Correction: An Empirical Investigation of Determinants & Sustainability of Public Debt in Pakistan.

[This corrects the article DOI: 10.1371/journal.pone.0275266.].

Inflation targeting: A time-frequency causal investigation.

The enduring discourse regarding the effectiveness of interest rate policy in mitigating inflation within developing economies is characterized by the interplay of structural and supply-side determinants. Moreover, extant academic literature fails to resolve the direction of causality between inflation and interest rates. Nevertheless, the prevalent adoption of interest rate-based monetary policies in numerous developing economies raises a fundamental inquiry: What motivates central banks in these nations to consistently espouse this strategy? To address this inquiry, our study leverages wavelet transformation to dissect interest rate and inflation data across a spectrum of frequency scales. This innovative methodology paves the way for a meticulous exploration of the intricate causal interplay between these pivotal macroeconomic variables for twenty-two developing economies using monthly data from 1992 to 2022. Traditional literature on causality tends to focus on short- and long-run timescales, yet our study posits that numerous uncharted time and frequency scales exist between these extremes. These intermediate scales may wield substantial influence over the causal relationship and its direction. Our research thus extends the boundaries of existing causality literature and presents fresh insights into the complexities of monetary policy in developing economies. Traditional wisdom suggests that central banks should raise interest rates to combat inflation. However, our study uncovers a contrasting reality in developing economies. It demonstrates a positive causal link between the policy rate and inflation, where an increase in the central bank's interest rates leads to an upsurge in price levels. Paradoxically, in response to escalating prices, the central bank continues to heighten the policy rate, thereby perpetuating this cyclical pattern. Given this observed positive causal relationship in developing economies, central banks must explore structural and supply-side factors to break this cycle and regain control over inflation.

An Entropic Approach for Pair Trading in PSX.

The perception in pair trading is to recognize that when two stocks move together, their prices will converge to a mean value in the future. However, finding the mean-reverted point at which the value of the pair will converge as well as the optimal boundaries of the trade is not easy, as uncertainty and model misspecifications may lead to losses. To cater to these problems, this study employed a novel entropic approach that utilizes entropy as a penalty function for the misspecification of the model. The use of entropy as a measure of risk in pair trading is a nascent idea, and this study utilized daily data for 64 companies listed on the PSX for the years 2017, 2018, and 2019 to compute their returns based on the entropic approach. The returns to these stocks were then evaluated and compared with the buy and hold strategy. The results show positive and significant returns from pair trading using an entropic approach. The entropic approach seems to have an edge to buy and hold, distance-based, and machine learning approaches in the context of the Pakistani market.

An empirical investigation of determinants & sustainability of public debt in Pakistan.

An assessment of debt dynamics and its sustainability is very important in formalizing prudent and effective macroeconomic policies especially for the economies with weak macroeconomic fundamentals and alarming debt levels. Keeping in view the recent debt escalation in Pakistan, this study aims to explore the important factors that influence the public debt dynamics in case of Pakistan and to evaluate its sustainability. This study applies the debt dynamic approach for empirical assessment of drivers of changing debt levels and analysis of public debt sustainability. Furthermore, ARDL approach is utilized to study the short- and long-run debt dynamics using historic data from 1975 to 2021. This study is distinct from already existing work on debt assessment in Pakistan as it examines both important dimensions of public debt (determinants & stability) by employing the novel dynamic debt modelling approach and using most recent data. The study finds a positive and significant impact of fiscal deficit, exchange rate depreciation and interest rate on public debt in Pakistan. The debt sustainability analysis also reveals the instability of public debt for the entire study period except for few years. The regression results corroborate with the findings from stability analysis, and the main driving forces for increasing the debt burden of the country are found to be the fiscal indiscipline along with the rising cost on account of ER depreciation and higher interest rates.

Health Concerns of Textile Workers and Associated Community.

BACKGROUND: Workers in the textile industry risk developing various respiratory and pulmonary diseases due to exposure to cotton dust. The particles from the cotton lint are inhaled by the workers and results in the breathing problems including asthma, shortness of breath, cough and tightness in the chest. The poor health of labor contributes to the low productivity of the labor and in serious cases loss of jobs leading to the poverty. OBJECTIVE: To assess the prevalence of respiratory symptoms among the textile workers and associated community. To contrast the health profiles of the textile workers, associated community and the control group to factor out any confounding factors. METHODS: This study explores the health profiles of the textile workers and associated community and contrast them against the health profile of the control group to factor out any confounding factors. The study is conducted on cotton industry in Kasur, Pakistan. We interviewed 207 workers, 226 people from associated community (living in vicinities of weaving units) and 188 people for control group (from areas far away from weaving units and people are not associated with weaving industry) based on stratified random sampling technique. We employed descriptive methods and logistic regression to explore the association between respiratory diseases and weaving workers. RESULTS: Overall, prevalence of postnasal drip, byssinosis, asthma, and chronic bronchitis were 47%, 35%, 20%, and 10%, respectively, among the workers. These percentages are significantly higher than the control group. An additional year of work increase the risk of postnasal drip, byssinosis, asthma, and chronic bronchitis by 5-6%. Among workers, 43% and 21% feel difficulty in hearing against noisy background and at low volume, respectively. Due to bad light arrangements at workstations, 21% and 31% workers are suffering from myopia and hyperopia, respectively. Proportions of the workers suffering from continuous headache, skin infection, depression, and low back pain are 28%, 29%, 27%, and 44%, respectively. Chi-square test results confirms that no confounding factor like air pollution is involved in this cause-and-effect study implying the association between the cotton dust and associated diseases is not spurious. CONCLUSION: Respiratory symptoms were statistically significantly more common in the weaving workers compared to control group. Better environment at workstations, use of protective gears and education are the factors which reduce the risk of associated diseases among workers.

Min-max approach for comparison of univariate normality tests.

Comparison of normality tests based on absolute or average powers are bound to give ambiguous results, since these statistics critically depend upon the alternative distribution which cannot be specified. A test which is optimal against a certain type of alternatives may perform poorly against other alternative distributions. Thus, an invariant benchmark is proposed in the recent normality literature by computing Neyman-Pearson tests against each alternative distribution. However, the computational cost of this benchmark is significantly high, therefore, this study proposes an alternative approach for computing the benchmark. The proposed min-max approach reduces the calculation cost in terms of computing and estimating the Neyman-Pearson tests against each alternative distribution. An extensive simulation study is conducted to evaluate the selected normality tests using the proposed methodology. The proposed min-max method produces similar results in comparison with the benchmark based on Neyman-Pearson tests but at a low computational cost.