As of 26 March 2020, Pakistan had 1179 cases of COVID-19, with most 421 cases from Sindh, 394 cases, 131 cases, 123 cases, 84 cases, 25 cases and 01 cases from Punjab, Balochistan, Khyber Pakhtunkhwa, Gilgit-Baltistan, Islamabad Capital Territory, and Azad Jammu and Kashmir respectively. Travel-related cases were the main source of SARS-CoV-2 infection during the early phase of the pandemic in Pakistan. Nevertheless, cases of local virus transmission are increasing day by day. As of 26 March 2020, nine deaths have been reported from COVID-19. The case fatality rate is 0.8%, which is less compare to China, Italy, USA, and Iran. The SIR (Susceptible-Infected-Recovered) model of epidemiological analysis predicts that almost 90 million population will be infected in the coming days with 5% critical cases that need health care facilities. However, the Pakistan health care system cannot provide services to this much population. Hence, we need to act timely to reduce this number by restricting local transmission of the disease. This can be done by mass testing, quarantine, isolation and social distancing of the active coronavirus cases in Pakistan. Moreover, better communication between the authorities is very much required to control disease transmission.
Purpose: Apart from standard spheres of financial institutions’ performance such as asset quality, profitability, liquidity and efficiency; the study investigates the influence of non-financial factors such as governance and management.
Design/Methodology/Approach: This study utilizes 2009 through 2018 data for the sample of commercial banks and insurance companies of Pakistan to analyze the significance of financial and non-financial information on credit rating. The study is done by employing frequently used Fully Modified Ordinary Least Square (FMOLS).
Findings: The main contribution lies including explanatory variables from various areas that have an impact on the financial position of the examined banks and insurance companies.
Implications/Originality/Value: The obtained results suggest that the combined use of financial and non-financial information tends to a significant impact on credit rating.
Corruption is a governance dilemma in emerging market economies (EMEs) with fragile law enforcement systems. Using annual data from 1997 to 2020, this study explores corruption-growth nexus in the World's most important emerging market economies. Since it takes into account the intrinsic characteristics of each country, the panel data fixed effect estimation method appears to be the best option. The fixed effect estimation results reveal that corruption has a significantly negative impact on economic growth of the EMEs under consideration, after controlling for the government spending, investment, human capital, trade openness, and population. The random effect estimation method used as a fallback does not significantly alter the empirical findings. A noteworthy fact revealed by the pragmatic findings is that when corruption is significant, the effect of government spending on economic growth becomes negative due to embezzlement and misallocation of public coffers.
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