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Article
Publication date: 4 January 2024

Mohit Kumar and P. Krishna Prasanna

To investigate the role of domestic and foreign economic policy uncertainty (EPU) in driving the corporate bond yields in emerging markets.

Abstract

Purpose

To investigate the role of domestic and foreign economic policy uncertainty (EPU) in driving the corporate bond yields in emerging markets.

Design/methodology/approach

The study utilizes monthly data from January 2008 to June 2023 from the selected emerging economies. The data analysis is conducted using univariate, bivariate and multivariate statistical techniques. The study includes bond market liquidity and global volatility (VIX) as control variables.

Findings

Domestic EPU has a significant role in driving corporate bond yields in these markets. The study finds weak evidence to support the role of the USA EPU in influencing corporate bond yields in emerging economies. Domestic EPU holds more weight and influence than the EPU originating from the United States of America.

Research limitations/implications

The findings provide useful insights to policymakers about the potential impact of policy uncertainty on corporate bond yields and enable them to make informed decisions regarding economic policies that maintains financial stability. Understanding the relationship between EPU and corporate bond yields enables investors to optimize their investment decisions in emerging market economies, opens the scope for further research on the interaction between EPU and volatility and other attributes of fixed income markets.

Originality/value

Focuses specifically on the emerging market economies in Asia, providing an in-depth analysis of the dynamics and challenges faced by these countries, Explores the influence of both domestic and the USA EPU on corporate bond yields in emerging markets, offering valuable insights into the transmission channels and impact of EPU from various sources.

Details

Journal of Economic Studies, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0144-3585

Keywords

Article
Publication date: 5 February 2024

Nikita Dhankar, Srikanta Routroy and Satyendra Kumar Sharma

The internal (farmer-controlled) and external (non-farmer-controlled) factors affect crop yield. However, not a single study has identified and analyzed yield predictors in India…

Abstract

Purpose

The internal (farmer-controlled) and external (non-farmer-controlled) factors affect crop yield. However, not a single study has identified and analyzed yield predictors in India using effective predictive models. Thus, this study aims to investigate how internal and external predictors impact pearl millet yield and Stover yield.

Design/methodology/approach

Descriptive analytics and artificial neural network are used to investigate the impact of predictors on pearl millet yield and Stover yield. From descriptive analytics, 473 valid responses were collected from semi-arid zone, and the predictors were categorized into internal and external factors. Multi-layer perceptron-neural network (MLP-NN) model was used in Statistical Package for the Social Sciences version 25 to model them.

Findings

The MLP-NN model reveals that rainfall has the highest normalized importance, followed by irrigation frequency, crop rotation frequency, fertilizers type and temperature. The model has an acceptable goodness of fit because the training and testing methods have average root mean square errors of 0.25 and 0.28, respectively. Also, the model has R2 values of 0.863 and 0.704, respectively, for both pearl millet and Stover yield.

Research limitations/implications

To the best of the authors’ knowledge, the current study is first of its kind related to impact of predictors of both internal and external factors on pearl millet yield and Stover yield.

Originality/value

The literature reveals that most studies have estimated crop yield using limited parameters and forecasting approaches. However, this research will examine the impact of various predictors such as internal and external of both yields. The outcomes of the study will help policymakers in developing strategies for stakeholders. The current work will improve pearl millet yield literature.

Details

Journal of Modelling in Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-5664

Keywords

Book part
Publication date: 1 May 2023

Hui-Chu Shu, Jung-Hsien Chang, Chia-Fen Tsai and Cheng-Wen Yang

This study investigates the impacts of operational risks and corporate governance on bond yield spreads, examining their impacts on bond yield spreads during the COVID-19…

Abstract

This study investigates the impacts of operational risks and corporate governance on bond yield spreads, examining their impacts on bond yield spreads during the COVID-19 pandemic. The results indicate that operational risks significantly raise yield spreads, especially for high-leverage firms. Moreover, a higher independent director percentage reduces debt costs. Furthermore, the results reveal more pronounced effects of operational risks on yield spreads during the COVID-19 pandemic, with these risks increasing the financing costs for large firms. When the effect of the independent director percentage on the yield spreads increases, this consequently raises the debt costs for large firms.

