Sexual orientation and earnings: a register data-based approach to identify homosexuals

This paper examines earnings differentials between homo- and heterosexual individuals by identifying sexual orientation with the help of information from register data. Register data enable us to avoid the misclassifications of sexual orientation often mentioned as a potential bias in survey-based studies. The results show that gay men are at an earnings disadvantage as compared to male heterosexuals while the earnings differential between lesbians and heterosexual women is very small. Our results are in line with results from previous research but are more reliable since we use a more reliable measure of sexual orientation than previous research.     

Anabolic-androgenic steroid effects on early morbid symptoms after open prostatectomy: A pilot study

Objectives.?Anabolic-androgenic steroids such as Nandrolone phenpropionate (NP) dramatically improve the tolerance to acute stress conditions, strength, and subsequently the quality of life in elderly men. We hypothesize that preoperative pulse-dose supraphysiological NP administration might improve the early morbid symptoms in older patients undergoing open prostatectomy.

Methods.?From 2005 to 2006, 54 patients with a mean age of 70 years, diagnosed as benign prostatic hyperplasia and hospitalized for open prostatectomy were enrolled in the study. They were randomly selected to receive preoperative supraphysiological NP (100 mg, intramuscularly, pulse-dose) or sesame oil placebo, prospectively. Early postoperative morbid symptoms including subjective urinary symptoms (dysuria, bladder retention sensation), incision site pain and general satisfaction of their current urinary condition were assessed by a 6-point scale, self-administrated questionnaire at 24 and 48 h, postoperatively. The sex hormone binding globulin and the testosterone levels were also measured.

Results.?The 24-h postoperative symptoms were significantly reduced in the NP group compared to the placebo (6.18 ± 2.81 versus 9.77 ± 2.15; P < 0.001). The postoperative symptoms were reported to have a decline in the 48 h following operation, though was calculated to be statistically insignificant (4.48 ± 2.32 versus 5.55 ± 1.84; P = 0.06). There was no complication attributed to NP therapy.

Conclusions.?The data supported the hypothesis that the preoperative anabolic steroid supplements (such as NP) could result in a better postoperative endurance in elderly men undergoing open prostatectomy. Further studies, longer and repeated pulse injections in a larger number of older men are mandatory to prove the claim.     

Measures of radial asymmetry for bivariate random vectors

This article considers the problem of measuring radial asymmetry of a bivariate vector of continuous random variables whose components are symmetric about the center of symmetry. We introduce a set of axioms for measures of radial asymmetry, define new measures satisfying the axiomatic, study some properties, and present corresponding results for sample statistics. Several examples illustrate our results.     

Zero Lower Bound and negative interest rates: Choices for monetary policy in the UK

There have been relatively few analyses of the policy context and consequences of a Zero Lower Bound (ZLB) for nominal interest rates. This paper sets out monetary policy alternatives, including negative interest rates, a revision of the inflation target, and rendering unconventional policy instruments such as QE conventional (permanent). Following extensive discussion of policy options, we set out a model that explores the impacts of the real policy rate on economic growth, employment and inflation, with particular attention to the British economy. We use a Time-Varying Structural Vector Auto-regressive (TVSVAR) Model where the sources of time variation are both the coefficients and variance–covariance matrix of the innovations. It was found that real rates have significant implications for real growth, the labour market and price stability even when monetary policy was constrained at the ZLB in nominal terms. The study additionally applies a discrete break in the data to focus on the Post-Global Financial Crisis and ZLB period. This indicates that the effectiveness of real rates did not diminish and this has important implications in terms of a policy approach which seeks to exploit real negative rates.     

Sectarian terrorism in Pakistan: Causes,impact and remedies

Although terrorism has been widely studied for its impact and potential determinants in Pakistan, the answer to the policy question regarding the role of external factors in influencing specifically the sectarian terrorism is not empirically well researched. The study, particularly, analyses the role of Pakistan’s regional foreign policy towards neighbouring India, Afghan wars, and the relations with bi-polar fundamental Muslim Block, the Kingdom of Saudi Arabia (KSA) and Iran, on sectarian (religious) terrorist incidents for the period 1973–2017. The findings suggest that economic cooperation with India which drive peace-making relations increases the sectarian terrorism. Both the bilateral loans disbursed by the KSA and trade relations with Iran, significantly increase the chances of sectarian terrorism in Pakistan by activating extremist (proxy) groups. However, the Afghan Wars that call for Pak-US strategic partnership helps Pakistan to control the religious terrorism.     

