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Convolutional neural networks (CNNs) trained with satellite imagery have been successfully used to generate measures of development indicators, such as poverty, in developing nations. This article explores a CNN‐based approach leveraging Landsat 8 imagery to predict locations of conflict‐related deaths. Using Nigeria as a case study, we use the Armed Conflict Location & Event Data (ACLED) dataset to identify locations of conflict events that did or did not result in a death. Imagery for each location is used as an input to train a CNN to distinguish fatal from non‐fatal events. Using 2014 imagery, we are able to predict the result of conflict events in the following year (2015) with 80% accuracy. While our approach does not replace the need for causal studies into the drivers of conflict death, it provides a low‐cost solution to prediction that requires only publicly available imagery to implement. Findings suggest that the information contained in moderate‐resolution imagery can be used to predict the likelihood of a death due to conflict at a given location in Nigeria the following year, and that CNN‐based methods of estimating development‐related indicators may be effective in applications beyond those explored in the literature.
Seth Goodman; Ariel BenYishay; Daniel Miller Runfola. A convolutional neural network approach to predict non‐permissive environments from moderate‐resolution imagery. Transactions in GIS 2020, 25, 674 -691.
AMA StyleSeth Goodman, Ariel BenYishay, Daniel Miller Runfola. A convolutional neural network approach to predict non‐permissive environments from moderate‐resolution imagery. Transactions in GIS. 2020; 25 (2):674-691.
Chicago/Turabian StyleSeth Goodman; Ariel BenYishay; Daniel Miller Runfola. 2020. "A convolutional neural network approach to predict non‐permissive environments from moderate‐resolution imagery." Transactions in GIS 25, no. 2: 674-691.
We present the geoBoundaries Global Administrative Database (geoBoundaries): an online, open license resource of the geographic boundaries of political administrative divisions (i.e., state, county). Contrasted to other resources geoBoundaries (1) provides detailed information on the legal open license for every boundary in the repository, and (2) focuses on provisioning highly precise boundary data to support accurate, replicable scientific inquiry. Further, all data is released in a structured form, allowing for the integration of geoBoundaries with large-scale computational workflows. Our database has records for every country around the world, with up to 5 levels of administrative hierarchy. The database is accessible at http://www.geoboundaries.org, and a static version is archived on the Harvard Dataverse.
Daniel Runfola; Austin Anderson; Heather Baier; Matt Crittenden; Elizabeth Dowker; Sydney Fuhrig; Seth Goodman; Grace Grimsley; Rachel Layko; Graham Melville; Maddy Mulder; Rachel Oberman; Joshua Panganiban; Andrew Peck; Leigh Seitz; Sylvia Shea; Hannah Slevin; Rebecca Youngerman; Lauren Hobbs. geoBoundaries: A global database of political administrative boundaries. PLOS ONE 2020, 15, e0231866 .
AMA StyleDaniel Runfola, Austin Anderson, Heather Baier, Matt Crittenden, Elizabeth Dowker, Sydney Fuhrig, Seth Goodman, Grace Grimsley, Rachel Layko, Graham Melville, Maddy Mulder, Rachel Oberman, Joshua Panganiban, Andrew Peck, Leigh Seitz, Sylvia Shea, Hannah Slevin, Rebecca Youngerman, Lauren Hobbs. geoBoundaries: A global database of political administrative boundaries. PLOS ONE. 2020; 15 (4):e0231866.
Chicago/Turabian StyleDaniel Runfola; Austin Anderson; Heather Baier; Matt Crittenden; Elizabeth Dowker; Sydney Fuhrig; Seth Goodman; Grace Grimsley; Rachel Layko; Graham Melville; Maddy Mulder; Rachel Oberman; Joshua Panganiban; Andrew Peck; Leigh Seitz; Sylvia Shea; Hannah Slevin; Rebecca Youngerman; Lauren Hobbs. 2020. "geoBoundaries: A global database of political administrative boundaries." PLOS ONE 15, no. 4: e0231866.
Since 1992, the Global Environment Facility (GEF) has mobilized over $131 billion in funds to enable developing and transitioning countries to meet the objectives of international environmental conventions and agreements. While multiple studies and reports have sought to examine the environmental impact of these funds, relatively little work has examined the potential for socioeconomic co-benefits. Leveraging a novel database on the geographic location of GEF project interventions in Uganda, this paper explores the impact of GEF projects on household assets in Uganda. It employs a new methodological approach, Quasi-experimental Geospatial Interpolation (QGI), which seeks to overcome many of the core biases and limitations of previous implementations of causal matching studies leveraging geospatial information. Findings suggest that Sustainable Forest Management (SFM) GEF projects with initial implementation dates prior to 2009 in Uganda had a positive, statistically significant impact of approximately $184.81 on the change in total household assets between 2009 and 2011. Leveraging QGI, we identify that (1) this effect was statistically significant at distances between 2 and 7 km away from GEF projects, (2) the effect was positive but not statistically significant at distances less than 2 km, and (3) there was insufficient evidence to establish the impact of projects beyond a distance of approximately 7 km.
