Entrepreneurial performance is often right-skewed and heavy-tailed, yet empirical studies typically focus on average outcomes, assuming normality. Recent research addresses this by examining full performance distributions. We extend this work by introducing an intuitive framework with three distinct characteristics of distributional tails: (a) tail impact, the contribution of star performers relative to the rest; (b) tail extremity, the extent by which the highest performer exceeds the typical performer; and (c) tail frequency, the fraction of performers who are stars. We outline a methodological guide, offer illustrative examples, and provide R code to enrich future investigations of star performance in entrepreneurship.
AkinshinA. (2024). Trimmed Harrell-Davis quantile estimator based on the highest density interval of the given width. Communications in Statistics-Simulation and Computation, 53(3), 1565–1575.
8.
AldrichH. E.MartinezM. A. (2001). Many are called, but few are chosen: An evolutionary perspective for the study of entrepreneurship. Entrepreneurship Theory and Practice, 25(4), 41–56.
9.
AlfaranoS.MilakovićM. (2008). Does classical competition explain the statistical features of firm growth?Economics Letters, 101(3), 272–274.
10.
AllisonP. D. (1978). Measures of inequality. American Sociological Review, 865–880.
11.
AndersonB. S.WennbergK.McMullenJ. S. (2019). Enhancing quantitative theory-testing entrepreneurship research. Journal of Business Venturing, 34(5), 105928.
12.
AndrianiP.McKelveyB. (2009). From Gaussian to Paretian thinking: Causes and implications of power laws in organizations. Organization Science, 20(6), 1053–1071.
13.
AndrianiP.McKelveyB. (2011). From skew distributions to power-law science. In AllenP.MaguireS.McKelveyB. (Eds.), The Sage handbook of complexity and management (pp. 254–273). Sage Publications Ltd.
14.
ArachchigeC. N.PrendergastL. A.StaudteR. G. (2022). Robust analogs to the coefficient of variation. Journal of Applied Statistics, 49(2), 268–290.
15.
ArikanI.ShenkarO. (2013). National animosity and cross-border alliances. Academy of Management Journal, 56(6), 1516–1544.
16.
BalandaK. P.MacGillivrayH. L. (1988). Kurtosis: A critical review. The American Statistician, 42(2), 111–119.
17.
BeamishP. W.HasseV. C. (2022). The importance of rare events and other outliers in global strategy research. Global Strategy Journal, 12(4), 697–713.
18.
BeckerT. E.RobertsonM. M.VandenbergR. J. (2019). Nonlinear transformations in organizational research: Possible problems and potential solutions. Organizational Research Methods, 22(4), 831–866.
19.
Ben-HafaïedhC.HamelinA. (2023). Questioning the growth dogma: A replication study. Entrepreneurship Theory and Practice, 47(2), 628–647.
20.
BerglundH.DimovD.WennbergK. (2018). Beyond bridging rigor and relevance: The three-body problem in entrepreneurship. Journal of Business Venturing Insights, 9, 87–91.
21.
BerkhoutP.HartogJ.Van PraagM. (2016). Entrepreneurship and financial incentives of return, risk, and skew. Entrepreneurship Theory and Practice, 40(2), 249–268.
22.
BooyaviZ.CrawfordG. C. (2023). Different, but same: A power law perspective on how rock star female entrepreneurs reconceptualize “gender equality.”Journal of Business Venturing Insights, 19, Article e00374.
23.
BorroniC. G.De CapitaniL. (2023). The relationship between shape parameters and kurtosis in some relevant models. Journal of the Korean Statistical Society, 52(3), 581–620.
24.
BottazziG.SecchiA. (2006). Gibrat’s law and diversification. Industrial and Corporate Change, 15(5), 847–875.
25.
BottazziG.SecchiA. (2011). A new class of asymmetric exponential power densities with applications to economics and finance. Industrial and Corporate Change, 20(4), 991–1030.
26.
BradleyK. J.AguinisH. (2023). Team performance: Nature and antecedents of non-normal distributions. Organization Science, 34(3), 987–1352.
27.
BrinkerinkJ. (2023). When shooting for the stars becomes aiming for asterisks: P-hacking in family business research. Entrepreneurship Theory and Practice, 47(2), 304–343.
BrownR.MawsonS.MasonC. (2017). Myth-busting and entrepreneurship policy: The case of high growth firms. Entrepreneurship & Regional Development, 29(5–6), 414–443.
