Handbook on Impact Evaluation

Khandker, Shahidur R.; Koolwal, Gayatri B.; Samad, Hussain A.

doi:10.1596/978-0-8213-8028-4

Cited by 514 publications

(453 citation statements)

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“…Therefore, as a robustness check to account for residual confounding, we additionally conducted an instrumental variable analysis, using the inverse of distance from the coastline to each resident's address at baseline as an instrument for housing damage. A valid instrument requires that it be associated with the treatment, but not directly affect the outcome (37). We calculated the distance for each residence using geographic information systems.…”

Section: Methodsmentioning

confidence: 99%

Increased risk of dementia in the aftermath of the 2011 Great East Japan Earthquake and Tsunami

Hikichi

Aida

Kondo

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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No previous study has been able to examine the association by taking account of risk factors for dementia before and after the disaster. We prospectively examined whether experiences of a disaster were associated with cognitive decline in the aftermath of the 2011 Great East Japan Earthquake and Tsunami. The baseline for our natural experiment was established in a survey of older community-dwelling adults who lived 80 km west of the epicenter 7 mo before the earthquake and tsunami. Approximately 2.5 y after the disaster, the follow-up survey gathered information about personal experiences of disaster as well as incidence of dementia from 3,594 survivors (82.1% follow-up rate). Our primary outcome was dementia diagnosis ascertained by in-home assessment during the follow-up period. Among our analytic sample (n = 3,566), 38.0% reported losing relatives or friends in the disaster, and 58.9% reported property damage. Fixed-effects regression indicated that major housing damage and home destroyed were associated with cognitive decline: regression coefficient for levels of dementia symptoms = 0.12, 95% confidence interval (CI): 0.01 to 0.23 and coefficient = 0.29, 95% CI: 0.17 to 0.40, respectively. The effect size of destroyed home is comparable to the impact of incident stroke (coefficient = 0.24, 95% CI: 0.11 to 0.36). The association between housing damage and cognitive decline remained statistically significant in the instrumental variable analysis. Housing damage appears to be an important risk factor for cognitive decline among older survivors in natural disasters.instrumental variable analysis U p to two-thirds of the affected populations in the 2011 Great East Japan Earthquake and Tsunami were older residents who were 60 y old or older (1). Recovery after major disaster poses a unique set of challenges for the elderly population, including disruption of medical care for preexisting conditions, preexisting functional limitations that impede recovery, and social isolation in the aftermath of housing loss and resettlement. A particular concern for older survivors is the potential risks of cognitive decline. In the 2011 earthquake and tsunami, an estimated 340,000 residents were displaced as a result of widespread destruction to residential properties. In turn, as a direct consequence of residential dislocation and resettlement in unfamiliar surroundings, many seniors experienced disorientation that could hasten cognitive decline (2). Psychological trauma, including posttraumatic stress disorder (PTSD) symptoms (3) and the onset of depression (4), may have additionally contributed to this risk.Two years after the 2011 Great East Japan Earthquake and Tsunami, a cross-sectional study found that 36.0% of seniors who moved to temporary housing in Kesen-numa city were suffering from dementia symptoms (5). Another cross-sectional study of seniors affected by the disaster reported that 47.9% showed signs of mild cognitive impairment, and an additional 16.0% of respondents were diagnosed as having dementia (6). However, ...

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Section: Methodsmentioning

confidence: 99%

Increased risk of dementia in the aftermath of the 2011 Great East Japan Earthquake and Tsunami

Hikichi

Aida

Kondo

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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“…However, households that do participate in an intervention are typically different from those who do not, whether due to targeting by project administrators or systematic differences among those choosing to participate and those not. A central challenge of impact evaluation is to eliminate the resulting selection bias by correcting for these differences (Ravallion 2001;Leeuw and Vaessen 2009;Khandker, Koolwal and Samad 2010).…”

Section: The Evolution Of Conventional Methods Of Quantitative Impactmentioning

confidence: 99%

“…One such method believed to be most effective at doing so is difference-in-difference propensity score matching (PSM), in which data from a panel survey 8 of participants and non-participants are first used to identify a comparable control group. Following, the change over the intervention implementation period for participant and control group households in the outcome of interest is used to estimate impact (Khandker, Koolwal and Samad 2010).…”

Section: The Evolution Of Conventional Methods Of Quantitative Impactmentioning

confidence: 99%

Admissible Evidence in the Court of Development Evaluation? The Impact of CARE’s SHOUHARDO Project on Child Stunting in Bangladesh

Smith

Kahn²,

Frankenberger

et al. 2013

World Development

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“…Authors such as Imbens andWooldridge (2009), Wooldridge (2010), Gertler et al (2011), Khandker et al (2010), Angrist and Krueger (2001), Angrist and Pischke (2009), Duflo et al (2007), Morgan and Winship (2010), Mouque (2012), Potluka (2014), Potluka and Špacek (2013), , Hora et al (2015), Zavřel (2015) focus only on assessing the impact of external incentives on business behavior in the case of the counterfactual impact evaluation. There is not experience with the implementation of the impact of internal incentives on business behavior in the case of the counterfactual impact evaluation.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Overall Equipment Effectiveness within Counterfactual Impact Evaluation Concept

Rylková

Stelmach

Vlček

2017

Scientific Annals of Economics and Business

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Counterfactual impact evaluation (CIE) is a scientific quantitative approach mainly based on experiments and quasi experiments. CIE is trying to prove a causal relationship between outputs and outcomes. CIE does not take into account coherence of external incentives of companies with internal incentives that have or may have an impact on the behaviour of enterprises. The paper sets up internal evaluation indicators for businesses, counterfactuals useful for creating a more complex metrics evaluating businesses in the area of performance. The aim of the paper is to present model situation using the elementary principle of counterfactual impact evaluation based on "the Overall Equipment Effectiveness (OEE)".

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Handbook on Impact Evaluation

Cited by 514 publications

References 0 publications

Increased risk of dementia in the aftermath of the 2011 Great East Japan Earthquake and Tsunami

Increased risk of dementia in the aftermath of the 2011 Great East Japan Earthquake and Tsunami

Admissible Evidence in the Court of Development Evaluation? The Impact of CARE’s SHOUHARDO Project on Child Stunting in Bangladesh

Overall Equipment Effectiveness within Counterfactual Impact Evaluation Concept

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