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This study aims to explore empirically the impact of various factors/determinants on housing prices at the country level as well as in Lahore, the most populous metropolitan city of the most populous province Punjab, Pakistan.

This study uses monthly data ranging from 2013M1 to 2020M1 on variables used in the study. Based on the stationarity results, the method of robust least square is used as an estimation technique. The validity of initial results is also authenticated by canonical cointegration regression.

The empirical result reveals that all included variables significantly affect housing prices both at country level as well as in Lahore. This study found negative impact of regressor age, real exchange rate and urbanization on housing prices, whereas the positive impact of gross domestic product (GDP) per capita, foreign remittances, broad money and real interest rate on housing prices in the case of Pakistan was found. On the other hand, results unveiled the negative impact of regressor age (proportion of population aged between 15 and 64), real exchange rate and urbanization on housing prices, whereas the positive impact of GDP per capita, foreign remittances, broad money and real interest rate on housing prices in Lahore metropolitan city was unveiled.

Based on the extant literature survey, this is a more holistic study of its kind that uncovers the macroeconomic determinants by considering the demand side, supply side and demographic factors of escalated housing prices in Pakistan, so that proper policies can be adopted to keep the housing sector stable. Empirical findings are helpful to acquire an enhanced understanding of how the housing price is determined and form a base for government to tackle the housing affordability problem.

This study aims to investigate the effect of monetary policy on housing prices for US economy. It specifically examines whether nominal or real interest rates are the key drivers behind fluctuations in housing prices in US.

Monthly data from January 1991 to July 2023 and various appropriate analytical tools such as unit root tests, Johansen’s cointegration test, vector error correction model (VECM), impulse response function and Granger causality test were applied for the data analysis.

The Johansen cointegration findings reveal the presence of a long-term relationship among the variables. VECM results indicate a negative correlation between nominal and real interest rates and housing prices in both the short and long terms, suggesting that a strict monetary policy can help in controlling the housing price increase in the USA. However, housing prices are more responsive to changes in nominal interest rates than to real interest rates. Additionally, the study reveals that the COVID-19 pandemic contributed to the upsurge in housing prices in the USA.

This study contributes by examining the role that nominal or real interest rates play in shaping housing prices in the USA. Moreover, given the recent significant upsurge in housing prices, this study presents a unique opportunity to investigate whether these price increases are influenced by the Federal Reserve's monetary policy decisions regarding nominal or real interest rates. Additionally, using monthly data, this study provides a deeper understanding of the fluctuations in housing prices and their connection to monetary policy tools.

Education transmits knowledge and abilities that are essential for any society’s socioeconomic progress. It improves the quality of life by providing both individuals and civilizations with several advantages. In this regard, women’s education is critical as they spend longer time with children than men. Despite the fact that education plays an immense role in overall wellbeing of society, in India, there are fewer educational opportunities available to young women than to young men. The gender bias that persists in Indian education and professional training is evident even in the richest countries in the world. In this regard, this study focuses on this intergenerational transmission of knowledge from the mother to her progenies in Karimganj District of Assam using the data from the household level primary survey. This study examines mothers’ educational profiles and ascertains the extent to which their education influence their children’s educational attainments. The results show that woman’s education has a direct role in enhancing the overall welfare of children and, thus, indirectly improves the economic status of the family. The results provide definite causal connections between a mother’s education and children’s educational attainment.

In this work, we estimated the different entropies like Shannon entropy, Rényi divergences, Csiszár divergence by using Jensen’s type functionals. The Zipf’s–Mandelbrot law and hybrid Zipf’s–Mandelbrot law are used to estimate the Shannon entropy. The Abel–Gontscharoff Green functions and Fink’s Identity are used to construct new inequalities and generalized them for m-convex function.

The purpose of this study is to integrate evidence on contributing factors, consequences, in addition to coping mechanisms of depression and anxiety in patients with heart failure.

An integrative review was conducted by searching three main electronic databases: Web of Sciences, MEDLINE and Science Direct. Twenty-four studies met the inclusion criteria and were included in the final review process.

The review identified the most common contributing factors, consequences and coping mechanisms of depression and anxiety in patients with heart failure. Patients with heart failure have high anxiety and depression prevalence rates.

It is recommended to include routine assessment and management of anxiety and depression in heart failure protocols to improve clinical outcomes.

This study examines the short-run and long-run impact of macroeconomic variables such as industrial production index, inflation, exchange rate, interest rate, foreign direct investment and trade balance, on KSE 100 index and sectorial stock indices under bearish, bullish and normal states of the stock market prices. Moreover, we take into account the effect of three crises observed from 2005 to 2009.

This study uses quantile autoregressive distributed lag (QARDL) model for examining the short-run and long-run effect across various quantiles of the dependent variables and compare its' results standard autoregressive distributed lag (ARDL) model.

ARDL estimates indicate that, in the long-run, industrial production index, trade balance and foreign direct investment significantly affect stock prices. These findings remain same when three crises have been taken into consideration. In addition, estimates from QARDL model indicate that, in the short-run, the effect of exchange rate, interest rate, consumer price index and foreign direct investment, varies across bearish, bullish and normal states of the overall stock prices. Moreover, the short-run findings for Auto Assembler, Cement, Commercial Banks sector are consistent with overall stock indices, whereas other sectors, such as, Oil and Gas and Power Generation and distribution are asymmetrically affected by all macroeconomic variables. In the long-run, the effect of all macro-variables varies across different states of the stock markets except industrial production index for Auto Assembler sector, Oil and Gas sector and composite index of KSE 100 index.

