Systemic banking panics, liquidity risk, and monetary policy

2019 ◽  
Vol 34 ◽  
pp. 20-42 ◽  
Author(s):  
Roberto Robatto
Keyword(s):  
Monetary Policy ◽  
Liquidity Risk ◽  
Banking Panics

DID THE FED RESPOND TO LIQUIDITY SHORTAGE EPISODES DURING THE GREAT DEPRESSION?

2018 ◽  
Vol 22 (7) ◽  
pp. 1727-1749 ◽  
Author(s):  
Olivier Damette ◽  
Antoine Parent
Keyword(s):  
New York ◽  
Monetary Policy ◽  
Great Depression ◽  
Liquidity Risk ◽  
Conventional Wisdom ◽  
Credit Spreads ◽  
Open Market ◽  
The Great Depression ◽  
Econometric Evidence ◽  
Open Markets

The October 1929 crash led to a complete freeze of New York open markets. Studying the Fed monetary policy conduct in a nonlinear framework, using credit spreads between open market rates and the Fed's instrument rates as a proxy for liquidity risk, we present econometric evidence that the Fed was well aware of such risks as early as 1930, reacted to the financial stress and altered its monetary policy in consequence. Our outcomes revisit conventional wisdom about the presumed passivity of the Fed throughout the 30s.

Housing, liquidity risk, and monetary policy

2019 ◽  
Vol 60 ◽  
pp. 138-162 ◽  
Author(s):  
Robert R. Reed ◽  
Ejindu S. Ume
Keyword(s):  
Monetary Policy ◽  
Liquidity Risk

scholarly journals Unconventional Monetary Policy and Funding Liquidity Risk

2020 ◽  
Author(s):  
Adrien d'Avernas ◽  
Quentin Vandeweyer ◽  
Matthieu Darracq Paries
Keyword(s):  
Monetary Policy ◽  
Liquidity Risk ◽  
Unconventional Monetary Policy ◽  
Funding Liquidity

scholarly journals The Impact of Macroeconomic Factors on Banks Liquidity Risk: Evidence From Pakistan

2021 ◽  
Vol 5 (2) ◽  
pp. 155-163
Author(s):  
Muhammad Yar Khan ◽  
Javaria Liaqat ◽  
Tahira Awan ◽  
Wajid Khan
Keyword(s):  
Economic Growth ◽  
Monetary Policy ◽  
Random Effect ◽  
Liquidity Risk ◽  
Price Inflation ◽  
Macroeconomic Factors ◽  
Fdi Inflows ◽  
Effect Regression ◽  
Time Invariant ◽  
The Impact

The aim of the study is to identify the factors that influence liquidity risks of the banks by considering the panel of 18 top listed banks in Pakistan during a period of 2010 -2016. The study employed panel random effect regression model to absorb time-invariant shocks, which gives robust inferences. The results of liquidity risk confirmed that the country’s economic growth and price inflation further escalates liquidly risk while, FDI inflows reduces liquidity risks in Pakistani’s banks, thus it is concluded that bank’s liquidity risks required easy monetary policy to advancing loans and charging low interest rate, which ultimately will increase ROA, and ROE, while it would helpful to decrease high risk of bank’s liquidly in a given country.

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