Daniel Runfola; Geeta Batra; Anupam Anand; Audrey Way; Seth Goodman. Exploring the Socioeconomic Co-benefits of Global Environment Facility Projects in Uganda Using a Quasi-Experimental Geospatial Interpolation (QGI) Approach. Sustainability 2020, 12, 3225 .
AMA StyleDaniel Runfola, Geeta Batra, Anupam Anand, Audrey Way, Seth Goodman. Exploring the Socioeconomic Co-benefits of Global Environment Facility Projects in Uganda Using a Quasi-Experimental Geospatial Interpolation (QGI) Approach. Sustainability. 2020; 12 (8):3225.
Chicago/Turabian StyleDaniel Runfola; Geeta Batra; Anupam Anand; Audrey Way; Seth Goodman. 2020. "Exploring the Socioeconomic Co-benefits of Global Environment Facility Projects in Uganda Using a Quasi-Experimental Geospatial Interpolation (QGI) Approach." Sustainability 12, no. 8: 3225.
There has been considerable debate regarding the efficacy of international aid in meeting the dual goals of human development and environmental sustainability. Many donors have sought to engage with this challenge by introducing environmental safeguard and monitoring initiatives; however, evidence on the success of these interventions is limited. Evaluating aid is a particular challenge in the case of donors that do not disclose information on the nature, geographic location, or extents of their interventions. In such cases, new methods that extract and geoparse data on the activities of opaque donors through the manual interpretation of thousands of news and other articles allow us to investigate the impacts of these activities. However, residual spatial uncertainty in these data remains a potential source of bias. In this article, we apply and discuss a Geographic Simulation and Extrapolation (GeoSIMEX) approach to mitigate the spatial imprecision inherent in geoparsed data. In conjunction with GeoSIMEX, we test and contrast multiple approaches to reducing the imprecision of aid, including high-assumption cases in which other covariates (i.e., nighttime lights) are leveraged to allocate aid. In our application, we find that methods which do not account for spatial imprecision find statistically significant relationships between Chinese aid and vegetation change; after accounting for spatial uncertainty, findings are similar for Rwanda and inconclusive for Burundi.
Robert Marty; Seth Goodman; Michael LeFew; Carrie Dolan; Ariel BenYishay; Daniel Runfola. Assessing the causal impact of Chinese aid on vegetative land cover in Burundi and Rwanda under conditions of spatial imprecision. Development Engineering 2018, 4, 100038 .
AMA StyleRobert Marty, Seth Goodman, Michael LeFew, Carrie Dolan, Ariel BenYishay, Daniel Runfola. Assessing the causal impact of Chinese aid on vegetative land cover in Burundi and Rwanda under conditions of spatial imprecision. Development Engineering. 2018; 4 ():100038.
Chicago/Turabian StyleRobert Marty; Seth Goodman; Michael LeFew; Carrie Dolan; Ariel BenYishay; Daniel Runfola. 2018. "Assessing the causal impact of Chinese aid on vegetative land cover in Burundi and Rwanda under conditions of spatial imprecision." Development Engineering 4, no. : 100038.
Interdisciplinary use of geospatial data requires the integration of data from a breadth of sources, and frequently involves the harmonization of different methods of sampling, measurement, and technical data types. These integrative efforts are often inhibited by fundamental geocomputational challenges, including a lack of memory efficient or parallel processing approaches to traditional methods such as zonal statistics. GeoQuery (geoquery.org) is a dynamic web application which utilizes a High Performance Computing cluster and novel parallel geospatial data processing methods to overcome these challenges. Through an online interface, GeoQuery users can request geospatial data - which spans categories including geophysical, environmental and social measurements - to be aggregated to user-selected units of analysis (e.g., subnational administrative boundaries). Once a request has been processed, users are provided with permanent links to access their customized data and documentation. Datasets made available through GeoQuery are reviewed, prepared, and provisioned by geospatial data specialists, with processing routines tailored for each dataset. The code used and steps taken while preparing datasets and processing user requests are publicly available, ensuring transparency and replicability of all data and processes. By mediating the complexities of working with geospatial data, GeoQuery reduces the barriers to entry and the related costs of incorporating geospatial data into research across disciplines. This paper presents the technology and methods used by GeoQuery to process and manage geospatial data and user requests.
