Coherent Trends, Turning Points, and Forecasts for ACS Data
نویسنده
چکیده
The American Community Survey (ACS) provides one-year (1y), three-year (3y), and fiveyear (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.
منابع مشابه
Sentiment-based predictions of housing market turning points with Google trends
Purpose – Recent research has found significant relationships between internet search volume and real estate markets. This paper aims to examine whether Google search volume data can serve as a leading sentiment indicator and are able to predict turning points in the US housing market. One of the main objectives is to find a model based on internet search interest that generates reliable real-t...
متن کاملProbabilistic mortality forecasting with varying age-specific survival improvements
Many mortality forecasting approaches extrapolate past trends. Their predictions of the future development can be quite precise as long as turning points and/or age-shifts of mortality decline are not present. To account even for such mortality dynamics, we propose a model that combines recently developed ideas in a single framework. It (1) uses rates of mortality improvement to model the aging...
متن کاملAnticipating business-cycle turning points in real time using density forecasts from a VAR
For the timely detection of business-cycle turning points we suggest to use mediumsized linear systems (subset VARs with automated zero restrictions) to forecast the relevant underlying variables, and to derive the probability of the turning point from the forecast density as the probability mass below (or above) a given threshold value. We show how this approach can be used in real time in the...
متن کاملProvisional Estimates of Output Miss Economic Turning Points ? Karen
Initial estimates of aggregate output and its components are based on very incomplete source data, so they may not fully capture shifts in economic conditions. In particular, if those estimates are based partly on trends in preceding quarters, one would expect to see provisional estimates overstating activity when actual output is decelerating and understating it when actual output is accelerat...
متن کاملA Classifying Procedure for Signaling Turning Points
A Hidden Markov Model (HMM) is used to classify an out of sample observation vector into either of two regimes. This leads to a procedure for making probability forecasts for changes of regimes in a time series, i.e. for turning points. Instead of maximizing a likelihood, the model is estimated with respect to known past regimes. This makes it possible to perform feature extraction and estimati...
متن کامل