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|Has paper status=R and RPublished

<pdf>File*The final version was accepted to Research Policy on May 17th, 2021. *The 50-day share link is:MeasuringHGHTEntrepreneurshipEcosystemsV3-3https://authors.elsevier.pdf<com/pdf> a/1d8SaB5ASINVf *The title was changed to "A Framework for Assessing Municipal High-Growth High-Tech Entrepreneurship Policy"

This paper came from a presentation that I made to the Kauffman UMM Grant Cohort. I originally attempted to add empirics but this approach necessarily reduced the coverage of material: Although the framework The BibTeX reference is simple and used in practice, it is also on the frontier of research, so there aren't any published academic papers (pending update with the empirics. So I opted to break the original submission in two - breaking the empirics back out volume and leaving this as the best attempt I could make at a narrative-based exploration of the whole framework. It is, as a consequence, a very unusual paper. But most people I showed it to were enthusiastic. It is also reference-bait. Outside the review process, some readers were both amused and worried about its snarky tone, which I'm still trying to address.number):

This paper had a storied submission process: @article{EGAN2021104292,*The deadline title = {A framework for resubmission was June 15th, 2020. Before this deadlineassessing municipal high-growth high-technology entrepreneurship policy}, I emailed the editors and offered them either this version of the paper, which contains no empirics, or an empirical paper without examples or definitions. I received no response.*This version of the paper was submitted as an R&R to a Special Issue of journal = {Research Policy on June 10th}, 2020 pages = {104292}, with manuscript number RESPOL-D-19-01438R1. *On September 15th year = {2021}, I sent an email to the editors requesting information but received no response. *I wrote to the editors again on October 27th issn = {0048-7333}, this time using the Elvesier form doi = {https://doi.org/10.1016/j.respol.2021.104292}, to request another update. The last status reported by Elvesier ( url = {https://eeswww.elseviersciencedirect.com/respolscience/article/pii/defaultS0048733321000937}, author = {Edward J.asp) was 'Required Reviews Complete' on October 9thEgan}, keywords = {Entrepreneurship, Ecosystem, Measurement, High-growth high-technology, Venture capital, Ecosystem support organization, Pipeline, Raise rate, Policy cartel}, 2020.*On October 28th abstract = {This paper advances a framework for making rudimentary need, impact, I received an email saying: "Hello Edand cost–benefit assessments of municipal high-growth high-tech entrepreneurship policy. I hope to get back to you shortly. I have two good reviews The framework views ecosystem support organizations like accelerators, incubators, and I’m waiting on hubs as components in a thirdcity’s venture pipeline. This most definitely will be another R&R. More soon"*On November 8thA component’s pipeline size, I got an official email about the paper that said: "We have now received the referees' reports on your paperraise rate, copies of which I enclose below for your informationand cost per raise measure its performance. As you will seeIn total, the referees make various comments framework consists of eight objective and suggestions for improvement. I have given up reproducible measures based on the third reviewer quantities and qualities of venture capital investment and want to return 16 definitions of related terms-of-the paper to you-art." HoweverThese measures and definitions are illustrated in 26 real-world policy examples, this email only contained one review. I requested clarification which assess initiatives in Houston and noted that Reviewer 3 had asked for empiricsSt.On November 11th I got an email that said: "Hello Ed, This is strangeLouis over the last 20 years. The comments were examples reveal an enormous variation in the comments to the editorwelfare effects, and some policies appear welfare destroying. Here they are Many non-profit organizations claim success (and win awards and they are not worth that muchacclaim) using non-standard measures despite performing at less than half benchmark levels. Policy cartels, which control startup policy in many U. This special issue has a specific purposeS. '''You do not need cities, also engage in non-market actions to run regressions!'''" The comments are below as Reviewer 1. They indicate that the reviewer accepted the paperprotect their rents.} }

