Author: Trond Pedersen

Microdata.no now makes it possible to export graphs in several formats, as well as edit them in the editing tool Vega.

The variable overview of microdata.no has now been greatly improved in that it is possible to filter by subject area or other characteristics of the data, while at the same time you can freely choose how the variable list should be sorted.

The user manual for microdata.no has now been updated and describes all new functionality that has been implemented since April 2022.

In addition to the command reshape-to-panel, we now introduce reshape-from-panel which makes it possible to go the opposite way, namely to restructure datasets from long- to wide-format. This provides significantly greater flexibility when adapting datasets for analyses.

The new command reshape-to-panel gives you the freedom to restructure your data to long-format, i.e. data where the information is organized downwards as observations / records.

The analysis directory in microdata.no has been expanded with the new command oaxaca. This is a tool to measure whether there are systematic differences between two groups, e.g. men and women, and the differences are further decomposed into an explained and an unexplained component.

It is now possible to calculate marginal effects for logistic regression analyzes in other ways than the default value “overall”, using the new option “mfx_at ()”.

For variable import in microdata.no, the standard solution is “left join”, where the first variable that is imported into a dataset determines the population. But now we introduce the possibility to import data using “outer join” so that also new individuals / units that don’t exist in your original population will be added to your…

The user manual has been updated and describes the latest commands and functionalities that have been implemented from September 2020 until January 2022.

How big is the economic inequality in Norway? Has this changed in recent years? Are there geographical differences? Such things can now be analyzed by calculating Gini coefficient values ​​in microdata.no.