We take into account the effect of three crises observed from 2005 to 2009 and also examine the macroeconomic effect across bullish, bearish and normal states of the sectorial stock indices and composite index of Pakistan stock exchange. Finally, we use novel approach, called QARDL model, which has several advantages over other techniques.

Recent literature has shifted to examining whether exchange rate volatility symmetrically or asymmetrically affects the trade flows. This study aims to extend the existing literature by examining the effects of extremely large to extremely small changes in exchange rate volatility series on the US imports from Brazil, India, Mexico and South Africa.

For examining the effects of extreme changes, multiple threshold nonlinear autoregressive distributed lag (MTNARDL) model is used and the exchange rate volatility series is divided into quintiles and deciles. It helps to examine the effects of each quintile/decile of exchange rate volatility series on the US imports.

Findings indicate that the effects of extremely large changes in the exchange rate volatility series significantly differ from the effects of extremely small changes in the exchange rate volatility series on the US imports.

The findings of this study are very important. These findings help to consider the effect of extreme changes before devising policies related to trade flows.

This study mainly focuses on US imports from Brazil, India, Mexico and South Africa. In addition, this study extends the existing literature by using a novel methodology called MTNARDL model.

Over the past few decades, the flow around circular cylinders has been one of the highly researched topics in the field of offshore engineering and fluid-structure interaction (FSI). In the current study, numerical simulations for flow around a fixed circular cylinder are performed at Reynolds number (Re) = 3900 with the LES method using the ICEM-CFD and ANSYS Fluent tool for meshing and analysis, respectively. Previously, similar studies have been conducted at the same Reynolds number, but there have been discrepancies in the results, particularly in calculating the recirculation length and angle of separation. In addition, the purpose of this study is to address the impact of time interval averaging to obtain the fully converged solution.

This study presents the LES method, using the ICEM-CFD and ANSYS fluent tool for meshing and analysis.

In the current study, turbulence statistics are sampled for 25, 50, 75 and 100 vortex-shedding cycles with the CFL value O (1). The recirculation length, angle of separation, hydrodynamic coefficients and the wake behind the cylinder are investigated up to ten diameters. The drag coefficient and Strouhal number are observed to be less sensitive, whereas the recirculation length appeared to be highly dependent on the average time statistics and the non-dimensional time step. Similarly, the mean streamwise and cross-flow velocity are observed to be sensitive to the average time statistics and non-dimensional time step in the wake region near the cylinder.

In the current investigation, turbulence statistics are sampled for 25, 50, 75 and 100 vortex-shedding cycles with the CFL value O (1), using large eddy simulation method at Re = 3900 around a circular cylinder. The impact of time interval averaging to obtain the fully converged mean flow field is addressed. No such consideration is yet published in the literature.

This study aims to examine how beliefs and expectations on collaboration for investment, technology advancement and governance can lead to sustainable income generation that succeeds in influencing the community to accept the proposed Waqf integrated income generating model (WIIGM).

This study empirically examined the beliefs and expectations on the proposed WIIGM model, which was adapted from the theory of reasoned action (TRA). Data was collected from 366 respondents selected via convenience sampling. Questionnaires were distributed online, of which responses were then analysed using partial least squares structural equation modelling for hypothesis testing. Ethical approval is also gathered before the data collection begins.

This study found that collaboration for investment and governance significantly contribute to sustainable income generation in waqf operations and management, which eventually results in the community’s trust and acceptance of the WIIGM model. Technology advancement also significantly influences sustainable income generation, which finally leads to the community's behavioural intention to participate in the WIIGIM model. Further studies on this variable may establish findings from other perspectives.

This paper is an original study that empirically examines the potential for a new waqf integrated income-generating model in building the trust of the community towards waqf institutions. This study is significantly important for practitioners and policymakers in evaluating the potential roles of waqf based on the belief and trust of the community.

This paper adds value to existing literature regarding the potential of a new waqf integrated income-generating model.

Using three theoretical lenses − organismic integration theory (OIT), theory of values-belief-norm (VBN) and gender schema theory (GST) − this study aims to examine the effect of environmental factors (environmental attitude, environmental concerns, perceived environmental responsibility and peer influence) on consumers' intentions to purchase eco-friendly athletic wear.

A sample of n = 380 Pakistani consumers was used to test hypothesized relationships. Data were analyzed through the partial least square structural equation modeling (PLS-SEM) technique using SmartPLS version 3.3.3.

Findings suggest that environmental attitude, environmental concerns, perceived environmental responsibility and peer influence are positively associated with green purchase behavior. The moderating effects of individual green values were found statistically significant between peer influence and green purchase behavior. The data further revealed that the effect of environmental attitude, environmental concerns, peer influence and perceived environmental responsibility on green purchase behavior varies across the gender.

This research is one of the first attempts to explore the effect of environmental motivational factors on consumers' intentions to purchase eco-friendly athletic wear using theories of OIT, VBN and GST. This study employs advanced analytical methods to perform multi-group analysis and establish the predictive relevance of the model, using PLS-SEM in sports management and marketing context.