Details

Advances in Pacific Basin Business, Economics and Finance
Type: Book
ISBN: 978-1-80382-401-7

Keywords

Article
Publication date: 6 September 2023

Francis Tsiboe, Jesse B. Tack, Keith Coble, Ardian Harri and Joseph Cooper

The increased availability and adoption of precision agriculture technologies has left researchers to grapple with how to best utilize the associated high-frequency large-volume…

Abstract

Purpose

The increased availability and adoption of precision agriculture technologies has left researchers to grapple with how to best utilize the associated high-frequency large-volume of data. Since the wealth of information from precision equipment can easily be aggregated in real-time, this poses an interesting question of how aggregates of high-frequency data may complement, or substitute for, publicly released periodic reports from government agencies.

Design/methodology/approach

This study utilized advances in event study and yield projection methodologies to test whether simulated weekly harvest-time yields potentially drive futures price that are significantly different from the status quo. The study employs a two-step methodology to ascertain how corn futures price reactions and price levels would have evolved if market participants had access to weekly forecasted yields. The marginal effects of new information on futures price returns are first established by exploiting the variation between news in publicly available information and price returns. Given this relationship, the study then estimates the counterfactual evolution of corn futures price attributable to new information associated with simulated weekly forecasted yields.

Findings

The results show that the market for corn exhibits only semi-strong form efficiency, as the “news” provided by the monthly Crop Production and World Agricultural Supply and Demand Estimates reports is incorporated into prices in at most two days after the release. As expected, an increase in corn yields relative to what was publicly known elicits a futures price decrease. The counterfactual analysis suggests that if weekly harvest-time yields were available to market participants, the daily corn futures price will potentially be relatively volatile during the harvest period, but the final price at the end of the harvest season will be lower.

Originality/value

The study uses simulation to show the potential evolution of corn futures price if market participants had access to weekly harvest-time yields. In doing so, the study provides insights centered around the ongoing debate regarding the economic value of USDA reports in the presence of growing information availability within the private sector.

Details

Agricultural Finance Review, vol. 83 no. 4/5
Type: Research Article
ISSN: 0002-1466

Keywords

Article
Publication date: 13 October 2023

Mohammad Saeid Aghighi, Christel Metivier and Sajad Fakhri

According to the research, viscoplastic fluids are sensitive to slipping. The purpose of this study is to determine whether slip affects the Rayleigh–Bénard convection of…

Abstract

Purpose

According to the research, viscoplastic fluids are sensitive to slipping. The purpose of this study is to determine whether slip affects the Rayleigh–Bénard convection of viscoplastic fluids in cavities and, if so, under what conditions.

Design/methodology/approach

The wall slip was evaluated using a model created for viscoplastic (Bingham) fluids. The coupled conservation equations were solved numerically using the finite element method. Simulations were performed for various parameters: the Rayleigh number, yield number, slip yield number and friction number.

Findings

Wall slip determines two essential yield stresses: a specific yield stress value beyond which wall slippage is impossible (S_Yc); and a maximum yield stress beyond which convective flow is impossible (Y_c). At low Rayleigh numbers, Y_c is smaller than S_Yc. Hence, the flow attained a stable (conduction) condition before achieving the no-slip condition. However, for more significant Rayleigh numbers Y_c exceeded S_Yc. Thus, the flow will slip at low yield numbers while remaining no-slip at high yield numbers. The possibility of slipping on the wall increases the buoyancy force, facilitating the onset of Rayleigh–Bénard convection.

Originality/value

An essential aspect of this study lies in its comprehensive examination of the effect of slippage on the natural convection flow of viscoplastic materials within a cavity, which has not been previously investigated. This research contributes to a new understanding of the viscoplastic fluid behavior resulting from slipping.

