ivx

Robust Econometric Inference for Predictive Regressions

https://github.com/kvasilopoulos/ivx

Science Score: 23.0%

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Found 4 DOI reference(s) in README
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Low similarity (17.2%) to scientific vocabulary

Keywords

inference ivx local-to-unity predictive-regressions

Last synced: 6 months ago · JSON representation

Repository

Robust Econometric Inference for Predictive Regressions

Basic Info

Host: GitHub
Owner: kvasilopoulos
License: gpl-3.0
Language: R
Default Branch: master
Homepage: https://kvasilopoulos.github.io/ivx/
Size: 13.5 MB

Statistics

Stars: 17
Watchers: 1
Forks: 6
Open Issues: 2
Releases: 0

Topics

inference ivx local-to-unity predictive-regressions

Created over 7 years ago · Last pushed almost 5 years ago

Metadata Files

Readme Contributing License Code of conduct

README.Rmd

---
output: github_document
---

```{r setup, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```
# ivx: Robust Econometric Inference 


[![DOI](https://zenodo.org/badge/137785074.svg)](https://zenodo.org/badge/latestdoi/137785074)
[![CRAN status](https://www.r-pkg.org/badges/version/ivx)](https://cran.r-project.org/package=ivx)
[![Lifecycle: maturing](https://img.shields.io/badge/lifecycle-maturing-blue.svg)](https://www.tidyverse.org/lifecycle/#maturing)
[![R build status](https://github.com/kvasilopoulos/ivx/workflows/R-CMD-check/badge.svg)](https://github.com/kvasilopoulos/ivx/actions)
[![Codecov test coverage](https://codecov.io/gh/kvasilopoulos/ivx/branch/master/graph/badge.svg)](https://codecov.io/gh/kvasilopoulos/ivx?branch=master)




Drawing statistical inference on the coefficients of a short- or long-horizon 
predictive regression with persistent regressors by using the IVX method of 
[Magdalinos and Phillips (2009)](https://doi.org/10.1017/S0266466608090154) and
[Kostakis, Magdalinos and Stamatogiannis (2015)](https://doi.org/10.1093/rfs/hhu139).

## Installation

You can install the development version from [GitHub](https://github.com/) with:

``` r
# Install release version from CRAN
install.packages("ivx")


# install.packages("devtools")
devtools::install_github("kvasilopoulos/ivx")
```
## Usage


```{r message = FALSE}
library(ivx)
library(magrittr)
```

This is a basic example, lets load the data first:

```{r example}
# Monthly data from Kostakis et al (2014)
kms %>%
  names()

```

## Univariate

And then do the univariate estimation:

```{r uni}
ivx(Ret ~ DP, data = kms) %>% 
  summary()

ivx(Ret ~ DP, data = kms, horizon = 4) %>% 
  summary()

```

## Multivariate

And the multivariate estimation, for one or multiple horizons:

```{r multi}
ivx(Ret ~ DP + TBL, data = kms) %>% 
  summary()

ivx(Ret ~ DP + TBL, data = kms, horizon = 4) %>% 
  summary()

```


## Yang et al. (2020) IVX-AR methodology

```{r uni-ar}
ivx_ar(hpi ~ cpi, data = ylpc) %>% 
  summary()

```




---

Please note that the 'ivx' project is released with a [Contributor Code of Conduct](https://github.com/kvasilopoulos/ivx/blob/master/.github/CODE_OF_CONDUCT.md). By contributing to this project, you agree to abide by its terms.

Owner

Name: Kostas Vasilopoulos
Login: kvasilopoulos
Kind: user
Location: Thessaloniki
Company: Reportbrain

Website: https://kvasilopoulos.com/
Repositories: 6
Profile: https://github.com/kvasilopoulos

Data Scientist | Economist (PhD)

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kvasilopoulos (2)
dazhwu (1)

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Packages

Total packages: 1
Total downloads:
- cran 230 last-month

Total dependent packages: 0
Total dependent repositories: 0
Total versions: 2
Total maintainers: 1

cran.r-project.org: ivx

Robust Econometric Inference

Homepage: https://github.com/kvasilopoulos/ivx
Documentation: http://cran.r-project.org/web/packages/ivx/ivx.pdf
License: GPL-3
Latest release: 1.1.0
published about 5 years ago

Versions: 2
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 230 Last month

Rankings

Forks count: 11.3%

Stargazers count: 15.1%

Dependent packages count: 29.8%

Average: 32.8%

Dependent repos count: 35.5%

Downloads: 72.2%

Maintainers (1)

k.vasilopoulo@gmail.com