taylor series approach. The empirical studies were conducted using stimulation to investigate the efficiency of the proposed estimators over the efficiency of the existing estimators. The results revealed that the proposed estimators have minimum MSEs and higher Percentage Relative Efficiencies (PREs) among all the competing estimators. These results implied that the proposed estimators are more efficient and can produce better estimate of the population mean compared to other existing estimators considered in the study. Therefore, it can be concluded that proposed estimators have better predictive power for estimating population mean when the study (interest) variables are characterized with outliers or extreme values.

A fiscal perspective of policy responses to COVID-19: Evidences from Emerging Economy India

The COVID-19 health crisis became a global economic crisis with mitigation measures leading to a steep decline in economic activity, disrupting demand and supply. To attenuate the economic impact of the pandemic, monetary and fiscal policies were used by governments, central banks and supranational institutions. This article analyzes the implications of fiscal and monetary policies used in India in response to the COVID-19 pandemic on the country’s public debt. India’s adoption of a unique calibrated expenditure strategy through fiscal stimulus provided a cushion to mounting expenditure requirements in a scenario of falling government revenue. Widening fiscal deficits due to the increased need for fiscal spending on the one hand, and a decline in revenue generation owing to fall in economic activities on the other, saw a surge in India’s public debt. Coordinated efforts by monetary and fiscal authorities through conventional and non-conventional measures added new dimensions to India’s debt management strategy. The unprecedented magnitude of the crisis pushed the Government of India to relax its debt and deficit indicators until the economy can move back to normalcy. Keywords: COVID-19, Fiscal deficit, Fiscal policy, Fiscal stimulus, Monetary policy, Public debt.

The dynamics of sexual repression, deceit, and coming out in African homosexual narratives

Homophobic attitudes continue to militate against the coming out of homosexuals in African societies. In this study, I examine the agentic difference between forced outing and self-outing among male homosexual characters in selected African fictional narratives. The texts employed are Jude Dibia’s Walking with Shadows and Tendai Huchu’s The Hairdresser of Harare. I argue that in forced outing, male homosexual characters undergo sexual oppression, are subjected to psychological oppression, and are denied their individual agency. In order to survive homophobia, these characters become liars, deceivers, and cheats. In their quest for social acceptance, they knowingly suppress their homosexual identity and pretend to perform societally normative heterosexuality. What is obvious in these novels is that queer visibility still represents a major challenge for members of minoritized sexual communities who consequently have to explore non-conventional measures in order to survive.

A Nonconventional Auxiliary Information Based Robust Class of Exponential-type Difference Estimators

This study proposes a new class of improved exponential-type difference estimators of finite population mean by using supplementary information of known median along with suitable combinations of the conventional and non-conventional measures of the auxiliary variables under simple random sampling scheme. The expressions for the mean squared error and minimum mean squared error are derived up to first order of the approximation. Six real data sets were used to assess the performance of proposed class of estimators in comparison with existing estimators. The compariosn established that the suggested class of estimators are efficient than their existing counterparts considered in this study. To further support the findings of the numerical comparison, a simulation study was carried out which also proved the superiority of the proposed class of estimators of population mean. To gauge the performance of the propsoed class of estimators when some outliers are present in the data, a robustness study was carried out which showed that the proposed estimators considerably outperform their existing counterparts in terms of lower mean squared errors.

On the Efficiency of Modified Regression-type Estimators Using Robust Regression Slopes and Non-conventional Measures of Dispersion

Supplementary variables associated with the study variables have been identified to be helpful in improving the efficiency of ratio, product and regression estimators both at planning and estimation stages. The existing regression-based estimators are functions of regression slopes and known auxiliary variables which are sensitive to outliers. Zaman & Bulut [1] and Zaman [2] addressed the issue of regression slopes in the aforementioned estimators using robust regression slopes like Huber-M, Hampel-M, Least Trimmed Squares (LTS) and Least Absolute Deviation (LAD). However, their estimators still utilized known auxiliary functions which are also sensitive to outliers or extreme values. Similarly, Yadav and Zaman [3] suggested non-conventional robust parameters of auxiliary variable which are robust against outliers. However, the problems of effects of outliers on regression slopes were not considered. In this study, the estimators of Zaman & Bulut [1] and Zaman [2] estimators were modified using robust non-conventional measures and Yadav and Zaman [3] estimators were modified using robust regression slopes. The properties (Biases and MSEs) of the modified estimators were derived up to the first order of approximation using Taylor series approach. The efficiency conditions of the proposed estimators over the existing estimators considered in the study were established. The empirical studies were conducted using stimulation data to investigate the efficiency of the proposed estimators over the efficiency of the existing estimators. The results revealed that the proposed estimators have minimum MSEs and higher PREs among all the competing estimators for the simulated populations in the study. This implies that the proposed estimators are more efficient and can produce better estimate of the population mean compared to other existing estimators considered in the study.

