Fixed_Effects: Fixed_Effects
In jpburgard/gravity: Estimation Methods for Gravity Models

Description Usage Arguments Details Value References See Also Examples

Fixed_Effects estimates gravity models via OLS and fixed effects for the countries of origin and destination. These effects catch country specific effects.

1 2	Fixed_Effects(y, dist, fe = c("iso_o", "iso_d"), x, vce_robust = TRUE, data, ...)

`y`	name (type: character) of the dependent variable in the dataset `data`, e.g. trade flows. This variable is logged and taken as the dependent variable in the estimation.
`dist`	name (type: character) of the distance variable in the dataset `data` containing a measure of distance between all pairs of bilateral partners. It is logged automatically when the function is executed.
`fe`	vector of names (type: character) of fixed effects. The default is set to the unilateral identifiers `"iso_o"` and `"iso_d"` for cross-sectional data. When using panel data, interaction terms of the iso-codes and time may be added in either `fe` or `x`.
`x`	vector of names (type: character) of those bilateral variables in the dataset `data` that should be taken as the independent variables in the estimation. If an independent variable is a dummy variable it should be of type numeric (0/1) in the dataset. If an independent variable is defined as a ratio, it should be logged. The fixed effects catch all unilateral effects. Therefore, no other unilateral variables such as GDP can be included as independent variables in the estimation.
`vce_robust`	robust (type: logic) determines whether a robust variance-covariance matrix should be used. The default is set to `TRUE`. If set `TRUE` the estimation results are consistent with the Stata code provided at the website Gravity Equations: Workhorse, Toolkit, and Cookbook when choosing robust estimation.
`data`	name of the dataset to be used (type: character). To estimate gravity equations, a square gravity dataset including bilateral flows defined by the argument `y`, ISO-codes of type character (called `iso_o` for the country of origin and `iso_d` for the destination country), a distance measure defined by the argument `dist` and other potential influences given as a vector in `x` are required. All dummy variables should be of type numeric (0/1). Missing trade flows as well as incomplete rows should be excluded from the dataset. Furthermore, flows equal to zero should be excluded as the gravity equation is estimated in its additive form. When using panel data, a variable for the time may be included in the dataset. Note that the variable for the time dimension should be of type: factor. The time variable can be used as a single dependent variable or interaction term with other variables such as country identifiers by inserting it into `x` or `fe`. See the references for more information on panel data.
`...`	additional arguments to be passed to `Fixed_Effects`.

To account for MR terms, Feenstra (2002) and Feenstra (2004) propose to use importer and exporter fixed effects. Due to the use of these effects, all unilateral influences such as GDPs can no longer be estimated. A disadvantage of the use of Fixed_Effects is that, when applied to panel data, the number of country-year or country-pair fixed effects can be too high for estimation. In addition, no comparative statistics are possible with Fixed_Effects as the MR terms are not estimated explicitly. Nevertheless, Head and Mayer (2014) highlight the importance of the use of fixed effects. To execute the function a square gravity dataset with all pairs of countries, ISO-codes for the country of origin and destination, a measure of distance between the bilateral partners as well as all information that should be considered as dependent an independent variables is needed. Make sure the ISO-codes are of type "character". Missing bilateral flows as well as incomplete rows should be excluded from the dataset. Furthermore, flows equal to zero should be excluded as the gravity equation is estimated in its additive form. Country specific fixed effects are considered by incorporating "iso_o" and "iso_d" in fe. By including country specific fixed effects, all monadic effects are captured, including Multilateral Resistance terms. Therefore, no other unilateral variables such as GDP can be included as independent variables in the estimation.

Fixed_Effects 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 at the website Gravity Equations: Workhorse, Toolkit, and Cookbook when choosing robust estimation. The function Fixed_Effects was therefore tested for For the use with panel data no tests were performed. Therefore, it is up to the user to ensure that the functions can be applied to panel data. Depending on the panel dataset and the variables - specifically the type of fixed effects - included in the model, it may easily occur that the model is not computable. Also, note that by including bilateral fixed effects such as country-pair effects, the coefficients of time-invariant observables such as distance can no longer be estimated. Depending on the specific model, the code of the respective function may has to be changed in order to exclude the distance variable from the estimation. At the very least, the user should take special care with respect to the meaning of the estimated coefficients and variances as well as the decision about which effects to include in the estimation. When using panel data, the parameter and variance estimation of the models may have to be changed accordingly. For a comprehensive overview of gravity models for panel data see Egger and Pfaffermayr (2003), Gomez-Herrera (2013) and Head, Mayer and Ries (2010) as well as the references therein.

The function returns the summary of the estimated gravity model as an lm-object.

For more information on fixed effects as well as informaton on gravity models, theoretical foundations and suitable estimation methods in general see

Anderson, J. E. (2010) <DOI:10.3386/w16576>

Head, K. and Mayer, T. (2014) <DOI:10.1016/B978-0-444-54314-1.00003-3>

as well as

Anderson, J. E. (1979) <DOI:10.12691/wjssh-2-2-5>

Anderson, J. E. and van Wincoop, E. (2003) <DOI:10.3386/w8079>

Baier, S. L. and Bergstrand, J. H. (2009) <DOI:10.1016/j.jinteco.2008.10.004>

Baier, S. L. and Bergstrand, J. H. (2010) in Van Bergeijk, P. A., & Brakman, S. (Eds.) (2010) chapter 4 <DOI:10.1111/j.1467-9396.2011.01000.x>

Head, K., Mayer, T., & Ries, J. (2010) <DOI:10.1016/j.jinteco.2010.01.002>

Santos-Silva, J. M. C. and Tenreyro, S. (2006) <DOI:10.1162/rest.88.4.641>

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

Egger, P., & Pfaffermayr, M. (2003) <DOI:10.1007/s001810200146>

Gomez-Herrera, E. (2013) <DOI:10.1007/s00181-012-0576-2>

and the references therein.

lm, coeftest, vcovHC

## Not run: 
data(Gravity_no_zeros)

Fixed_Effects(y="flow", dist="distw", fe=c("iso_o", "iso_d"), 
x=c("rta"), vce_robust=TRUE, data=Gravity_no_zeros)

Fixed_Effects(y="flow", dist="distw", fe=c("iso_o", "iso_d"), 
x=c("rta", "comcur", "contig"), vce_robust=TRUE, data=Gravity_no_zeros)

## End(Not run)