Methods

Suppose a vector autoregressive moving-average model is estimated for m observed variables of primary interest for an appli-cation and n–m observed secondary variables to aid in the application. An application indicates the variables of primary interest but usually only broadly suggests secondary variables that may or may not be useful. Often, one has many potential sec-ondary variables to choose from but is unsure which ones to include in or exclude from the application. The article proposes a method called weighted-covariance factor decomposition (WCFD), comparable to Stock and Watson’s method here called principle-components factor decomposition (PCFD), for reducing the secondary variables to fewer factors to obtain a parsi-monious estimated model that is more effective in an application. The WCFD method is illustrated in the article by forecasting quarterly observed U.S. real GDP at monthly intervals using monthly observed four coincident and eight leading indicators from the Conference Board (http://www.conference-board.org). The results show that root mean-squared errors of GDP fore-casts of PCFD-factor models are 0.9–11.3% higher than those of WCFD-factor models especially as estimation-forecasting periods pass from the pre-2007 Great Moderation through the 2007–2009 Great Recession to the 2009–2016 Slow Recovery.

This paper reviews the efforts of the Bureau of Economic Analysis (BEA) to measure international services categorized by mode of supply. BEA has adopted a survey form that uses an innovative approach to collect information on mode of supply by simply having companies report the percentage of its services supplied through one mode as opposed to all modes, with the idea that the other modes can be estimated as a residual or using other data sources. Of the few previous efforts by countries to measure trade by mode of supply, most are based on assumptions about industry practices or on surveys that simply asked for the predominant mode of supply rather than a more precise percentage supplied by mode. BEA also uses a pioneering method to measure services supplied through affiliates across service types by mapping its comprehensive industry-based foreign affiliate statistics to its product-based trade statistics. The estimates also include a breakdown of the mode where consumers obtain the service outside their home territory, such as services received when traveling abroad, that more closely corresponds with guidelines set out in the General Agreement on Trade in Services than most previous efforts.

Developing a national account-based measure of the distribution of income from the commonly used Census based concept of money income has been the subject of earlier research. We use publicly available survey and administrative data to construct a distribution of personal income after enhancing the top income distribution in the Current Population Survey (2007 and 2012). We show that inequality measures are fairly sensitive to the definition of income contemporaneously and across time. This work helps bridge the gap between micro data and macro statistics and informs about results from other studies, such as Piketty et al. (2018).