Aaronson, D., Mazumder, B.: Intergenerational economic mobility in the United States, 1940 to 2000. J. Hum. Resour. 43(1), 139–172 (2008)
Google Scholar
Arlot, S., Celisse, A.: A survey of cross-validation procedures for model selection. Stat. Surv. 4(2010), 40–79 (2010)
Athey, S., Imbens, G.W.: The state of applied econometrics: causality and policy evaluation. J. Econ. Perspect. 31(2), 3–32 (2017)
Article
Google Scholar
Belloni, A., Chernozhukov, V., Hansen, C.: High-dimensional methods and inference on structural and treatment effects. J. Econ. Perspect. 28(2), 29–50 (2014)
Article
Google Scholar
Björklund, A., Jäntti, M.: Intergenerational income mobility in Sweden compared to the United States. Am. Econ. Rev. 87(4), 1009–1018 (1997)
Google Scholar
Björklund, A., Jäntti, M.: Intergenerational income mobility and the role of family background. In: Salverda, W., Nolan, B., Smeeding, T. (eds.) Handbook of Economic Inequality. Oxford University Press, Oxford (2009)
Blanden, J.: Cross-country rankings in intergenerational mobility: a comparison of approaches from economics and sociology. J. Econ. Surv. 27(1), 38–73 (2013)
Article
Google Scholar
Blundell, J., Risa, E.: Income and family background: are we using the right models?Available at SSRN: https://ssrn.com/abstract=3269576 or https://doi.org/10.2139/ssrn.3269576 (2019)
Brunori, P., Ferreira, F.H.G., Peragine, V., Piraino, P., Van der Weide, R., Bloise, F., Gupta, R., Gasparini, L., Lakner, C., Luppi, F., Mahler, D., Narayan, A., Neidhöfer, G., Palmisano, F., Randazzo, T., Rampino, T., Serlenga, L., Serrano, J., Triventi, M.: Equal chances: equality of opportunity and intergenerational mobility around the world. University of Bari, mimeo (2020)
Chen, W.-H., Ostrovsky, Y., Piraino, P.: Lifecycle variation, errors-in-variables bias and nonlinearities in intergenerational income transmission: new evidence from Canada. Labour Econ. 44, 1–12 (2017)
Article
Google Scholar
Chetty, R., Hendren, N., Kline, P., Saez, E.: Where is the land of opportunity? The geography of intergenerational mobility in the United States. Quart. J. Econ. 129(4), 1553–1623 (2014)
Article
Google Scholar
Clark, G.: The son also rises: surnames and the history of social mobility. Princeton University Press,Princeton (2014)
Corak, M.: Do poor children become poor adults? Lessons from a cross-country comparison of generational earnings mobility. Res. Econ. Inequality 13(1), 143–188 (2006)
Article
Google Scholar
Corak, M.: Income inequality, equality of opportunity, and intergenerational mobility. J. Econ. Perspect. 27(3), 79–102 (2013)
Article
Google Scholar
Efron, B., Hastie, T., Johnstone, I., Tibshirani, R.: Least angle regression. Ann. Stat. 32, 407–451 (2004)
Article
Google Scholar
Emran, M.S., Shilpi, F.J.: Economic approach to intergenerational mobility: Measures, methods, and challenges in developing countries. (No. 2019/98). UNU-WIDER Working Paper(2019)
Finn, A., Leibbrandt, M., Ranchhod, V.: Patterns of persistence: Intergenerational mobility and education in South Africa. Cape Town: SALDRU, UCT. (SALDRU Working Paper Number 175/ NIDS Discussion Paper 2016/2)(2017)
Gong, H., Leigh, A., Meng, X.: Intergenerational income mobility in urban China. Rev. Income Wealth 58(3), 481–503 (2012)
Article
Google Scholar
Haider, S., Solon, G.: Life-cycle variation in the association between current and lifetime earnings. Am. Econ. Rev. 96(4), 1308–1320 (2006)
Article
Google Scholar
Hastie, T., Tibshirani, R., Friedman, J.: The elements of statistical learning: data mining, inference, and prediction. Springer Science & Business Media, Berlin (2009)
Hastie, T., Tibshirani, R., Tibshirani, R.J.: Extended comparisons of best subset selection, forward stepwise selection, and the lasso. arXiv preprint arXiv:1707.08692(2017)
James, G., Witten, D., Hastie, T., Tibshirani, R.: “An introduction to statistical learning”. Springer, New York (2013)
Jerrim, J., Choi, A., Simancas, R.: Two-Sample Two-Stage Least Squares (TSTSLS) estimates of earnings mobility: how consistent are they? Surv. Res. Methods 10(2), 85–102 (2016)
Google Scholar
McKenzie, D., Sansone, D.: Predicting entrepreneurial success is hard: Evidence from a business plan competition in Nigeria. J. Dev. Econ. 141, 1–18.(2019)
Meinshausen, N.: Relaxed Lasso. Comput. Stat. Data Anal. 52, 374–393 (2007)
Mullainathan, S., Spiess, J.: Machine learning: an applied econometric approach. J. Econ. Perspect. 31(2), 87–106 (2017)
Article
Google Scholar
Narayan, A., Van der Weide, R., Cojocaru, A., Lakner, C., Redaelli, S., Mahler, D.G., Ramasubbaiah, R.G., Thewissen, S.: Fair Progress? In: Economic mobility across generations around the world. World Bank Group,Washington, DC (2018)
Nybom, M., Stuhler, J.: Heterogeneous income profiles and lifecycle bias in intergenerational mobility estimation. J. Hum. Resour. 51(1), 239–268 (2016)
Article
Google Scholar
Olivetti, C., Paserman, D.: In the name of the son (and the Daughter): intergenerational mobility in the United States. Am. Econ. Rev. 105(8), 1850–1940 (2015)
Article
Google Scholar
Piraino, P.: Intergenerational earnings mobility and equality of opportunity in South Africa. World Dev. 67, 396–405 (2015)
Article
Google Scholar
Santavirta, T., Stuhler, J.: Name-based estimators of intergenerational mobility. Mimeo., Stockholm University (2020)
Schonlau, M.: BOOST: Stata module to perform boosted regression. Available at: https://ideas.repec.org/c/boc/bocode/s458541.html (2018)
Solon, G.: Intergenerational income mobility in the United States. Am. Econ. Rev. 82(3), 393–408 (1992)
Google Scholar
Solon, G.: Cross-country differences in intergenerational earnings mobility. J. Econ. Perspect. 16(3), 59–66 (2002)
Article
Google Scholar
Townsend, W.: ELASTICREGRESS: Stata module to perform elastic net regression, lasso regression, ridge regression. Available at: https://ideas.repec.org/c/boc/bocode/s458397.html (2017)
Varian, H.: Big data: new tricks for econometrics. J. Econ. Perspect. 28(2), 3–27 (2014)
Article
Google Scholar
Zou, H., Hastie, T.: Regularization and variable selection via the elastic net. J. Roy. Stat. Soc. B 67.2, 301–320.” (2005)
Article
Google Scholar
Zou, Y.R., Schonlau, M.: RFOREST: Stata module to implement Random Forest algorithm. Available at: https://ideas.repec.org/c/boc/bocode/s458614.html (2019)