IIASA RepositoryAnticipating Recessions using Inclination AnalysisE.ShchekinovaauthorA.PuchkovaauthorE.RovenskayaauthorU.DieckmannauthorRecessions are economic downturns that can be recognized from macro-indicators such as the Dow Jones Industrial Average (DJIA) and the Federal Reserve Interest Rate (FRIR). To provide early-warning signals of recessions and similar systemic transitions, here we propose a new approach based on pattern recognition, called inclination analysis [1, 2]. For this purpose, we develop a stochastic model based on time-series analysis to assess the probability of a recession to occur at a given moment in the past, present, or future. Calibrating our model to data proceeds in three steps, involving the coarse-graining of the available input time series, the identification of short series motifs that foreshadow recessions, and the optimization of key model parameters according to the model’s desired forecasting horizon.2017-02-27Conference or Workshop Item

For work being deposited by its own author: In self-archiving this collection of files and associated bibliographic metadata, I grant IIASA Repository the right to store them and to make them permanently available publicly for free on-line. I declare that this material is my own intellectual property and I understand that IIASA Repository does not assume any responsibility if there is any breach of copyright in distributing these files or metadata. (All authors are urged to prominently assert their copyright on the title page of their work.)

For work being deposited by someone other than its author: I hereby declare that the collection of files and associated bibliographic metadata that I am archiving at IIASA Repository) is in the public domain. If this is not the case, I accept full responsibility for any breach of copyright that distributing these files or metadata may entail.

Clicking on the deposit button indicates your agreement to these terms.