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Robust methods for nonstandard situations, their diagnostics and implementations

Project goals

Robustified (with respect to contamination) versions of econometric methods have to consider realistically the character of economic data, e. g. correletion of regressors and disturbances nearly automatiaclly implies heteroscedastcity or collinearity can mask contamination. So, the robustified versions are to work under ``combined’’ distortion of classical assumptions –i. e. under nonstandard situations. Some nonstandard situations were not yet exhaustively studied with a goal of robustified tool for coping with them, as binary or limited response, even worse situation is with the censored and missing data. Only some basic diagnostic tools were considered for robustified regression model identification methods, namely for least weighted squares and instrumental weighted variables. Diagnostic tools have to be tailored individually for every robustified method (as they were tailored for the OLS in the past). Algorithmization, implementation and verification are tiresome work without which the theoretical findings lose on reliability and attractivity. It implies what is to be done.

Keywords

Regression modelrobust estimatorsdiagnosticsrobust tests of orthogonalityhomoscedasticitycollinearitymodels with effects and qualitative responseefficiency of robust analysissignificance of regressorsalgorithmstheir implementations and verification of tightness of solutions

Public support

  • Provider

    Czech Science Foundation

  • Programme

    Standard projects

  • Call for proposals

    Standardní projekty 17 (SGA0201300005)

  • Main participants

    Univerzita Karlova / Fakulta sociálních věd

  • Contest type

    VS - Public tender

  • Contract ID

    13-01930S

Alternative language

  • Project name in Czech

    Robustní procedury pro nestandardní situace, jejich diagnostika a implementace

  • Annotation in Czech

    Robustifikované (vzhledem ke kontaminaci dat) verze ekonometrických metod by měly realisticky předpokládat charakter ekonomických dat, např. korelace mezi regresory a disturbancemi téměř automaticky implikuje heteroskedasticitu a kolinearita zase může maskovat kontaminaci. Robustifikované metody by tedy měly fungovat i při ``kombinovaných narušeních‘‘ klasických předpokladů. Některé takové nestandardní situace nebyly dosud dostatečně prostudovány s cílem navržení robustních nástrojů, které si s nimi poradí, jako je model s binární či limitovanou závislé proměnnou, modely uvažující censorovaná či chybějící data. Zatím byly nalezeny jen robustifikované verze některých diagnostických nástrojů, zejména pro nejmenší vážené čtverce a instrumentální vážené proměnné. Diagnostické nástroje musí totiž být robustifikovány individuálně pro každou robustifikovanou metodu (původně byly tyto konstruovány pro NČ). Algoritmizace, implementace a odzkoušení jsou sice únavné práce, ale bez nich ztrácí naše výsledky atraktivitu a spolehlivost v aplikacích. To implikuje, co bychom měli studovat.

Scientific branches

  • R&D category

    ZV - Basic research

  • CEP classification - main branch

    AH - Economics

  • CEP - secondary branch

  • CEP - another secondary branch

  • 50201 - Economic Theory
    50202 - Applied Economics, Econometrics
    50203 - Industrial relations
    50204 - Business and management
    50205 - Accounting
    50206 - Finance

Completed project evaluation

  • Provider evaluation

    U - Uspěl podle zadání (s publikovanými či patentovanými výsledky atd.)

  • Project results evaluation

    The work plan of the project was fulfilled. The main investigator managed to process and publish the principal research objectives contained in the proposal. In view of the professional reputation of the investigator one can expect these publications to have a corresponding impact on their field of study.

Solution timeline

  • Realization period - beginning

    Feb 1, 2013

  • Realization period - end

    Dec 31, 2016

  • Project status

    U - Finished project

  • Latest support payment

    Apr 5, 2016

Data delivery to CEP

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

  • Data delivery code

    CEP17-GA0-GA-U/03:1

  • Data delivery date

    Jun 28, 2017

Finance

  • Total approved costs

    4,263 thou. CZK

  • Public financial support

    4,263 thou. CZK

  • Other public sources

    0 thou. CZK

  • Non public and foreign sources

    0 thou. CZK