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The authors’ conclusions are based on mathematical derivations that are supported by computer simulations and three worked examples in applications of economics and finance. Finally, the authors provide a link to a computer program so that researchers can perform the analyses easily.

Based on a parameter estimation goal, the present work is concerned with determining the minimum sample size researchers should collect so their sample medians can be trusted as good estimates of corresponding population medians. The authors derive two solutions, using a normal approximation and an exact method.

The exact method provides more accurate answers than the normal approximation method. The authors show that the minimum sample size necessary for estimating the median using the exact method is substantially smaller than that using the normal approximation method. Therefore, researchers can use the exact method to enjoy a sample size savings.

In this paper, the a priori procedure is extended for estimating the population median under the skew normal settings. The mathematical derivation and with computer simulations of the exact method by using sample median to estimate the population median is new and a link to a free and user-friendly computer program is provided so researchers can make their own calculations.

This study aims to examine the tail connectedness between the Chinese and Association of Southeast Asian Nations (ASEAN) stock markets. More specifically, the authors measure the return spillovers at three quantile levels: median (t = 0.5), lower extreme (t = 0.05) and upper extreme (t = 0.95). The connectedness at extreme upper and lower quantiles provides insightful information to investors regarding tail risk propagation, which ultimately suggests that investors adjust their portfolios according to the extreme bullish and bearish market conditions.

The authors employ the quantile connectedness approach of Ando et al. (2022) to examine the quantile transmission mechanism among the ASEAN and Chinese stock markets.

The results show significant evidence of a higher level of connectedness between Chinese and ASEAN stock markets at extreme upper and lower quantiles compared to the median quantiles, which suggests the use of a quantile-based connectedness approach instead of an average-measure-based one. Furthermore, the time-varying connectedness analysis shows that the total spillovers reach the highest peaks during the global financial crisis, the Chinese stock market crash and the COVID-19 pandemic at the upper, lower and median quantiles. Finally, the static and dynamic pairwise spillovers between the Chinese and ASEAN markets vary over quantiles as well.

This study is the first attempt to examine quantile vector autoregression (VAR)-based return spillovers between China and ASEAN stock markets during different market statuses. Besides, the COVID-19 has intensified the uncertainty in Asian countries, mainly China and ASEAN economies.

This paper aims to explore the citation aging pattern of Library and Information Science (LIS) and further investigate the impact of interdisciplinary citation on the aging of scientific literature.

The study examines LIS journal articles published between 2016 and 2020. Articles were retrieved from the Web of Science (WoS) and were organized using Scopus's discipline classification system. Citation aging patterns within LIS are described using literature aging indicators. The study examines the effect of interdisciplinary citations on the literature aging pattern by comparing the half-life of LIS literature and the median age of interdisciplinary citations.

The study results show that the citation aging rate of LIS in the last five years has been slow, and the rate of slowing down is decreasing. Interdisciplinary citations are sourced from various disciplines, focusing on computer science, social sciences and business. The proportion of self-citations is declining. The Reference Diversity Index (RDI) increases from 0.690 to 0.724 between 2016 and 2020. Currently, the median age of interdisciplinary citations is higher than the LIS's half-life. It has a diminishing effect on the citation aging rate. But the median age of interdisciplinary citations is decreasing. The interdisciplinary citation may contribute to the literature aging rate in the future. The effect of interdisciplinary citation on literature aging needs to be judged dialectically.

This study still has some limitations. Due to the wide variety of citation journals in LIS, there is no database to cover all journals, so it is impossible to match all citation journals with disciplines. Therefore, it is still feasible to analyze interdisciplinary citations based on the two-eight principle for large-scale data. This approach necessarily sacrifices some of the precision of the study. However, the results of this paper can still be helpful for the development of the discipline. In addition, LIS is a discipline with solid cross-cutting properties, and this paper concludes only with this interdisciplinary discipline in mind. It is necessary to test the applicability of the findings to other disciplines.

The study explores the impact of interdisciplinary citation on literature aging from a professional communication perspective. The results reveal underlying reasons for the aging of scientific literature. These findings further enrich the study of the effect of interdisciplinary communication.

Press reports have indicated that firms frequently underprice restricted stock and employee stock options. I test for underpricing of stock and options.

I examined a sample of 5,333 private firm stock and option issuances between 1985 and 2017. I tested for underpricing using two approaches: assuming investors have no special market-timing ability and assuming instead they have perfect market-timing ability.

