scholarly journals The Impact of Macroprudential Policies on the Vulnerability of the Banking System: Dynamic Panel Model

2020 ◽  
Vol 15 (4) ◽  
pp. 357-379
Author(s):  
Nafiseh Keshtgar ◽  
◽  
Mosayeb Pahlavani ◽  
Seyed Hossein Mirjalili ◽  
◽  
...  
Keyword(s):  
Banking System ◽  
System Dynamic ◽  
Dynamic Panel ◽  
Dynamic Panel Model ◽  
Macroprudential Policies ◽  
Panel Model ◽  
The Impact

scholarly journals Does Bank Competition Enhance or Hinder Financial Stability? Evidence from Indian Banking

2020 ◽  
Vol 9 (s1) ◽  
pp. 75-102
Author(s):  
Bijoy Rakshit ◽  
Samaresh Bardhan
Keyword(s):  
Commercial Banks ◽  
Financial Stability ◽  
Positive Impact ◽  
Banking System ◽  
Bank Competition ◽  
Z Score ◽  
Dynamic Panel ◽  
Dynamic Panel Model ◽  
Panel Model ◽  
The Impact

AbstractThe primary purpose of this paper is to empirically investigate the impact of bank competition on financial stability in India. We use a dynamic panel model to examine whether an increase in bank competition hindrances financial stability of commercial banks in India over the period 1996 to 2016. Findings reveal that in India, a higher degree of bank competition is positively associated with the prevalence of non-performing loans. Additionally, the positive impact of the Lerner index on Z-score lends support to competition-fragility hypothesis. However, we argue that both the views of competition-stability and competition-fragility can coexist in a single banking system like India.

scholarly journals The Influence of Urban Haze Pollution on Urban Shrinkage in China – An Analysis of the Mediating Effect of the Labour Supply

2021 ◽  
Author(s):  
Xiaohong Liu
Keyword(s):  
Panel Data ◽  
Labour Supply ◽  
Mediating Effect ◽  
Dynamic Panel ◽  
Dynamic Panel Model ◽  
Panel Model ◽  
Influence Mechanism ◽  
Effect Model ◽  
Haze Pollution ◽  
The Impact

Abstract Panel data of 234 cities in China from 2011 to 2018 is used to measure the urban shrinkage index. PM2.5 is used as an indicator of haze pollution, and labour supply is the mediator. On this basis, the influence mechanism of haze pollution on urban shrinkage is analysed theoretically. Next, using the dynamic panel model and the mediating effect model, we empirically examine the impact of urban shrinkage on haze pollution and the mediating effect of labour supply. The main findings are as follows: haze pollution increases the degree of urban shrinkage, and labour supply plays a regulatory role in the process of haze pollution affecting urban shrinkage. According to our research, pertinent policies and suggestions are proposed to reduce both urban shrinkage and haze pollution.

scholarly journals Economic Diversity and the Resource Curse: A Dynamic Panel Model

2018 ◽  
Author(s):  
Fred Olayele ◽  
Kwok Soo
Keyword(s):  
Economic Growth ◽  
Resource Curse ◽  
Dynamic Panel Data ◽  
Policy Implications ◽  
Panel Data Models ◽  
Dynamic Panel ◽  
Dynamic Panel Model ◽  
Economic Diversity ◽  
Panel Model ◽  
The Impact

This paper contributes to the debate on the impact of economic diversity and the resource curse on economic growth. We use dynamic panel data models on data on Canadian and US sub-national jurisdictions. We find evidence for a positive relationship between diversity and growth. Based on the Krugman Specialization Index, our analysis shows that the required threshold for not having the resource curse is 0.209. Above this threshold, the marginal contribution of natural resources to economic growth is lower for a more diversified regional economy than a less diversified one. We highlight the policy implications of these findings.

scholarly journals Regional differences in the capitalisation of first and second pillar payments of the CAP into land rental prices

2020 ◽  
Author(s):  
Klaus Salhofer ◽  
Paul Feichtinger
Keyword(s):  
Agricultural Policy ◽  
Regional Differences ◽  
Dynamic Panel ◽  
Accounting Data ◽  
Dynamic Panel Model ◽  
Panel Model ◽  
Land Rental ◽  
Part Time ◽  
High Yields ◽  
Large Farms

Abstract Nearly 80 per cent of Common Agricultural Policy (CAP) expenditures are spent on three different measures: first pillar payments (FPPs), agri-environmental payments (AEPs) and less favoured area payments (LFAPs). Based on a dynamic panel model and farm accounting data for Bavaria, we find that, on average, 30 per cent of FPPs, 40–50 per cent of LFAPs, but no relevant share of AEPs are capitalised into land rental prices. The capitalisation ratio varies considerably across regions. Above average capitalisation ratios for FPPs are observed in more favourable areas with high yields, a low grassland share and large farms. The same is true for LFAPs for areas with high yields, large farms and a greater share of part-time farmers.

scholarly journals DEMOGRAPHIC BONUS ANALYSIS AND ECONOMIC GROWTH OF EAST JAVA

2018 ◽  
Vol 2 (1) ◽  
pp. 8-21
Author(s):  
Amirusholihin ◽  
Listiono
Keyword(s):  
Negative Impact ◽  
Positive Impact ◽  
Demographic Variables ◽  
Spatial Inequality ◽  
Solow Model ◽  
Dynamic Panel Model ◽  
Goods And Services ◽  
Panel Model ◽  
Working Age ◽  
The Impact

BKKBN predicts that Indonesia will get demographic bonus in 2020 until 2030. The question is whether the demographic bonus has a positive impact on the economy of East Java or even a negative impact. Based on data from BPS, by 2015 the workingage population in East Java is around 69.4 percent of the total population, while the child and old-age is 30.6 percent. The size of the working-age population is closely related to the amount of labor, which also greatly determines the amount of output on goods and services produced. This paper aims to explain how the impact of demographic bonuses on East Java's regional economy, based on the Solow model extended to include demographic variables. The analysis uses a dynamic panel model by 38 districts in East Java that have demographic bonuses in 2020 with GDP as a reference in determining the growth of economists. From these analyzes it can be seen the impact of demographic bonuses in East Java as an advantage or even create new spatial inequality between regions.

scholarly journals X-Differencing and Dynamic Panel Model Estimation

2010 ◽  
Author(s):  
Chirok Han ◽  
Peter C. B. Phillips ◽  
Donggyu Sul
Keyword(s):  
Model Estimation ◽  
Dynamic Panel ◽  
Dynamic Panel Model ◽  
Panel Model
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