Difference between revisions of "The Impact of Entrepreneurship Hubs on Urban Venture Capital Investment"

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*This page [[Hubs (Academic Paper)]] is the main page for the Hubs project!
 
*This page [[Hubs (Academic Paper)]] is the main page for the Hubs project!
 
*The old work done by Rachael is on the [[Hubs]] page
 
*The old work done by Rachael is on the [[Hubs]] page
 +
*There is also [[Old Completed Work on Hubs]]
 
*For a high-level overview of the variables for the scorecard go to [[Hubs Scorecard (Academic Paper)]]. This summarizes:
 
*For a high-level overview of the variables for the scorecard go to [[Hubs Scorecard (Academic Paper)]]. This summarizes:
 
**Current work in progress for building the Hubs scorecard: [[Hubs: Hubs Scorecard]]
 
**Current work in progress for building the Hubs scorecard: [[Hubs: Hubs Scorecard]]
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=Abstract=
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==Abstract==
  
 
The Hubs Research Project is a full-length academic paper analyzing the effectiveness of "hubs", a component of the entrepreneurship ecosystem, in the advancement and growth of entrepreneurial success in a metropolitan area.
 
The Hubs Research Project is a full-length academic paper analyzing the effectiveness of "hubs", a component of the entrepreneurship ecosystem, in the advancement and growth of entrepreneurial success in a metropolitan area.
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=Current Work=
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==Current Work==
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==General Overview==
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===General Overview===
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Currently there are '''3''' major tasks being performed (list to be updated):
 
Currently there are '''3''' major tasks being performed (list to be updated):
 
#'''Creation of VC data table''': '''UPDATE: Complete''' (see completed work section below)
 
#'''Creation of VC data table''': '''UPDATE: Complete''' (see completed work section below)
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#'''Hazard Rate Model''': '''UPDATE: (7/11) Spoke to Xun Tang, econometrics professor in Rice's Economics Department, and now looking for appropriate proportional rate hazard models with time varying covariates.''' In order to perform our diff-diff model, we need to match MSAs.  In order to do so, we will be using a hazard rate model to produce a probability that a MSA gets a Hub and compare MSAs that do and don't have hubs with similar probabilities.
 
#'''Hazard Rate Model''': '''UPDATE: (7/11) Spoke to Xun Tang, econometrics professor in Rice's Economics Department, and now looking for appropriate proportional rate hazard models with time varying covariates.''' In order to perform our diff-diff model, we need to match MSAs.  In order to do so, we will be using a hazard rate model to produce a probability that a MSA gets a Hub and compare MSAs that do and don't have hubs with similar probabilities.
  
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==Work In Progress==
 
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=Completed Work=
 
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==Venture Capital Data General Overview==
 
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The main goal of the data set is to aggregate company, fund, and round level data to be analyzed at a combined MSA and year level. The data set is compromised of two major parts: a granular company/fund/round and an aggregated CMSA-Year.  The data includes all United States Venture Capital transactions (moneytree) from the twenty-five year period of 1990 through 2015.
 
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The Hubs data set, from SDC Platinum, has been constructed in the server:
 
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Data files are in 128.42.44.181/bulk/Hubs
 
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All files are in 128.42.44.182/bulk/Projects/Hubs
 
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psql Hubs2
 
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Sql files:
 
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:<code>E:\McNair\Projects\Hubs\Data Script v10.txt</code>
 
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Note: We need to check that everything in '''Data Script v9 Ariel.txt''' has been incorporated into v10
 
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Table Header Rows + 5 lines:
 
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:<code>E:\McNair\Projects\Hubs\Data Table List v2.txt</code>
 
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Note: This was generated by '''Data Script v10.txt'''
 
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===Procedure - Granular Table===
 
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#Start with separate raw datasets for Companies, Funds, and Rounds - '''Locate Raw Datasets and Determine Pedigree'''
 
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#Add Data to Each Individual dataset (e.g. add MSA code)
 
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#Clean and standardize names (e.g. company or fund name) for each dataset
 
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#Join the Datasets (here we need to exclude undisclosed companies)
 
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===Procedure - CMSA-Year Table===
 
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#Create a consistent CMSA-Year table to be used later
 
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#Using the tables from the granular table, parse out the right data
 
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#Join the parsed out data with the CMSA-Year Table
 
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#Join these Tables
 
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==VC Specific Tables and Procedure==
 
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===Raw data tables===
 
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#'''Funds''': fund name, first investment date, last investment date, fund closing date, address, known investment, average investment, number of companies invested, MSA, MSA code.
 
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#'''Rounds''': round date, company name, state, round number, stage 1, stage 2, stage 3
 
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#'''Combined Rounds''': company name, round date, disclosed amount, investor
 
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#'''Companies''': company name, first investment, last investment, MSA, MSA code, address, state, date founded, known funding, industry
 
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#'''MSA List''': MSA, MSA code, CMSA, CMSA code
 
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#'''Industry List''': changes 6 industry categories to 4— ICT, Life Sciences, Semiconductors, Other
 
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===Granular Table (Fund-Round-Company)===
 
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The final table here contains all venture capital transactions by disclosed funds and portfolio companies, together with their CMSAs.
 
