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

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  • Stephen M. Miller

    (University of Nevada, Las Vegas and University of Connecticut)

  • Luis F. Martins

    (ISCTE-IUL)

  • Rangan Gupta

    (University of Pretoria)

Abstract

Money demand specifications exhibits instability, especially for long spans of data. This paper reconsiders the welfare cost of inflation for the US economy using a flexible time-varying cointegration methodology to estimate the money demand function. We find evidence that the time-varying 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-percent inflation rate lies in the range of 0.025 to 0.75 percent of GDP and averages 0.27 percent. When we plug in the actual inflation rate series over the sample period, we find that the welfare cost of inflation lies in the range of 0.009 to 0.33 percent of GDP. In sum, our findings fall well within the ranges of existing studies of the welfare cost of inflation. Finally, the interest elasticity of money demand shows substantial variability over our sample period.

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Bibliographic Info

Paper provided by University of Connecticut, Department of Economics in its series Working papers with number 2014-11.

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Length: 32 pages
Date of creation: May 2014
Date of revision:
Handle: RePEc:uct:uconnp:2014-11

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Keywords: Money Demand Function; Welfare cost of inflation; Time-varying cointegration;

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  2. Furkan Emirmahmutoglu & Nicholas Apergis & Beatrice D. Simo-Kengne & Tsangyao Chang & Rangan Gupta, 2014. "Causal relationship between asset prices and output in the US: Evidence from state-level panel Granger causality test," Working Papers 201411, University of Pretoria, Department of Economics.
  3. Rangan Gupta & Lardo Stander, 2014. "Endogenous Fluctuations in an Endogenous Growth Model with Ination Targeting," Working Papers 2014-461, Department of Research, Ipag Business School.
  4. Essahbi Essaadi & Zied Ftiti, 2008. "The inflation Targeting effect on the inflation series: ANew Analysis Approach of evolutionary spectral analysis," Post-Print halshs-00355637, HAL.
  5. Wendy Nyakabawo & Stephen M. Miller & Mehmet Balcilar & Sonali Das & Rangan Gupta, 2013. "Temporal Causality between House Prices and Output in the U. S.: A Bootstrap Rolling-Window Approach," Working Papers 201329, University of Pretoria, Department of Economics.
  6. Beatrice D. Simo-Kengne & Stephen M. Miller & Rangan Gupta, 2013. "Evolution of Monetary Policy in the US: The Role of Asset Prices," Working Papers 201343, University of Pretoria, Department of Economics.
  7. Rangan Gupta & Patrick T. Kanda & Mampho P. Modise & Alessia Paccagnini, 2014. "DSGE Model-Based Forecasting of Modeled and Non-Modeled Ination Variables in South Africa," Working Papers 2014-562, Department of Research, Ipag Business School.
  8. Pejman Bahramian & Mehmet Balcilar & Rangan Gupta & Patrick T. Kanda, 2014. "Forecasting South African Ination Using Non-linear Models: A Weighted Loss-based Evaluation," Working Papers 2014-471, Department of Research, Ipag Business School.
  9. Mohamed Arouri & Shawkat Hammoudeh & Fredj Jawadi & Duc Khuong Nguyen, 2014. "Financial Linkages between U.S. Sector Credit Default Swaps Markets," Working Papers 2014-553, Department of Research, Ipag Business School.
  10. Frederic Teulon, 2014. "A la recherche de Maurice Allais," Working Papers 2014-548, Department of Research, Ipag Business School.
  11. Goodness C. Aye & Rangan Gupta & Stephen M. Miller & Mehmet Balcilar, 2014. "Forecasting US Real Private Residential Fixed Investment Using a Large Number of Predictors," Working papers, University of Connecticut, Department of Economics 2014-10, University of Connecticut, Department of Economics.

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