30.
CassarG. (2010). Are individuals entering self-employment overly optimistic? An empirical test of plans and projections on nascent entrepreneur expectations. Strategic Management Journal, 31(8), 822–840.
31.
CertoS. T.BusenbarkJ. R.KalmM.LePineJ. A. (2020). Divided we fall: How ratios undermine research in strategic management. Organizational Research Methods, 23(2), 211–237.
32.
CertoS. T.RaneyK.AlbaderL.BusenbarkJ. R. (2024). Out of shape: The implications of (extremely) nonnormal dependent variables. Organizational Research Methods, 27(2), 195–222.
33.
CirilloP. (2013). Are your data really Pareto distributed?Physica A: Statistical Mechanics and Its Applications, 392(23), 5947–5962.
34.
ClarkD. R.CrawfordG. C.PidduckR. J. (2023). Exceptionality in entrepreneurship: Systematically investigating outlier outcomes. Journal of Business Venturing Insights, 20, Article e00422.
35.
ClausetA.ShaliziC. R.NewmanM. E. (2009). Power-law distributions in empirical data. SIAM Review, 51(4), 661–703.
36.
CoadA. (2009). The growth of firms: A survey of theories and empirical evidence. Edward Elgar Publishing.
37.
CoadA.BornhällA.DaunfeldtS. O.McKelvieA. (2024). Scale-ups and high-growth firms: Theory, definitions, and measurement. Springer Nature.
38.
CoadA.FrankishJ. S.StoreyD. J. (2020). Too fast to live? Effects of growth on survival across the growth distribution. Journal of Small Business Management, 58(3), 544–571.
39.
CochraneJ. H. (2005). The risk and return of venture capital. Journal of Financial Economics, 75(1), 3–52.
40.
ConnellyB. L.IrelandR. D.ReutzelC. R.CoombsJ. E. (2010). The power and effects of entrepreneurship research. Entrepreneurship Theory and Practice, 34(1), 131–149.
41.
CrawfordG. C.AguinisH.LichtensteinB.DavidssonP.McKelveyB. (2015). Power law distributions in entrepreneurship: Implications for theory and research. Journal of Business Venturing, 30(5), 696–713.
42.
CrawfordG. C.JooH.AguinisH. (2024). Under the weight of heavy tails: A power law perspective on the emergence of outliers in entrepreneurship. Journal of Business Venturing Insights, 21, Article e00447.
43.
CrawfordG. C.LinderC.LechnerC.VillaniE. (2024). Outlier entrepreneurs: Nonlinear paths and novel ventures. Journal of Business Venturing Insights, 21, Article e00437.
44.
CrawfordG. C.SkorodziyevskiyV.FridC. J.NelsonT. E.BooyaviZ.HechavarriaD. M.LiX.ReynoldsP. D.TeymourianE. (2022). Advancing entrepreneurship theory through replication: A case study on contemporary methodological challenges, future best practices, and an entreaty for communality. Entrepreneurship Theory and Practice, 46(3), 779–799.
45.
CristelliM.ZaccariaA.PietroneroL. (2012). Universal relation between skewness and kurtosis in complex dynamics. Physical Review E—Statistical, Nonlinear, and Soft Matter Physics, 85(6), Article 066108.
CutoloD.KenneyM. (2021). Platform-dependent entrepreneurs: Power asymmetries, risks, and strategies in the platform economy. Academy of Management Perspectives, 35(4), 584–605.
48.
DavidssonP. (2021). It’s the product-market fit, stupid! Commentary on “Early indicators of very long-term venture performance: A 20-year panel study” by Eli Gimmon and Jonathan Levie. Academy of Management Discoveries, 7(2), 317–320.
49.
DavidssonP.GruenhagenJ. H. (2021). Fulfilling the process promise: A review and agenda for new venture creation process research. Entrepreneurship Theory and Practice, 45(5), 1083–1118.
50.
DavidssonP.ReckerJ.Von BrielF. (2020). External enablement of new venture creation: A framework. Academy of Management Perspectives, 34(3), 311–332.
51.
DavidssonP.WiklundJ. (Eds.). (2013). New perspectives on firm growth. Edward Elgar Publishing.
52.
DeanM. A.ShookC. L.PayneG. T. (2007). The past, present, and future of entrepreneurship research: Data analytic trends and training. Entrepreneurship Theory and Practice, 31(4), 601–618.
