https://github.com/zeileis/ivreg

2SLS Regression with Diagnostics in R
https://github.com/zeileis/ivreg

instrumental-variables regression-diagnostics two-stage-least-squares-regression

Last synced: 2 months ago
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2SLS Regression with Diagnostics in R

• Host: GitHub
• URL: https://github.com/zeileis/ivreg
• Owner: zeileis
• Created: 2019-09-24T00:49:57.000Z (over 5 years ago)
• Default Branch: main
• Last Pushed: 2023-06-24T16:56:16.000Z (over 1 year ago)
• Last Synced: 2023-12-19T18:51:17.899Z (about 1 year ago)
• Topics: instrumental-variables, regression-diagnostics, two-stage-least-squares-regression
• Language: R
• Homepage: https://zeileis.github.io/ivreg/
• Size: 19.4 MB
• Stars: 13
• Watchers: 5
• Forks: 6
• Open Issues: 1
• Metadata Files:
  • Readme: README.Rmd

Awesome Lists containing this project

README

        
---

output: github_document

---

```{r, include = FALSE}

knitr::opts_chunk$set(

  fig.path = "man/figures/README-"

)

```

## Two-Stage Least-Squares Regression with Diagnostics

An implementation of instrumental variables regression using two-stage least-squares

(2SLS) estimation, based on the `ivreg()` function previously in the

[AER](https://CRAN.R-project.org/package=AER) package. In addition to standard regression

functionality (parameter estimation, inference, predictions, etc.) the package provides

various regression diagnostics, including hat values, deletion diagnostics such as

studentized residuals and Cook's distances; graphical diagnostics such as

component-plus-residual plots and added-variable plots; and effect plots with partial

residuals.

**Instrumental variables regression:**

```

library("ivreg")

ivreg(Q ~ P + D | D + F + A, data = Kmenta)

```

**Via two-stage least squares (2SLS):**

```{r 2sls, echo=FALSE, results="hide"}

exams::tex2image("\\begin{eqnarray*}

  y                                  & = & X \\beta + \\varepsilon \\\\

  \\widehat{X}                       & = & Z (Z^\\top Z)^{-1} Z^\\top X \\\\

  \\widehat{\\beta}_{\\mathrm{2SLS}} & = & (\\widehat{X}^\\top \\widehat{X})^{-1} \\widehat{X}^\\top y

\\end{eqnarray*}",

  format = "svg", header = "", pt = 14,

  dir = file.path(getwd(), "man", "figures"), name = "README-2sls")

```



**With diagnostics:**

```{r effects, echo=FALSE, results="hide", message=FALSE, fig.height=4.7, fig.width=5, fig.show="hide"}

library("ivreg")

library("effects")

library("car")

deq <- ivreg(Q ~ P + D | D + F + A, data = Kmenta)

plot(predictorEffect("P", deq, residuals = TRUE), partial.residuals = list(span = 1))

```

```{r qqplot, echo=FALSE, results="hide", message=FALSE, fig.height=4.7, fig.width=5, fig.show="hide"}

qqPlot(deq, main = "QQ plot")

## mtext("QQ plot", line = 1.5, cex = 1.2, font = 2)

```

```{r influenceplot, echo=FALSE, results="hide", message=FALSE, fig.height=4.7, fig.width=5, fig.show="hide"}

influencePlot(deq, main = "")

mtext("Influence plot", line = 2, cex = 1.2, font = 2)

```