skip to content
Approximating high-dimensional dynamic models : sieve value function iteration Preview this item
ClosePreview this item
Checking...

Approximating high-dimensional dynamic models : sieve value function iteration

Author: Peter Arcidiacono; National Bureau of Economic Research.
Publisher: Cambridge, Mass. : National Bureau of Economic Research, ©2012.
Series: Working paper series (National Bureau of Economic Research), no. 17890.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
Many dynamic problems in economics are characterized by large state spaces which make both computing and estimating the model infeasible. We introduce a method for approximating the value function of high-dimensional dynamic models based on sieves and establish results for the: (a) consistency, (b) rates of convergence, and (c) bounds on the error of approximation. We embed this method for approximating the solution  Read more...
Rating:

(not yet rated) 0 with reviews - Be the first.

Subjects
More like this

 

Find a copy online

Links to this item

Find a copy in the library

&AllPage.SpinnerRetrieving; Finding libraries that hold this item...

Details

Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Peter Arcidiacono; National Bureau of Economic Research.
OCLC Number: 779321526
Notes: Title from http://www.nber.org/papers/17890 viewed March 6, 2012.
"March 2012."
Description: 1 online resource (42 pages).
Series Title: Working paper series (National Bureau of Economic Research), no. 17890.
Responsibility: Peter Arcidiacono [and others].

Abstract:

Many dynamic problems in economics are characterized by large state spaces which make both computing and estimating the model infeasible. We introduce a method for approximating the value function of high-dimensional dynamic models based on sieves and establish results for the: (a) consistency, (b) rates of convergence, and (c) bounds on the error of approximation. We embed this method for approximating the solution to the dynamic problem within an estimation routine and prove that it provides consistent estimates of the model's parameters. We provide Monte Carlo evidence that our method can successfully be used to approximate models that would otherwise be infeasible to compute, suggesting that these techniques may substantially broaden the class of models that can be solved and estimated.

Reviews

User-contributed reviews
Retrieving GoodReads reviews...
Retrieving DOGObooks reviews...

Tags

Be the first.

Similar Items

Confirm this request

You may have already requested this item. Please select Ok if you would like to proceed with this request anyway.

Linked Data


Primary Entity

<http://www.worldcat.org/oclc/779321526> # Approximating high-dimensional dynamic models : sieve value function iteration
    a schema:MediaObject, schema:CreativeWork, schema:Book ;
   library:oclcnum "779321526" ;
   library:placeOfPublication <http://experiment.worldcat.org/entity/work/data/1083723314#Place/cambridge_mass> ; # Cambridge, Mass.
   library:placeOfPublication <http://id.loc.gov/vocabulary/countries/mau> ;
   schema:about <http://id.loc.gov/authorities/subjects/sh85040857> ; # Economics--Mathematical models
   schema:about <http://dewey.info/class/330/> ;
   schema:about <http://id.worldcat.org/fast/902155> ; # Economics--Mathematical models
   schema:about <http://id.worldcat.org/fast/1118215> ; # Sieves (Mathematics)
   schema:bookFormat schema:EBook ;
   schema:contributor <http://viaf.org/viaf/58742536> ; # Peter Arcidiacono
   schema:contributor <http://viaf.org/viaf/135446122> ; # National Bureau of Economic Research.
   schema:copyrightYear "2012" ;
   schema:datePublished "2012" ;
   schema:description "Many dynamic problems in economics are characterized by large state spaces which make both computing and estimating the model infeasible. We introduce a method for approximating the value function of high-dimensional dynamic models based on sieves and establish results for the: (a) consistency, (b) rates of convergence, and (c) bounds on the error of approximation. We embed this method for approximating the solution to the dynamic problem within an estimation routine and prove that it provides consistent estimates of the model's parameters. We provide Monte Carlo evidence that our method can successfully be used to approximate models that would otherwise be infeasible to compute, suggesting that these techniques may substantially broaden the class of models that can be solved and estimated."@en ;
   schema:exampleOfWork <http://worldcat.org/entity/work/id/1083723314> ;
   schema:inLanguage "en" ;
   schema:isPartOf <http://experiment.worldcat.org/entity/work/data/1083723314#Series/working_paper_series_national_bureau_of_economic_research> ; # Working paper series (National Bureau of Economic Research) ;
   schema:isPartOf <http://experiment.worldcat.org/entity/work/data/1083723314#Series/nber_working_paper_series> ; # NBER working paper series ;
   schema:name "Approximating high-dimensional dynamic models : sieve value function iteration"@en ;
   schema:productID "779321526" ;
   schema:publication <http://www.worldcat.org/title/-/oclc/779321526#PublicationEvent/cambridge_mass_national_bureau_of_economic_research_2012> ;
   schema:publisher <http://experiment.worldcat.org/entity/work/data/1083723314#Agent/national_bureau_of_economic_research> ; # National Bureau of Economic Research
   schema:url <http://papers.nber.org/papers/w17890> ;
   schema:url <http://ezproxy.eui.eu/login?url=http://papers.nber.org/papers/> ;
   wdrs:describedby <http://www.worldcat.org/title/-/oclc/779321526> ;
    .


Related Entities

<http://experiment.worldcat.org/entity/work/data/1083723314#Agent/national_bureau_of_economic_research> # National Bureau of Economic Research
    a bgn:Agent ;
   schema:name "National Bureau of Economic Research" ;
    .

<http://experiment.worldcat.org/entity/work/data/1083723314#Place/cambridge_mass> # Cambridge, Mass.
    a schema:Place ;
   schema:name "Cambridge, Mass." ;
    .

<http://experiment.worldcat.org/entity/work/data/1083723314#Series/nber_working_paper_series> # NBER working paper series ;
    a bgn:PublicationSeries ;
   schema:hasPart <http://www.worldcat.org/oclc/779321526> ; # Approximating high-dimensional dynamic models : sieve value function iteration
   schema:name "NBER working paper series ;" ;
    .

<http://experiment.worldcat.org/entity/work/data/1083723314#Series/working_paper_series_national_bureau_of_economic_research> # Working paper series (National Bureau of Economic Research) ;
    a bgn:PublicationSeries ;
   schema:hasPart <http://www.worldcat.org/oclc/779321526> ; # Approximating high-dimensional dynamic models : sieve value function iteration
   schema:name "Working paper series (National Bureau of Economic Research) ;" ;
    .

<http://id.loc.gov/authorities/subjects/sh85040857> # Economics--Mathematical models
    a schema:Intangible ;
   schema:name "Economics--Mathematical models"@en ;
    .

<http://id.worldcat.org/fast/1118215> # Sieves (Mathematics)
    a schema:Intangible ;
   schema:name "Sieves (Mathematics)"@en ;
    .

<http://id.worldcat.org/fast/902155> # Economics--Mathematical models
    a schema:Intangible ;
   schema:name "Economics--Mathematical models"@en ;
    .

<http://viaf.org/viaf/135446122> # National Bureau of Economic Research.
    a schema:Organization ;
   schema:name "National Bureau of Economic Research." ;
    .

<http://viaf.org/viaf/58742536> # Peter Arcidiacono
    a schema:Person ;
   schema:familyName "Arcidiacono" ;
   schema:givenName "Peter" ;
   schema:name "Peter Arcidiacono" ;
    .


Content-negotiable representations

Close Window

Please sign in to WorldCat 

Don't have an account? You can easily create a free account.