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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.

Using various proxies for the firms' return on equity (ROE) and retention ratios (b) the authors calculate 36 sustainable growth rates, on a rolling basis, for a comprehensive set of firms over a 52-year period. The authors then assess the ability of these different sustainable growth rates to predict the actual, out-of-sample, five-year growth rates of the firms' earnings.

The authors compare the forecast to determine which method of estimating ROE and b produce the lowest mean-squared-errors and then determine the estimation method that works best for firms with different characteristics and for firms in different industries.

Overall, using the median ROE of all firms in the market and the 5-year average of the specific firm's retention ratio produces the lowest, statistically significant, forecast errors. Variations are documented based on firm characteristics, including dividend payout, level of ROE and industry.

The findings can guide practitioners in using the best earnings forecasting method.

Financial textbooks seem universally to suggest that one method of estimating the growth rate of a firm's earnings is to calculate the “sustainable growth rate” by multiplying the firm's ROE by the firm's b. At the same time, multiple methods of proxying for both ROE and b have been suggested; therefore, it is an interesting and useful empirical question, which, heretofore, has not been addressed in the literature, as to which estimation of the sustainable growth rate best approximates the actual future growth of the firm's earnings. The findings can guide practitioners in using the best earnings forecasting method.

This study proposes a novel measure for management’s horizon (short-termism or myopia vs long-termism or hyperopia) derived from easily obtainable firm-level accounting and stock market performance data. The authors use the measure to explore the impact of managements’ horizon on firms’ investment efficiency.

The authors rely on two commonly used but uncorrelated measures of management performance: accounting performance (return on capital employed, ROCE) and stock market performance (average abnormal return, AAR). The authors combine these measures to develop a multidimensional framework for performance, which classifies firms into four groups: efficient (high accounting and high market performance), poor (low accounting and low market performance), myopic (high accounting and low market performance) and hyperopic (low accounting and high market performance). The authors validate this framework and deploy it to explore the relationship between horizon and firms’ investment efficiency.

In validation tests, the authors show that management myopia (hyperopia) explains firms’ decision to cut (grow) research and development investments. Further, as expected, myopic (hyperopic) firms are associated with significantly more (less) accrual and real earnings management. The empirical tests on the link between horizon and investment efficiency suggest that myopic managers cut new investments while their hyperopic counterparts grow the same. Ultimately, the authors find that myopia (hyperopia) exacerbates(mitigates) the over-investment of free cash flow problem.

The authors introduce a framework for assessing management’s horizon using easily obtainable measures of performance. The framework explains inconsistencies in prior empirical research using different measures of performance (accounting versus market). The authors demonstrate its utility by showing that the measure explains decisions around research and development investment, earnings management and firm investments.

First is to develop the time truncated median control chart for the Rayleigh distribution (RD) and generalized RD (GRD), respectively. Second is to evaluate the performance of the proposed attribute control chart which depends on the average run length (ARL) and third is to include real life examples for application purpose of the proposed attribute control chart.

(1) Select a random sample of size n from each subgroup from the production process and put them on a test for specified time t, where t = ? × µe. Then, count the numbers of failed items in each subgroup up to time t. (2) Step 2: Using np chart, define D = np, the number of failures, which also a random variable follows the Binomial distribution. It is better to use D = np chart rather than p chart because the authors are using number of failure rather than proportion of failure p. When the process is in control, then the parameters of the binomial distribution are n and p0, respectively. (3) Step 3: The process is said to be in control if LCL = D = UCL; otherwise, the process is said to be out of control. Hence, LCL and UCL for the proposed control chart.

From the findings, it is concluded that the GRD has smaller ARL values than the RD for specified values of parameters, which indicate that GRD performing well for out of control signal as compared to the RD.

This developed control chart is applicable when real life situation coincide with RD and GRD.

Researcher can directly use presented study and save consumers from accepting bad lot and also encourage producers to make good quality products so that society can take benefit from their products.

This article dealt with time truncated attribute median control chart for non-normal distributions, namely, the RD and GRD, respectively. The structure of the proposed control chart is developed based on median lifetime of the RD and GRD, respectively.

The purpose of this paper is to design a modified version of the double sampling plan to handle the inspection processes requiring a minimum sample size to assure the median life for the products under the new Weibull–Pareto distribution. The economic design of the proposed plan is also considered to assure the product's lifetime with minimum cost.

The authors have developed an optimization model for obtaining the required plan parameters by solving simultaneously two non-linear inequalities and such inequalities have been formed based on the two points on the operating characteristic curve approach.

The results show that the average sample number, average total inspection and total inspection cost under the proposed plan are smaller than the same of a single sampling plan. This means that the proposed plan will be more efficient than a single sampling plan in reducing inspection effort and cost while providing the desired protection.

The proposed modified double sampling plan designed to assure the median life of the products under the new Weibull–Pareto distribution is not available in the literature. The proposed plan will be very useful in assuring the product median lifetime with minimum sample size as well as minimum cost in all the manufacturing industries.