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To get the table, we processed the raw data sets in the following steps:
 
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#Clean '''Company''' data
 
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##Import raw data companies
 
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##Add variable 'CMSA' from data set MSA list, update variable 'industry' by joining data set industry list
 
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##Remove duplicates and remove undisclosed companies
 
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#Clean '''Fund''' data
 
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##Import raw data funds
 
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##Add variable 'CMSA'
 
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##Remove duplicates and remove undisclosed funds
 
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##Match fund names with itself using [[The Matcher (Tool) |The Matcher]] to get the standard fund names
 
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#Clean '''Round''' data
 
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##Import raw data rounds and combined rounds
 
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##Add variables 'number of investment', 'estimated investment' and 'year'
 
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##Remove duplicates and remove undisclosed funds
 
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#'''Combine''' '''Companies''' and '''Rounds'''
 
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##Combine cleaned companies and rounds data table on company names
 
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##Add variable 'round number' and 'stage'
 
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##Remove duplicates
 
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#'''Combine''' '''Funds''' and '''rounds-companies'''
 
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##Match fund names in rounds data table with standard fund names using [[The Matcher (Tool) |The Matcher]] to standardize fund names in rounds data table
 
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##Join standard fund names to rounds-companies table
 
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##Join cleaned funds table to rounds-companies table on standard fund names
 
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Note: This was done by Ariel and then edited by Todd.
 
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===CMSA-Year Aggregated Table===
 
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The original MSA to CMSA was done by Rachel and used here. '''LOCATE THE FILE!!!'''
 
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The final table contains number of companies and amount of investment, categorized by distance and stages, of each CMSA.
 
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We processed data as follows:
 
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#Create the '''CMSA-Year''' Table
 
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##Create single variable tables: Distinct CMSA, year, stage, found year of fund and found year of company.
 
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##Create the cross production tables: CMSA-year, CMSA-year-fund year founded and CMSA-year-company year founded
 
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#Draw data from cleaned companies, funds and rounds tables
 
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##Create a table with 'CMSA', 'number of companies' and 'year Founded' from cleaned companies table and join it to CMSA -year founded
 
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##Create a table with 'Company CMSA', 'round year', 'disclosed amount' from rounds-companies combined table, and add stage binary variables. Join it to CMSA-year-company year founded
 
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##Create a table with 'CMSA', 'fund year', 'number of investors' from cleaned funds table and join it to CMSA-year-fund year founded
 
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#Create '''near-far''' and stages table
 
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##Add fund data to rounds-companies
 
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##Create near-far and stages binary variable
 
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##Count investment and deals by CMSA and year, categorized by near-far and stages
 
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#Combine all tables by CMSA and round-year
 
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==Supplementary Data Sets==
 
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Supplementary data sets are cleaned and joined back to CMSAyear table on CMSA and year:
 
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#Number of STEM graduate student, by university and year(2005 to 2014).
 
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#University R&D spending, by university and year(2004 to 2014).
 
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#Income per capital, by MSA and year(2000 to 2012)
 
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#Wages and salaries, by MSA and year(2000 to 2012)
 
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All of these files were created originally by Rachel. Some were cleaned in Excel. No new data was added (some extra cols, no extra rows).
 
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The datasets can respectively be found at:
 
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E:\McNair\Projects\Hubs\STEM grads for upload v2.xls
 
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  --Contains: university zipcode newmsacode msa msacode cmsa cmsacode year nostudents
 
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  --CMSA code inside sheet seems to be ours. Check with Ariel.
 
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E:\McNair\Projects\Hubs\NSF spending for upload.xls
 
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  --Contains: Institution MSA CMSA code Year Spending
 
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  --We think the CMSA Code is ours. Check with Ariel.
 
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E:\McNair\Projects\Hubs\Income per capita upload.xls
 
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  --Contains: Fips Area Year Income
 
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  --Lookup to CMSA was done using VLOOKUPs in Excel. See Matcher Helper vTR.xls, and other Matcher Helper ???.xls files
 
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E:\McNair\Projects\Hubs\Wage for upload v2.xls
 
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  --Contains: Fips MSA Year Wage
 
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  --Lookup to CMSA was done using VLOOKUPs in Excel. See Matcher Helper vTR.xls, and other Matcher Helper ???.xls files
 
  
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=Resources=
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==Resources==
  
 
===Additional Resources===
 
===Additional Resources===

Revision as of 12:14, 20 June 2017

Academic Paper
Title Hubs (Academic Paper)
Author Ed Egan, Yael Hochberg
RAs Ariel Sun
Status In development
© edegan.com, 2016


Hubs Pages


Abstract

The Hubs Research Project is a full-length academic paper analyzing the effectiveness of "hubs", a component of the entrepreneurship ecosystem, in the advancement and growth of entrepreneurial success in a metropolitan area.

This research will primarily be focused on large and mid-sized Metropolitan Statistical Areas (MSAs), as that is where the greater majority of Venture Capital funding is located.

A general overview of entrepreneurial ecosystems can be found here: Entrepreneurial Ecosystem.


Current Work

General Overview

Currently there are 3 major tasks being performed (list to be updated):

  1. Creation of VC data table: UPDATE: Complete (see completed work section below)
  2. Creation of Hubs Dataset: UPDATE: See current work in progress for updates We will collect key variables for potential Hubs.
  3. Hazard Rate Model: UPDATE: (7/11) Spoke to Xun Tang, econometrics professor in Rice's Economics Department, and now looking for appropriate proportional rate hazard models with time varying covariates. In order to perform our diff-diff model, we need to match MSAs. In order to do so, we will be using a hazard rate model to produce a probability that a MSA gets a Hub and compare MSAs that do and don't have hubs with similar probabilities.


Resources

Additional Resources

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