Description Usage Arguments Details References See Also Examples

Returns an object of class `urq`

. that represents an Unconditional Quantile Regression Fit

1 |

`formula` |
a formula object, with the response on the left of a ~ operator, and the terms, separated by + operators, on the right. |

`data` |
a |

`tau` |
the quantile(s) to be estimated, this must be a number (or a vector of numbers) strictly between 0 and 1. |

`kernel` |
a character string giving the smoothing kernel to be used. This must match one of "gaussian", "rectangular", "triangular", "epanechnikov", "biweight", "cosine" or "optcosine", with default "gaussian". |

`cre` |
The CRE formula (right hand side only) is a specification of the variables in the CRE component. These are possibly endogenous variables (in the sense that they are affected by the fixed effects) and must be time-varying. If left empty, a cross-sectional analysis is performed. |

`id` |
defines the structure of the panel. |

This function returns a Recentered Influence Function regression of given quantiles as proposed by Firpo, S., Fortin, N. M., & Lemieux, T. (2009). Panel data analysis is performed extending the correlated random effects (CRE) model by Mundlak (1978) and Chamberlain (1984) to an unconditional quantile regression framework. See Abrevaya and Dahl (2008) and Bache et al (2011) for more details.

Firpo, S., Fortin, N. M., & Lemieux, T. (2009). Unconditional quantile regressions. Econometrica, 77(3), 953-973.

Mundlak, Y. 1978. On the pooling of time series and cross section data. Econometrica 46: 69-85.

Chamberlain G (1984) Panel Data. In: Griliches Z, Intriligator MD (eds) Handbook of Econometrics, vol 2, Elsevier Science B. V., pp 1247-1318

Abrevaya, Jason and Christian M. Dahl. 2008. The effects of birth inputs on birthweight. Jounal of Business and Economic Statistics. 26-4. Pages 379-397.

Bache, Stefan Holst; Christian M. Dahl; Johannes Tang Kristensen. 2011. Headlights on tobacco road to low birthweight - Evidence from a battery of quantile regression estimators and a heterogeneous panel.

1 2 3 4 5 6 7 8 9 10 11 12 | ```
### example for cross-sectional data ###
data(engel)
formula = foodexp ~ income
rifreg=urq(formula,data = engel)
### example for panel data ###
data(trust)
formula=Trust_in_the_ECB~Trust_in_the_EU+Trust_in_National_Government
cre=~Trust_in_the_EU+Trust_in_National_Government
rif=urq(formula,data=trust,cre=cre,id="countryname")
``` |

```
Loading required package: Hmisc
Loading required package: lattice
Loading required package: survival
Loading required package: Formula
Loading required package: ggplot2
Attaching package: 'Hmisc'
The following objects are masked from 'package:base':
format.pval, round.POSIXt, trunc.POSIXt, units
Loading required package: gtools
```

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