I find evidence of widespread stock and option underpricing by private firms before they go public reflecting large discounts that exceed reasonable compensation for lack of marketability. Unreported underpricing is more frequent in the last pre-IPO private equity transactions that offer the last opportunity to give such discounts before the stock is publicly traded, but the discounts are greater in the earlier pre-IPO transactions where unreported discounts are presumably tougher for the SEC to detect. Underpricing is still detected even when the actual DLOMs are tested against a benchmark that assumes investors have perfect market-timing ability.

Firms frequently underprice restricted stock and employee stock options. Firms tend to underprice stock options more frequently than restricted stock, but restricted stock tends to be priced at deeper discounts when recipients are assumed not to have any special market-timing ability.

Private firms issue restricted stock and options as incentive compensation. Lowballing the valuation transfers wealth from outside stockholders to employees/insiders. Wealth transfers take place through the issuance of equity claims to employees/insiders before firms go public. I found that more than a quarter of the DLOMs exceed the theoretical maximum by, on average, between 16% (median) and 20% (mean). This finding raises two questions worthy of investigation. First, to what extent do the frequency and magnitude of DLOMs above the theoretical maximum depend on whether a board of directors obtains an independent appraisal of a stock’s fair market value? Second, if DLOMs above the theoretical maximum are observed even when the stock is independently appraised, how do appraisers justify such large DLOMs?

The wealth transfers that take place through the issuance of equity claims to employees/insiders before firms go public benefit employees/insiders at the expense of outside shareholders.

My paper is the first to furnish evidence of widespread stock and option underpricing by private firms before they go public; demonstrate that the unreported underpricing is more frequent in the last pre-IPO private equity transactions that offer the last opportunity to give such discounts before the stock is publicly traded and show that the discounts are greater in the earlier pre-IPO transactions where unreported discounts are presumably tougher for the SEC to detect.

This study aims to investigate the variation in overvaluation proxies and volatility across industry sectors and time.

Using industry sector data from the S&P Capital IQ database, this study applies traditional cross-sectional regressions to investigate the relationship between overvaluation and volatility over the 2001–2020 time period.

This study finds that the most volatile industry sectors generally do not coincide with overvalued industry sectors in the cross-section, implying that there are limitations to price-multiple methods for forecasting future volatility. Rather, this study finds that historical volatility significantly increases the goodness-of-fit when modeling volatility in the cross section of industry sectors. The findings of this study imply that firms should increase disclosures and transparency about corporate practices to decrease downside risk that stems from bad news. In addition, the findings underline the consistency between market efficiency and high levels of volatility in periods of significant uncertainty.

This study proposes a novel approach to examining the cross section of volatility across time for industry sectors.

This study aims to identify the determinants of housing affordability in an effort to inform policy.

The authors use econometric analysis to determine variables that impact housing affordability in the USA.

The authors find that affordability depends on a number of demographic factors as well as physical characteristics of properties, including average age of homeowner, family size and average dwelling square footage. The authors also find that vacancy rates, increase in house price and median family income also have a significant impact on housing affordability. Additionally, the authors find that households with high-cost burdens are more vulnerable to mortgage rates and property taxes than those with moderate-cost burdens. As a result, changes in economic or policy variables tend to have a disproportionate impact on high-cost-burdened households, and they are more vulnerable to economic and policy shocks.

To date, the literature has not done a systematic investigation of housing affordability using detailed census data.

It is generally believed that business spending on capital expenditure tends to decrease as interest rates rise, and vice versa, this is not always the case. The previous literature produces inconclusive results vis-à-vis the interest rate and investment nexus. This study analyzes the responsiveness of investment to changes in high and low levels of interest rates in India through a quantile-based, non-parametric method utilizing annual data from 1980 to 2022.

This study uses Quantile-on-quantile (QQ) technique proposed by Sim and Zhou (2015) to examine the impact of interest rate quantiles on quantiles of investment. In addition, long-term association and the direction of causality are estimated through the Cho et al. (2015) test of quantile cointegration and the Jeong et al. (2012) Granger causality in quantile (GCQ) test, respectively.

The empirical evidence validates that the linkage between investments and interest rate is not consistently negative and varies from quantile to quantile. The study finds a negative impact at median quantiles and a positive impact at extreme higher quantiles. Conversely, the impact at lower quantiles is negligible, which is also observed from quantile cointegration, indicating the presence of a statistically significant association above the median quantiles. Additionally, the study finds one interesting finding that there exists unidirectional causality from investment to interest rates in India rather than other way around.

