Analyzing time–frequency relationship between oil price and exchange rate in Pakistan through wavelets

This study analyzed the time–frequency relationship between oil price and exchange rate for Pakistan by using measures of continuous wavelet such as wavelet power, cross-wavelet power, and cross-wavelet coherency (WTC). The results of cross-wavelet analysis indicated that covariance between oil price and exchange rate is unable to give clear-cut results, but both variables have been in phase and out phase (i.e. they are anti-cyclical and cyclical in nature) in some or other durations. However, results of squared wavelet coherence disclose that both variables are out of phase and real exchange rate was leading during the entire period studied, corresponding to the 10–15 months’ scale. These results are the unique contribution of the present study, which would have not been drawn if one would have utilized any other time series or frequency domain-based approach. This finding provides evidence of anti-cyclical relationship between oil price and real effective exchange rate; however, in most of the period studied, real exchange rate was leading and passing anti-cycle effects on oil price shocks which is the major contribution of the study.     

Bayesian and Robust Bayesian analysis under a general class of balanced loss functions

For estimating an unknown parameter θ, we introduce and motivate the use of balanced loss functions of the form L_{r, w, d0}(q, d)=wr(d₀, d)+ (1-w) r(q, d){L_{rho, omega, delta_0}(theta, delta)=omega rho(delta_0, delta)+ (1-omega) rho(theta, delta)}, as well as the weighted version q(q) L_{r, w, d0}(q, d){q(theta) L_{rho, omega, delta_0}(theta, delta)}, where ρ(θ, δ) is an arbitrary loss function, δ ₀ is a chosen a priori “target” estimator of q, w ? [0,1){theta, omega in[0,1)}, and q(·) is a positive weight function. we develop Bayesian estimators under L_{r, w, d0}{L_{rho, omega, delta_0}} with ω > 0 by relating such estimators to Bayesian solutions under L_{r, w, d0}{L_{rho, omega, delta_0}} with ω = 0. Illustrations are given for various choices of ρ, such as absolute value, entropy, linex, and squared error type losses. Finally, under various robust Bayesian analysis criteria including posterior regret gamma-minimaxity, conditional gamma-minimaxity, and most stable, we establish explicit connections between optimal actions derived under balanced and unbalanced losses.     

The matched pair sign test using bivariate ranked set sampling for different ranking based schemes

Bivariate rank set sample (BVRSS) matched pair sign test is introduced and investigated for different ranking based schemes. We show that this test is asymptotically more efficient and more powerful than its counterpart sign test based on a bivariate simple random sample (BVSRS) for different ranking schemes. The asymptotic null distribution and the efficiency of the test are derived. Pitman’s asymptotic relative efficiency is used to compare the asymptotic performance of the matched pair sign test using BVRSS versus using BVSRS in all ranking cases. For small sample sizes, the bootstrap method is used to estimate P-values. Numerical comparisons are used to gain insight about the efficiency of the BVRSS sign test compared to the BVSRS sign test. Our numerical and theoretical results indicate that using any ranking scheme of BVRSS for the matched pair sign test is more efficient than using BVSRS.     

Health Disorder of Climate Migrants in Khulna City: An Urban Slum Perspective

As the most vulnerable climatic region in the country, Khulna City is increasingly experiencing climate‐change‐induced urban problems. For instance, occupancy by climate migrants (delete the term “illegal migrant”), drainage congestion, water logging and reduced fresh water availability are all increasing problems. In the last decade, the population in the city increased by more than 20 per cent due to migration from nearby climate vulnerable districts. This study explores the health disorders of climate migrants occupying the urban slums and squats of the Khulna City area. This study found that these climate migrants settled in the urban slums and squats and, as such, they do not have access to urban amenities such as clean drinking water, hygiene services, and health facilities. This study noted that these displaced people are at increased risk of health issues from unhygienic and overcrowded living conditions and from water and sanitation problems. They often suffer from different waterborne diseases, under‐nutrition and micronutrient deficiencies. This study suggests that there is a need for better planning, preparation and training in Bangladesh to which migrants move, including better training in health and related services on how to recognize and respond to health problems that may be slow to manifest. Education and training also need to be provided for the migrants themselves, to help them adapt culturally and to enhance their skills and potential for employment.     

Social Protection Spending in Context of Structural and Institutional Performance: A Global Empirical Analysis

Social Indicators Research - An understanding about the dynamics of social protection spending is made in the context of structural and institutional performances. A dataset of 134 countries for...     

‘Rachel's not here’: Constructed dialogue in gossip

Sociolinguistic research has demonstrated that gossip is a co‐constructed phenomenon, which allows participants to establish solidarity and build alignments with each other, while evaluating an absent party. Gossip can also serve important social functions, such as helping to establish and reconfirm group norms and values. The present study provides a detailed analysis of an extended gossip episode that occurred within an institutional context: a study group interaction at a U.S. university. Our analysis shows how, in gossip, constructed dialogue both prompts and legitimizes pejorative evaluations towards an absent third party, and is actually the pivot around which group members negotiate values and norms in the process of arriving at a shared moral stance. Our analysis also demonstrates that alignment in gossip interactions is tenuous and must be continuously renewed.     

Bayesian classification with multivariate autoregressive sources that might have different orders

The main objective of this paper is to develop an exact Bayesian technique that can be used to assign a multivariate time series realization to one of several autoregressive sources, with unknown coefficients and precision, that might have different orders. The foundation of the proposed technique is to develop the posterior mass function of a classification vector, in an easy form, using the conditional likelihood function. A multivariate time series realization is assigned to the multivariate autoregressive source with the largest posterior probability. A simulation study, with uniform prior mass function, is carried out to demonstrate the performance of the proposed technique and to test its adequacy in handling the multivariate classification problems. The analysis of the numerical results supports the adequacy of the proposed technique in solving the classification problems with multivariate autoregressive sources.