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Essays on Economic Signals with Credit-Card-Augmented Divisia Monetary Aggregates
Park, Sohee
Park, Sohee
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Abstract
When the economy encounters unforeseen economic events such as the pandemic or the GreatRecession, volatile macroeconomic variables are the issue. Especially during the pandemic, the economy has faced high inflation pressure. Therefore, the prediction ability is getting more crucial at this time and I predict macroeconomic variables in many different ways. Moreover, the share of payment instrument usage of the credit card is getting bigger. There is a new idea, credit-card-augmented Divisia monetary aggregates which include the amount of credit card transactions volume in money measure. The purpose of my dissertation is to examine the performance of the prediction ability of the credit-card-augmented Divisia for various macroeconomic variables. I find the better research method to make more accurate predictions of macroeconomic variables such as inflation and GDP. My dissertation consists of four chapters: The study of the new monetary aggregates, Divisia monetary aggregates, is continually being developed. While simple sum measures have the same weight for each monetary asset, Divisia monetary aggregates impute different component expenditure shares with user cost pricing and reflect the real world. First chapter in this dissertation “Development of Divisia Monetary Aggregates and Its Applications" is the literature survey of the Divisia monetary aggregates that are prefered to the simple sum in much economic research since monetary components are not perfect substitutes. We introduce and organize various literature about the traditional Divisia, credit-card-augmented Divisia, and credit-card-augmented Divisia inside money. Second chapter “Forecasting Inflation and Output Growth with Credit-Card-Augmented Divisia Monetary Aggregates" 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. Third chapter “Welfare Cost of Inflation with Credit Card Transactions in Money Measures" investigates the welfare costs that occurred by anticipated inflation when we add the volume of credit card transactions to the measurement of money. First, we use the concept of credit-card-augmented Divisia in the dynamic stochastic general equilibrium (DSGE) model and calculate the welfare costs of inflation. This paper assumes money yields utility in the money-in-the-utility function of Sidrauski (1967). This paper also empirically examines the welfare costs of inflation in the U.S. by deriving the inverse money demand functions with the consumer surplus approach using the Divisia indices from the Center for Financial Stability (CFS). The welfare costs of inflation with credit card services are lower than those with no credit card services in the New Keynesian model. With the empirical method, we see more sensitive changes in the welfare cost of inflation with broad money and the monetary aggregation containing the credit card transactions volume when the inflation target changes. Last chapter is “The Role of Broad Money: Tracking Economic Signals." Fed discontinued announcing broader monetary aggregate. For example, M3 was discontinued to publish in 2006 and only M3 data set borrowed from OECD has been displayed. Moreover, we cannot track M4 data series in FRED anymore. Although the importance of monetary aggregate is increasing (as a tool of understanding monetary transmission mechanism), researchers cannot approach a reliable data set. As we see in the Divisia data provided by the Center for Financial Stability (CFS), many economic events can be tracked by the broader money rather than the narrow money. Clearly, there would be an economic implication provided by the broader monetary aggregate. The purpose of this paper is to examine the availability of Divisia-type monetary aggregates for all ranges by conducting several tests. Following the philosophy of Bernanke and Blinder (1992) and Belongia and Ireland (2015), we test the causal relationship between real economic variables and monetary aggregates. We also set up a basic recursive VAR and Leeper-Roush type (2003) non-recursive VAR model, and study the economic implications given by the results.
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Date
2022-08-31
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University of Kansas
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Keywords
Economics, Applied Econometrics, Divisia, Macroeconomics, Monetary Economics, Time Series Analysis