Editing Econometric model

{{Short description|Statistical models used in econometrics}}
'''Econometric models''' are [[statistical model]]s used in [[econometrics]]. An econometric model specifies the [[statistics|statistical]] relationship that is believed to hold between the various economic quantities pertaining to a particular economic phenomenon. An econometric model can be derived from a [[Deterministic system (philosophy)|deterministic]] [[economic model]] by allowing for uncertainty, or from an economic model which itself is [[stochastic]]. However, it is also possible to use econometric models that are not tied to any specific economic theory.<ref name=sims80>{{cite journal
  | last = Sims
  | first = Christopher A.
  | title = Macroeconomics and Reality
  | journal = [[Econometrica]]
  | volume = 48
  | issue = 1
  | pages = 1–48
  | year = 1980
  | jstor = 1912017| doi = 10.2307/1912017| citeseerx = 10.1.1.163.5425}}</ref>

A simple example of an econometric model is one that assumes that monthly [[Consumption (economics)|spending by consumers]] is linearly [[Dependent and independent variables|dependent]] on consumers' income in the previous month. Then the model will consist of the equation

:<math>C_t = a + bY_{t-1} + e_t,</math>

where ''C''<sub>''t''</sub> is [[consumer spending]] in month ''t'', ''Y''<sub>''t''-1</sub> is income during the previous month, and ''e<sub>t</sub>'' is an [[Errors and residuals in statistics|error term]] measuring the extent to which the model cannot fully explain consumption. Then one objective of the [[econometrician]] is to obtain estimates of the [[parameter]]s ''a'' and ''b''; these estimated parameter values, when used in the model's equation, enable predictions for future values of consumption to be made contingent on the prior month's income.

==Formal definition==
In [[econometrics]], as in [[statistics]] in general, it is presupposed that the quantities being analyzed can be treated as [[random variable]]s. An econometric model then is a [[set (mathematics)|set]] of [[joint probability distribution]]s to which the true joint probability distribution of the variables under study is supposed to belong. In the case in which the elements of this set can be [[index set|index]]ed by a finite number of real-valued ''parameters'', the model is called a [[parametric model]]; otherwise it is a [[non-parametric statistics|nonparametric]] or [[semiparametric model]]. A large part of econometrics is the study of methods for [[model selection|selecting]] models, [[estimation theory|estimating]] them, and carrying out [[statistical inference|inference]] on them.

The most common econometric models are [[structural equation models|structural]], in that they convey causal and [[Counterfactual conditional|counterfactual]] information,<ref name=pearl-causality>{{cite book |last=Pearl |first=J. |title=Causality: Models, Reasoning, and Inference |url=https://archive.org/details/causalitymodelsr0000pear |url-access=registration |publisher=Cambridge University Press |year=2000 |location=New York |isbn=0521773628 }}</ref> and are used for policy evaluation. For example, an equation modeling consumption spending based on income could be used to see what consumption would be contingent on any of various hypothetical levels of income, only one of which (depending on the choice of a [[fiscal policy]]) will end up actually occurring.

==Basic models==
Some of the common econometric models are:
*[[Linear regression]]
*[[Generalized linear model]]s
*[[Probit]]
*[[Logit]]
*[[Tobit model|Tobit]]
*[[ARIMA]]
*[[Vector Autoregression]]
*[[Cointegration]]
*Hazard

==Use in policy-making==
Comprehensive models of [[macroeconomics|macroeconomic]] relationships are used by [[central bank]]s and governments to evaluate and guide economic policy. One famous econometric model of this nature is the [[Federal Reserve Bank]] econometric model.

==See also==
* [[Benefit financing model]]

==References==
{{Reflist}}

==Further reading==
* {{cite book |last=Asteriou |first=Dimitros |last2=Hall |first2=Stephen G. |title=Applied Econometrics |publisher=Palgrave MacMillan |year=2011 |edition=Second |isbn=978-0-230-27182-1 |chapter=The Classical Linear Regression Model |pages=29–91 }}
*{{cite book
  | last = Davidson
  | first = Russell
  |author2=James G. MacKinnon
  | title = Estimation and Inference in Econometrics
  | publisher = Oxford University Press
  | year = 1993
  | isbn = 0-19-506011-3 }}
*{{cite book
  | last = Granger
  | first = Clive
  | title = Modelling Economic Series: Readings in Econometric Methodology
  | publisher = Oxford University Press
  | year = 1991
  | url = https://archive.org/details/modellingeconomi0000unse
  | isbn = 0-19-828736-4
  | url-access = registration
  }}
*{{cite book
  | last = Pagan
  | first = Adrian
  | author2 = Aman Ullah
  | title = Nonparametric Econometrics
  | publisher = Cambridge University Press
  | year = 1999
  | url = https://archive.org/details/nonparametriceco00paga
  | isbn = 0-521-58611-9
  | url-access = registration
  }}
* {{cite book |last=Pedace |first=Roberto |title=Econometrics for Dummies |location=Hoboken, NJ |publisher=Wiley |year=2013 |isbn=978-1-118-53384-0 |chapter=Building the Classical Linear Regression Model |pages=59–134 }}

==External links==
* [http://www.ssc.wisc.edu/~bhansen/econometrics/ Manuscript of Bruce Hansen's book on Econometrics]
* {{YouTube|id=WK03XgoVsPM&list=PLD15D38DC7AA3B737&index=1#t=14m52s|title=Econometrics lecture (introduction to regression models)}} by [[Mark Thoma]]

{{Quantitative forecasting methods}}
{{Authority control}}

{{DEFAULTSORT:Econometric Model}}
[[Category:Econometric models|*]]
[[Category:Mathematical and quantitative methods (economics)]]

[[pl:Model ekonometryczny]]