On enhanced exponential‐cum‐ratio estimators using robust measures of location

AbstractMany studies are mainly concerned with the estimation of finite population mean and the well‐known preferences for it are ratio estimators. This article offers a remedy for improvement in the estimation of a study variable, based on supplementary information related to dual auxiliary variables in the context of simple random sampling without replacement scheme. We proposed two new general classes of exponential‐cum‐ratio estimators to estimate a finite population mean utilizing dual auxiliary variables with suitable combinations of the conventional and nonconventional measures. The expression for the mean square error (MSE) and theoretical conditions for proposed classes have been obtained for evaluation purposes. The performance of the proposed classes has been compared with existing estimators in terms of MSE. It is revealed that proposed estimators are more efficient than usual and existing estimators considered in this article. The simulation and robustness studies are also part of this article. Moreover, a variety of real data sets is also considered for an empirical study to support the theoretical results.

On Using the Conventional and Nonconventional Measures of the Auxiliary Variable for Mean Estimation

In this paper, we propose an improved new class of exponential-ratio-type estimators for estimating the finite population mean using the conventional and the nonconventional measures of the auxiliary variable. Expressions for the bias and MSE are obtained under large sample approximation. Both simulation and numerical studies are conducted to validate the theoretical findings. Use of the conventional and the nonconventional measures of the auxiliary variable is very common in survey research, but we observe that this does not add much value in many of the estimators except for our proposed class of estimators.

Enhanced Estimators of Population Variance with the Use of Supplementary Information in Survey Sampling

In the present study, we propose the proficient class of estimators of the finite population mean, while incorporating the nonconventional location and nonconventional measures of dispersion with coefficient of variation of the auxiliary variable. Properties associated with the suggested class of improved estimators are derived, and an efficiency comparison with the usual unbiased ratio estimator and other existing estimators under consideration in the present study is established. An empirical study has also been provided to validate the theoretical results. Finally, it is established that the proposed class of estimators of the finite population variance proves to be more efficient than the existing estimators mentioned in this study.

Modified moment estimators based on non-conventional measures for the power function distribution

Power function is amougst the most suitable probability models for survival or failure times analysis, particularly of electronic components and product reliability. The article proposes some new modified moment estimators for parameter estimation of the power function distribution. The proposed estimators are based on some non-conventional descriptive measures like harmonic mean, quartile deviation, Shannon entropy and Gini index. The performance of the proposed estimators is compared with the traditional moment and existing modified moment estimators. Performance is assessed through the Monte Carlo simulation and three real-life data sets representing failure and survival times of components and infected animals, respectively. Some common accuracy measures are used as performance indicators. From both, Monte Carlo simulation and all real-life applications, the results show better performance of proposed modified moment estimators based on the Gini index and harmonic mean. Hence, the use of these modified estimators is recommended for parameter estimation of the power function distribution.

Trust in the European Union project and the role of ECB

Was the European Central Bank able to assure the relaunch of the European project after the weakening of the post-crisis period? To answer this question, this paper presents an empirical analysis connecting citizen trust in the European Union with a variable intended to be a measure of the monetary policy strategy of the European Central Bank, namely, the interest rate on government bonds extracted from the 1-year maturity yield curve. The dynamic panel technique, applied to nineteen Eurozone countries for the time span of 2004–2018, estimates the presence of a long-run common relationship between the variables despite allowing different short-run adjustment mechanisms. Results are revealed to be not univocal: the easy monetary policy strategy is associated for the whole period with a decline of trust, and therefore, despite its impressiveness, it was not sufficient to relaunch the European Union project. However, when considering the change in strategy of the post-2013 period, it seemed to have contributed to a slight inversion of the decline of trust. These results highlight the importance of non-conventional measures and call for further support from coordinated policy action as a response to the negative shock deriving from the COVID-19 pandemic.

Improvement of the lightning performance of transmission lines by combining conventional and non-conventional measures

This work discusses the use of combined measures for improving the lightning performance of transmission lines exhibiting high backflashover rate. It developed a methodology for assessing how the line performance is affected by installing underbuilt wires combined with the reduction of tower-footing resistance and the partial protection of the phases by surge arresters. The methodology can be applied to any transmission line. To develop a quantitative idea of the impact of the combined measures, a 230-kV double-circuit transmission line installed in a region of very high flash density and extremely unfavorable soil resistivity was used as reference. The range of efficient application of the tested solutions was determined as a function of tower-footing resistance for this line.

