tetrads | R Documentation |

`tetrads`

estimates gravity models
by taking the ratio of the ratio of flows.

```
tetrads(
dependent_variable,
distance,
additional_regressors,
code_origin,
code_destination,
filter_origin = NULL,
filter_destination = NULL,
multiway = FALSE,
data,
...
)
```

`dependent_variable` |
(Type: character) name of the dependent variable. This variable is logged and then used as the dependent variable in the estimation. |

`distance` |
(Type: character) name of the distance variable that should be taken as the key independent variable in the estimation. The distance is logged automatically when the function is executed. |

`additional_regressors` |
(Type: character) names of the additional regressors to include in the model (e.g. a dummy
variable to indicate contiguity). Unilateral metric variables such as GDP should be inserted via the arguments
Write this argument as |

`code_origin` |
(Type: character) country of origin variable (e.g. ISO-3 country codes). The variables are grouped using this parameter. |

`code_destination` |
(Type: character) country of destination variable (e.g. country ISO-3 codes). The variables are grouped using this parameter. |

`filter_origin` |
(Type: character) Reference exporting country. |

`filter_destination` |
(Type: character) Reference importing country. |

`multiway` |
(Type: logical) in case |

`data` |
(Type: data.frame) the dataset to be used. |

`...` |
Additional arguments to be passed to the function. |

`tetrads`

is an estimation method for gravity models
developed by \insertCiteHead2010;textualgravity.

The function `tetrads`

utilizes the multiplicative form of the
gravity equation. After choosing a reference exporter `A`

and
importer `B`

one can eliminate importer and exporter fixed effects
by taking the ratio of ratios.

Only those exporters trading with the reference importer and importers trading with the reference exporter will remain for the estimation. Therefore, reference countries should preferably be countries which trade with every other country in the dataset.

After restricting the data in this way, `tetrads`

estimates the gravity
equation in its additive form by OLS.

By taking the ratio of ratios, all monadic effects diminish, hence no unilateral variables such as GDP can be included as independent variables.

`tetrads`

estimation can be used for both, cross-sectional as well as
panel data. Nonetheless, the function is designed to be consistent with the
Stata code for cross-sectional data provided on the website
Gravity Equations: Workhorse, Toolkit, and Cookbook
when choosing robust estimation.

The function `tetrads`

was therefore tested for cross-sectional data.

If tetrads is used for panel data, the user may have to drop distance as an independent variable as time-invariant effects drop.

For applying `tetrads`

to panel data see \insertCiteHead2010;textualgravity.

The function returns the summary of the estimated gravity model as an
`lm`

-object.

For more information on gravity models, theoretical foundations and estimation methods in general see

\insertRefAnderson1979gravity

\insertRefAnderson2001gravity

\insertRefAnderson2010gravity

\insertRefBaier2009gravity

\insertRefBaier2010gravity

\insertRefFeenstra2002gravity

\insertRefHead2010gravity

\insertRefHead2014gravity

\insertRefSantos2006gravity

and the citations therein.

See Gravity Equations: Workhorse, Toolkit, and Cookbook for gravity datasets and Stata code for estimating gravity models.

For estimating gravity equations using panel data see

\insertRefEgger2003gravity

\insertRefGomez-Herrera2013gravity

and the references therein.

`lm`

, `coeftest`

,

```
# Example for CRAN checks:
# Executable in < 5 sec
library(dplyr)
data("gravity_no_zeros")
# Choose 5 countries for testing
countries_chosen <- c("AUS", "CHN", "GBR", "BRA", "CAN")
grav_small <- filter(gravity_no_zeros, iso_o %in% countries_chosen)
fit <- tetrads(
dependent_variable = "flow",
distance = "distw",
additional_regressors = "rta",
code_origin = "iso_o",
code_destination = "iso_d",
filter_origin = countries_chosen[1],
filter_destination = countries_chosen[2],
data = grav_small
)
```

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