Given the high number of requests, my colleagues and I have decided to provide a brief tutorial on how to get started with xsmle. First of all, you have to install the command by typing

net install xsmle, all from(

It is fundamental to use the option all because when you install a user-written package without using this option, the ancillary files (in this case "product.dta" and "usaww.spmat") won't be downloaded, while with the all option all the ancillary files will always (conditionally on the presence of an internet connection) be downloaded to 1) your current working directory OR 2) the directory you specified for ancillary files using the net set other command.

Now, lets assume that you haven't changed your "ancillary files" directory and that your Stata current working directory is the Desktop. Then, you should now find on your Desktop two new files: "product.dta" and "usaww.spmat". These files contain informations on public capital productivity in 48 US states observed over 17 years, as well as the spatial weights matrix for the US states (Munnel, 1990). The examples reported in the xsmle help file make use of these files, also available in R through the Ecdat package.

The first step is to load the "product.dta" into memory by typing

use product.dta, clear

Then, you have to do the same for the spatial weights matrix contained in the "usaww.spmat" file. Being an spmat file, this can be done by typing

spmat use W using "usaww.spmat"

At this stage, after computing the logarithm of the dependent and independent variables, we have all the ingredients to estimate a spatial panel data model. For instance, the syntax to estimate a Spatial AutoRegressive (SAR) model with random effects is

xsmle lngsp lnpcap lnpc lnemp unemp, wmat(W) model(sar)

Notice that the dataset "product.dta" has been already declared to be a panel. In general, you need to declare your dataset to be a panel dataset by using the xtset command.


Munnell AH (1990). “Why Has Productivity Growth Declined? Productivity and Public Investment.” New England Economic Review, 1990, 3–22.

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