Hubs Analysis 2017
|Hubs Analysis 2017|
|Has title||Hubs Analysis 2017|
|Has owner||Hira Farooqi|
|Has start date|
|Has deadline date|
|Has keywords||Data Analysis|
|Has project status||Subsume|
|Has sponsor||McNair Center|
|Has project output||Data|
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Analysis Stage 1
The results are based on preliminary data analysis. The do-file that performs some analysis is located here:
It is titled load_vc_hubs_data.do.
The sample of hubs used at this stage is the 29-30 hubs that were shortlisted in summer 2016. After data cleaning we get a sample of ~ 25 hubs. Important observations from initial fixed effects regressions are:
- The sign of correlation between vc funding and the presence of hubs is very sensitive to the measure of vc funding. It is positive for early investment and negative for later investments.
- The size and significance of the correlation is sensitive to number of deals vs the amount of funding. Results are more significant for number of deals compared to the results for value of the deals.
- Including SBIR data significantly reduces the number of groups in the panel and hence the sample size.
All the final data files related to Hubs analysis are located here:
- The stata do file hubs_load_data.do uploads the final hubs data file. This is the raw data that includes variables early funding, late funding, number of early funding deals, number of late funding deals, dummies for whether a hub is present etc. The do file processes data, creates more variables. It also estimates the hazard rate model, and matches the sample based on estimated hazard ratios. It eliminates all city_states that were never matched with a neighbor in ANY year from 2000-2017. The output from this file is matched_hubs.dta.
- We need a panel data with controls and treatments, such that for each matched control-treatment pair, with pairid = n, in matched_hubs.dta we assign the same pairid = n to observations of city_states 2 periods before and after they were assigned control and treatment status originally. The matlab code in time_matching_hubs.m performs this. However the resulting panel has problems of overlap. For instance if chicago_2008 was treatment and boulder_2014 was control with pair id 200 in the original hazard rate match, chicago_2009 is a control in some pair 203 and this observation gets matched with our pair id 200. Need to resolve this.
- The stata do file hubs_load_clean.do uploads this final panel data set - but this panel has the problem of overlaps discussed above.