Seth Goodman; Ariel BenYishay; Zhonghui Lv; Daniel Runfola. GeoQuery: Integrating HPC systems and public web-based geospatial data tools. Computers & Geosciences 2018, 122, 103 -112.
AMA StyleSeth Goodman, Ariel BenYishay, Zhonghui Lv, Daniel Runfola. GeoQuery: Integrating HPC systems and public web-based geospatial data tools. Computers & Geosciences. 2018; 122 ():103-112.
Chicago/Turabian StyleSeth Goodman; Ariel BenYishay; Zhonghui Lv; Daniel Runfola. 2018. "GeoQuery: Integrating HPC systems and public web-based geospatial data tools." Computers & Geosciences 122, no. : 103-112.
We evaluated the local impacts of World Bank development projects on sites of recognized conservation significance (Important Bird and Biodiversity Areas [IBAs]) using tree cover change data and in situ state, pressure, and response monitoring data. IBAs adjacent to World Bank project locations and a matched set of IBAs distant from World Bank project locations had similar rates of tree loss and similar in situ measurements of conservation outcomes. Thus, we did not detect any significant net negative impacts of World Bank projects on tree cover or conservation outcomes. These results are encouraging because 89% of World Bank projects that are close to IBAs are environmentally sensitive projects (so-called Category A and Category B projects) subjected to the organization’s most stringent safeguards. However, the limitations of our evaluation design do not allow us to rule out the possibility that World Bank projects had positive or negative effects that were undetectable.
Graeme M. Buchanan; Bradley C. Parks; Paul F. Donald; Brian F. O’Donnell; Daniel Miller Runfola; John P. Swaddle; Łukasz Tracewski; Stuart H. M. Butchart. The Local Impacts of World Bank Development Projects Near Sites of Conservation Significance. The Journal of Environment & Development 2018, 27, 299 -322.
AMA StyleGraeme M. Buchanan, Bradley C. Parks, Paul F. Donald, Brian F. O’Donnell, Daniel Miller Runfola, John P. Swaddle, Łukasz Tracewski, Stuart H. M. Butchart. The Local Impacts of World Bank Development Projects Near Sites of Conservation Significance. The Journal of Environment & Development. 2018; 27 (3):299-322.
Chicago/Turabian StyleGraeme M. Buchanan; Bradley C. Parks; Paul F. Donald; Brian F. O’Donnell; Daniel Miller Runfola; John P. Swaddle; Łukasz Tracewski; Stuart H. M. Butchart. 2018. "The Local Impacts of World Bank Development Projects Near Sites of Conservation Significance." The Journal of Environment & Development 27, no. 3: 299-322.
Governments use a variety of policies to increase the impact of foreign investment on economic growth. An increasingly popular policy is to require that foreign companies provide public goods near the communities where their commercial investments are sited. This approach seeks to crowd in additional investments, create clusters of interconnected firms, and set in motion economic agglomeration processes. Post-2006 Liberia represents an ideal empirical setting to test the effectiveness of this approach. We construct a new dataset that measures the precise locations of 557 natural resource concessions granted to investors. We then merge these data with a remotely sensed measure of nighttime light growth at the 1 km × 1 km grid cell level and analyze it using a matched difference-in-differences strategy. We find heterogeneous treatment effects across sectors and investor types: mining (specifically iron-ore) investments projects have positive growth effects, while agriculture and forestry investment projects do not; furthermore, concessions granted to Chinese investors have positive growth effects while those given to U.S. investors do not. These patterns of heterogeneous treatment effects across sectors and investor types are consistent with the theory of change underpinning the government’s development corridor strategy.
Jonas B. Bunte; Harsh Desai; Kanio Gbala; Bradley Parks; Daniel Miller Runfola. Natural resource sector FDI, government policy, and economic growth: Quasi-experimental evidence from Liberia. World Development 2018, 107, 151 -162.
AMA StyleJonas B. Bunte, Harsh Desai, Kanio Gbala, Bradley Parks, Daniel Miller Runfola. Natural resource sector FDI, government policy, and economic growth: Quasi-experimental evidence from Liberia. World Development. 2018; 107 ():151-162.
Chicago/Turabian StyleJonas B. Bunte; Harsh Desai; Kanio Gbala; Bradley Parks; Daniel Miller Runfola. 2018. "Natural resource sector FDI, government policy, and economic growth: Quasi-experimental evidence from Liberia." World Development 107, no. : 151-162.
