An Introduction to Time Series Modeling and Forecasting

Abstract

Listen

Translate article

An important aspect of financial decision making may depend on the forecasting effectiveness of the composite index of leading economic indicators, LEI. The leading indicators can be used as an input to a transfer function model of real Gross Domestic Product, GDP. The previous chapter employed four quarterly lags of the LEI series to estimate regression models of association between current rates of growth of real US GDP and the composite index of LEI. This chapter asks the question as to whether changes in forecasted economic indexes help forecast changes in real economic growth. The transfer function model forecasts are compared to several naive models in terms of testing which model produces the most accurate forecast of real GDP. No-change (NoCH) forecasts of real GDP and random walk with drift (RWD) models may be useful forecasting benchmarks (Mincer and Zarnowitz 1969; Granger and Newbold 1977). Economists have constructed LEI series to serve as a business barometer of the changing US economy since the time of Mitchell (1913). The purpose of this study is to examine the time series forecasts of composite economic indexes produced by The Conference Board (TCB), and test the hypothesis that the leading indicators are useful as an input to a time series model to forecast real output in the United States.