Joshua Wilde, B. Apouey, Joseph Coleman, G. Picone
We examine the extent to which recent declines in child mortality and fertility in Sub-Saharan Africa can be attributed to insecticide-treated bed nets (ITNs). Exploiting the rapid increase in ITNs since the mid-2000s, we employ a difference-in-differences estimation strategy to identify the causal effect of ITNs on mortality and fertility. We show that the ITN distribution campaigns reduced all-cause child mortality, but surprisingly increased total fertility rates in the short run in spite of reduced desire for children and increased contraceptive use. We explain this paradox in two ways. First, we show evidence for an unexpected increase in fecundity and sexual activity due to the better health environment after the ITN distribution. Second, we show evidence that the effect on fertility is positive only temporarily – lasting only 1-3 years after the beginning of the ITN distribution programs – and then becomes negative. Taken together, these results suggest the ITN distribution campaigns may have caused fertility to increase unexpectedly and temporarily, or that these increases may just be a tempo effect – changes in fertility timing which do not lead to increased completed fertility.
{"title":"The Effect of Antimalarial Campaigns on Child Mortality and Fertility in Sub-Saharan Africa","authors":"Joshua Wilde, B. Apouey, Joseph Coleman, G. Picone","doi":"10.2139/ssrn.3452844","DOIUrl":"https://doi.org/10.2139/ssrn.3452844","url":null,"abstract":"We examine the extent to which recent declines in child mortality and fertility in Sub-Saharan Africa can be attributed to insecticide-treated bed nets (ITNs). Exploiting the rapid increase in ITNs since the mid-2000s, we employ a difference-in-differences estimation strategy to identify the causal effect of ITNs on mortality and fertility. We show that the ITN distribution campaigns reduced all-cause child mortality, but surprisingly increased total fertility rates in the short run in spite of reduced desire for children and increased contraceptive use. We explain this paradox in two ways. First, we show evidence for an unexpected increase in fecundity and sexual activity due to the better health environment after the ITN distribution. Second, we show evidence that the effect on fertility is positive only temporarily – lasting only 1-3 years after the beginning of the ITN distribution programs – and then becomes negative. Taken together, these results suggest the ITN distribution campaigns may have caused fertility to increase unexpectedly and temporarily, or that these increases may just be a tempo effect – changes in fertility timing which do not lead to increased completed fertility.","PeriodicalId":102634,"journal":{"name":"BioRN: Transmission (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122289101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we study the problem of identifying network effects in contagion processes and present an application to the propagation of influenza in the United States. In particular, using data on the evolution of infections over time, the travel intensity between states as well as environmental conditions we first provide a framework to identify the true network effect of traveling between states. Any identification strategy in this context needs to handle the following challenges: the reflection problem and the time correlation problem. The reflection problem arises from the observation that when sampling from the contagion process is frequent (in our case, weekly), the (potential) endogenous network effect cannot be discriminated from the correlation effect (such as that due to similar environmental conditions). The time-correlation effect stems from the observation that contagion processes are naturally characterized by correlation across different lags. We propose an instrumental variable approach, based on a spatiotemporally lagged versions of the observed data, and we show that our approach effectively tackles the aforementioned issues both theoretically and through a series of robustness checks. Finally, we use our estimates to propose and evaluate the performance of intervention and control policies, illustrating the benefits of network-based interventions.
{"title":"Network Effects in Contagion Processes: Identification and Control","authors":"K. Drakopoulos, Fanyin Zheng","doi":"10.2139/ssrn.3091313","DOIUrl":"https://doi.org/10.2139/ssrn.3091313","url":null,"abstract":"In this paper, we study the problem of identifying network effects in contagion processes and present an application to the propagation of influenza in the United States. In particular, using data on the evolution of infections over time, the travel intensity between states as well as environmental conditions we first provide a framework to identify the true network effect of traveling between states. Any identification strategy in this context needs to handle the following challenges: the reflection problem and the time correlation problem. The reflection problem arises from the observation that when sampling from the contagion process is frequent (in our case, weekly), the (potential) endogenous network effect cannot be discriminated from the correlation effect (such as that due to similar environmental conditions). The time-correlation effect stems from the observation that contagion processes are naturally characterized by correlation across different lags. We propose an instrumental variable approach, based on a spatiotemporally lagged versions of the observed data, and we show that our approach effectively tackles the aforementioned issues both theoretically and through a series of robustness checks. Finally, we use our estimates to propose and evaluate the performance of intervention and control policies, illustrating the benefits of network-based interventions.","PeriodicalId":102634,"journal":{"name":"BioRN: Transmission (Topic)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127495372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：