The policy choices of local governments are highly relevant today, but we know relatively little about how or when local governments choose to respond to a given issue and why this might vary between policy areas. A key variant for local governments is the proximity of policy issues: they are engaged in solving local, regional, and global problems. Using evidence from the United States on the policy issues of social inclusion, watershed management, and climate change, we demonstrate that the drivers of policy response vary with the proximity of the problem. When an issue is highly local, policy response is influenced by problem severity; when an issue is global, policy response is influenced by local political leanings; and when an issue is regional, policy response is driven by the actions of neighboring and state level governments. Local governments consider different factors and respond to different cues when engaging with different types of policy issues. Our findings provide a more nuanced understanding of sustainability policy adoption in local governments, and further our understanding of the domain-contingent nature of policy response in local governments and the structuring role of problem proximity. 如今地方政府的政策选择呈现高度相关性, 但我们几乎不了解的是, 地方政府会如何、或在何时选择回应既定议题, 以及为什么不同政策领域之间这一情况会有差异。本地政府间存在的关键变量是政策议题的接近性:这些议题用于解决本地、区域和全球问题。通过使用美国针对社会包容(social inclusion)、流域管理和气候变化的政策议题所得出的证据, 本文证明, 驱动政策回应的因素会由于问题接近性而变化。当议题呈现高度本地化时, 问题严重性会影响政策回应;当议题呈现全球化时, 本地政治倾向会影响政策回应;当议题呈现区域化时, 领国政府和国家政府会驱动政策回应。本地政府会考量不同因素, 并在处理不同类型的政策议题时对不同信号予以回应。本文研究结果为本地政府关于采纳可持续政策提供了细致入微的见解, 同时进一步加深了对本地政府政策回应的领域依赖性、以及问题接近性的结构性角色的理解。 Las elecciones políticas de los gobiernos locales son muy relevantes hoy en día, pero sabemos relativamente poco acerca de cómo o cuándo los gobiernos locales eligen responder a un tema específico y por qué esto podría variar entre las áreas políticas. Una variable clave para los gobiernos locales es la proximidad a los temas políticos: están involucrados en la solución de problemas locales, regionales y globales. Utilizando evidencia de los temas políticos de Estados Unidos acerca de la inclusión social, el manejo de cuencas y el cambio climático, demostramos que los factores que impulsan las respuestas varían dependiendo de la proximidad al problema. Cuando un tema es altamente local, la respuesta política está influenciada por la gravedad del problema; cuando un tema es regional, la respuesta política está influenciada por las preferencias políticas; y cuando un problema es regional, la respuesta política es impulsada por las acciones de los gobiernos vecinos y gobiernos a nivel estatal. Los gobiernos locales consideran diferentes factores y responden a diferentes pistas cuando tratan con diferentes tipos de temas políticos. Nuestros hallazgos proporcionan un entendimiento más detallado de la adopción de políticas de sustentabilidad en gobiernos locales, e incrementan nuestra comprensión de la dependencia en el dominio que es una característica de la respuesta a las políticas en los gobiernos locales y el papel estructurador de la proximidad a los temas.
Sara Hughes; Daniel Miller Runfola; Benjamin Cormier. Issue Proximity and Policy Response in Local Governments. Review of Policy Research 2018, 35, 192 -212.
AMA StyleSara Hughes, Daniel Miller Runfola, Benjamin Cormier. Issue Proximity and Policy Response in Local Governments. Review of Policy Research. 2018; 35 (2):192-212.
Chicago/Turabian StyleSara Hughes; Daniel Miller Runfola; Benjamin Cormier. 2018. "Issue Proximity and Policy Response in Local Governments." Review of Policy Research 35, no. 2: 192-212.
The World Bank provides billions of dollars in development finance to countries across the world every year. As many projects are related to the environment, we want to understand the World Bank projects impact to forest cover. However, the global extent of these projects results in substantial heterogeneity in impacts due to geographic, cultural, and other factors. Recent research by Athey and Imbens has illustrated the potential for hybrid machine learning and causal inferential techniques which may be able to capture such heterogeneity. We apply their approach using a geolocated dataset of World Bank projects, and augment this data with satellite-retrieved characteristics of their geographic context (including temperature, precipitation, slope, distance to urban areas, and many others). We use this information in conjunction with causal tree (CT) and causal forest (CF) approaches to contrast ‘control’ and ‘treatment’ geographic locations to estimate the impact of World Bank projects on vegetative cover.
Jianing Zhao; Daniel Miller Runfola; Peter Kemper. Quantifying Heterogeneous Causal Treatment Effects in World Bank Development Finance Projects. Transactions on Petri Nets and Other Models of Concurrency XV 2017, 204 -215.
AMA StyleJianing Zhao, Daniel Miller Runfola, Peter Kemper. Quantifying Heterogeneous Causal Treatment Effects in World Bank Development Finance Projects. Transactions on Petri Nets and Other Models of Concurrency XV. 2017; ():204-215.
