Contributed by economists and others from the US, Australia, and Denmark, the articles discuss the history of the Advances in Econometrics series, its role, and topics such as Stein-rule estimation, weak instruments in a panel data context, the role of weak instruments in spatial models, testing for trend breaks, Bayesian unit root tests, time-varying tail dependence using Copula-GARCH (generalized autoregressive conditional heteroscedastic) models, sectoral effects of aggregate shocks, co-movements between output, prices, and inflation, and Monte Carlo experiments using Stata.
What does AR stand for?
AR stands for Autoregressive
This definition appears very frequently
See other definitions of AR
We have 156 other meanings of AR in our Acronym Attic
- Authorized Representative
- Authorized Reseller
- Auto Redial
- Automated Reasoning
- Automatic Recall (Bellcore)
- Automatic Response
- Automatic Resupply
- Automation Recall
- Automation Resources
- Autonomous Republic
- Autosomal Recessive (genetics; recessive gene on one of the 23 pairs of autosomes)
- Auxiliary Receiver
- Auxiliary Relay
- Auxiliary Room
- Avance-Retard (French)
- Avis de Réception (Canada Post)
- Axial Ratio
- Ayn Rand (novelist and philosopher)
- End of message / Out (logging abbreviation)
- Postal Fiscal (Scott Catalogue prefix; philately)
Samples in periodicals archive:
3) In models such as ours, which are vector autoregressive and estimated with Bayesian methods, the past level of the federal funds rate has considerable explanatory power for the current level.
By taking into account time-lagged soil water content, time-lagged soil temperature, autoregressive processes and seasonality, the model provides more-detailed information on the nature of the relationship between [N.
The present paper focuses on modeling and forecasting of livestock feed resources, using probabilistic models such as Autoregressive (AR), to study the influence of climatic and non-climatic variables on the availability of feed resources.
A Bayesian spatial conditional autoregressive model was fitted at the LGA level to quantify the relationship between DF and socioecologic factors.
This form of interdependence is referred to as a spatial autoregressive model.
An Autoregressive Distribution Lag method was used, which allowed the team toinvestigate both short and long term dynamics.