索马里农业投资的决定因素:var模型的应用

Q2 Economics, Econometrics and Finance
A. Nur
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引用次数: 0

摘要

本研究的主要目的是利用2015年至2021年的季度时间序列数据,研究索马里农业投资的决定因素。本研究选取融资资产(FA)、农业产出(FO)、商业银行信贷(CCB)和储蓄(S)作为宏观经济变量。采用增强Dickey-Fuller (ADF)检验评价变量的平稳性,采用格兰杰因果检验评价研究变量之间的因果关系。结果发现,所有变量在第二个差值处都是平稳的,在1%、5%和10%的三个临界水平上都有一个趋势。格兰杰因果检验表明,索马里农业投资、农业产出、商业银行金融资产、商业银行储蓄和商业银行贷款之间存在单向因果关系。向量自回归(VAR)估计表明,决定系数解释了98%的模型,普通最小二乘(OLS)估计显示出高度显著的p值。结果表明,如果有效和高效地管理,融资资产和储蓄将增加农业产量。根据调查结果,该研究建议政府将重点放在索马里的整体制度框架上,以促进经济增长、减少贫困和可持续发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Determinants of farm investment in Somalia: A var model application
The main objective of this study is to examine the determinants of farm investment in Somalia using quarterly time-series data from 2015 to 2021. The study selected financing assets (FA), farm output (FO), credit for commercial banks (CCB), and saving (S) as macroeconomic variables. The augmented Dickey–Fuller (ADF) test was employed to evaluate the stationarity of the variables, and the Granger causality test was used to assess the causal relationship between the study variables. It was found that all variables became stationary at the second difference, with a trend for each of the three critical levels of 1%, 5%, and 10%. The Granger causality test indicates a unidirectional causal connection between farm investment, farm output, financial assets for commercial banks, savings for commercial banks, and loans for commercial banks in Somalia. The vector autoregressive (VAR) estimation revealed that the coefficient of determination explains 98% of the model, and the ordinary least squares (OLS) estimation showed a highly significant P-value. The results show that financing assets and savings will increase farm output if managed effectively and efficiently. Based on the findings, the study recommends that the government focus on the overall institutional framework in Somalia to facilitate economic growth, poverty reduction, and sustainable development.
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来源期刊
Asian Economic and Financial Review
Asian Economic and Financial Review Economics, Econometrics and Finance-Economics, Econometrics and Finance (all)
CiteScore
1.80
自引率
0.00%
发文量
64
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