In many disciplines of science it is vital to know the effect of a 'treatment' on a response variable of interest; the effect being known as the 'treatment effect'. Here, the treatment can be a drug, an education program or an economic policy, and the response variable can be an illness,academic achievement or GDP. Once the effect is found, it is possible to intervene to adjust the treatment and attain a desired level of the response variable.A basic way to measure the treatment effect is to compare two groups, one of which received the treatment and the other did not. If the two groups are homogenous in all aspects other than their treatment status, then the difference between their response outcomes is the desired treatment effect. Butif they differ in some aspects in addition to the treatment status, the difference in the response outcomes may be due to the combined influence of more than one factor. In non-experimental data where the treatment is not randomly assigned but self-selected, the subjects tend to differ in observedor unobserved characteristics. It is therefore imperative that the comparison be carried out with subjects similar in their characteristics. This book explains how this problem can be overcome so the attributable effect of the treatment can be found.This book brings to the fore recent advances in econometrics for treatment effects. The purpose of this book is to put together various economic treatments effect models in a coherent fashion, make it clear which can be parameters of interest, and show how they can be identified and estimated underweak assumptions. The emphasis throughout the book is on semi- and non-parametric estimation methods, but traditional parametric approaches are also discussed. This book is ideally suited to researchers and graduate students with a basic knowledge of econometrics.

This book provides the most comprehensive treatment to date of microeconometrics, the analysis of individual-level data on the economic behavior of individuals or firms using regression methods for cross section and panel data. The book is oriented to the practitioner. A basic understanding of the linear regression model with matrix algebra is assumed. The text can be used for a microeconometrics course, typically a second-year economics PhD course; for data-oriented applied microeconometrics field courses; and as a reference work for graduate students and applied researchers who wish to fill in gaps in their toolkit. Distinguishing features of the book include emphasis on nonlinear models and robust inference, simulation-based estimation, and problems of complex survey data. The book makes frequent use of numerical examples based on generated data to illustrate the key models and methods. More substantially, it systematically integrates into the text empirical illustrations based on seven large and exceptionally rich data sets.

The estimation of the effects of treatments endogenous variables representing everything from individual participation in a training program to national participation in a World Bank loan program has occupied much of the theoretical and applied econometric research literatures. This volume presents a collection of papers on this topic.

This book provides advanced theoretical and applied tools for the implementation of modern micro-econometric techniques in evidence-based program evaluation for the social sciences. The author presents a comprehensive toolbox for designing rigorous and effective ex-post program evaluation using the statistical software package Stata. For each method, a statistical presentation is developed, followed by a practical estimation of the treatment effects. By using both real and simulated data, readers will become familiar with evaluation techniques, such as regression-adjustment, matching, difference-in-differences, instrumental-variables, regression-discontinuity-design, and synthetic control method, and are given practical guidelines for selecting and applying suitable methods for specific policy contexts. The second revised and extended edition features two new chapters on some recent development of difference-in-differences. Specifically, chapter 5 introduces advanced difference-in-differences methods when many times are available and treatment can be either time-varying or fixed at a specific time. Chapter 6 introduces the synthetic control method, a treatment effect estimation approach suitable when only one unit is treated. Both chapters present applications using the software Stata.

Up-to-date coverage of most micro-econometric topics; first half parametric, second half semi- (non-) parametric Many empirical examples and tips in applying econometric theories to data Essential ideas and steps shown for most estimators and tests; well-suited for both applied and theoretical readers

Inclusive Growth in Africa analyzes the concept of inclusion within the challenges facing Africa’s rapidly growing economies, where rising affluence for some has been accompanied almost everywhere with rising inequality. Using a combination of political economy analyses, sector studies and econometric models, the contributors delve into a range of areas associated to the new realities on the continent. Topics covered include issues of disability, corruption, capital flight, and their implications for economic sustainability. There is also a discussion of the impact on development of dependence on externally determined prices for Africa’s natural resources. Other sector analyses look at agriculture and wind power, and the innovations required to make a difference for the poorer majority. The book comprises of a rich array of essays on socio-economic inclusion in Africa by authors drawn from academia, African think tanks and international organizations. It would be of interest to scholars and students of many disciplines, including: Economics, Sociology, Development Studies, and African Studies.

The humid highlands in sub-Saharan Africa (SSA) are characterized by high population densities and require intensification. The Consortium for Improving Agriculture-based Livelihoods in Central Africa (CIALCA) has set up a research for development platform in various mandate areas in DR Congo, Burundi, and Rwanda, aiming to identify improved production, market, and nutrition options and facilitating the access for development partners to these options. This platform is supported by capacity building, multi-stakeholder dialogue, and monitoring and evaluation efforts. The conference, facilitated by CIALCA, aimed to (i) take stock of the state-of the art in agricultural intensification in the highlands of SSA and (ii) chart the way forward for agricultural research for development in the humid highlands of SSA, and more specifically in the recently launched Humidtropics Consortium Research Programme, through keynote, oral and poster presentations, and strategic panel discussions.