Modeling with Time Series: Issues and Common Errors

Abdulhakeem Kilishi

No 24, Working Papers from Department of Economics, University of Ilorin

Abstract: Time series data are widely used in empirical research but it is observed that most often the modeling is done with errors. It is common for researchers to use a given estimation method without considering the stochastic properties of the variable. When time series data are used in estimation without addressing the problem of stochastic innovations, the result may be biased with invalid inferential statistics. Hence, hypothesis test will be unreliable and conclusion misleading. This paper provides simple discussion of potential problems that could arise while modeling with time series. Practical step by step approaches of modeling time series variables at different circumstances is also discussed in the paper. It is concluded that necessary pre estimation tests should always be carried out before choosing the appropriate method.

Keywords: Time Series; Time Trend; Nonstationary; Modeling (search for similar items in EconPapers)
JEL-codes: C18 C32 C51 C82 (search for similar items in EconPapers)
Pages: 13 pages
Date: 2022-03-25
New Economics Papers: this item is included in nep-ore
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Persistent link: https://EconPapers.repec.org/RePEc:ris:decilo:0024

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