53.
DeCarloL. T. (1997). On the meaning and use of kurtosis. Psychological Methods, 2, 292–307.
54.
DeckerR.HaltiwangerJ.JarminR.MirandaJ. (2014). The role of entrepreneurship in US job creation and economic dynamism. Journal of Economic Perspectives, 28(3), 3–24.
55.
DelmarF.DavidssonP.GartnerW. B. (2003). Arriving at the high-growth firm. Journal of Business Venturing, 18(2), 189–216.
56.
DenrellJ.FangC.LiuC. (2015). Chance explanations in the management sciences. Organization Science, 26(3), 923–940.
57.
DenrellJ.LiuC. (2012). Top performers are not the most impressive when extreme performance indicates unreliability. Proceedings of the National Academy of Sciences, 109(24), 9331–9336.
58.
DenrellJ.LiuC. (2021). When reinforcing processes generate an outcome-quality dip. Organization Science, 32(4), 1079–1099.
59.
DoaneD. P.SewardL. E. (2011). Measuring skewness: A forgotten statistic?Journal of Statistics Education, 19(2) 47–53.
60.
DorogovtsevS. N.MendesJ. F. F. (2000). Evolution of networks with aging of sites. Physical Review E, 62(2), Article 1842.
61.
dos SantosP. L.ScharfenakerE. (2019). Competition, self-organization, and social scaling: Accounting for the observed distributions of Tobin’s Q. Industrial and Corporate Change, 28(6), 1587–1610.
62.
DownesP. E.LeeE. S. (2023). A relational view of shiftwork: Co-scheduling with higher performers. Human Resource Management, 62(4), 429–443.
63.
DunkelbergW.MooreC.ScottJ.StullW. (2013). Do entrepreneurial goals matter? Resource allocation in new owner-managed firms. Journal of Business Venturing, 28(2), 225–240.
64.
FanT.SchwabA.GengX. (2021). Habitual entrepreneurship in digital platform ecosystems: A time-contingent model of learning from prior software project experiences. Journal of Business Venturing, 36(5), 106140.
65.
FiebigD. G. (2001). Seemingly unrelated regression. In BaltagiB. H. (Ed.), A companion to theoretical econometrics (pp. 101–121). Blackwell.
66.
FoxJ. (2005). Nonparametric regression. In EverittB.HowellD. C. (Eds.), Encyclopedia of statistics in behavioral science (pp. 1426–1430). John Wiley & Sons.
67.
FreelM.GordonI. (2022). On the consequences of firm growth. International Small Business Journal, 40(6), 684–709.
68.
GalaK.SchwabA. (2024). Stars everywhere: Revealing the prevalence of star performers using empirical data published in entrepreneurship research. Journal of Business Venturing Insights, 22, Article e00492.
69.
GalaK.SchwabA.MuellerB. A. (2024). Star entrepreneurs on digital platforms: Heavy-tailed performance distributions and their generative mechanisms. Journal of Business Venturing, 39(1), Article 106347.
70.
GalaK.ValladaresC. D.MuellerB. A. (2023). Students’ assumptions of entrepreneurs’ performance: The paradox of excess entry and missed opportunity. Journal of Business Venturing Insights, 20, Article e00425.
71.
GibbertM.NairL. B.WeissM.HoeglM. (2021). Using outliers for theory building. Organizational Research Methods, 24(1), 172–181.
72.
GlaubM. E.FreseM.FischerS.HoppeM. (2014). Increasing personal initiative in small business managers or owners leads to entrepreneurial success: A theory-based controlled randomized field intervention for evidence-based management. Academy of Management Learning & Education, 13(3), 354–379.
73.
HarrellF. E.DavisC. E. (1982). A new distribution-free quantile estimator. Biometrika, 69(3), 635–640.
74.
HarrisonD. A.KleinK. J. (2007). What’s the difference? Diversity constructs as separation, variety, or disparity in organizations. Academy of Management Review, 32(4), 1199–1228.
75.
HartwigF. P.Davey SmithG.SchmidtA. F.SterneJ. A.HigginsJ. P.BowdenJ. (2020). The median and the mode as robust meta-analysis estimators in the presence of small-study effects and outliers. Research Synthesis Methods, 11(3), 397–412.
76.
