Determination and Measurement of the Index of Total Monetary Assets Services in Iran

Erfani, Alireza; Davoudi, Parviz; Sabahi, Ahmad; Sadeqi, Farzaneh

doi:10.22055/jqe.2018.23993.1766

Determination and Measurement of the Index of Total Monetary Assets Services in Iran

https://doi.org/10.22055/jqe.2018.23993.1766

Volume 15, Issue 2 - Serial Number 57

Vol. 15, No. 2, Summer 2018

Summer 2018

Pages 131-156

Quarterly Journal of Quantitative Economics (JQE)

Document Type : Research Paper

Authors

Alireza Erfani ¹

parviz Davoudi ²

Ahmad Sabahi ³

Farzaneh Sadeqi ⁴

¹ Department of economic and management, Semnan University, Semnan, Iran

² Shahid Beheshti University, Tehran, Iran

³ Faculty of Economics and Business Administration Ferdowsi University Of Mashhad (FUM), Mashhad, Iran

⁴ Semnan university

Abstract

This paper provides a new formula for aggregating monetary assets of consumers, firms, public enterprise and government, in line with Barnett's (1984) model that used two agents: consumers and firms. The Bamol sales revenue maximization model has been used to model public enterprise. By solving the model, the user cost of the monetary assets services demanded by public enterprise is completely different from the Barnett formula for his agents. Since the government's monetary assets provide the same services, in fact, these assets are complete substitutes and simple sum aggregation can be used to aggregate these assets. In order to investigate the new aggregation formula achieved from the research, we used quarterly data of 1991Q1-2011Q4 for estimating and forecasting GDP and consumer price index in the period of 2012Q1-2016Q4. According to the results, for the consumer price index, the new aggregation has lower error rates and, therefore, higher predictive power than the simple sum aggregation in both M1 and M2. In the prediction of GDP, this aggregation at M1 level is better than simple sum, although at M2 level, with a very small difference in prediction error, simple sum aggregation performance is better. However, it can be argued that to predict the future trend of prices and production, in order to control and direct the government's monetary and fiscal policies, calculating the volume of liquidity by using the new aggregation has preferences over the simple sum aggregation.

Keywords

Monetary aggregation

Index Numbers Approach

Public enterprise

ability of forecasting

Bamoul Sales model

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