1 separately for each critical period k, results in which we aggregate over temperature bins j to examine more parsimonious forms of temperature heterogeneity j ? [ < 0 °C, 0–24 °C, 24–28 °C, 28–32 °C, 32+ °C], results for outcomes at different follow-up ages, and results using different sets of outcome variables. Finally, we estimate regressions that include additional interaction terms between T e m p c d t j k and our county ? year measure of AC adoption, while also including the main effects of county AC exposure, y i r g c d t = ? k ? j [ ( ? j k T c d t j k ) + ? j k ( T c d t j k ? A C c t ) + P c d t k ? ] + ? A C c t + ? r g c d + ? t + ? i r g c d t , where the new set of coefficients ? j k provides an estimate of the dose–response relationship of earnings at ages 29–31 y to early childhood temperature exposure in various critical periods and in hypothetical counties that have 100% of households with AC in the county ? year (i.e., where A C c t = 1 ). This specification tests the extent to which AC can mitigate the effects of extremely hot temperature days on long-run outcomes.
The baseline model delivers 54 regression coefficients (9 temperature bins j and 6 critical periods k). We summarize our results graphically to better interpret the large number of coefficients. Our table-form results rely on more parsimonious specifications with fewer temperature bins j ? [ < 0 °C, 0–24 °C, 24–28 °C, 28–32 °C, 32+ °C], with j ? [0–24 °C] as the omitted category. We conduct inference using standard errors clustered at the state level to account for various forms of both spatial and temporal dependence in the data. Clustering at the state level gives comparable standard errors to approaches that more specifically model the covariance of error terms between counties as a function of distance (40), while also remaining computationally easier to implement (41).
The study explained might have been authorized by the College or university out-of Ca within Berkeley Organization Remark Panel as well as the College out-of California within Santa Barbara Workplace of Research Individual Victims Committee.
We plus consider if observed different variation be able to help you mitigate some of the direct biological outcomes of temperatures towards the long-label financial effects. Adaptation in order to extreme temperature could occur because of psychological acclimatization (i.elizabeth., alterations in skin blood circulation, metabolism, outdoors practices, and you will key heat) (21), short-run temporal replacing anywhere between affairs (we.elizabeth., restricting go out spent external), or even the adoption out-of a whole lot more long lasting strategies regarding heat control such as for example because air conditioning (AC), and this i investigation here.
We 2nd check out results from analytical habits you to definitely just be sure to target these issues while also flexibly acting the heat–people money matchmaking
To get a feeling of the newest you can easily scale and scope regarding brand new influence of extreme temperature towards person financing development, we earliest take a look at the relationship within conditional mean earnings within years 31 and also the conditional suggest heat having confirmed few days off beginning. Continue reading We establish multiple reliable specifications that are included with results in which we estimate Eq