nep-dem New Economics Papers
on Demographic Economics
Issue of 2020‒06‒15
three papers chosen by
Héctor Pifarré i Arolas
Universitat Pompeu Fabra

  1. Immigration, Innovation, and Growth By Burchardi, Konrad B.; Chaney, Thomas; Hassan, Tarek Alexander; Tarquinio, Lisa; Terry, Stephen
  2. Beyond Birthweight: The Origins of Human Capital By Conti, Gabriella; Hanson, Mark; Inskip, Hazel; Crozier, Sarah; Cooper, Cyrus; Godfrey, Keith
  3. A Comparison of Living Standards Across the States of America By Elena Falcettoni; Vegard Nygaard

  1. By: Burchardi, Konrad B.; Chaney, Thomas; Hassan, Tarek Alexander; Tarquinio, Lisa; Terry, Stephen
    Abstract: We show a causal impact of immigration on innovation and dynamism in US counties. To identify the causal impact of immigration, we use 130 years of detailed data on migrations from foreign countries to US counties to isolate quasi-random variation in the ancestry composition of US counties that results purely from the interaction of two historical forces: (i) changes over time in the relative attractiveness of different destinations within the US to the average migrant arriving at the time and (ii) the staggered timing of the arrival of migrants from different origin countries. We then use this plausibly exogenous variation in ancestry composition to predict the total number of migrants flowing into each US county in recent decades. We show four main results. First, immigration has a positive impact on innovation, measured by the patenting of local firms. Second, immigration has a positive impact on measures of local economic dynamism. Third, the positive impact of immigration on innovation percolates over space, but spatial spillovers quickly die out with distance. Fourth, the impact of immigration on innovation is stronger for more educated migrants.
    Keywords: dynamism; Endogenous Growth; Innovation; Migrations; patents
    JEL: J61 O31 O40
    Date: 2020–05
  2. By: Conti, Gabriella (University College London); Hanson, Mark (University of Southampton); Inskip, Hazel (University of Southampton); Crozier, Sarah (University of Southampton); Cooper, Cyrus (University of Southampton); Godfrey, Keith (University of Southampton)
    Abstract: Birth weight is the most widely used indicator of neonatal health, mainly because it is routinely recorded in birth registries. But are better measures available? We use unique data including fetal ultrasounds to show that more specific measures of the fetus and of the newborn are more informative about the prenatal environment and more predictive of child health and development, beyond birth weight. Our results are robust to correcting for measurement error and accounting for child- and mother-specific unobserved heterogeneity. Our analysis rationalizes a common finding in the early origins literature, that prenatal events can influence postnatal development without aecting birth outcomes.
    Keywords: birth weight, fetal development, child health, developmental origins, measurement
    JEL: I12 J13 J24
    Date: 2020–05
  3. By: Elena Falcettoni; Vegard Nygaard
    Abstract: We use an expected utility framework to examine how living standards vary across the United States and how each state's living standards have evolved over time. Our welfare measure accounts for cross-state variations in mortality, consumption, education, inequality, and cost of living. We find that per capita income is a good indicator of living standards, with a correlation of 0.80 across states. Living standards in most states, however, appear closer to those in the richest states than their difference in per capita income would suggest. Whereas high-income states benefit from higher life expectancy, consumption, and college attainment, low-income states benefit from lower cost of living. All states experienced positive welfare growth, and hence rising living standards, between 1999 and 2015. The annual welfare growth rate, however, varied from 1.38 to 3.76 percent across states due to varying gains in life expectancy, consumption, and college attainment, with life ex pectancy accounting for 50.3 percent of the variation. Finally, the growth rate of per capita income is a poor proxy for how fast living standards are rising in a particular state since the correlation between welfare growth and per capita income growth is only 0.38, and deviations are often large.
    Keywords: Expected utility; Living standards; Inequality; Cost of living; Welfare comparison; States of America; Quality of life
    JEL: D63 I31 O50 R13
    Date: 2020–05–22

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