Chicago/Turabian StyleJianing Zhao; Daniel Miller Runfola; Peter Kemper. 2017. "Quantifying Heterogeneous Causal Treatment Effects in World Bank Development Finance Projects." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 204-215.
Quantifying the impact of an intervention or treatment in a real setting is a common and challenging problem. For example, we would like to calculate the environmental implications of aid projects in third world countries that target economic development. For causal inference problems of this kind, the Rubin causal model is one of several popular theoretical frameworks that comes with a set of algorithmic methods to quantify treatment effects. However, for a given data set, we neither know the ground truth nor can we easily increase the size of the data set. So, simulation is a natural choice to evaluate the applicability of a set of methods for a particular problem. In this paper, we report findings of a simulation study with four causal inference approaches, namely two single tree approaches (transformed outcome tree, causal tree), and two random forest versions of the former.
Jianing Zhao; Daniel M. Runfola; Peter Kemper. Simulation study in quantifying heterogeneous causal effects. 2017 Winter Simulation Conference (WSC) 2017, 2650 -2661.
AMA StyleJianing Zhao, Daniel M. Runfola, Peter Kemper. Simulation study in quantifying heterogeneous causal effects. 2017 Winter Simulation Conference (WSC). 2017; ():2650-2661.
Chicago/Turabian StyleJianing Zhao; Daniel M. Runfola; Peter Kemper. 2017. "Simulation study in quantifying heterogeneous causal effects." 2017 Winter Simulation Conference (WSC) , no. : 2650-2661.
Ariel BenYishay; Silke Heuser; Daniel Miller Runfola; Rachel Trichler. Indigenous land rights and deforestation: Evidence from the Brazilian Amazon. Journal of Environmental Economics and Management 2017, 86, 29 -47.
AMA StyleAriel BenYishay, Silke Heuser, Daniel Miller Runfola, Rachel Trichler. Indigenous land rights and deforestation: Evidence from the Brazilian Amazon. Journal of Environmental Economics and Management. 2017; 86 ():29-47.
Chicago/Turabian StyleAriel BenYishay; Silke Heuser; Daniel Miller Runfola; Rachel Trichler. 2017. "Indigenous land rights and deforestation: Evidence from the Brazilian Amazon." Journal of Environmental Economics and Management 86, no. : 29-47.
Migration provides a strategy for rural Mexican households to cope with, or adapt to, weather events and climatic variability. Yet prior studies on environmental migration in this context have not examined the differences between choices of internal (domestic) or international movement. In addition, much of the prior work relied on very coarse spatial scales to operationalise the environmental variables such as rainfall patterns. To overcome these limitations, we use fine‐grain rainfall estimates derived from NASA's Tropical Rainfall Measuring Mission satellite. The rainfall estimates are combined with population and agricultural census information to examine associations between environmental changes and municipal rates of internal and international migration during 2005–2010. Our findings suggest that municipal‐level rainfall deficits relative to historical levels are an important predictor of both international and internal migration, especially in municipalities with predominantly rainfed agriculture. Although our findings do not contradict results of prior studies using coarse spatial resolution, they offer clearer evidence and a more spatially nuanced examination of migration as related to social and environmental vulnerability. Copyright © 2017 John Wiley & Sons, Ltd.
Stefan Leyk; Dan Runfola; Raphael J. Nawrotzki; Lori M. Hunter; Fernando Riosmena. Internal and International Mobility as Adaptation to Climatic Variability in Contemporary Mexico: Evidence from the Integration of Census and Satellite Data. Population, Space and Place 2017, 23, e2047 .
AMA StyleStefan Leyk, Dan Runfola, Raphael J. Nawrotzki, Lori M. Hunter, Fernando Riosmena. Internal and International Mobility as Adaptation to Climatic Variability in Contemporary Mexico: Evidence from the Integration of Census and Satellite Data. Population, Space and Place. 2017; 23 (6):e2047.
Chicago/Turabian StyleStefan Leyk; Dan Runfola; Raphael J. Nawrotzki; Lori M. Hunter; Fernando Riosmena. 2017. "Internal and International Mobility as Adaptation to Climatic Variability in Contemporary Mexico: Evidence from the Integration of Census and Satellite Data." Population, Space and Place 23, no. 6: e2047.
Since 1945, over $4.9 trillion dollars of international aid has been allocated to developing countries. To date, there have been no estimates of the regional impact of this aid on the carbon cycle. We apply a geographically explicit matching method to estimate the relative impact of large-scale World Bank projects implemented between 2000 and 2010 on sequestered carbon, using a novel and publicly available data set of 61,243 World Bank project locations. Considering only carbon sequestered due to fluctuations in vegetative biomass caused by World Bank projects, we illustrate the relative impact of World Bank projects on carbon sequestration. We use this information to illustrate the geographic variation in the apparent effectiveness of environmental safeguards implemented by the World Bank. We argue that sub-national data can help to identify geographically heterogeneous impact effects, and highlight many remaining methodological challenges.
