Journal of the American Statistical Association · 1981 · 447 citations · 35 references
Social SciencesEconomicsEconometricsLabor EconomicsTime Series AnalysisFactor AnalysisFactor ModelsState-space ModelsTime Series EconometricsTime Series ForecastingTime Series ModelingMaximum Likelihood EstimatorMultivariate State-space ModelsMultivariate Time Series ForecastingMultivariate Time Series ModelingOut-of-sample Forecast EvaluationSingle-factor ModelStatistical Time Series Models
Abstract The paper formulates and estimates a single-factor multivariate time series model. The model is a dynamic generalization of the multiple indicator (or factor analysis) model. It is shown to be a special case of the general state space model and can be estimated by maximum likelihood methods using the Kalman filter algorithm. The model is used to obtain estimates of the unobserved metropolitan wage rate for Los Angeles, based on observations of sectoral wages within the Standard Metropolitan Statistical Area. Hypothesis tests, model diagnostics, and out-of-sample forecasts are used to evaluate the model.
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