Identifying inter-seasonal drought characteristics using binary outcome panel data models. Issue 1 (31st December 2023)

• Record Type: Journal Article
• Authors: Niaz, Rizwan; Hussain, Anwar; Almazah, Mohammed M. A.; Hussain, Ijaz; Ali, Zulfiqar; Al-Rezami, A. Y.
• Is Part Of: Geocarto international. Volume 38:Issue 1(2023)
• Publication Date: 2023-12-31
• Subjects: Standardized drought indices -- meteorological drought -- drought persistence -- Conditional Fixed Effect Logistic Regression Model -- random effect logistics model; Remote sensing -- Periodicals; Geographic information systems -- Periodicals; Geology -- Periodicals; Cartography -- Periodicals; 621.3678
• DOI: 10.1080/10106049.2023.2178527
• Languages: English
• ISSNs: 1010-6049

Abstract

Abstract: This study mainly focuses on spatiotemporal and inter-seasonal meteorological drought characteristics. Random Effect Logistic Regression Model (RELRM) and Conditional Fixed Effect Logistic Regression Model (CFELRM) are used to identify the spatiotemporal and inter-seasonal characteristics of meteorological drought in selected stations. The log-likelihood Ratio Chi-Square (LRCST) and Wald chi-square tests (WCTs) are used to assess the significance of RELRM and CFELRM. The Hausman test (HT) is applied to select the appropriate model between RELRM and CFELRM. For instance, HT suggests the CFELRM as an appropriate model in spring-to-summer spatiotemporal drought modelling. The significant coefficient from CFELRM indicates that an increment in moisture conditions of the spring season will decrease the probability of drought in the summer. The odds ratio of 0.1942 means that 19.42% chance of being in a higher category. Similarly, in summer-to-autumn using RELRM the computed odds ratio of 0.0673 shows that 6.73% chance of being in a higher category.