Macro Roundup

Daniel Kroening, "Software Ate the World, and Soon It Will Write Itself,"Wall Street Journal, December 3, 2020, https://www.wsj.com/articles/software-ate-the-world-and-soon-it-will-write-itself-11607037000

Andreas Fagereng, Magne Mogstad, Marte Rønning, "Why do wealthy parents have wealthy children?∗," University Of Chicago, June 2020, https://www.journals.uchicago.edu/doi/abs/10.1086/712446

Study looks at Korean-born children who were adopted at infancy by Norwegian parents (the distribution to parents was effectively random) thus removing any genetic component for lack of future/ or future successes. They look at the parents and then the kids outcomes in terms of net wealth, and financial wealth (they use the parents wealth btw 1994-1996 and the kids wealth btw 2012-2014)

Primary findings, “…We use the quasi-random assignment of the Korean-Norwegian adoptees to estimate the causal effects from a child being raised in one type of family versus another. Our findings show that family background matters significantly, even after removing the genetic connection between children and the parents raising them. In particular, adoptees raised by wealthy parents are more likely to be well off themselves, whereas adoptees’ stock market participation and portfolio risk are increasing in the financial risk taking of their adoptive parents….”
However they also look at biological children of parents where being genetically related to rich parents has a significant impact, "...To help interpret the economic significance of family background,we compare the intergenerational associations in wealth for adoptees to those for non-adopted children. This enables us to compare the predictive influence of parental wealth when there is and is not a genetic link between children and the parents raising them. We find that the intergenerational association in wealth is more than twice as large for parents and own birth children as compared to parents and adoptees..."

Overall findings, “…Strong intergenerational associations in wealth have fueled a longstanding debate over why children of wealthy parents tend to be well off themselves. We investigate the role of family background in determining children’s wealth accumulation and investor behavior as adults. The analysis is made possible by linking Korean-born children who were adopted at infancy by Norwegian parents to a population panel data set with detailed information on disaggregated wealth portfolios and socio-economic characteristics. The mechanism by which these Korean Norwegian adoptees were assigned to adoptive families is known and effectively random. We use the quasi-random assignment to estimate the causal effects from an adoptee being raised in one type of family versus another. Our findings show that family background matters significantly for children’s accumulation of wealth and investor behavior as adults, even when removing the genetic connection between children and the parents raising them. In particular, adoptees raised by wealthy parents are more likely to be well off themselves, whereas adoptees’ stock market participation and portfolio risk are increasing in the financial risk taking of their adoptive parents. The detailed nature of our data allows us to explore mechanisms, assess the generalizability of the lessons from adoptees, and compare our findings to results from behavioral genetics decompositions…. Figure 3 summarizes the dependence in net wealth across generations by displaying the relationship between parent and child ranks in the net wealth distributions.6 Panel A considers the non-adoptees, whereas panel B shows results for the Korean-Norwegian adoptees. We measure the percentile rank of parents based on their positions in the entire distribution of parental wealth, pooling parents of the non-adoptees and the Korean-Norwegian adoptees. Similarly, we define children’s percentile ranks based on their positions in the entire distribution of child wealth, including both the non-adoptees and adoptees. To adjust for differences in age across children and parents, we regress their wealth on a full set of indicator variables for child and parent birth years, and use the residuals from these regressions to measure child and parent ranks. Each dot represents the mean child rank (measured on the y-axis) for a given parental rank (measured on the x-axis). The solid thick line comes from a local linear regression of child wealth rank on parental wealth rank, the solid thin line is the estimated slope coefficient from a linear regression of child rank on parent rank, and the dashed line is the 45 degree line (representing perfect dependence). The linear rank correlations are 0.24 and 0.16 for the samples of non-adoptees and adoptees, respectively. This means that, on average, a 10 percentile increase in parent net wealth is associated with a 2.4 percentile increase in a biological child’s net wealth and a 1.6 percentile increase in an adoptees’ net wealth. The conditional expectation of child net wealth given parent net wealth is relatively linear in percentile ranks across most of the net wealth distribution. At the top of the net wealth distribution, however, the dependence is stronger than what is predicted from a linear regression of child rank on parent rank…”