Details

Multidiscipline Modeling in Materials and Structures, vol. 19 no. 6
Type: Research Article
ISSN: 1573-6105

Keywords

Article
Publication date: 20 June 2023

Kei Kimura, Takeshi Onogi and Fuminobu Ozaki

This work examines the effects of strain rate on the effective yield strength of high-strength steel at elevated temperatures, through tensile coupon tests at various strain…

Abstract

Purpose

This work examines the effects of strain rate on the effective yield strength of high-strength steel at elevated temperatures, through tensile coupon tests at various strain rates, to propose appropriate reduction factors considering the strain rate effect.

Design/methodology/approach

The stress–strain relationships of 385 N/mm2, 440 N/mm2 and 630 N/mm2-class steel plates at elevated temperatures are examined at three strain rate values (0.3%/min, 3.0%/min and 7.5%/min), and the reduction factors for the effective yield strength at elevated temperatures are evaluated from the results. A differential evolution-based optimization is used to produce the reduction-factor curves.

Findings

The strain rate effect enhances with an increase in the standard design value of the yield point. The effective yield strength and standard design value of the yield point exhibit high linearity between 600 and 700 °C. In addition to effectively evaluating the test results, the proposed reduction-factor curves can also help determine the ultimate strength of a steel member at collapse.

Originality/value

The novelty of this study is the quantitative evaluation of the relationship between the standard design value of yield point at ambient temperature and the strain-rate effect at elevated temperatures. It has been observed that the effect of the strain rate at elevated temperatures increases with the increase in the standard design value of the yield point for various steel strength grades.

Details

Journal of Structural Fire Engineering, vol. 15 no. 1
Type: Research Article
ISSN: 2040-2317

Keywords

Article
Publication date: 28 March 2023

Juan Chen, Hongling Guo and Zuoping Xiao

This study aims to investigate how high-speed railway (HSR) development affects urban construction investment (UCI) bond yield spreads based on China’s background.

Abstract

Purpose

This study aims to investigate how high-speed railway (HSR) development affects urban construction investment (UCI) bond yield spreads based on China’s background.

Design/methodology/approach

This study constructs a quasi-natural experiment and adopts regression analyses to empirically examine the relation between HSR development and UCI bond yield spreads. The empirical analysis is based on a Chinese sample of 15,109 bond offering observations from 2008 to 2019.

Findings

The results show that HSR development reduces UCI bond yield spreads. Mechanistic analysis shows that HSR development increases land prices and the level of urbanization, which in turn lowers the UCI bond yield spreads. In addition, the impact of HSR development on UCI bond yield spreads is more significant at higher marketization levels and lower degrees of dependence on land finance cities where UCI corporations are located.

Research limitations/implications

The results imply that transportation infrastructure improvement, such as HSR development, helps to enhance the credit of local governments and the solvency of UCI corporations and ultimately reduces the financing cost of UCI bonds.

Originality/value

This paper provides theoretical support and empirical evidence for the impact of transportation infrastructure construction on the implicit debt risks of local governments in China, which enriches the research on the “HSR economy” from a micro perspective and expands the research on the influencing factors of local governments’ debt risk.

Open Access
Article
Publication date: 22 June 2023

Omar Esqueda and Thomas O'Connor

The authors measure the cost of equity to earnings yield differential for a sample of 2,035 non-financial firms. In a series of Logit and Tobit regressions, the authors examine if…

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Abstract

Purpose

The authors measure the cost of equity to earnings yield differential for a sample of 2,035 non-financial firms. In a series of Logit and Tobit regressions, the authors examine if the cost of equity to earnings yield differential is related to dividend policy in the manner predicted by agency theory.

Design/methodology/approach

Agency theory says a firm's optimal dividend policy is partially determined by the relationship between the earnings yield and the cost of equity capital. When the cost of equity is higher (lower) than the earnings yield, firms are motivated to (not) pay dividends as this reduces the cost of capital and holding other things constant, increases corporate valuations. The authors test whether managers set dividend policies to maximize the value of the firm.

