# stabsim2: Simulated data for college admissions problem In matchingMarkets: Analysis of Stable Matchings

## Description

Simulate data for two-sided matching markets. In the simulation for the Sorensen (2007) model with one selection equation, an equal sharing rule of λ = 0.5 is used.

## Usage

 ```1 2``` ```stabsim2(m, nStudents, nColleges = length(nSlots), nSlots, colleges, students, outcome, selection, binary = FALSE, seed = 123, verbose = TRUE) ```

## Arguments

 `m` integer indicating the number of markets to be simulated. `nStudents` integer indicating the number of students per market. `nColleges` integer indicating the number of colleges per market. `nSlots` vector of length `nColleges` indicating the number of places at each college, i.e. the college's quota. `colleges` character vector of variable names for college characteristics. These variables carry the same value for any college. `students` character vector of variable names for student characteristics. These variables carry the same value for any student. `outcome` formula for match outcomes. `selection` formula for match valuations. `binary` logical: if `TRUE` outcome variable is binary; if `FALSE` outcome variable is continuous. `seed` integer setting the state for random number generation. Defaults to `set.seed(123)`. `verbose` .

## Value

`stabsim2` returns a list with the following items.

 `OUT` `SEL` `SELc` `SELs`

Thilo Klein

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```## Simulate two-sided matching data for 2 markets (m=2) with 10 students ## (nStudents=10) per market and 3 colleges (nColleges=3) with quotas of ## 2, 3, and 5 students, respectively. xdata <- stabsim2(m=2, nStudents=10, nSlots=c(2,3,5), verbose=FALSE, colleges = "c1", students = "s1", outcome = ~ c1:s1 + eta + nu, selection = ~ -1 + c1:s1 + eta ) head(xdata\$OUT) head(xdata\$SEL) ```

matchingMarkets documentation built on Jan. 11, 2018, 3 p.m.