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Forecasting the Forecasts of Others
Journal of Political Economy, 1983This paper explores the formulation and analysis of linear equilibrium models of investment in which learning is perpetual and informationally decentralized firms need never share the same beliefs concerning time series relevant to their decisions.
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Journal of Monetary Economics, 1999 This paper investigates forecasts of U.S. inflation at the 12-month horizon. The starting point is the conventional unemployment rate Phillips curve, which is examined in a simulated out of sample forecasting framework. Inflation forecasts produced by the Phillips curve generally have been more accurate than forecasts based on other macroeconomic ...
James H. Stock, Mark W. Watson
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Learning Lane Graph Representations for Motion Forecasting
European Conference on Computer Vision, 2020We propose a motion forecasting model that exploits a novel structured map representation as well as actor-map interactions. Instead of encoding vectorized maps as raster images, we construct a lane graph from raw map data to explicitly preserve the map ...
Ming Liang +6 more
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SSRN Electronic Journal, 2010
AbstractThis article studies two issues in forecast combination, first considering ways to combine forecasts from surveys and time series models. Second, it considers the possibility, advanced by Hendry and Clements (2004), that model instability can help explain the gains in forecasting performance resulting from combination.
Marco Aiolfi +2 more
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AbstractThis article studies two issues in forecast combination, first considering ways to combine forecasts from surveys and time series models. Second, it considers the possibility, advanced by Hendry and Clements (2004), that model instability can help explain the gains in forecasting performance resulting from combination.
Marco Aiolfi +2 more
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TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables
Neural Information Processing SystemsDeep models have demonstrated remarkable performance in time series forecasting. However, due to the partially-observed nature of real-world applications, solely focusing on the target of interest, so-called endogenous variables, is usually insufficient ...
Yuxuan Wang +7 more
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Science, 2016
Police are turning to big data to stop crime before it happens. But is predictive policing biased—and does it even work?
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Police are turning to big data to stop crime before it happens. But is predictive policing biased—and does it even work?
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2011
Suggested Citation: Armstrong, J.S., Green, K.C. and Graefe, A. "Forecasting Principles." In International Encyclopedia of Statistical Science (Ed. M. Lovric). Springer, 2011.
Armstrong, J. Scott +2 more
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Suggested Citation: Armstrong, J.S., Green, K.C. and Graefe, A. "Forecasting Principles." In International Encyclopedia of Statistical Science (Ed. M. Lovric). Springer, 2011.
Armstrong, J. Scott +2 more
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Forecasting Inflation Forecast Errors [PDF]
, 2008 We evaluate inflation forecasts from the Survey of Professional Forecasters (SPF) of the Central Bank of Chile. Forecast errors for the period 2000-2008 show an excess of autocorrelation and a statistically significant bias at the end of the sample. We take advantage of the autocorrelation structure of the forecast errors to build new and more accurate
Andrea Betancor, Pablo Pincheira
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Climacteric, 2015
Recent epidemiological studies from various countries point at the mounting incidence of cancer. This continuous increase in the number of cancer cases will keep its pace in the future. The lifetime risk of cancer for people born since 1960 is forecast to be more than 50%.
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Recent epidemiological studies from various countries point at the mounting incidence of cancer. This continuous increase in the number of cancer cases will keep its pace in the future. The lifetime risk of cancer for people born since 1960 is forecast to be more than 50%.
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Microfounded Forecasting [PDF]
, 2014 In this paper, we propose a microfounded framework to investigate a panel of forecasts (e.g. model-driven or survey-based) and the possibility to improve their out-of-sample forecast performance by employing a bias-correction device. Following Patton and Timmermann (2007), we theoretically justify the modeling of forecasts as function of the ...
Gaglianone, Wagner Piazza +1 more
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