The study provides significant implications for policymakers as it suggests that during extreme economic conditions, the effectiveness of traditional monetary policy tools to boost capital formation is restricted. Policymakers may consider alternative measures to stimulate investment during these time periods. The study additionally posits that the neoclassical theory of investment may not be readily applicable in emerging economies in its unaltered state, mostly due to the lack of well-developed financial markets.

There is a limited literature available on non-linear linkage between interest rates and investment. The present study adds to the existing knowledge by investigating how investment responds differently to fluctuations in interest rates, while incorporating the complete distribution of both the variables.

By comparing regression models, this study aims to analyze the added home value of green sustainability features and green efficiency characteristics, rather than green certifications, in the city of Austin.

The adoption of home green energy efficiency upgrades has emerged as a new trend in the real estate industry, offering several benefits to builders and home buyers. These include tax reductions, health improvements and energy savings. Previous studies have shown that energy-certified single-family homes command a premium in the marketplace. However, the literature is limited in its analysis of the effects of green upgrades and certification on different types of single-family homes. To address this gap, this research collected data from 21,292 multiple listing services (MLS) closed home-selling listings in Austin, Texas, over a period of 35 months.

The analysis results showed that green efficiency features could generally increase single-family housing prices by 11.9%, whereas green sustainability upgrades can potentially bring a 11.7% higher selling price. Although green housing certification did not have significant effects on most housing groups, it did increase closing prices by 13.2% for single-family residences sold at the medium price range, which is higher than the impacts from simply listing the green features on MLS.

The study contributes to the body of knowledge by examining the market value of broadly defined energy efficiency and sustainability features in the residential housing market. The findings can help policymakers, brokerage firms, home builders and owners adjust their policies and strategies related to single-family home sales and mortgage approvals. The research also highlights the potential benefits of capitalizing on green housing features other than certifications.

Despite endeavors to alleviate construction and demolition waste and the indications that the process of deconstruction has the potential to steer waste reduction initiatives, there has not been a progressive increase in the adoption of Design for Deconstruction (DfD) in the global south, especially Ghana. This paper aims to identify and analyze the barriers to implementing DfD in developing countries.

A structured questionnaire survey was used to solicit the views of 240 design professionals in the Ghanaian construction industry (GCI). The questionnaire was developed by reviewing pertinent literature and complemented with a pilot review. Data were analyzed using descriptive and nonparametric statistics.

The findings revealed ten (10) significant impediments to implementing DfD within the construction industries in developing economies. These impediments revolve around cost, legal matters, storage, incentive and design-related matters. Key among these barriers is “For recovered materials, there are little performance guarantees,” “The absence of strict regulations regarding design for deconstruction,” “Lack of a large market enough for components that have been recovered,” “The need for building codes that address how to design with reused materials” and “Lack of effective design for deconstruction tools.”

The results of this research shed light on a relatively unexplored area within the construction sector, particularly in a developing country like Ghana. Furthermore, to the best of the authors’ knowledge, the study contributes fresh and supplementary knowledge and perspectives regarding the challenges in implementing DfD practices.

Physical environments, especially the sound environments of ILSs on a university campus, have become increasingly important in satisfying the diverse needs of students. Poor sound environments are widely acknowledged to lead to inefficient and underutilised spaces and to negatively influence students' learning outcomes. This study proposes two hypotheses to explore whether students' sound environment perceptions are related to their individual characteristics and whether students' preferences for the type of ILS are related to their sound environment sensitivities.

An investigation through a questionnaire survey has been conducted on both students' individual characteristics affecting their sound environment perceptions in informal learning spaces (ILSs) of a university campus and their sensitivities to the sound environments in ILSs affecting their preferences for the type of ILSs.

The research findings indicate that students' sound environment perceptions are associated with some of their individual characteristics. In addition, the results show that students' sound environment sensitivities affect their preferences for the type of ILS they occupy.

This study could help architects and managers of university learning spaces to provide better sound environments for students, thereby improving their learning outcomes. The article contributes valuable insights into the correlation between students' individual characteristics, sound environment perceptions and preferences for ILSs. The research findings add to the existing knowledge in this field and offer practical implications for enhancing design and management of university learning environments.