Nowcasting: An R Package for Predicting Economic Variables Using Dynamic Factor Models

被引:0
|
作者
de Valk, Serge [1 ]
de Mattos, Daiane [2 ]
Ferreira, Pedro [2 ]
机构
[1] EPGE Brazilian Sch Econ & Finance FGV EPGE, 60 Barao de Itambi, Rio De Janeiro, RJ, Brazil
[2] FGV IBRE, 60 Barao de Itambi, Rio De Janeiro, RJ, Brazil
来源
R JOURNAL | 2019年 / 11卷 / 01期
关键词
NUMBER;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The nowcasting package provides the tools to make forecasts of monthly or quarterly economic variables using dynamic factor models. The objective is to help the user at each step of the forecasting process, starting with the construction of a database, all the way to the interpretation of the forecasts. The dynamic factor model adopted in this package is based on the articles from Giannone et al. (2008) and Banbura. et al. (2011). Although there exist several other dynamic factor model packages available for R, ours provides an environment to easily forecast economic variables and interpret results.
引用
收藏
页码:230 / 244
页数:15
相关论文
共 50 条
  • [41] medflex: An R Package for Flexible Mediation Analysis using Natural Effect Models
    Steen, Johan
    Loeys, Tom
    Moerkerke, Beatrijs
    Vansteelandt, Stijn
    JOURNAL OF STATISTICAL SOFTWARE, 2017, 76 (11):
  • [42] Estimating Population Abundance Using Sightability Models: R Sightability Model Package
    Fieberg, John R.
    JOURNAL OF STATISTICAL SOFTWARE, 2012, 51 (09): : 1 - 20
  • [43] PReMiuM: An R Package for Profile Regression Mixture Models Using Dirichlet Processes
    Liverani, Silvia
    Hastie, David I.
    Azizi, Lamiae
    Papathomas, Michail
    Richardson, Sylvia
    JOURNAL OF STATISTICAL SOFTWARE, 2015, 64 (07): : 1 - 30
  • [44] Predicting human performance in interactive tasks by using Dynamic Models
    Sanz, Maria
    Arnau, David
    Gonzalez-Calero, J. A.
    Ferri, Francesc J.
    Arevalillo-Herraez, Miguel
    2017 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2017, : 776 - 780
  • [45] Estimating Animal Abundance with N-Mixture Models Using the R-INLA Package for R
    Meehan, Timothy D.
    Michel, Nicole L.
    Rue, Havard
    JOURNAL OF STATISTICAL SOFTWARE, 2020, 95 (02): : 1 - 26
  • [46] Input variables selection of fuzzy dynamic models by using genetic algorithm
    Escano, Juan Manuel
    Sanchez, Adolfo J.
    Witheephanich, Kritchai
    Roshany-Yamchi, Samira
    2016 27TH IRISH SIGNALS AND SYSTEMS CONFERENCE (ISSC), 2016,
  • [47] Macroeconometric forecasting using a cluster of dynamic factor models
    Christian Glocker
    Serguei Kaniovski
    Empirical Economics, 2022, 63 : 43 - 91
  • [48] Macroeconometric forecasting using a cluster of dynamic factor models
    Glocker, Christian
    Kaniovski, Serguei
    EMPIRICAL ECONOMICS, 2022, 63 (01) : 43 - 91
  • [49] Bond portfolio optimization using dynamic factor models
    Caldeira, Joao F.
    Moura, Guilherme V.
    Santos, Andre A. P.
    JOURNAL OF EMPIRICAL FINANCE, 2016, 37 : 128 - 158
  • [50] Nowcasting inflation in India with daily crowd-sourced prices using dynamic factors and mixed frequency models
    Yadav, Varun
    Das, Abhiman
    APPLIED ECONOMICS LETTERS, 2023, 30 (02) : 167 - 177