Metadata-Version: 2.4
Name: paneltime
Version: 1.2.68
Summary: Panel regression simultaneously solving for ARIMA/GARCH and random/fixed effects.
Author-email: Espen Sirnes <espen.sirnes@uit.no>
License-Expression: GPL-3.0-only
Project-URL: Homepage, https://github.com/espensirnes/paneltime
Keywords: econometrics
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.11
Requires-Dist: pandas>=1.0
Requires-Dist: mpmath>=1.1
Provides-Extra: linux
Requires-Dist: gcc; extra == "linux"
Dynamic: license-file




**Paneltime** is a statistical tool for estimating regressions on datasets that:  

- Are **panels** (have both a time and a group dimension)  
- Are **non-stationary in means** (ARIMA)  
- Are **non-stationary in variance** (GARCH)  

Unlike any other statistical tool currently available, **Paneltime** simultaneously estimates **random/fixed effects**, **ARIMA**, and **GARCH** parameters.  

The package can also be used on **non-panel data** or datasets that only exhibit ARIMA or GARCH characteristics. However, if your data has none of these issues, **OLS is the preferred method**.  

**Author:** Espen Sirnes  
**Current version:** 1.2.67  


# Installation


"pip install paneltime" for installation


# Usage

Datasets are estimated with 

```
paneltime.execute(model_string, dataframe, T,
						ID=None, HF=None,
						instruments=None)
```
It takes the following arguments:

- `model_string`: A string on the form 'Y ~ X1 + X2 + X3', where Y is the dependent and X1-X3 are the independents, as named in the dataframe (required)
- `dataframe`: a dataframe consisting of variables with the names used in `model_string` (required)
- `T`: the time identifier (required)
- `ID`: The group identifier (optional)
- `HF`: list with names of heteroskedasticity factors (optional)
- `instruments`: list with names of instruments (optional)
  
## The model string

The model string can contain operations supported by the `numpy` package, using `np` as alias for numpy. For example `np.abs(x)` will result in a 
variable that is the absolute value of x. 


# Example using world bank data
```python
{{< include example.py >}}
```

[Download working example zip](working_example.zip)