HealyK.MoodyJ. (2014). Data visualization in sociology. Annual Review of Sociology, 40(1), 105–128.
77.
HendersonA. D.RaynorM. E.AhmedM. (2012). How long must a firm be great to rule out chance? Benchmarking sustained superior performance without being fooled by randomness. Strategic Management Journal, 33(4), 387–406.
78.
HogarthR. M.KarelaiaN. (2012). Entrepreneurial success and failure: Confidence and fallible judgment. Organization Science, 23(6), 1733–1747.
79.
HuntR. A.LernerD. A. (2017). Tales left tails tell: Addressing left-side truncation in strategy research (Working Paper No. 2017-04). Colorado School of Mines, Division of Economics and Business.
80.
HymerC. B.SmithA. D. (2024). Making exceptions exceptional: A cross-methodological review and future research agenda. Journal of Management, 50(6), 2374–2402.
JooH.AguinisH.BradleyK. J. (2017). Not all nonnormal distributions are created equal: Improved theoretical and measurement precision. Journal of Applied Psychology, 102(7), 1022–1053.
83.
KhuranaI.TamvadaJ. P.AudretschD. B. (2023). The weaker sex? A tale of means and tails. Journal of Business Venturing Insights, 20, Article e00407.
84.
KoenkerR. (2017). Quantile regression: 40 years on. Annual Review of Economics, 9(1), 155–176.
85.
KokkoH.MackenzieA.ReynoldsJ. D.LindströmJ.SutherlandW. J. (1999). Measures of inequality are not equal. The American Naturalist, 154(3), 358–382.
86.
KolokasD.VanackerT.VeredasD.ZahraS. A. (2022). Venture capital, credit, and fintech start-up formation: A cross-country study. Entrepreneurship Theory and Practice, 46(5), 1198–1230.
87.
KulichC.TrojanowskiG.RyanM. K.Alexander HaslamS.RenneboogL. D. (2011). Who gets the carrot and who gets the stick? Evidence of gender disparities in executive remuneration. Strategic Management Journal, 32(3), 301–321.
88.
LaherrereJ.SornetteD. (1998). Stretched exponential distributions in nature and economy: “Fat tails” with characteristic scales. The European Physical Journal B-Condensed Matter and Complex Systems, 2, 525–539.
89.
LeysC.DelacreM.MoraY. L.LakensD.LeyC. (2019). How to classify, detect, and manage univariate and multivariate outliers, with emphasis on pre-registration. International Review of Social Psychology, 32(1), 1–5.
90.
LeysC.LeyC.KleinO.BernardP.LicataL. (2013). Detecting outliers: Do not use standard deviation around the mean, use absolute deviation around the median. Journal of Experimental Social Psychology, 49(4), 764–766.
91.
LiM. (2015). Moving beyond the linear regression model: Advantages of the quantile regression model. Journal of Management, 41(1), 71–98.
92.
LimpertE.StahelW. A.AbbtM. (2001). Log-normal distributions across the sciences: Keys and clues; on the charms of statistics, and how mechanical models resembling gambling machines offer a link to a handy way to characterize log-normal distributions, which can provide deeper insight into variability and probability—Normal or log-normal; that is the question. BioScience, 51(5), 341–352.
93.
LinderC.MoulickA. G.LechnerC. (2023). Necessary conditions and theory-method compatibility in quantitative entrepreneurship research. Entrepreneurship Theory and Practice, 47(5), 1971–1994.
94.
LiuC.De RondM. (2016). Good night, and good luck: Perspectives on luck in management scholarship. Academy of Management Annals, 10(1), 409–451.
95.
LuJ.DimovD. (2023). A system dynamics modelling of entrepreneurship and growth within firms. Journal of Business Venturing, 38(3), 106285.
96.
MakinoS.ChanC. M. (2017). Skew and heavy-tail effects on firm performance. Strategic Management Journal, 38(8), 1721–1740.
MasonC. M.HarrisonR. T. (2002). Is it worth it? The rates of return from informal venture capital investments. Journal of Business Venturing, 17(3), 211–236.
99.
MaulaM.StamW. (2020). Enhancing rigor in quantitative entrepreneurship research. Entrepreneurship Theory and Practice, 44(6), 1059–1090.
100.
MicceriT. (1989). The unicorn, the normal curve, and other improbable creatures. Psychological Bulletin, 105(1), 156, 1–18.
