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Coherent Trends, Turning Points, and Forecasts for ACS Data

Tucker McElroy

KEY WORDS: Filtering, Frequency Domain, Nonstationary time series.

ABSTRACT

The American Community Survey (ACS) provides one-year (1y), three-year (3y), and five- year (5y) multi-year estimates (MYEs) of various demographic and economic variables for each \community," although for small communities the 1y and 3y may not be available. These survey estimates are not truly measuring the same quantities, since they each cover different time spans. We present a metric to measure the compatibility of different MYEs; for those that are deemed to be sufficiently compatible, we describe methods for generating trends, turning points, and forecasts of ACS data at 1y, 3y, and 5y intervals, in such a way that the different estimates can be compared with one another. The filters utilized are non-model-based, require only a short span of data, and are designed to preserve the appropriate linear characteristics of the time series that are relevant for trends, turning points, and forecasts respectively. The basic method, which only requires polynomial algebra, is outlined and applied on ACS data. The resulting filters are analyzed in the frequency domain.

CITATION:

Source: U.S. Census Bureau, Statistical Research Division

Created: September 6, 2007
Last revised: September 6, 2007


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Source: U.S. Census Bureau | Statistical Research Division | (301) 763-3215 (or chad.eric.russell@census.gov) |   Last Revised: October 08, 2010