Manuel PPdagogique En Panels Dynamiques Non Stationnaires: Application sur Stata et Eviews (Textbook on Non-Stationary Dynamic Panel: Application on STATA and Eviews)

2012 ◽  
Author(s):  
Mariam Djelassi
Keyword(s):  
2021 ◽  
pp. 009365022199149
Author(s):  
Shan Xu ◽  
Zheng Wang

This study integrates the theory of multiple selves within the theoretical framework of dynamic motivational activation (DMA) to identify the dynamic patterns of multiple self-concepts (i.e., the potential self, the actual self) in multitasking (e.g., primary and secondary activities) in daily life. A three-week experience sampling study was conducted on college students. Dynamic panel modeling results suggest that the self-concepts are both sustaining and shifting in daily activities and media activities. Specifically, the potential and actual selves sustained themselves over time in primary and secondary activities, but they also shifted from one to another to achieve a balance in primary activities over time. Interestingly, secondary activities were not driven by the alternative self-concept in primary activities, but instead, by the emotional experiences of primary activities. Furthermore, the findings identified that multitasking to fulfill their actual self did not motivate people to re-prioritize their potential self later.


2021 ◽  
Vol 40 (7) ◽  
pp. 607-634
Author(s):  
Moonhee Cho ◽  
Xiaoyong Zheng

2021 ◽  
pp. 097215092098030
Author(s):  
Richa Verma Bajaj ◽  
Gargi Sanati ◽  
Chetan Lodha

Our study significantly contributes in understanding a comparative framework and the interactions of idiosyncratic and systematic factors for determining non-performing assets (NPA) and rate of recovery for banks in India, as put forward by Basel committee. Although determinants of NPA is very well debated issue, the comparison of public and private sector banks in terms of their assets quality i.e. NPAs and rate of recovery and their determinants like collateral, operational inefficiency, GDP growth rate etc. are the added contribition of this study. We have employed Arrelano–Bond dynamic panel method on 35 banks in India for the period 1998–1999 to 2017–2018 for determinants of NPAs, while determinants of rate of recovery are studied for the period 2003–2004 to 2017–2018. Our findings show that the priority sector loan has significant differences in determining NPA across banks despite them having sufficient collateral. The negative relationship between collateral and recovery, especially for private sector banks, signifies low recovery for illliquid collateral. This study may recommend that a bank with high net interest margin (NIM), high proportion of secured and liquid collateral, and sufficient mix of long- and short-duration loans in line with bank’s asset liability policy can manage their portfolio well.


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