Findings

The study’s findings show that when the cost of equity is higher (lower) than earnings yield, firms are more (less) likely to be dividend payers and the payouts are higher (lower). The results are robust to the inclusion of share repurchases as an alternative to cash distributions. The study’s findings support the cost of equity hypothesis and are consistent with alternative dividend theories.

Originality/value

The study’s findings support the cost of equity hypothesis and are consistent with alternative dividend theories. To the authors’ knowledge, this is the first paper testing the cost of equity hypothesis.

Details

Managerial Finance, vol. 50 no. 2
Type: Research Article
ISSN: 0307-4358

Keywords

Article
Publication date: 27 April 2023

Wanderson Ferreira dos Santos, Ayrton Ribeiro Ferreira and Sergio Persival Baroncini Proença

The present paper aims to explore a computational homogenisation procedure to investigate the full geometric representation of yield surfaces for isotropic porous ductile media…

Abstract

Purpose

The present paper aims to explore a computational homogenisation procedure to investigate the full geometric representation of yield surfaces for isotropic porous ductile media. The effects of cell morphology and imposed boundary conditions are assessed. The sensitivity of the yield surfaces to the Lode angle is also investigated in detail.

Design/methodology/approach

The microscale of the material is modelled by the concept of Representative Volume Element (RVE) or unit cell, which is numerically simulated through three-dimensional finite element analyses. Numerous loading conditions are considered to create complete yield surfaces encompassing high, intermediate and low triaxialities. The influence of cell morphology on the yield surfaces is assessed considering a spherical cell with spherical void and a cubic RVE with spherical void, both under uniform strain boundary condition. The use of spherical cell is interesting as preferential directions in the effective behaviour are avoided. The periodic boundary condition, which favours strain localization, is imposed on the cubic RVE to compare the results. Small strains are assumed and the cell matrix is considered as a perfect elasto-plastic material following the von Mises yield criterion.

Findings

Different morphologies for the cell imply in different yield conditions for the same load situations. The yield surfaces in correspondence to periodic boundary condition show significant differences compared to those obtained by imposing uniform strain boundary condition. The stress Lode angle has a strong influence on the geometry of the yield surfaces considering low and intermediate triaxialities.

Originality/value

The exhaustive computational study of the effects of cell morphologies and imposed boundary conditions fills a gap in the full representation of the flow surfaces. The homogenisation-based strategy allows us to further investigate the influence of the Lode angle on the yield surfaces.

Details

Engineering Computations, vol. 40 no. 4
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 18 January 2023

Payam Najafi, Akram Eftekhari and Alireza Sharifi

In the past three decades, remote sensing-based models for estimating crop yield have addressed critical problems of general food security, as the unavailability of grains such as…

Abstract

Purpose

In the past three decades, remote sensing-based models for estimating crop yield have addressed critical problems of general food security, as the unavailability of grains such as rice creates serious worldwide food insecurity problems. The main purpose of this study was to compare the potential of time-series Landsat-8 and Sentinel-2 data to predict rice yield several weeks before harvest on a regional scale.

Design/methodology/approach

To this end, the sum of normalized difference vegetation index (NDVI)-based models created the best agreement with actual yield data at the golden time window of six weeks before harvest when rice grains were in milky and mature growth stages. The application of nine other vegetation indicators was also investigated in the golden time window in comparison to NDVI.

Findings

The findings of this study demonstrate the viability of identifying locations with poor and superior performance in terms of production management approaches through a rapid and economical solution for early rice grain yield assessment. Results indicated that while some of those, such as enhanced vegetation index (EVI) and optimized soil adjusted vegetation index, were able to estimate rice yield with high accuracy, NDVI is still the best indicator to predict rice yield before harvest. However, experiments can be conducted in different regions in future studies to evaluate the generalizability of the approach.

Originality/value

To achieve this objective, the authors considered the following purposes: using Sentinel-2 time-series data, determining the appropriate growth stage for estimating rice yield and evaluating different vegetation indices for estimating rice yield.

Details

Aircraft Engineering and Aerospace Technology, vol. 95 no. 5
Type: Research Article
ISSN: 1748-8842

Keywords

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