frameworks and methods for impact assessment

This study provides an overview of existing approaches and methods for assessing the environmental impacts of trade and trade-related activities. It considers both approaches that are tailored to the assessment of trade- environment linkages and more generic approaches for environmental assessment and analyzes their respective usability in the context of trade-related development cooperation. The study thereby aims to contribute to a more extensive use of such tools, while improving the practice and application of environmental assessments of trade-related policies and programs. In doing so, the study will complement the existing study on the assessment of the socio- economic impacts from trade carried out by the Overseas Development Institute (ODI)1. The study is divided into two parts. Part I begins with a brief discussion on trade-related development cooperation followed by a short overview of the debate on trade, development and the environment. Next it provides an overview of existing approaches to conceptualizing environmental impacts from trade-related activities. After this, it provides a general introduction to impact assessment (IA) and the assessment of environmental impacts in this context. It closes with a brief overview of the assessment of environmental aspects in German development cooperation. Part II provides a more detailed review of existing frameworks and methods for assessing the environmental impacts from trade-related policies and programs

Impact Evaluations and Development: Nonie Guidance on Impact Evaluation

In international development, impact evaluation is principally concerned with final results of interventions (programs, projects, policy measures, reforms) on the welfare of communities, households, and individuals, including taxpayers and voters. Impact evaluation is one tool within the larger toolkit of monitoring and evaluation (including broad program evaluations, process evaluations, ex ante studies, etc.).The Network of Networks for Impact Evaluation (NONIE) was established in 2006 to foster more and better impact evaluations by its membership -- the evaluation networks of bilateral and multilateral organizations focusing on development issues, as well as networks of developing country evaluators. NONIE's member networks conduct a broad set of evaluations, examining issues such as project and strategy performance, institutional development, and aid effectiveness. By sharing methodological approaches and promoting learning by doing on impact evaluations, NONIE aims to promote the use of this more specific approach by its members within their larger portfolio of evaluations. This document, by Frans Leeuw and Jos Vaessen, has been developed to support this focus.For development practitioners, impact evaluations play a keyrole in the drive for better evidence on results and development effectiveness. They are particularly well suited to answer important questions about whether development interventions do or do not work, whether they make a difference, and how cost-effective they are. Consequently, they can help ensure that scarce resources are allocated where they can have the most developmental impact

Strategic Review of Tropical Fisheries Management

This project addresses the constraints to tropical fisheries development with sustainable exploitation through a strategic assessment of tropical fisheries management with the following purposes: (1) To evaluate relevant research methods for the development of assessment models appropriate to the circumstances of tropical coastal fisheries; and (2) To evaluate the utility of existing strategies for the implementation of management advice. The report consists of three substantive chapters. Chapter 2 contains a detailed socio-economic assessment of various instruments and implementation strategies applicable to tropical capture fisheries. In Chapter 3, a detailed assessment of the fisheries for tropical large marine ecosystems has been conducted using a technique developed by FAO (Granger & Garcia 1996). The data used were the FAO statistics published regularly by FAO. This analysis has been conducted for each of the tropical large marine ecosystems and indicates that there is the potential for increased fishing in a number of these ecosystems. One of the clear requirements identified in Chapter 2 and implicit in Chapter 3, is that there is a significant need for simple and robust fisheries assessment methods which can estimate the potential of a particular resource, its capacity in terms of the level of fishing effort and its current status ie whether it is currently exploited sustainably or not. In Chapter 4, these problems are addressed directly and, using two approaches, significant simplification of fishery methods is developed. In the first approach, simple empirical relationships between the life history parameters of a species are used to develop models of potential yield which can be determined by a simple assessment of fish growth. In the second approach, optimal life history theory is applied to the key demographic parameters of exploited fish populations and using estimates of the Beverton & Holt invariants a significant simplifying of the basic stock assessment equations is developed

Impact synergies, institutions, and food security: an evaluation methodology with empirical results

Food securityInstitutionsModels

Using data differently and using different data

The lack of adequate measures is often an impediment to robust policy evaluation. We discuss three approaches to measurement and data usage that have the potential to improve the way we conduct impact evaluations. First, the creation of new measures, when no adequate ones are available. Second, the use of multiple measures when a single one is not appropriate. And third, the use of machine learning algorithms to evaluate and understand programme impacts. We motivate the relevance of each of the categories by providing examples where they have proved useful in the past. We discuss the challenges and risks involved in each strategy and conclude with an outline of promising directions for future work

Strategies for sustainable land management and poverty reduction in Uganda:

"The government of Uganda, with help from its development partners, is designing and implementing policies and strategies to address poverty, land degradation, and declining agricultural productivity. Land degradation, especially soil erosion and depletion of soil nutrients, is widespread in Uganda and contributes to declining productivity, which in turn increases poverty. The report has four major objectives: (1) to examine the causes of land degradation in Uganda; (2) to identify the determinants of income strategies and land management decisions and their impacts on agricultural productivity, soil erosion, and household income; (3) to assess the trade-offs and complementarities among these different objectives; and (4) to analyze the soil nutrient depletion in eastern Uganda to determine the factors that influence it." from Text

Policy and Place: A Spatial Data Science Framework for Research and Decision-Making

abstract: A major challenge in health-related policy and program evaluation research is attributing underlying causal relationships where complicated processes may exist in natural or quasi-experimental settings. Spatial interaction and heterogeneity between units at individual or group levels can violate both components of the Stable-Unit-Treatment-Value-Assumption (SUTVA) that are core to the counterfactual framework, making treatment effects difficult to assess. New approaches are needed in health studies to develop spatially dynamic causal modeling methods to both derive insights from data that are sensitive to spatial differences and dependencies, and also be able to rely on a more robust, dynamic technical infrastructure needed for decision-making. To address this gap with a focus on causal applications theoretically, methodologically and technologically, I (1) develop a theoretical spatial framework (within single-level panel econometric methodology) that extends existing theories and methods of causal inference, which tend to ignore spatial dynamics; (2) demonstrate how this spatial framework can be applied in empirical research; and (3) implement a new spatial infrastructure framework that integrates and manages the required data for health systems evaluation. The new spatially explicit counterfactual framework considers how spatial effects impact treatment choice, treatment variation, and treatment effects. To illustrate this new methodological framework, I first replicate a classic quasi-experimental study that evaluates the effect of drinking age policy on mortality in the United States from 1970 to 1984, and further extend it with a spatial perspective. In another example, I evaluate food access dynamics in Chicago from 2007 to 2014 by implementing advanced spatial analytics that better account for the complex patterns of food access, and quasi-experimental research design to distill the impact of the Great Recession on the foodscape. Inference interpretation is sensitive to both research design framing and underlying processes that drive geographically distributed relationships. Finally, I advance a new Spatial Data Science Infrastructure to integrate and manage data in dynamic, open environments for public health systems research and decision- making. I demonstrate an infrastructure prototype in a final case study, developed in collaboration with health department officials and community organizations.Dissertation/ThesisDoctoral Dissertation Geography 201