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596 bytes added ,  13:47, 21 September 2020
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{{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)]]
[[Leveraged Buyout Innovation (Academic Paper)]]
==Instructions for running matching code==
===Inputs and Outputs===
*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
===Running Code===
*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")
===Options===
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.
Before running, modify the following options if necessary:
*If matching ===Specify input file (if using different file, modifyline 12: readtable("Filepath"than default)===
Line 12: df = readtable(Not implemented yet"E: More user-friendly way to input restrictions/McNair/Projects/LBO/Clean/STATApredictLBOclean.txt", separator = '\t'); *===Specify which observations are valid for matching. ===*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*See inline comments in code for detailed description of what matchfilter2, matchfilter4, etc. represent
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
*===Specify propensity score type to use for matching=== *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, hrwline 58: mscore = :logitpw; *Specify whether matching priority should be deterministic or random. If deterministic, priority goes to lower GVKEYline 61: randoption = 0;
*Specify additional constraints on valid matches (modify code within function mcexpr as desired)Line 58: 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. mscore = :logitpw;
lines 69-81:===Specify whether matching priority should be deterministic or random===*If deterministic, priority goes to lower GVKEY
function mcexpr(i)Line 61: randoption = 0;
#note that the below syntax is the simplest way to store a long string over multiple lines #===Specify additional constraints on valid matches (i.e., appending additional characters per linemodify code within function mcexpr as desired)=== #Also*For example, note that order of operations default code forces us matches to put each condition in parenthesesbe within the same industry group, within the same decade, and with patent stocks within +/- 20% of LBO firm.
Lines 69-81: function mcexpr(i) #note that the below syntax is the simplest way to store a long string over multiple lines #(i.e., appending additional characters per line) #Also, note that order of operations forces us to put each condition in parentheses mcriteria = "nonLBOs[:matchsubset] = (nonLBOs[:industrygroup3].== LBOs[$i,:industrygroup3])" mcriteria = mcriteria * " .* (nonLBOs[:decade].==LBOs[$i,:decade])" mcriteria = mcriteria * " .* (nonLBOs[:patentstock] .>= (LBOs[$i,:patentstock]*.8))" mcriteria = mcriteria * " .* (nonLBOs[:patentstock] .<= (LBOs[$i,:patentstock]*1.2))" mcriteria = mcriteria * " .* (nonLBOs[:matchpair] .== 0 )" return eval(parse(mcriteria)) end

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