Matching LBOs (Julia) - Revision history

Ed at 17:47, 21 September 2020

2020-09-21T17:47:39Z

2020-09-21T17:34:34Z

2020-09-20T17:20:05Z

2020-09-20T17:12:18Z

2017-10-31T15:07:09Z

2017-06-30T16:33:38Z

Specify which observations are valid for matching

2017-06-30T09:11:00Z

Options

2017-06-30T09:10:15Z

Specify propensity score type to use for matching

2017-06-30T09:09:40Z

Options

2017-06-30T09:09:19Z

Specify which observations are valid for matching.

@@ Line 1: / Line 1: @@
 {{Project
-|Has project output=
+|Has project output=Tool
 |Has sponsor=McNair Center
 |Has title=Matching LBOs (Julia)

@@ Line 1: / Line 1: @@
 {{Project
 |Has sponsor=McNair Center
 |Has title=Matching LBOs (Julia)

@@ Line 1: / Line 1: @@
 {{Project
 |Has title=Matching LBOs (Julia)
 |Has owner=James Chen,

@@ Line 1: / Line 1: @@
-{{McNair Projects
+{{Project
 |Has title=Matching LBOs (Julia)
 |Has owner=James Chen,

@@ Line 3: / Line 3: @@
 |Has owner=James Chen,
 |Has keywords=Tool
-|Has project status=Active
+|Has project status=Complete
 }}
 [[Leveraged Buyout Innovation (Academic Paper)]]

← Older revision		Revision as of 16:33, 30 June 2017
Line 45:		Line 45:

	Lines 38-48		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===		===Specify propensity score type to use for matching===

← Older revision		Revision as of 09:11, 30 June 2017
Line 31:		Line 31:
	==Options==		==Options==

−	There are a few options that can be customized in the script before running. Getting ~~this~~ 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.	+	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.

@@ Line 48: / Line 48: @@
 ===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, with regressions performed using winsorized values of regressors (trimmed at 1st and 99th percentiles): logitpw, probitpw, hrw
+*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:

@@ Line 53: / Line 53: @@
   mscore = :logitpw;
-===Specify whether matching priority should be deterministic or random.===
+===Specify whether matching priority should be deterministic or random===
 *If deterministic, priority goes to lower GVKEY

@@ Line 39: / Line 39: @@
   df = readtable("E:/McNair/Projects/LBO/Clean/STATApredictLBOclean.txt", separator = '\t');
-===Specify which observations are valid for matching.===
+===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