scholarly journals A Time-Varying Approach of the US Welfare Cost of Inflation

2014 ◽  
Author(s):  
Stephen M. Miller ◽  
Luis Filipe Martins ◽  
Rangan Gupta
2017 ◽  
Vol 23 (2) ◽  
pp. 775-797 ◽  
Author(s):  
Stephen M. Miller ◽  
Luis Filipe Martins ◽  
Rangan Gupta

Money-demand specifications exhibit instability, especially for long spans of data. This paper reconsiders the welfare cost of inflation for the US economy using a flexible time-varying (TV) cointegration methodology to estimate the money-demand function. We find evidence that the TV cointegration estimation provides a better fit of the actual data than a time-invariant estimation and that the throughout unitary income elasticity only exists for the log–log form over the entire sample period. Our estimate of the welfare cost of inflation for a 10% inflation rate lies in the range of 0.025–0.75% of gross domestic product (GDP) and averages 0.27%. In sum, our findings fall well within the ranges of existing studies of the welfare cost of inflation. We find that the welfare cost averages 7.4% higher during expansions than recessions for 10% inflation rate. Finally, the interest elasticity of money demand shows substantial variability over our sample period.


2019 ◽  
Vol 23 (1) ◽  
pp. 137-160
Author(s):  
Eduardo Lima Campos ◽  
Rubens Penha Cysne

This paper compares the time-varying cointegration and the Kalman filter techniques to estimate the Brazilian money demand between 1996 and 2015. The estimation using Kalman filtering performs better and is subsequently used to calculate the welfare cost of inflation. Taking into consideration the time variability of the interest-rate elasticity during the period, the average welfare cost amounts to 0.24% of the GDP, for an average annual inflation of 6.63%.


2021 ◽  
Vol 14 (1) ◽  
pp. 21
Author(s):  
Mariagrazia Fallanca ◽  
Antonio Fabio Forgione ◽  
Edoardo Otranto

Several studies have explored the linkage between non-performing loans and major macroeconomic indicators, using a wide variety of methodologies, sometimes with different results. This occurs, we argue, because these relationships are generally derived in terms of correlation coefficients evaluated in certain time spans, which represent a sort of average level of correlations. However, such correlations are necessarily time-varying, because the relationships between bank loan indicators and macroeconomic variables could be stronger during particular periods or in correspondence with important economic events. We propose an empirical exercise using dynamic conditional correlation models, with constant and time-varying parameters. Applying these models to quarterly delinquency rates and an array of macroeconomic variables for the US, for the period 1985–2019, we find that the correlation is often negligible in this period except during periods of economic crises, in particular the early 1990 crisis and the subprime mortgage crisis.


2018 ◽  
Vol 58 (5) ◽  
pp. 2249-2285 ◽  
Author(s):  
Vasilios Plakandaras ◽  
Rangan Gupta ◽  
Constantinos Katrakilidis ◽  
Mark E. Wohar

2008 ◽  
Vol 40 (18) ◽  
pp. 2353-2360 ◽  
Author(s):  
Florian Höppner ◽  
Christian Melzer ◽  
Thorsten Neumann

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