101.
Miron-SpektorE.BearJ. B.EliavE. (2023). Think funny, think female: The benefits of humor for women’s influence in the digital age. Academy of Management Discoveries, 9(3), 281–296.
102.
MitzenmacherM. (2004). A brief history of generative models for power law and lognormal distributions. Internet Mathematics, 1(2), 226–251.
103.
MorrisonM.TobiasF. (1965). Some statistical characteristics of a peak to average ratio. Technometrics, 7(3), 379–385.
104.
MundtP.AlfaranoS.MilakovićM. (2016). Gibrat’s Law Redux: Think profitability instead of growth. Industrial and Corporate Change, 25(4), 549–571.
105.
MundtP.AlfaranoS.MilakovićM. (2020). Exploiting ergodicity in forecasts of corporate profitability. Journal of Economic Dynamics and Control, 111, Article 103820.
106.
MundtP.AlfaranoS.MilakovićM. (2022). Survival and the ergodicity of corporate profitability. Management Science, 68(5), 3726–3734.
NairJ.WiermanA.ZwartB. (2022). The fundamentals of heavy tails: Properties, emergence, and estimation. Cambridge University Press.
109.
NelsonR. R.WinterS. G. (1982). Evolutionary theory of economic change. Harvard University Press.
110.
NystromP. C.SoofiE. S.Yasai-ArdekaniM. (2010). Identifying and analyzing extremes: Illustrated by CEOs’ pay and performance. Organizational Research Methods, 13(4), 782–805.
111.
OanceaB.PirjolD. (2019). Extremal properties of the Theil and Gini measures of inequality. Quality & Quantity, 53(2), 859–869.
112.
O’BoyleE. H.GötzM. (2025). Rethinking stardom: A relativistic approach to studying the absolute best performers. Annual Review of Organizational Psychology and Organizational Behavior, 13, 1–30.
113.
ParkerS. C. (2005). The economics of entrepreneurship: What we know and what we don’t. Foundations and Trends in Entrepreneurship, 1(1), 1–54.
114.
ParkerS. C. (2007). Policymakers beware! In AudretschD. B.GriloI.ThurikA. R. (Eds.), The international handbook of entrepreneurship policy research (pp. 54–63). Edward Elgar.
115.
PinskyE.KlawanskyS. (2023). MAD (about median) vs. quantile-based alternatives for classical standard deviation, skewness, and kurtosis. Frontiers in Applied Mathematics and Statistics, 9, Article 1206537.
116.
RönkköM.AaltoE.TenhunenH.Aguirre-UrretaM. I. (2022). Eight simple guidelines for improved understanding of transformations and nonlinear effects. Organizational Research Methods, 25(1), 48–87.
117.
RousseeuwP. J.CrouxC. (1993). Alternatives to the median absolute deviation. Journal of the American Statistical Association, 88(424), 1273–1283.
118.
RousseeuwP. J.HubertM. (2011). Robust statistics for outlier detection. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 1(1), 73–79.
119.
RuefM.BirkheadC. (2024). Learning from outliers and anomalies. Academy of Management Perspectives, in press.
120.
RuefM.BirkheadC.AldrichH. (2023). What can outliers teach us about entrepreneurial success?Journal of Small Business and Enterprise Development, 30(3), 427–447.
121.
SætreA. S.Van de VenA. (2021). Generating theory by abduction. Academy of Management Review, 46(4), 684–701.
122.
ScharfenakerE.SemieniukG. (2017). A statistical equilibrium approach to the distribution of profit rates. Metroeconomica, 68(3), 465–499.
123.
SchwabA. (2018). Investigating and communicating the uncertainty of effects: The power of graphs. Entrepreneurship Theory and Practice, 42(6), 823–834.
124.
SchwabA.MinerA. S.O’TooleJ. (2025). Innovation learning-outcome variability: A convergence-divergence model for population-level learning. Organization Studies. Advance online publication. https://doi.org/10.1177/01708406251357841.
125.
SchwabA.StarbuckW. H. (2017). A call for openness in research reporting: How to turn covert practices into helpful tools. Academy of Management Learning & Education, 16(1), 125–141.
126.
SethnaJ. P. (2021). Statistical mechanics: Entropy, order parameters, and complexity. Oxford University Press.
127.
