Arbeitspapier

Aplicação do modelo fatorial dinâmico para previsão da receita tributária no Brasil

This article aims to estimate the dynamic factor model for prediction tax receipts in Brazil using monthly data for the period 2001-2013. The factorial model allows to reduce the dimensionality of the high number of taxes taking into account the information contained in the existing interrelations between them and allowing to identify only the relevant information through the variables named factors. Further, in our model the seasonal component of the series of taxes is treated endogenously. This procedure permits to obtain better data fitting and more reliable predictions - once seasonality is a hallmark of certain series of tributes. We confront the predictions of the factorial model with those generated by linear dynamic model applied to each tribute separately and found that the factor model brings considerable gains in terms of efficiency and prediction.

Language
Portugiesisch

Bibliographic citation
Series: Texto para Discussão ; No. 2064

Classification
Wirtschaft
Taxation, Subsidies, and Revenue: General
Taxation and Subsidies: Incidence
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Subject
gross tax burden
seasonality
dynamic factor model
Kalman filter and Gibbs sampling

Event
Geistige Schöpfung
(who)
Mendonça, Mário Jorge
Medrano, Luis Alberto
Event
Veröffentlichung
(who)
Instituto de Pesquisa Econômica Aplicada (IPEA)
(where)
Brasília
(when)
2015

Handle
Last update
10.03.2025, 11:43 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Mendonça, Mário Jorge
  • Medrano, Luis Alberto
  • Instituto de Pesquisa Econômica Aplicada (IPEA)

Time of origin

  • 2015

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