Métodos de estimación no lineal aplicados al problema de expectativas de inflación

Mauricio Arriagada-Benítez; Héctor Valdés-González; Liliana Pedraja-Rejas

Métodos de estimación no lineal aplicados al problema de expectativas de inflación

Translated title of the contribution: Nonlinear estimation methods applied to a problem of expected inflation

Universidad Andrés Bello

Research output: Contribution to journal › Article › peer-review

Abstract

This work describes and analyses the Extended Kalman Filter with regard to an equation that relates the dynamic of the expected real interest rates and inflation. An estimation of the ex ante inflation for a preestablished data set is carried out. This is compared with the same calculation using a moving horizon estimation method for situations that are non lineal due to parametric uncertainties of the model. From the application of these methods to real data, it can be concluded that the estimations based on the moving horizon method, combined with a heuristic optimization algorithm, yield better results.

Translated title of the contribution	Nonlinear estimation methods applied to a problem of expected inflation
Original language	Spanish
Pages (from-to)	404-411
Number of pages	8
Journal	Ingeniare
Volume	17
Issue number	3
State	Published - Dec 2009

Cite this

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title = "M{\'e}todos de estimaci{\'o}n no lineal aplicados al problema de expectativas de inflaci{\'o}n",

abstract = "This work describes and analyses the Extended Kalman Filter with regard to an equation that relates the dynamic of the expected real interest rates and inflation. An estimation of the ex ante inflation for a preestablished data set is carried out. This is compared with the same calculation using a moving horizon estimation method for situations that are non lineal due to parametric uncertainties of the model. From the application of these methods to real data, it can be concluded that the estimations based on the moving horizon method, combined with a heuristic optimization algorithm, yield better results.",

keywords = "Econometric models, Inflation, Kalman filter, MHSE method",

author = "Mauricio Arriagada-Ben{\'i}tez and H{\'e}ctor Vald{\'e}s-Gonz{\'a}lez and Liliana Pedraja-Rejas",

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AU - Arriagada-Benítez, Mauricio

AU - Valdés-González, Héctor

AU - Pedraja-Rejas, Liliana

PY - 2009/12

Y1 - 2009/12

N2 - This work describes and analyses the Extended Kalman Filter with regard to an equation that relates the dynamic of the expected real interest rates and inflation. An estimation of the ex ante inflation for a preestablished data set is carried out. This is compared with the same calculation using a moving horizon estimation method for situations that are non lineal due to parametric uncertainties of the model. From the application of these methods to real data, it can be concluded that the estimations based on the moving horizon method, combined with a heuristic optimization algorithm, yield better results.

AB - This work describes and analyses the Extended Kalman Filter with regard to an equation that relates the dynamic of the expected real interest rates and inflation. An estimation of the ex ante inflation for a preestablished data set is carried out. This is compared with the same calculation using a moving horizon estimation method for situations that are non lineal due to parametric uncertainties of the model. From the application of these methods to real data, it can be concluded that the estimations based on the moving horizon method, combined with a heuristic optimization algorithm, yield better results.

KW - Econometric models

KW - Inflation

KW - Kalman filter

KW - MHSE method

UR - https://www.scopus.com/pages/publications/74949118273

M3 - Article

AN - SCOPUS:74949118273

SN - 0718-3291

VL - 17

SP - 404

EP - 411

JO - Ingeniare

JF - Ingeniare

IS - 3

ER -

Métodos de estimación no lineal aplicados al problema de expectativas de inflación

Abstract

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