The purpose of this paper is to propose a scenario-based grey methodology using clustering and optimizing with imprecise and uncertain body size data in an emergency assembly point area to assign the people on a campus to reach the emergency assembly points under uncertain disaster times.

Grey clustering and a new grey p-median linear programming model are developed to determine which units to assign to the pre-determined assembly points for a main campus in case of a disaster. The models have two scenarios: 70 and 100% occurrence capacities of administrative and academic personnel and students.

In this study, the academic and administrative units have been assigned to determine five different emergency assembly points on the main campus by using the numbers of the academic and administrative personnel and student and distances of the units to the assembly point areas of each other. The alternative solutions are obtained effectively by evaluating capacity utilization rates in the scenarios.

It is often unclear when disasters can occur and therefore, a preliminary preparation time must be required to minimize the risk. In the case of natural, man-made (unnatural) or technological disasters, the people are required to defend themselves and move away from the disaster area as soon as possible in a proper direction. The proposed assignment model yields a final solution that effectively eliminates uncertainty regarding the selection of emergency assembly points for administrative and academic staff as well as students, in the event of disasters.

Grey clustering suggests an assignment plan and concurrently, an investigation is underway utilizing the grey p-median linear programming model. This investigation aims to optimize various scenarios and body sizes concerning emergency assembly areas. All campus users who are present at the disaster in units of the campus are getting uncertainty about which emergency assembly point to use, and with this study, the vital risks aim to be ultimately reduced with reasonable plans.

This chapter investigates the cost of public debt for firms using a comprehensive sample consisting of 17,368 industrial bond issues from 1970 to 2011. The empirical evidence shows that yield spreads for seasoned bond issues are significantly lower than those for initial bond issues. This seasoning effect is robust across different sample periods, subsamples, and model specifications. On average, the yield spreads for seasoned bond issues are around 50 bps lower than those for initial bond issues. This difference cannot be explained by other bond and firm characteristics. The seasoning effect is more pronounced for firms with higher levels of uncertainty, lower information disclosure quality, and longer time intervals between the first and subsequent issues. Our empirical findings provide supportive evidence for the extant theories that aim to rationalize the information role in determining the cost of capital.

This study investigates the impact of international remittances on the economic growth of remittance-receiving countries, using data from 113 developing countries between 1990 and 2015.

The authors used a novel approach to address the potential endogeneity of remittances. The authors estimated bilateral remittances and use them to create weighted indicators of remittance-sending countries, which the authors then use as instruments for remittance inflows to remittance-receiving countries.

The results indicate that while remittances have a positive impact on economic growth in developing countries with high human capital, they do not contribute to growth in developing countries with low human capital. The authors also examined the channels through which remittances affect growth. The findings suggested that remittances do not impact labor supply in developing countries with high human capital, but they reduce labor supply in countries with low human capital. Additionally, remittances increase investment in physical capital in developing countries with high human capital, but they do not have an effect on investment in developing countries with low human capital.

The authors investigated the impact of remittances on economic growth using a novel approach to address the endogeneity of remittances. Additionally, the authors examined the different indirect channels through which remittances can impact economic growth, such as their effect on labor supply and investment.

This study investigates the effects of elements of corporate governance along with firm specific variables on the financial leverage of listed Indian firms in the context of agency conflicts and new governance laws.

A series of panel ordinary least squares as well as fixed/random effects regression models of book and market value of financial leverage on variables of corporate governance (board size, board composition, board meeting, board attendance and board gender) along with a set of control variables (asset tangibility, firm size, growth, liquidity and profitability) were estimated by employing 113 listed Indian firms during 2010–2021. Dynamic panel generalized method of moments models were also estimated to check the robustness of empirical results. Further, the full sample of firms was divided into small and large board sized companies using the median approach to investigate differences between small and large board characteristics on financial leverage.

The evidence predominantly suggested that the governance variables have significant impact on leverage ratios of selected firms. Governance variables such as board size, composition, attendance and gender are significantly found to be reducing the financial leverage of firms indicating that in general these attributes in a way, through monitoring managers, put pressure on them to pursue lower financial leverage. Board meeting is found to be positive and significantly related with financial leverage suggesting that the frequency of meetings signals its monitoring ability that may influence lenders' risk assessment lowering borrowing cost. The results on small and large board sized companies indicate that firms with small boards relatively issue more debt compared to firms with large boards suggesting that small boards adopt high debt policy.

The main policy implication of the study is that elements of internal corporate governance is a significant governance tool that has the potential to reduce agency conflict between the managers and agents through monitoring and decision making that has tangible effects on critical corporate decisions such as capital structure choices.

This paper contributes to the existing literature by bringing new evidence relating to agency conflicts and capital structure decisions in an emerging market like India post adoption of new regulations related to corporate governance specified in Clause 49 of Securities and Exchange Board of India and Companies Act, 2013 as there is significant dearth of such empirical work.