===2nd R&R=== Note that there Reviewer 2 never returned any comments. Summarizing reviewer 1's comment (reading between the lines):*The writing is currently pretty good: '''it is well done'''... '''the paper is polished'''... '''very nicely done'''.*It works as a whole. The reviewer didn't want anything cut: '''It is a collection of case studies and definitions''', and '''I don't have ... major comments'''. Reviewer 3's comments are more problematic. As is often the case, I wonder whether the reviewer actually read the paper:*The paper advances seven new measures, not 15 as the reviewer claims*Policy cartels are introduced in section 4.1 (out of 5), and aren't the main focus of the paper per se*I never use the entire battery of measures -- different measures are applicable in different contexts *A key point of the paper is to stop organizations from self-selecting into measures that they do well on*All bar two sentences of the 'substantive material' in the review (i.e., from "First..." to the end) don't mention anything to do with the paper! At this point in my career, I'm unique placed to give the response that every academic really wants to give to the 'self-aggrandizing idiot' that somehow always ends up controlling the fate of our hard work, namely: :"Dear Reviewer. After carefully considering your comments, I would like the offer the following response: I find your suggestions for my beautiful paper to puerile/irrelevant/narcissistic/useless/stupid/all-of-the-above (delete as appropriate), so I'm going to ignore them and, by extension, you. Up yours."  However, it does seem that '''some''' of reviewer 3's comments would lead to improvements in the paper. These are:#Being clearer that standardized measures aren't a panacea#A better discussion of gaming and incentives#Better framing in the front end of why these measures make sense (likely using the points from RFP for the special issue) I would need to address Reviewer 3's comments point-by-point, so here they are:#Consider possible downsides of each individual metric#Consider possible downsides in using the entire battery of measures#Test alternatives to this measurement approach#Discuss when "standardized measurement" improves outcomes, when it does, and perhaps how.#Discuss systematic bias due to gaming metrics incentivized by rewards attached to the measurement (old and new). Specifically, note that this behavioral change might have nothing to do with the underlying phenomenon of interest. (Think "Rewarding A While Hoping For B", etc., multitask, etc.)#Justify the choices in the reduction of the measurement space Measurement is often reductive: What is left out? Is it important? Discuss the difference between the conceptual phenomenon and how it is operationalized.#Test the effects of using a framework on various outcomes. In my letter to the reviewer, I can explain that this paper is for a special issue and that the editors and I have agreed that this should not be and an empirical paper and that should not contain regressions or other tests. That might tamp down their vitriol somewhat. ====Reviewer 1's Comments==== First of all, my sincere apologies to you and the authors for my very late report on the manuscript. Please excuse me for the delay.  The authors study measures of high-growth, high-tech entrepreneurship activity across the U.S. and provide concrete examples of how municipalities can use these to assess various policy initiatives. The authors claim that policy interventions at the municipal level have a significant impact on pre-venture startups, and that this has been missing from the extant academic literature.  Regarding my take on the paper: it is well done and given that it has already been revised once, I don't have many more major comments, but I do have one thing I would like to bring to your attention final file series was v4-6- although the paper is polished, it doesn't seem like an academic paper with extensive empirical analysis (in fact, it doesn't have even a single regression) or with an analytical model that enhances our understanding of theory (doesn't have a single equation either). It is a collection of case studies and definitions, albeit very nicely done. Given my area of expertise in entrepreneurial finance and my own experience publishing an empirical study in ResPol, I feel ill-equipped to offer a recommendation on whether or not this paper fits the scope of ResPol. I believe that is largely an editorial decision and you would be the best judge for it. So, I will let you decide on this bigger question and will skip my minor suggestions for the author. I hope that is alright.  ====Reviewer 3's Comments====  Reviewer #3: I'm recommending a major revision to the paper, which would likely constitute a lot of additional work, but I feel would greatly strengthen its contribution. The objective of this paper is establishing fifteen measures of HGHT entrepreneurship activity, and giving examples of their application and potential usefulness especially with regard to the behavior of what the author terms policy cartels. The defining of key terms is a useful contribution of this paper, as are the identification of potentially useful metrics of HGHT entrepreneurship. Furthermore, the examples are often helpful in highlighting their various applications. In my view, the major flaws in the study are not (1) considering possible downsides of each individual metric, (2) considering possible downsides in using the entire battery of measures, and (3) testing alternatives to this measurement approach. I briefly elaborate on these three points in the following paragraphs. In the conclusion, the author states that two antecedents to improved policy are "standardized measures, to reduce the information asymmetry between policymakers and constituents…and…a simple but grounded framework that can reduce the expertise required to develop and enact productive startup policy." First, it is not necessarily true that "standardized measurement" improves outcomes, such as policy, overall. Measurements are rarely if ever neutral (vis-à-vis behavior). Two examples are,* First, we often implicitly assume that more information in the hands of decision makers is unambiguously good. But this requires a lot of assumptions that do not hold in real life. An additional measure, say, would influence decision making but perhaps the distortion is welfare decreasing. Nassim Taleb gives the example of "value at risk" (VAR), a metric commonly used in finance, in the foreword of the book Lecturing Birds on Flying (pp. xvi).* Second, systematic bias due to gaming metrics incentivized by rewards attached to the measurement. Said differently, an agent would have the incentive to change behavior in the least costly way in order to maximize the payoff associated with the measurement---this behavioral change might have nothing to do with the underlying phenomenon of interest. By way of example, Weisbrod, Ballou, Asch in their book Mission and Money, discuss various measures used in university rankings published by US News & World Report, and how these are often finessed by schools in ways that have little to do with education (see pp. 64-65 for one such discussion). The point is, any conceived standardized framework is not necessarily better than nothing, and not all frameworks would be of equal value. I would have liked to see a more rigorous discussion of the merits of the framework purposed, which analysis would include at least the following:* Discussion of alternative calculations of a measure when applicable. For example, the paper's Measure 1 is a composite measure of three sub-measures: why was this particular normalization of sub-measures (i.e., ranking) used? Why was this particular aggregation method (i.e., summation) used? What are the upsides and downsides of this and other approaches? For example, "the flow of dollars" would have a long right tail, which is obliterated when transformed to a rank. Is this a good or bad thing and why?* Measurement is often reductive (in the sense that they constitute a mapping from a high-dimensional, potentially complex space, to a far simpler space). What is left out? Is it important? In part this translates to discussing the difference between the conceptual phenomenon and how it is operationalized?* Might a measure be systematically biased or lead to bias if implemented?* Tests of the effects of using a framework on various outcomes.In summary, more skepticism about the usefulness of the metrics and the framework, and more empiricism is necessary. ==Files== The files are in:

This The original Measuring HGHT Entrepreneurship Ecosystems paper was broken into two:*Measuring HGHT :'''A Framework for Assessing Municipal High-Growth High-Technology Entrepreneurship Ecosystems: This Policy''' now contains the definitions, measures, and exampleexamples. It is an informalinductive, bycase-example theory study paper.

The paper will use uses [[vcdb4VCDB20]] and [[US Startup City Ranking]], as well as a wealth of old McNair material. Sources include (copied to the project folder unless otherwise noted):