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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)]]
==Inputs and Outputs==
*Input: tab delimited file "E:/McNair/Projects/LBO/Clean/STATApredictLBOclean.txt"
**This contains list of LBO and nonLBO firms from compustat 1970-2015, propensity scores, patent data, and other variables generated from stata code "statadatasetup4.do" and "statapredictLBOclean.do"
*Output: tab delimited file "E:/McNair/Projects/LBO/New matching/matchresults.txt"
**This is the input file, except with an additional column "matchpair" indicating matched pairs:
**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 options that can be customized in the script before running. Getting 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. ===Specify input file (if using different file than default)=== Line 12: df = readtable("E:/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 above options, 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 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. 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[Leveraged Buyout Innovation :patentstock] .>= (Academic PaperLBOs[$i,:patentstock]*.8))" mcriteria = mcriteria * " .* (nonLBOs[:patentstock].<= (LBOs[$i,:patentstock]*1.2))" mcriteria = mcriteria * " .* (nonLBOs[:matchpair] .== 0 )" return eval(parse(mcriteria)) end