The cross-impact between financial markets,Covid-19 pandemic,and economic sanctions: The case of Iran

The main financial markets in the Iranian Economy include the stock exchange, foreign exchange, oil, and gold markets. The sharp fluctuations in these markets, especially those caused by the severe sanctions imposed on Iran in May 2018, and the pandemic outbreak of Covid-19 have led to more confusion and uncertainty among investors. One of the effective approaches to examine such unstable conditions is to study the co-movement(s) between markets to identify the leading variable(s). Thus, in the present study, Wavelet Coherence Analysis was applied to examine the co-movements between markets in a time period from September 2014 to June 2020, as an intense period of uncertainty in Iran. In other words, in this study, the markets were investigated in different sub-periods. Also, the Segmented Regression was performed to estimate the impact of sanctions and the Covid-19 pandemic on the co-movements of financial markets in Iran.The results showed that the oil price had a low co-movement with the other three markets, i.e. stock exchange, exchange rate, and gold markets. Thus, the oil market can be a suitable alternative for risk aversion investors. Meanwhile, the oil market could also act as a source of finance for the government during the sanctions period. That possibly explains the recent decision by the Iranian government to use the oil market to finance its budget deficit. Between the exchange rate and gold price, the gold price was identified as the leading variable. While the exchange rate and gold price did not show a significant co-movement in stable conditions, they did show a significant co-movement in unstable conditions, as in times of sanctions or during a global pandemic and thus influenced the investors’ portfolio risk. This result is important from a policy-making perspective. Based on this result, the policymakers can, especially during crises and unstable conditions, control the gold market and make it more stable by managing the foreign exchange market.     

Estimation of P(X>Y) with Topp–Leone distribution

We consider the estimation problem of the probability P=P(X>Y) for the standard Topp–Leone distribution. After discussing the maximum likelihood and uniformly minimum variance unbiased estimation procedures for the problem on both complete and left censored samples, we perform a Monte Carlo simulation to compare the estimators based on the mean square error criteria. We also consider the interval estimation of P.     

A comparative study for robust canonical correlation methods

The aim of this study is to obtain robust canonical vectors and correlation coefficients based on the percentage bend correlation and winsorized correlation in the correlation matrix and fast consistent high breakdown (FCH), reweighted fast consistent high breakdown (RFCH), and reweighted multivariate normal (RMVN) estimators to estimate the covariance matrix and then compare these estimators with the existing estimators. In the correlation matrix of canonical correlation analysis (CCA), we present an approach that substitutes the percentage bend correlation and the winsorized correlation in place of the widely employed the Pearson correlation. Moreover, we employ the FCH, RFCH, and RMVN estimators to estimate the covariance matrix in the CCA. We conduct a simulation study and employ real data with the objective of comparing the performance of the different estimators for canonical vectors and correlation with that of our proposed approaches. The breakdown plots and independent tests are employed as differentiating criteria of the robustness and performance of the estimators. Based on our computational and real data studies, we propose suggestions and guidelines on the practical implications of our findings.     

Inference and prediction for the burr type x model based on records

Based on record values, the maximum likelihood, minimum variance unbiased and Bayes estimators of the one parameter of the Burr type X distribution are computed and compared. The Bayesian and non-Bayesian confidence intervals for this parameter are also presented. A Bayesian prediction interval for the sth future record is obtained in a closed form. Based on simulated record values, numerical computations and comparisons between the different estimators are given     

Bayesian Identification of Moving Average Models

This study approaches the Bayesian identification of moving average processes using an approximate likelihood function and a normal gamma prior density. The marginal posterior probability mass function of the model order is developed in a convenient form. Then one may investigate the posterior probabilities over the grid of the order and choose the order with the highest probability to solve the identification problem. A comprehensive simulation study is carried out to demonstrate the performance of the proposed procedure and check its adequacy in handling the identification problem. In addition, the proposed Bayesian procedure is compared with some non Bayesian automatic techniques and another Bayesian technique. The numerical results support the adequacy of using the proposed procedure in solving the identification problem of moving average processes.