Thesis advisor: Thomas J. Chemmanur / My dissertation consists of three chapters. In the first chapter, I study the impact of a place-based tax credit policy, the Opportunity Zone program created under the Tax Cuts and Jobs Act of 2017, on local private investments and entrepreneurship. Using a difference-in-differences approach and comparing census tracts designated as Opportunity Zones and other eligible but non-designated tracts, I find that the policy has drawn significantly more private investments to economically distressed areas. Surprisingly, however, these private investments have led to decreases in local new business registration. The decrease in entrepreneurship was mainly in the non-tradable sector, which is more sensitive to local conditions than the tradable or construction sector. Further robustness tests suggest that the above results are causal. I provide one explanation for the above findings that more private investments went to existing and older firms in Opportunity Zones, discouraging potential entrepreneurs from competing with the better-financed firms locally.
In the second chapter, I examine how changes in investor protection regulations affect local entrepreneurial activity, relying on the heterogeneous impact of a 2011 SEC regulation change on the definition of accredited investors across U.S. cities. Using a difference-in-differences approach, I show that cities more affected by the regulation change experienced a significantly larger decrease in local angel financing, entrepreneurial activity, innovation output, employment, and sales. I find that small business loans and second-lien mortgages became entrepreneurs’ partial substitutes for angel investment. My cost-benefit analysis suggests that the costs of protecting angel investors through the 2011 regulation change outweigh its benefits.
In the third chapter, which is co-authored with Thomas Chemmanur and Harshit Rajaiya, we address three important research questions by using a large sample of angel and venture capital (VC) financing data from the Crunchbase and VentureXpert databases and private firm data from the NETS database. First, we analyze the relative extent of value addition by angels versus VCs to startup firms. We show that startups financed by angels rather than VCs are associated with a lower likelihood of successful exit (IPO or acquisition), lower sales and employment growth, lower quantity and quality of innovation, and lower net inflow of high-quality inventors. We disentangle selection and monitoring effects using instrumental variable (IV) and switching regression analyses and show that our baseline results are causal. Second, we investigate the complementarity versus substitution relationship between angel and VC financing. We find that a firm that received a larger fraction of VC or angel financing in the first financing round is likely to receive a larger fraction of the same type of financing in a subsequent round; however, when we include other non-VC financing sources such as accelerators and government grants into the analysis, a firm that received angel (rather than other non-VC) financing in the first round is also more likely to receive VC financing in a subsequent round. Third, we analyze how the financing sequence (order of investments by angels and VCs across rounds) of startup firms is related to their successful exit probability. We find that firms that received primarily VC financing in the first round and continued to receive VC financing in subsequent rounds (VC-VC) or those that received primarily angel financing in the first round and received VC financing in subsequent rounds (Angel-VC) have a higher chance of successful exit compared to those with other financing sequences (VC-Angel or Angel-Angel). / Thesis (PhD) — Boston College, 2022. / Submitted to: Boston College. Carroll School of Management. / Discipline: Finance.
| Identifer | oai:union.ndltd.org:BOSTON/oai:dlib.bc.edu:bc-ir_109386 |
| Date | January 2022 |
| Creators | Xu, Jiajie |
| Publisher | Boston College |
| Source Sets | Boston College |
| Language | English |
| Detected Language | English |
| Type | Text, thesis |
| Format | electronic, application/pdf |
| Rights | Copyright is held by the author, with all rights reserved, unless otherwise noted. |
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