Yuan feng Zhao, Zhihui Chai, Michael S Delgado and Paul V Preckel
The purpose of this paper is to assess the effect of crop insurance on farmer income in Inner Mongolia, China
Abstract
Purpose
The purpose of this paper is to assess the effect of crop insurance on farmer income in Inner Mongolia, China
Design/methodology/approach
We use a survey of farmers in Inner Mongolia, China, with difference-in-difference, propensity score matching, and hybrid propensity score matching difference-in-difference treatment effect estimators to assess the effectiveness of crop insurance on farmer income.
Findings
The empirical results show that crop insurance does not significantly affect farmer income under the current policy of “low-premium, wide-coverage, low-guarantee and low-indemnity.”
Research limitations/implications
A possible limitation of this study is that the data includes only one geographic area, Inner Mongolia, China, and so results may not generalize to other regions of China.
Practical implications
This research provides empirical estimates of the impact of crop insurance on farm household income. Given the results, we speculate that a number of specific changes to the crop insurance program might increase its positive impacts.
Originality/value
We believe this is the first study to use individual farm household level survey data to evaluate the impact of crop insurance on farmer income in China.
Donghai Wang, Wei Sun, Zhihui Gao and Hui Li
In many cases, the external pipelines of aero-engine are subjected to random excitation. The purpose of this paper is to reduce the vibration response of the pipeline system…
Abstract
Purpose
In many cases, the external pipelines of aero-engine are subjected to random excitation. The purpose of this paper is to reduce the vibration response of the pipeline system effectively by adjusting the hoop layout.
Design/methodology/approach
In this paper, a spatial pipeline supported by multi-hoops is taken as the object, the methods of solution of the vibration response of the pipeline system by using pseudo excitation and hoop layouts optimization with amplitude reduction of vibration response as the goal are presented. First, the finite element model of the spatial pipeline system is presented. Then, an optimization model spatial pipeline is established. Finally, a case study is carried out to prove the rationality of the random vibration response analysis of the pipeline system. Furthermore, the proposed optimization model and genetic algorithm are applied to optimize the hoop layout.
Findings
The results show that the maximum response variance after optimization is reduced by 32.8%, which proves the rationality of the developed hoop layout optimization method.
Originality/value
The pseudo excitation method is used to solve the vibration response of aero-engine pipeline system, and the optimization of the hoop layout for aero-engine spatial pipelines under random excitation to reduce random vibration response is studied systematically.
Details
Keywords
Wing-Keung Wong, Zhihui Lv, Christian Espinosa and João Paulo Vieito
To the best of the authors’ knowledge, this study is the first to investigate the intricate relationship between crude oil spot and futures prices, focusing on both cointegration…
Abstract
Purpose
To the best of the authors’ knowledge, this study is the first to investigate the intricate relationship between crude oil spot and futures prices, focusing on both cointegration and market efficiency during the COVID-19 pandemic, and the beginning of the Russia–Ukraine conflict. Using daily West Texas Intermediate data from January 2020 to March 2024, like Cunado and Pérez de Gracia (2003), the authors use advanced statistical methods to identify structural breaks and assess cointegration levels. Linear and nonlinear Granger causality tests are used to reveal underlying dynamics.
Design/methodology/approach
This paper uses the Lagrange Multiplier test by Arai and Kurozumi (2007) to check for cointegration with various shifts in crude oil spot and futures markets. The two-step procedure by Kejriwal and Perron (2010) and Kejriwal et al. (2022) is then applied to assess partial parameter stability in cointegration models. Efficiency is examined using both bivariate and trivariate models based on non-arbitrage and expectations hypotheses. Finally, causality is analyzed with the vector error correction model for linear Granger causality, and the tests by Bai et al. (2018) and Diks and Panchenko (2006) for nonlinear causality.
Findings
The analysis reveals that futures prices generally lead spot prices through both linear and nonlinear causality during certain periods, while only linear causality is present in others. This inconsistency suggests fluctuating market efficiency and potential arbitrage opportunities. Structural breaks indicate that the equilibrium between spot and futures prices adjusts in response to significant events like the COVID-19 pandemic and the Russia–Ukraine war. The study identifies specific periods, particularly between January 2020 and March 2024, where both linear and nonlinear forecasting between futures and spot oil prices are effective, highlighting the dynamic nature of their relationship.
Research limitations/implications
Despite extensive efforts, pinpointing the exact break date for COVID-19 remains challenging due to limitations in the data set and methodology. Additionally, the analysis of the Russia–Ukraine conflict is still ongoing. These challenges highlight the complexity of addressing structural breaks linked to unprecedented events.
Practical implications
The findings offer valuable insights for both academia and industry practitioners. The study reveals potential arbitrage opportunities stemming from inconsistent market efficiency and fluctuating causality between futures and spot prices, allowing traders to optimize their trades and timing. It also enhances risk management by identifying when linear and nonlinear causality is most effective. Policymakers can use these insights to evaluate market stability, especially during major disruptions such as the COVID-19 pandemic and geopolitical conflicts, guiding regulatory decisions. Furthermore, the study highlights the importance for investors to adjust their strategies in response to structural breaks and evolving market conditions.
Social implications
This study’s social implications are diverse, extending beyond finance and academia. It influences economic stability by revealing inefficiencies and arbitrage opportunities in crude oil markets, aiding better resource allocation. Enhanced transparency benefits stakeholders, promoting fair market practices and consumer protection. Policymakers can refine regulations based on identified structural breaks, ensuring market stability. The study indirectly impacts environmental discussions by examining crude oil’s link to global energy consumption. Financially, it guides investment strategies, influencing resource distribution and the broader economy. Additionally, its educational contribution stimulates academic discourse, fostering growth in energy economics and financial market knowledge, shaping future research.
Originality/value
The originality and value of this paper lie in its comprehensive examination of the dynamic relationship between futures and spot oil prices, particularly through both linear and nonlinear causality across different periods. By identifying and analyzing periods of both linear and nonlinear causality, the study uncovers fluctuating market efficiency and potential arbitrage opportunities that are not typically addressed in conventional analyses. Additionally, the paper’s focus on the impact of significant global events, such as the COVID-19 pandemic and the Russia–Ukraine war, on the equilibrium between spot and futures prices offers a novel perspective on how structural breaks influence market dynamics. This nuanced understanding enhances both theoretical and practical knowledge, offering valuable insights for traders, investors and policymakers to navigate and respond to evolving market conditions.