Methodological notes

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Battaglia, M. P., Frankel, M. and Hoaglin, D. (2009). Practical considerations in raking survey data. Survey Practice, 2(5): 1-10.

Deming, E. W. and Stephan, F. F. (1940). On a Least Squares Adjustment of a Sampled Frequency Table When the Expected Marginal Totals are Known. Annals of Mathematical Statistics, 11(4): 427–444.

Everitt, B.S., Landau, S., Leese, M. and Stahl, D. (2011). Cluster Analysis. Wiley Series in Probability and Statistics. Wiley.

Frölich, M. (2004). Finite-sample properties of propensity-score matching and weighting estimators. The Review of Economics and Statistics 86(1):77-90.

Kolenikov, S. (2014). Calibrating survey data using iterative proportional fitting (raking). The Stata Journal, 14(1): 22-59.

Kraemer-Eis, H., Botsari, A., Gvetadze, S., Lang, F. and Torfs, W. (2019). European Small Business Finance Outlook: December 2017. EIF Working Paper 2019/57. EIF Research & Market Analysis. June 2019.

Pavlova, E. and Signore, S. (2019). The European venture capital landscape: an EIF perspective. Volume V: The economic impact of VC investments supported by the EIF. EIF Working Paper 2019/55, EIF Research & Market Analysis. April 2019.

Rosenbaum, P.R. and Rubin, D.B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1): 41–55.

Rubin, D.B. (1974). Estimating causal effects of treatments in randomized and nonrandomized studies. Journal of Educational Psychology, 66(5): 688–701.

Signore, S. (2016). The European venture capital landscape: an EIF perspective. Volume II: Growth patterns of EIF-backed startups. EIF Working Paper 2016/38, EIF Research & Market Analysis. December 2016.

Skrondal, A. and Rabe-Hesketh, S. (2004). Generalized latent variable modeling: Multilevel, longitudinal, and structural equation models. Chapman and Hall/CRC.