1999Journal of Economic and Social MeasurementRequires access

An application of the Stock/Watson index methodology to the Massachusetts economy

Alan Clayton-Matthews, James H. Stock

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Abstract

The Stock/Watson index methodology is applied to the Massachusetts economy to estimate coincident and leading indexes for the state. A coincident index, calibrated to trend with gross state product, is estimated as a dynamic single factor, multiple indicator model, using the Kalman filter and smoother on a set of coincident indicators. The leading index is a six-month ahead forecast of the coincident index, based on a regression on recent growth in the coincident index and a set of leading indicators. Filtering of noisy data and model selection in the context of a short historical span of data are two issues common to index construction at the state and regional levels that the authors address.

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What this paper is about

The Stock/Watson index methodology is applied to the Massachusetts economy to estimate coincident and leading indexes for the state. A coincident index, calibrated to trend with gross state product, is estimated as a dynamic single factor, multiple indicator model, using the Kalman filter and smoother on a set of coincident indicators. The leading index is a six-month ahead forecast of the coincident index, based on a regression on recent growth in the coincident index and a set of leading indicators. Filtering of noisy data and model selection in the context of a short historical span of data are two issues common to index construction at the state and regional levels that the authors address.

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Available abstract

The Stock/Watson index methodology is applied to the Massachusetts economy to estimate coincident and leading indexes for the state. A coincident index, calibrated to trend with gross state product, is estimated as a dynamic single factor, multiple indicator model, using the Kalman filter and smoother on a set of coincident indicators. The leading index is a six-month ahead forecast of the coincident index, based on a regression on recent growth in the coincident index and a set of leading indicators. Filtering of noisy data and model selection in the context of a short historical span of data are two issues common to index construction at the state and regional levels that the authors address.

Key concepts: Index (typography), Kalman filter, Econometrics, Stock (firearms), Economic indicator, Context (archaeology), Hodrick–Prescott filter, Gross domestic product

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