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Working Paper
Metro Business Cycles
We construct monthly economic activity indices for the 50 largest U.S. metropolitan statistical areas (MSAs) beginning in 1990. Each index is derived from a dynamic factor model based on twelve underlying variables capturing various aspects of metro area economic activity. To accommodate mixed-frequency data and differences in data-publication lags, we estimate the dynamic factor model using a maximum- likelihood approach that allows for arbitrary patterns of missing data. Our indices highlight important similarities and differences in business cycles across MSAs. While a number of MSAs ...
Working Paper
Modeling anchoring effects in sequential Likert scale questions
Surveys in many different research fields rely on sequences of Likert scale questions to assess individuals' general attitudes toward a set of related topics. Most analyses of responses to such a series do not take into account the potential measurement error introduced by the context effect we dub "sequential anchoring," which occurs when the rating for one question influences the rating given to the following question by favoring similar ratings. The presence of sequential anchoring can cause systematic bias in the study of relative ratings. We develop a latent-variable framework for ...
Working Paper
Common Factors, Trends, and Cycles in Large Datasets
This paper considers a non-stationary dynamic factor model for large datasets to disentangle long-run from short-run co-movements. We first propose a new Quasi Maximum Likelihood estimator of the model based on the Kalman Smoother and the Expectation Maximisation algorithm. The asymptotic properties of the estimator are discussed. Then, we show how to separate trends and cycles in the factors by mean of eigenanalysis of the estimated non-stationary factors. Finally, we employ our methodology on a panel of US quarterly macroeconomic indicators to estimate aggregate real output, or Gross ...