Forecasting Inflation and Output Growth with Credit-Card-Augmented Divisia Monetary Aggregates

William Barnett and Sohee Park

MPRA Paper from University Library of Munich, Germany

Abstract: This paper investigates the performance of the Credit-Card-Augmented Divisia monetary aggregates in forecasting U.S. inflation and output growth at the 12-month horizon. We compute recursive and rolling out-of-sample forecasts using an Autoregressive Distributed Lag (ADL) model based on Divisia monetary aggregates. We use the three available versions of those monetary aggregate indices, including the original Divisia aggregates, the credit card-augmented Divisia, and the credit-card-augmented Divisia inside money aggregates. The source of each is the Center for Financial Stability (CFS). We find that the smallest Root Mean Square Forecast Errors (RMSFE) are attained with the credit-card-augmented Divisia indices used as the forecast indicators. We also consider Bayesian vector autoregression (BVAR) for forecasting annual inflation and output growth.

Keywords: Divisia; credit-card-augmented Divisia; monetary aggregates; forecasting; Bayesian vector autoregression; inflation; output growth. (search for similar items in EconPapers)
JEL-codes: C32 C53 E31 E47 E51 (search for similar items in EconPapers)
Date: 2021-10-19
New Economics Papers: this item is included in nep-ban, nep-for, nep-mac, nep-mon and nep-pay
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Related works:
Journal Article: Forecasting inflation and output growth with credit‐card‐augmented Divisia monetary aggregates (2023)
Working Paper: Forecasting Inflation and Output Growth with Credit-Card-Augmented Divisia Monetary Aggregates (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:110298

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