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Estimating Unobserved Complementarities between Entrepreneurs and Venture Capitalists (view source)
Revision as of 14:43, 8 July 2019
, 14:43, 8 July 2019no edit summary
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==Current Work== All work is in: E:\projects\unobservedcomplementarities Dataset was buit from '''vcdb3''' (see below). Latest data files are:*MasterRealC20YearFullPlus.txt*MasterRealC20YearFullPlus - DataDictionary.txt Subdirectories:*Marcos' old work is in .\marcos*Chenyu's code and datasets are in .\matlab*.\linearmodel is the current STATA work ===Linear Model=== The objective is to add city ranking and serials, possibly as well as no. coinvestors, and VC experience x no. coinvestors, to a linear model.The data for the linear model should include real and synthetic matches. However, to make it comparable to Chenyu's data, we likely need to exclude some markets. Some of Marcos' do files were not in the dropbox. ===Notes from Conference Call===
On July 5th at 10am, the co-authors had a conference call. These are the notes from that call:
Ed described the data. Chenyu said that he is running the estimation as two periods: one before and one after dot com crash. He is estimating:
*VCExperience (# prior deals in pccode20) x ranking ($amount or overall, lagged 1yr or 5yr)
*No. of Co-investors
*Rochester - 120hr max war time
==Latest Work=VCDB3 Rebuild===
The dataset was rebuilt using vcdb3 -- See [[VentureXpert Data]] and then fixed by Ed using RevisedDbaseCode.sql in E:\projects\vcdb3 and /bulk/vcdb3.
*MasterRealC20YearFullPlus - DataDictionary.txt
===Current Plan=Variables for inclusion====
New potential variables still being considered for inclusion:
[[Fox Hsu Yang (2015) - Unobserverd Heterogeneity in Matching Games with an Application to Venture Capital]] provides some notes.
==Previous Work (for reference)== ===Matlab Code===
[[Abhijit Brahme (Work Log)]] contains his notes on working with the Matlab code. There is a seperate page here: [[Estimating Unobserved Complementarities between Entrepreneurs and Venture Capitalists Matlab Code]].
Z:\Projects\MatchingAcceleratorsToVCs
===Data foundations===
The database is '''vcdb2'''
E:\McNair\Projects\MatchingEntrepsToVC\DataWork
===Dataset build===
====Decisions====
Decisions we need to make:
*How to collapse VC rounds (date, amount, etc.): We will use only seed, early, later stage investment and insist on the presence of seed/early for inclusion. We can then have date first, investment duration (to date last), total investment.
====Objective dataset description====
Unit of observation - a startup-fund match.
*maybe stage-match (doesn't make a lot of sense when collapsing rounds) between lead and port co.
====Identifying lead VCs====
Possible methods:
*Participant in earliest round that stayed in for longest with tie-breaker
====Minor Industry====
Across all time and without regard to SEL vs. transaction, here's the minor industry list and counts:
Consumer Related | 3161
===Literature from David===
Literature to "validate" our sample. I think you probably know the papers I reference below (let me know if you need any of them-some for which I am coauthor you can get from my website).
#If we have access to more individual data: VCs prefer to invest in founders with similar demographic characteristics relative to their own characteristics (Gompers et al within the past few years in JFE, Bengtsson and Hsu in JBV within the last few years).
==Work Done in Late November by Dylan & Ed=SBIR and Patent Data===
SBIR Data taken from McNair\Projects\SBIR\Data\Aggregate SBIR\SBIR.txt. -Note! This file needed to be opened in excel to be readable, and took a very long time to open due to its large size. SBIR firm names converted to a pivot table to eliminate exact repeat entries, and then exported to a txt file, NSBIR. NSBIR then matched using The Matcher in mode 2 with the following code:
