Unlike initially predicted by WHO, the severity of the novel coronavirus pandemic has remained relatively low in Sub-Saharan Africa, more than two months after the first confirmed cases were identified. In this paper, we analyze the extent to which demographic and geographic factors associated to the disease explain this phenomenon. We use publicly available data from a cross-section of 182 countries worldwide, and we employ a regression analysis that accounts for possible misreporting of COVID-19 cases, as well as a Ramsey-type specification that preserves degree of freedom. We found that proportion of population aged 65+, population density, and urbanization are significantly positively associated with high numbers of active infected cases, while mean temperature around the first quarter (January-March) is negatively associated to this COVID-19 outcome. These factors are those for which Africa has a comparative advantage. In contrast, factors for which Africa has a relative disadvantage, such as income and quality of health care infrastructure, are found to be insignificant predictors of the spread of the pandemic. These results hold even when accounting for possible underreporting, as well as differences in the duration of the epidemic in each country, as measured by the time elapsed since the first confirmed case occurred. We conclude that differences in demographic and geographic characteristics help understand the relatively low progression of the pandemic in sub-Saharan Africa as well as the gap in the number of active cases between this region and the rest of the World. We also found, however, that this gap is insignificant beyond these factors, and is expected to narrow over time as the pandemic evolves. These results provide insights for relevant urban policies and kinds of development planning to consider in the fight against disease spreads of the coronavirus type.

This article examines the impact that misreporting adoption status has on the identification and estimation of causal effects on productivity. In particular, by comparing measurement error‐ridden self‐reported adoption data with measurement‐error‐free DNA‐fingerprinted adoption data, we investigate the extent to which such errors bias the causal effects of adoption on productivity. Taking DNA‐fingerprinted adoption data as a benchmark, we find 25% “false negatives” and 10% “false positives” in farmers’ responses. Our results show that misreporting of adoption status is not exogenous to household characteristics, and produces a bias of about 22 percentage points in the productivity impact of adoption. Ignoring inherent behavioral adjustments of farmers based on perceived adoption status has a bias of 13 percentage points. The results of this article underscore the crucial role that correct measurement of adoption plays in designing policy interventions that address constraints to technology adoption in agriculture.

Performance-based financing (PBF) is a mechanism by which health providers are paid on the basis of outputs or results delivered. A PBF program was implemented on the provision of HIV, prevention of mother-to child HIV transmission (PMTCT), and maternal/child health (MCH) services in two provinces of Mozambique. A retrospective case–control study design was used in which PBF provinces were matched with control provinces to evaluate the impact of PBF on 18 indicators. Due to regional heterogeneity, we evaluated the intervention sites (North and South) separately. Beginning January 2011, 11 quarters (33 months or 2.75 years) of data from 134 facilities after matching (84 in the North and 50 in the South) were used. Our econometric framework employed a multi-period, multi-group difference-in-differences model on data that was matched using propensity scoring. The regression design employed a generalized linear mixed model with both fixed and random effects, fitted using the seemingly unrelated regression technique. PBF resulted in positive impacts on MCH, PMTCT and paediatric HIV program outcomes. The majority of the 18 indicators responded to PBF (77% in the North and 66% in the South), with at least half of the indicators demonstrating a statistically significant increase in average output of more than 50% relative to baseline. Excluding pregnant women, the majority of adult HIV treatment indicators did not respond to PBF. On average, it took 18 months (six quarters) of implementation for PBF to take effect, and impact was generally sustained thereafter. Indicators were not sensitive to price, but were inversely correlated to the level of effort associated with marginal output. No negative impacts on incentivized indicators nor spill-over effects on non-incentivized indicators were observed. The PBF program in Mozambique has produced large, sustained increases in the provision of PMTCT, paediatric HIV and MCH services. Our results demonstrate that PBF is an effective strategy for driving down the HIV epidemic and advancing MCH care service delivery as compared with input financing alone.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in On the Estimation of Treatment Effects with Endogenous Misreporting MARCH 2018Any opinions expressed in this paper are those of the author(s) and not those of IZA. Research published in this series may include views on policy, but IZA takes no institutional policy positions. The IZA research network is committed to the IZA Guiding Principles of Research Integrity. The IZA Institute of Labor Economics is an independent economic research institute that conducts research in labor economics and offers evidence-based policy advice on labor market issues. Supported by the Deutsche Post Foundation, IZA runs the world's largest network of economists, whose research aims to provide answers to the global labor market challenges of our time. Our key objective is to build bridges between academic research, policymakers and society. IZA Discussion Papers often represent preliminary work and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be available directly from the author. show that failure to account for endogenous misreporting can result in the estimate of the treatment effect having an opposite sign from the true effect. We present an expression for the asymptotic bias of both OLS and IV estimators and discuss the conditions under which sign reversal may occur. We provide a method for eliminating this bias when researchers have access to information related to both participation and misreporting. We establish the consistency and asymptotic normality of our estimator and assess its small sample performance through Monte Carlo simulations. An empirical example is given to illustrate the proposed method. JEL Classification:C35, C51

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