Daniel Runfola; Ariel BenYishay; Jeffery Tanner; Graeme Buchanan; Jyoteshwar Nagol; Matthias Leu; Seth Goodman; Rachel Trichler; Robert Marty. A Top-Down Approach to Estimating Spatially Heterogeneous Impacts of Development Aid on Vegetative Carbon Sequestration. Sustainability 2017, 9, 409 .
AMA StyleDaniel Runfola, Ariel BenYishay, Jeffery Tanner, Graeme Buchanan, Jyoteshwar Nagol, Matthias Leu, Seth Goodman, Rachel Trichler, Robert Marty. A Top-Down Approach to Estimating Spatially Heterogeneous Impacts of Development Aid on Vegetative Carbon Sequestration. Sustainability. 2017; 9 (3):409.
Chicago/Turabian StyleDaniel Runfola; Ariel BenYishay; Jeffery Tanner; Graeme Buchanan; Jyoteshwar Nagol; Matthias Leu; Seth Goodman; Rachel Trichler; Robert Marty. 2017. "A Top-Down Approach to Estimating Spatially Heterogeneous Impacts of Development Aid on Vegetative Carbon Sequestration." Sustainability 9, no. 3: 409.
Objective Cross-national studies provide inconclusive results as to the effectiveness of foreign health aid. We highlight a novel application of using subnational data to evaluate aid impacts, using Malawi as a case study. Design We employ two rounds of nationally representative household surveys (2004/2005 and 2010/2011) and geo-referenced foreign aid data. We examine the determinants of Malawi's traditional authorities receiving aid according to health, environmental risk, socioeconomic and political factors. We use two approaches to estimate the impact of aid on reducing malaria prevalence and increasing healthcare quality: difference-in-difference models, which include traditional authority and month-of-interview fixed effects and control for individual and household level time-varying factors, and entropy balancing, where models balance on health-related and socioeconomic baseline characteristics. General health aid and four specific health aid sectors are examined. Results Traditional authorities with greater proportions of individuals living in urban areas, more health facilities and greater proportions of those in major ethnic groups were more likely to receive aid. Difference-in-difference models show health infrastructure and parasitic disease control aid reduced malaria prevalence by 1.20 (95% CI −0.36 to 2.76) and 2.20 (95% CI 0.43 to 3.96) percentage points, respectively, and increased the likelihood of individuals reporting healthcare as more than adequate by 12.1 (95% CI 1.51 to 22.68) and 14.0 (95% CI 0.11 to 28.11) percentage points. Entropy balancing shows similar results. Conclusions Aid was targeted to areas with greater existing health infrastructure rather than areas most in need, but still effectively reduced malaria prevalence and enhanced self-reported healthcare quality.
Robert Marty; Carrie B Dolan; Matthias Leu; Daniel Runfola. Taking the health aid debate to the subnational level: the impact and allocation of foreign health aid in Malawi. BMJ Global Health 2017, 2, e000129 .
AMA StyleRobert Marty, Carrie B Dolan, Matthias Leu, Daniel Runfola. Taking the health aid debate to the subnational level: the impact and allocation of foreign health aid in Malawi. BMJ Global Health. 2017; 2 (1):e000129.
Chicago/Turabian StyleRobert Marty; Carrie B Dolan; Matthias Leu; Daniel Runfola. 2017. "Taking the health aid debate to the subnational level: the impact and allocation of foreign health aid in Malawi." BMJ Global Health 2, no. 1: e000129.
Evidence is increasing that climate change and variability may influence human migration patterns. However, there is less agreement regarding the type of migration streams most strongly impacted. This study tests whether climate change more strongly impacted international compared to domestic migration from rural Mexico during 1986–99. We employ eight temperature and precipitation-based climate change indices linked to detailed migration histories obtained from the Mexican Migration Project. Results from multilevel discrete-time event-history models challenge the assumption that climate-related migration will be predominantly short distance and domestic, but instead show that climate change more strongly impacted international moves from rural Mexico. The stronger climate impact on international migration may be explained by the self-insurance function of international migration, the presence of strong migrant networks, and climate-related changes in wage difference. While a warming in temperature increased international outmigration, higher levels of precipitation declined the odds of an international move.
Raphael J. Nawrotzki; Daniel M. Runfola; Lori M. Hunter; Fernando Riosmena. Domestic and International Climate Migration from Rural Mexico. Human Ecology 2016, 44, 687 -699.
