Getting accurate data on less developed countries has created great problems for studying these areas. Yet until recently students of development economics have relied on standard econometrics texts, which assume a Western context. Econometrics and Data Analysis for Developing Countries solves this problem. It will be essential reading for all advanced students of development economics.
Exploring and understanding the analysis of economic development is essential as global economies continue to experience extreme fluctuation. Econometrics brings together statistical methods for practical content and economic relations. Econometric Methods for Analyzing Economic Development is a comprehensive collection that focuses on various regions and their economies at a pivotal time when the majority of nations are struggling with stabilizing their economies. Outlining areas such as employment rates, utilization of natural resources, and regional impacts, this collection of research is an excellent tool for scholars, academics, and professionals looking to expand their knowledge on todays turbulent and changing economy.
"This book examines the application of econometric methods as used by researchers in academia, public policy, and areas in social science and business"--
What guidance does academic research really provide to economic policy development? The critical and analytical surveys in this volume investigate links between policies and outcomes by surveying work from broad macroeconomic policies to interventions in microfinance. Asserting that there are no universal correspondences between policies and outcomes, contributors demonstrate instead that only an intense familiarity with the development context and the universe of applicable economic models can generate successful policies. Getting cause-and-effect right is essential for policy design and implementation. With the goal of drawing researchers and policy makers closer, this volume highlights our increasing understanding of ways to combine economic theorizing with careful, thoughtful empirical work. - Presents an accurate, self-contained survey of the current state of the field - Summarizes the most recent discussions, and elucidates new developments - Although original material is also included, the main aim is the provision of comprehensive and accessible surveys
Using data from several countries, including Cote d'Ivoire, India, Pakistan, Taiwan, and Thailand, this book analyzes household survey data from developing countries and illustrates how such data can be used to cast light on a range of short-term and long-term policy issues.
Analysis of Economic Data has, over three editions, become firmly established as a successful textbook for students studying data analysis whose primary interest is not in econometrics, statistics or mathematics. It introduces students to basic econometric techniques and shows the reader how to apply these techniques in the context of real-world empirical problems. The book adopts a largely non-mathematical approach relying on verbal and graphical inuition and covers most of the tools used in modern econometrics research. It contains extensive use of real data examples and involves readers in hands-on computer work.
With new technologies, such as computer vision, internet of things, mobile computing, e-governance and e-commerce, and wide applications of social media, organizations generate a huge volume of data and at a much faster rate than several years ago. Big data in large-/small-scale systems, characterized by high volume, diversity, and velocity, increasingly drives decision making and is changing the landscape of business intelligence. From governments to private organizations, from communities to individuals, all areas are being affected by this shift. There is a high demand for big data analytics that offer insights for computing efficiency, knowledge discovery, problem solving, and event prediction. To handle this demand and this increase in big data, there needs to be research on innovative and optimized machine learning algorithms in both large- and small-scale systems. Applications of Big Data in Large- and Small-Scale Systems includes state-of-the-art research findings on the latest development, up-to-date issues, and challenges in the field of big data and presents the latest innovative and intelligent applications related to big data. This book encompasses big data in various multidisciplinary fields from the medical field to agriculture, business research, and smart cities. While highlighting topics including machine learning, cloud computing, data visualization, and more, this book is a valuable reference tool for computer scientists, data scientists and analysts, engineers, practitioners, stakeholders, researchers, academicians, and students interested in the versatile and innovative use of big data in both large-scale and small-scale systems.
