Naive Model

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Naive Model

A very complicated economic or political science model that is likely to be highly inaccurate. Naive models are sometimes created intentionally in academia to demonstrate the idea that complex models are not necessarily predictive. Sometimes, however, they are used to clarify thinking, even if their results are inaccurate.
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Sims, 1980) moved away from using a structural model to univariate time-series naive models and subsequently to the vector autoregression (VAR) model.
These methods can be generally categorised into four types: (1) naive models, e.g.
Projections of industry employment resulted in sizable errors for both the BLS and the naive models. Again, in both models, errors for 2008 and 2010 were much larger than those errors for 2006.
Sadly, discussions by professional historians have been dominated by implicit models that downplay the ability of an unfettered market to achieve widespread prosperity, preferring naive models in which government can snap its fingers and magically solve all of society's perceived ills--if the opposition would only get out of the way.
For the estimation of naive models we used a generalized linear model (GLM) with a binomial distribution and logit link function to address this interval restriction.
The table shows classification comparisons between naive models that assume mat no bonds are called, logit models without the refunding constraint variables, and logit models including the refunding constraint variables.
The discrepancy in the performance of the two naive models also illustrated the important role of seasonal adjustment.
OLS-based naive models. This reduction, however, is not sufficiently large to negate the predictive performance of the models combining both ARMs and beta, relative to the beta-only models.
"Forecasting Presidential Elections: A Comparison of Naive Models." Political Behavior 6: 9-21.
To provide a baseline estimation and comparison, we ran naive models that did not account for the unobservable correlation between insurance and use of care.
In actuality, the benchmarks are naive models such as: (1) projecting the latest available information; or (2) predicting that the change over the forecast period is equal to that observed over the previous time interval, which is of the same length as the forecast period.
Our notion of robustness is that the model consistently lies near the top of performance lists of alternative models and is consistently more successful than models based only on past inflation, such as Atkeson and Ohanian's naive model.