AMA StyleRaphael J. Nawrotzki, Daniel M. Runfola, Lori M. Hunter, Fernando Riosmena. Domestic and International Climate Migration from Rural Mexico. Human Ecology. 2016; 44 (6):687-699.
Chicago/Turabian StyleRaphael J. Nawrotzki; Daniel M. Runfola; Lori M. Hunter; Fernando Riosmena. 2016. "Domestic and International Climate Migration from Rural Mexico." Human Ecology 44, no. 6: 687-699.
In the face of climate change-induced economic uncertainties, households may em-ploy migration as an adaptation strategy to diversify their livelihood portfolio through remit-tances. However, it is unclear whether such climate-related migration will be documented or undocumented. In this study we combined detailed migration histories with daily temperature and precipitation information from 214 weather stations to investigate whether climate change more strongly impacted undocumented or documented migrations from 68 rural Mexican mu-nicipalities to the U.S. from 1986−1999. We employed two measures of climate change, the warm spell duration index (WSDI) and precipitation during extremely wet days (R99PTOT). Results from multi-level event-history models demonstrated that climate-related international migration from rural Mexico was predominantly undocumented. We conclude that programs to facilitate climate change adaptations in rural Mexico may be more effective in reducing undo-cumented border crossings than increasing border fortification.
Raphael J. Nawrotzki; Fernando Riosmena; Lori M. Hunter; Daniel M. Runfola. Undocumented migration in response to climate change. International Journal of Population Studies 2015, 1, 60 -74.
AMA StyleRaphael J. Nawrotzki, Fernando Riosmena, Lori M. Hunter, Daniel M. Runfola. Undocumented migration in response to climate change. International Journal of Population Studies. 2015; 1 (1):60-74.
Chicago/Turabian StyleRaphael J. Nawrotzki; Fernando Riosmena; Lori M. Hunter; Daniel M. Runfola. 2015. "Undocumented migration in response to climate change." International Journal of Population Studies 1, no. 1: 60-74.
A flexible procedure for the development of a multi-criteria composite index to measure relative vulnerability under future climate change scenarios is presented. The composite index is developed using the Weighted Ordered Weighted Average (WOWA) aggregation technique which enables the selection of different levels of trade-off, which controls the degree to which indicators are able to average out others. We explore this approach in an illustrative case study of the United States (US), using future projections of widely available indicators quantifying flood vulnerability under two scenarios of climate change. The results are mapped for two future time intervals for each climate scenario, highlighting areas that may exhibit higher future vulnerability to flooding events. Based on a Monte Carlo robustness analysis, we find that the WOWA aggregation technique can provide a more flexible and potentially robust option for the construction of vulnerability indices than traditionally used approaches such as Weighted Linear Combinations (WLC). This information was used to develop a proof-of-concept vulnerability assessment to climate change impacts for the US Army Corps of Engineers. Lessons learned in this study informed the climate change screening analysis currently under way.
Daniel Miller Runfola; Samuel Ratick; Julie Blue; Elia Axinia Machado; Nupur Hiremath; Nick Giner; Kathleen White; Jeffrey Arnold. A multi-criteria geographic information systems approach for the measurement of vulnerability to climate change. Mitigation and Adaptation Strategies for Global Change 2015, 22, 349 -368.
AMA StyleDaniel Miller Runfola, Samuel Ratick, Julie Blue, Elia Axinia Machado, Nupur Hiremath, Nick Giner, Kathleen White, Jeffrey Arnold. A multi-criteria geographic information systems approach for the measurement of vulnerability to climate change. Mitigation and Adaptation Strategies for Global Change. 2015; 22 (3):349-368.
Chicago/Turabian StyleDaniel Miller Runfola; Samuel Ratick; Julie Blue; Elia Axinia Machado; Nupur Hiremath; Nick Giner; Kathleen White; Jeffrey Arnold. 2015. "A multi-criteria geographic information systems approach for the measurement of vulnerability to climate change." Mitigation and Adaptation Strategies for Global Change 22, no. 3: 349-368.
Between 2005 and 2010, 6.3 million migrants (approximately 6% of the population) moved domestically within Mexico. These shifts have potential implications for exposure to natural disasters. To examine this relationship, we use census microdata in conjunction with information on natural disaster events. The populations exposed to extreme weather events are first calculated based on observed disasters and demographic change between 2005 and 2010. This is compared to a hypothetical scenario with no migration between 2005 and 2010. The results presented in this research note demonstrate that while migration has slightly decreased overall exposure within Mexico, this influence is highly localized in select areas, with internal migration increasing exposure in key urban destinations. This highlights the need to better understand the interacting roles of household-scale migratory decision making and economic/urban growth policy in climate change mitigation, and provides guidance on geographic regions to target for more detailed analysis.
