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The main goal of this study is to analyze how monetary debt effects firm behavior of 167 registered manufacturing companies in G-7 countries.

The sample of the present study is taken from the listed firms in G-7 countries. For the building companies, the yearly financial statements of 2007–2018 have been taken from world stock exchange and Thomson Reuters Data Stream. In this study, regression analysis are directed with panel data over the period of 2007–2018 using ordinary least square summary statistics, correlation matrix and generalized method moments. Data were analyzed by employing E Views and Stata 13 software.

The significant findings of the current study indicated that fixed assets, tangible assets, taxes, net cash and profitability have positive association with debt level.

The current work include only registered manufacturing firms in G-7 countries. Moreover, ownership types are not accounted for in this study.

The current analysis is an empirical investigation of antecedents of debt regarding G-7 countries with up-to-date data. Various regression inquires have been made to design the models using different measures of debt and measure of firm performance indicators. These works will assist G-7 countries firms to know the effects of identified factors on time raising debt level.

The current work has been finalized using genuine data of yearly reports and database. This study incorporated antecedents of debt, which have limited discourse in prior literature. Furthermore, this study explores the connection between debt level and firm performance of G-7 countries.

This study aims to investigate the satisfaction of farmers with the compensation policy for wildlife-caused damages and its influencing factors, analyze the current situation of satisfaction with the compensation policy among farmers, identify factors significantly affecting satisfaction, and explore ways to optimize the compensation policy and improve the satisfaction of farmers based on the effects of various influencing factors.

The Xishuangbanna National Nature Reserve in Yunnan Province, China, is selected as the research area for the study. Through field interviews, 370 valid questionnaires were collected to obtain relevant data on farmers' satisfaction with the compensation policy for wildlife-caused damages. The Oprobit model is utilized to explore the factors influencing farmer satisfaction and to analyze their underlying reasons.

The study reveals that farmers in the communities surrounding the Xishuangbanna National Nature Reserve generally experience low satisfaction with the compensation policy, particularly concerning satisfaction with compensation amounts, which tends to be dissatisfied on average. Satisfaction with the compensation policy is significantly influenced by individual characteristics and household labor structure, while the degree of human-wildlife conflict, wildlife conservation attitudes and household income structure have insignificant impact. Among individual characteristics, gender, education level, health status, and ethnicity are highly significant. In household labor structure, the number of agricultural laborers, non-agricultural laborers, and household agricultural labor time are highly significant.

Building on the overall satisfaction of farmers with the compensation policy, this study further decomposes policy satisfaction into satisfaction with compensation amounts, coverage, and procedures. It provides more targeted recommendations for enhancing satisfaction with the compensation policy, which can help effectively mitigate human-wildlife conflicts and achieve harmonious coexistence between humans and nature.