VC Startup Matching Stata Work - Revision history

Ed at 17:47, 21 September 2020

2020-09-21T17:47:42Z

2020-09-21T17:34:37Z

2020-09-20T17:20:19Z

2020-09-20T17:12:31Z

2018-08-22T20:08:22Z

Paralelization of Matlab Code

2018-08-22T20:01:10Z

2018-08-22T19:51:16Z

Building new Dataset in SQL for a Linear Probability Model

2018-08-22T19:47:12Z

Linear Probability Model

2018-08-22T19:46:59Z

Linear Probability Model

2018-07-30T21:38:37Z

Building new Dataset in SQL for a Linear Probability Model

@@ Line 1: / Line 1: @@
 {{Project
-|Has project output=
+|Has project output=Tool
 |Has sponsor=McNair Center
 |Has title=VC Startup Matching Stata Work

@@ Line 1: / Line 1: @@
 {{Project
 |Has sponsor=McNair Center
 |Has title=VC Startup Matching Stata Work

@@ Line 1: / Line 1: @@
 {{Project
 |Has title=VC Startup Matching Stata Work
 |Has owner=Marcos Ki Hyung Lee,

@@ Line 1: / Line 1: @@
-{{McNair Projects
+{{Project
 |Has title=VC Startup Matching Stata Work
 |Has owner=Marcos Ki Hyung Lee,

← Older revision		Revision as of 20:08, 22 August 2018
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	==Paralelization of Matlab Code==		==Paralelization of Matlab Code==

−	This was done by [[Wei Wu]]	+	This was done by [[Wei Wu]]. I will briefly summarize what he told me.
		+
		+	His main objective was to paralelize as much as possible Chenyu's code in Matlab. Apparently, this was done successfully. What changed is documented in [[Parallelize msmf corr coeff.m]].
		+
		+	He also had two other projects that did not end up working. One was to use the GPU to speed up even more the code. The reasons are well documented in [[Matlab, CUDA, and GPU Computing]].
		+
		+	Finally, he also tried expanding the paralelization by using NOTS (Night Owls Time-Sharing Service), a computing cluster. Since the paralelization was succesful, expanding the number of cores available was the logical next step. He ran into problems which I couldn't understand very well. Additionally, NOTS is not Windows-friendly. Check [[NOTS Computing for Matching Entrepreneurs to VCs]] for more.

← Older revision		Revision as of 20:01, 22 August 2018
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	E:\McNair\Projects\MatchingEntrepsToVC\Stata\Tex		E:\McNair\Projects\MatchingEntrepsToVC\Stata\Tex
		+
		+
		+	==Reduced Form Analysis of the Dataset==
		+
		+	An extensive reduced form analysis was employed with a lot of back and forth feedback between Jeremy Fox and Ed Egan and me. I documented everything I did in a pdf file generated from LaTeX. Since converting it to Wiki format would be too cumbersome, including converting multiple tables and figures, I've decided it is better to host the latex files and pdf in the folder below
		+
		+	E:\McNair\Projects\MatchingEntrepsToVC\Stata\Pdf
		+
		+	Everything necessary to produce the pdf file is there. Open the .tex file 'regressions.tex' and build it using your preferred latex compiler. A very easy option is to use some online compiler.
		+
		+	==Paralelization of Matlab Code==
		+
		+	This was done by [[Wei Wu]]

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 After that we can simply append/union the real match table and calculate the variables from the original dataset on this new table.
-The code that does this is called 'CreatingLPM_withoutsyn.sql' when using code100, and 'CreatingLPM_withoutsyn_code20.sql'
+The code that does this is called 'CreatingLPM_withoutsyn.sql' when using code100, and 'CreatingLPM_withoutsyn_code20.sql'. Augi reworked and streamlined it.
 ===Histograms===

@@ Line 55: / Line 55: @@
 ===Linear Probability Model===
-THIS IS OBSELETE AS OF NEW SQL CODE
+THIS IS OBSOLETE AS OF NEW SQL CODE
 A linear probability model was suggested by Jeremy Fox, where Y=1 when the match is real, and Y=0 when the match is synthetic, and independent variables are characteristics from the VCs.

← Older revision		Revision as of 19:46, 22 August 2018
Line 54:		Line 54:

	===Linear Probability Model===		===Linear Probability Model===
		+
		+	THIS IS OBSELETE AS OF NEW SQL CODE

	A linear probability model was suggested by Jeremy Fox, where Y=1 when the match is real, and Y=0 when the match is synthetic, and independent variables are characteristics from the VCs.		A linear probability model was suggested by Jeremy Fox, where Y=1 when the match is real, and Y=0 when the match is synthetic, and independent variables are characteristics from the VCs.

@@ Line 86: / Line 86: @@
 To run the linear probability model, we need to build a new dataset. This was partially done in the Stata Do-File explained above, but doing it in SQL will give the opportunity to be more flexible when choosing the synthetic match.
-We want to create a table that lists for each unique portco all its eligible firms, ie, active in the year it had its first investment from the real matched VC and that had invested in a portco of the same code100 in that year.
+The end result is a table that lists all matches that could have occurred in every possible market, including the real one.
 After that we can simply append/union the real match table and calculate the variables from the original dataset on this new table.
-The final code is called 'CreatingLPM_withoutsyn.sql'
+The code that does this is called 'CreatingLPM_withoutsyn.sql' when using code100, and 'CreatingLPM_withoutsyn_code20.sql'