Daniel Miller Runfola; Patricia Romero-Lankao; Leiwen Jiang; Lori M. Hunter; Raphael Nawrotzki; Landy Sanchez. The Influence of Internal Migration on Exposure to Extreme Weather Events in Mexico. Society & Natural Resources 2015, 29, 750 -754.
AMA StyleDaniel Miller Runfola, Patricia Romero-Lankao, Leiwen Jiang, Lori M. Hunter, Raphael Nawrotzki, Landy Sanchez. The Influence of Internal Migration on Exposure to Extreme Weather Events in Mexico. Society & Natural Resources. 2015; 29 (6):750-754.
Chicago/Turabian StyleDaniel Miller Runfola; Patricia Romero-Lankao; Leiwen Jiang; Lori M. Hunter; Raphael Nawrotzki; Landy Sanchez. 2015. "The Influence of Internal Migration on Exposure to Extreme Weather Events in Mexico." Society & Natural Resources 29, no. 6: 750-754.
Increasing rates of climate migration may be of economic and national concern to sending and destination countries. It has been argued that social networks—the ties connecting an origin and destination—may operate as “migration corridors” with the potential to strongly facilitate climate change-related migration. This study investigates whether social networks at the household and community levels amplify or suppress the impact of climate change on international migration from rural Mexico. A novel set of 15 climate change indices was generated based on daily temperature and precipitation data for 214 weather stations across Mexico. Employing geostatistical interpolation techniques, the climate change values were linked to 68 rural municipalities for which sociodemographic data and detailed migration histories were available from the Mexican Migration Project. Multi-level discrete-time event-history models were used to investigate the effect of climate change on international migration between 1986 and 1999. At the household level, the effect of social networks was approximated by comparing the first to the last move, assuming that through the first move a household establishes internal social capital. At the community level, the impact of social capital was explored through interactions with a measure of the proportion of adults with migration experience. The results show that rather than amplifying, social capital may suppress the sensitivity of migration to climate triggers, suggesting that social networks could facilitate climate change adaptation in place.
Raphael J. Nawrotzki; Fernando Riosmena; Lori M. Hunter; Daniel Miller Runfola. Amplification or suppression: Social networks and the climate change—migration association in rural Mexico. Global Environmental Change 2015, 35, 463 -474.
AMA StyleRaphael J. Nawrotzki, Fernando Riosmena, Lori M. Hunter, Daniel Miller Runfola. Amplification or suppression: Social networks and the climate change—migration association in rural Mexico. Global Environmental Change. 2015; 35 ():463-474.
Chicago/Turabian StyleRaphael J. Nawrotzki; Fernando Riosmena; Lori M. Hunter; Daniel Miller Runfola. 2015. "Amplification or suppression: Social networks and the climate change—migration association in rural Mexico." Global Environmental Change 35, no. : 463-474.
Studies investigating migration as a response to climate variability have largely focused on rural locations to the exclusion of urban areas. This lack of urban focus is unfortunate given the sheer numbers of urban residents and continuing high levels of urbanization. To begin filling this empirical gap, this study investigates climate change impacts on U.S.-bound migration from rural and urban Mexico, 1986–1999. We employ geostatistical interpolation methods to construct two climate change indices, capturing warm and wet spell duration, based on daily temperature and precipitation readings for 214 weather stations across Mexico. In combination with detailed migration histories obtained from the Mexican Migration Project, we model the influence of climate change on household-level migration from 68 rural and 49 urban municipalities. Results from multilevel event-history models reveal that a temperature warming and excessive precipitation significantly increased international migration during the study period. However, climate change impacts on international migration is only observed for rural areas. Interactions reveal a causal pathway in which temperature (but not precipitation) influences migration patterns through employment in the agricultural sector. As such, climate-related international migration may decline with continued urbanization and the resulting reductions in direct dependence of households on rural agriculture.
Raphael J. Nawrotzki; Lori M. Hunter; Daniel M. Runfola; Fernando Riosmena. Climate change as a migration driver from rural and urban Mexico. Environmental Research Letters 2015, 10, 1 .
AMA StyleRaphael J. Nawrotzki, Lori M. Hunter, Daniel M. Runfola, Fernando Riosmena. Climate change as a migration driver from rural and urban Mexico. Environmental Research Letters. 2015; 10 (11):1.
Chicago/Turabian StyleRaphael J. Nawrotzki; Lori M. Hunter; Daniel M. Runfola; Fernando Riosmena. 2015. "Climate change as a migration driver from rural and urban Mexico." Environmental Research Letters 10, no. 11: 1.