help mtad
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Title

    mtad - Multinomial Test of Agglomeration and Dispersion

Syntax

mtad varlist, mkt(varname) [options]

    options               Description
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      mkt(integer)        market identifier
      wide                specifies one observation per market
      probs(numlist)      user provided baseline probabilties
      niter(integer)      number of monte carlo draws

Description

    mtad calculates a multinomial test-statistic for agglomeration or
    dispersion.  See Shane Greenstein and Marc Rysman (2005). "Testing for
    Agglomeration and Dispersion." Economics Letters 86(3): 405-411.

    Given a cross-section of "markets" this statistic indicates whether
    "plants" from two or more "industries" are more/less concentrated than
    would be observed under a random allocation.

    If wide is not specified (the default), each observation represents a
    plant, and varlist must be a single categorical variable that indicates
    the industry of that plant/observation.

    In wide mode, each observation represents a market and varlist must
    contain two or more count variables that indicate the number of plants
    for each industry in that market/observation.


Options

    mkt(varname) is required, and specifies the (numeric) identifier variable
        for the cross-section of markets/groups.

    wide is optional. If wide is specified, each observation represents a
        single market. If wide is not specified (the default) each
        observation represents a single plant.

    probs(numlist) is optional and can only be used in wide mode. This option
        allows the user to specify a known baseline probability of observing
        a plant in each industry. If this option is not used, mtad assumes
        that the probabilities of each plant-type correspond to the
        unconditional mean of that plant type in the data set.  The order of
        probabilities in probs(numlist) must correspond to the order of
        industires in varlist, and the probabilities must sum to 1.

    niter(integer) allows the user to specify the number of draws used in a
        Monte Carlo simulation to calcultae the mean and std deviation of the
        sample likelihood under random choice. The default is 50.


Saved Results

    Scalars   
      r(logl)         likelihood of observed data
      r(elogl)        simulated likelihood under random assignment
      r(sd)           standard deviation of simulated likelihood

    Macros    
      r(mtad)         String equal to "Agglomeration/Dispersion" if r(elogl)
                       is greater/less than r(logl)

Examples
    . sysuse bplong.dta
    . mtad sex, mkt(agegrp)

    . gen male = (sex==0)
    . gen female = (sex==1)
    . collapse (sum) male female, by(agegrp)
    . mtad male female, mkt(agegrp) wide prob(0.5 0.5) niter(250)


    To report bugs or give comments, please contact Timothy Simcoe