Generalized Class of Mean Estimators with Known Measures for Outliers Treatment

In estimation theory, the researchers have put their efforts to develop some estimators of population mean which may give more precise results when adopting ordinary least squares (OLS) method or robust regression techniques for estimating regression coefficients. But when the correlation is negative and the outliers are presented, the results can be distorted and the OLS-type estimators may give misleading estimates or highly biased estimates. Hence, this paper mainly focuses on such issues through the use of non-conventional measures of dispersion and a robust estimation method. Precisely, we have proposed generalized estimators by using the ancillary information of non-conventional measures of dispersion (Gini’s mean difference, Downton’s method and probability-weighted moment) using ordinary least squares and then finally adopting the Huber M-estimation technique on the suggested estimators. The proposed estimators are investigated in the presence of outliers in both situations of negative and positive correlation between study and auxiliary variables. Theoretical comparisons and real data application are provided to show the strength of the proposed generalized estimators. It is found that the proposed generalized Huber-M-type estimators are more efficient than the suggested generalized estimators under the OLS estimation method considered in this study. The new proposed estimators will be useful in the future for data analysis and making decisions.

Real interest rate convergence and monetary policy independence in CEE countries

In this paper we provide new empirical evidence relevant for discussions on monetary policy independence in the context of euro adoption in three Central and Eastern European (CEE) countries: Czechia, Hungary and Poland. Unlike many other authors, in this paper we focus on real and not nominal interest rates as real interest rates are at the hearth of modern macroeconomic and monetary policy theory. In the paper we employ several methodologies to test the convergence of real interest rates between these countries and the euro area and to determine the main drivers of real interest rates. Based on the unit root analysis we find evidence of convergence of real interest rates in these countries, thus confirming the real interest rate parity (RIRP) hypothesis. Next, using principle component analysis (PCA) we show that common factor extracted from the sample of CEE countries and individual euro area countries can explain high proportion of real interest rate developments in these countries. Finally, results of our newly proposed analytical framework for the analysis of determinants of real interest rates in small open economies, based on a Bayesian VAR model with block exogeneity, show that external shocks have non-negligible effect on real interest rate developments in selected CEE countries. Thus, our results indicate that real interest rates in CEE depend on factors that are beyond the scope of domestic monetary policy makers. In this sense we can conclude that (conventional) monetary policy independence in these countries is limited. Thus, we see the loss of monetary policy independence as overly emphasized argument in discussions on the euro adoption in these countries. However, we are aware that national central banks in CEE started to rely more on non-conventional measures recently, which gives them a higher degree of flexibility (and autonomy).

Quantum Entanglement in Fenna—Matthews—Olson Photosynthetic Light—Harvesting complexes: A Short Review of Analysis Methods

The Fenna-Matthews-Olson light-harvesting complexes have become a center of attention due to their high excitation energy transfer efficiency, which may surpass 98%. Experimental results reveal the presence of quantum entanglement in the protein structure, which seems to be associated to such a remarkably high efficiency. Notably, Redfield and Lindblad master equations have been already used to model the chromophore excitation in the protein complex as well as its interactions with the environment. The entanglement arising during the process has been quantified through several measures. This work provides a short review of methods used to model the above described system. It is also discussed the introduction of two nonconventional measures addresed to quantify the emergent entanglement.

Use of Nonconventional Dispersion Measures to Improve the Efficiency of Ratio-Type Estimators of Variance in the Presence of Outliers

The use of auxiliary information in survey sampling to enhance the efficiency of the estimators of population parameters is a common phenomenon. Generally, the ratio and regression estimators are developed by using the known information on conventional parameters of the auxiliary variables, such as variance, coefficient of variation, coefficient of skewness, coefficient of kurtosis, or correlation between the study and auxiliary variable. The efficiency of these estimators is dubious in the presence of outliers in the data and a nonsymmetrical population. This study presents improved variance estimators under simple random sampling without replacement with the assumption that the information on some nonconventional dispersion measures of the auxiliary variable is readily available. These auxiliary variables can be the inter-decile range, sample inter-quartile range, probability-weighted moment estimator, Gini mean difference estimator, Downton’s estimator, median absolute deviation from the median, and so forth. The algebraic expressions for the bias and mean square error of the proposed estimators are obtained and the efficiency conditions are derived to compare with the existing estimators. The percentage relative efficiencies are used to numerically compare the results of the proposed estimators with the existing estimators by using real datasets, indicating the supremacy of the suggested estimators.

Measuring tourism success – alternative outcome variables: a perspective article

PurposeThe focus of this perspective paper is to provide new directions in the ontology of thinking about outcome variables by observational analysis of past and linking it to the present research.Design/methodology/approachThis perspective paper follow a critical review approach that is reflective and speculative in its orientation.FindingsOutcome variables are assumed to serve as the dependent variables which are observed and measured by changing independent variables. It is argued that there would certainly be more and innovative concerted efforts in the future that would focus on non-conventional measures as outcome variables. These efforts would help researchers better understand the contribution of tourism activities to well-being of stakeholders. By doing so, success in tourism can be ensured.Originality/valueProposing, in addition to conventional outcome variables, new/possible outcome variables to enrich research.