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[[Leveraged Buyout Innovation (Academic Paper)]]
==Instructions for running matching code==
===Inputs and Outputs===
===Running Code===
===Options===
Before running, modify the following options if necessary:
====Specify input file (if using different file than default)====
====Specify which observations are valid for matching.====
'''===Specify propensity score type to use for matching'''===
*Specify additional constraints on valid matches (modify code within function mcexpr as desired)
**For example, default code forces matches to be within the same industry group, within the same decade, and with patent stocks within +/- 20% of LBO firm.
Matching LBOs (Julia) (view source)
Revision as of 13:47, 21 September 2020
, 13:47, 21 September 2020no edit summary
{{Project|Has project output=Tool|Has sponsor=McNair ProjectsCenter
|Has title=Matching LBOs (Julia)
|Has owner=James Chen,
|Has keywords=Tool
|Has project status=ActiveComplete
}}
[[Leveraged Buyout Innovation (Academic Paper)]]
*Input: tab delimited file "E:/McNair/Projects/LBO/Clean/STATApredictLBOclean.txt"
**Positive integers identify pairs matched, negative integers identify matched non-LBOs in years other than the match, -0.1 identifies LBOs that failed to match to any non-LBOs under constraints provided
*Open Julia command line in administrator mode
*Change directory to E:\McNair\Projects\LBO\New matching\
cd("E:/McNair/Projects/LBO/New\ matching")
*Run script LBOmatchscript.jl include("LBOmatchscript.jl")
There are a few things options that can be customized in the scriptbefore running. Getting this the code into a more user-friendly form is a WIP. In fact, some parts might be difficult, if not impossible, to write in a more accessible way.
Line 12:
df = readtable("E:/McNair/Projects/LBO/Clean/STATApredictLBOclean.txt", separator = '\t');
*For now, we filter out all firms that were never granted a single patent in the period 1970-2015
*For firms that LBO, we also drop their observations in all other years from the list of candidates to match to other LBOs
Lines 38-48
#Splitting dataset into LBO and non-LBO firms
#Note that we also filter out all firms that were never granted a single patent in the period 1970-2015
LBOs = @from i in df begin
@where i.everlbo == 1 && (i.matchfilter4 == 1 ||i.matchfilter2b == 1) && i.lboentry == 1
@select i
@collect DataFrame
end
nonLBOs = @from i in df begin
@where i.everlbo == 0 && (i.matchfilter4 == 1 ||i.matchfilter2b == 1)
@select i
@collect DataFrame
end
*Options are: logitp (panel logit), probitp (panel probit), or Cox proportional hazard (hr)
*Alternatively, can use the aboveoptions, with regressions performed using winsorized values of regressors (trimmed at 1st and 99th percentiles): logitpw, probitpw, hrw
Line 58:
mscore = :logitpw;
===Specify whether matching priority should be deterministic or random===
*If deterministic, priority goes to lower GVKEY
Line 61:
randoption = 0;
===Specify whether matching priority should be deterministic or random. additional constraints on valid matches (modify code within function mcexpr as desired)===*If deterministicFor example, priority goes default code forces matches to lower GVKEYbe within the same industry group, within the same decade, and with patent stocks within +/- 20% of LBO firm.
Lines 69-81:
return eval(parse(mcriteria))
end