ShaneS. (2009). Why encouraging more people to become entrepreneurs is bad public policy. Small Business Economics, 33, 141–149.
128.
ShepherdD.WennbergK.SuddabyR.WiklundJ. (2019). What are we explaining? A review and agenda on initiating, engaging, performing, and contextualizing entrepreneurship. Journal of Management, 45(1), 159–196.
129.
ShepherdD.WiklundJ. (2009). Are we comparing apples with apples or apples with oranges? Appropriateness of knowledge accumulation across growth studies. Entrepreneurship Theory and Practice, 33(1), 105–123.
130.
SongY.LiuY.WangM.LanajK.JohnsonR. E.ShiJ. (2018). A social mindfulness approach to understanding experienced customer mistreatment: A within-person field experiment. Academy of Management Journal, 61(3), 994–1020.
131.
SornetteD. (2006). Critical phenomena in natural sciences: Chaos, fractals, self-organization and disorder: Concepts and tools. Springer Science & Business Media.
132.
SternadD.MödritscherG. (2022). Entrepreneurial leaps: Growth processes in transition phases between dynamic states. Entrepreneurship Theory and Practice, 46(4), 952–984.
133.
StumpfM. P.PorterM. A. (2012). Critical truths about power laws. Science, 335(6069), 665–666.
134.
SullivanJ. H.WarkentinM.WallaceL. (2021). So many ways for assessing outliers: What really works and does it matter?Journal of Business Research, 132, 530–543.
135.
TalebN. N. (2020). What you see and what you don’t see: The hidden moments of a probability distribution. arXiv preprint arXiv:2004.05894.
136.
TuretskyA. I. A. (2018). Making heads and tails of distributional patterns: A value-creation-type and sector-based analysis among private-equity-owned companies [Doctoral dissertation, Case Western Reserve University].
137.
Van SelstM.JolicoeurP. (1994). A solution to the effect of sample size on outlier elimination. The Quarterly Journal of Experimental Psychology Section A, 47(3), 631–650.
138.
VancouverJ. B.LiX.WeinhardtJ. M.SteelP.PurlJ. D. (2016). Using a computational model to understand possible sources of skews in distributions of job performance. Personnel Psychology, 69(4), 931–974.
139.
Vidal-TomásD.Ruiz-BufornA.Blanco-ArroyoO.AlfaranoS. (2022). A cross-sectional analysis of growth and profit rate distribution: The Spanish case. Mathematics, 10(6), Article 926.
140.
WalesW.BelitskiM.MartinJ. A.StettlerT. (2025). Breaking away from the pack: Uncovering the characteristics of exceptional firms in power-law performance distributions. Academy of Management Perspectives, in press.
141.
WennbergK.AndersonB. S. (2020). Enhancing the exploration and communication of quantitative entrepreneurship research. Journal of Business Venturing, 35(3), Article 105938.
142.
WestS. G.FinchJ. F.CurranP. J. (1995). Structural equation models with nonnormal variables: Problems and remedies. In HoyleR. H. (Ed.), Structural equation modeling: Concepts, issues, and applications (pp. 56–75). Sage Publications.
143.
WestfallP. H. (2014). Kurtosis as peakedness, 1905–2014. RIP. The American Statistician, 68(3), 191–195.
144.
WibbensP. D. (2024). A simple law for the distribution of long-term profit: The empirical regularity behind the 1% of firms that capture 73% of value. Organization Science, 36(4), 1531–1550.
145.
WiklundJ.DavidssonP.DelmarF. (2003). What do they think and feel about growth? An expectancy–value approach to small business managers’ attitudes toward growth. Entrepreneurship Theory and Practice, 27(3), 247–270.
146.
WilcoxR. R.KeselmanH. J. (2003). Modern robust data analysis methods: Measures of central tendency. Psychological Methods, 8(3), 254–274.
147.
WooffD. A.JamalzadehA. (2013). Robust and scale-free effect sizes for non-normal two-sample comparisons, with applications in e-commerce. Journal of Applied Statistics, 40(11), 2495–2515.
148.
XieX.LiL.ZhouG. (2023). Economic inequality and entrepreneurship: Micro-evidence from China. Strategic Entrepreneurship Journal, 17(1), 160–185.
149.
ZellnerA. (1962). An efficient method of estimating seemingly unrelated regressions and tests for aggregation bias. Journal of the American Statistical Association, 57(298), 348–368.
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