Deep Mukherjee – författare

This book analyzes different perspectives around sustainable development, risk management and managing demand across various sectors in India. Diverse theories and analytical methods from various disciplines, as well as case studies, are brought together to present an in-depth study.The book discusses the challenges of achieving sustainability, the role of quantitative research to assess current scenarios, and the role of policy making to bring improvements in the Indian context. It examines the socioeconomic ways of pursuing sustainable development in the areas of agriculture, climate change and energy; the environment and natural resources; health and society. It also analyzes important quantitative models for sustainability policy analysis and provides case studies to understand the practical implementations of the models.This book will be a great reference manual that covers a whole gamut of analytical techniques that are useful for students, research scholars and practitioners of economics, environmental studies, development studies, sociology, South Asian studies and public policy, among others.

This book analyzes different perspectives around sustainable development, risk management and managing demand across various sectors in India. Diverse theories and analytical methods from various disciplines, as well as case studies, are brought together to present an in-depth study.The book discusses the challenges of achieving sustainability, the role of quantitative research to assess current scenarios, and the role of policy making to bring improvements in the Indian context. It examines the socioeconomic ways of pursuing sustainable development in the areas of agriculture, climate change and energy; the environment and natural resources; health and society. It also analyzes important quantitative models for sustainability policy analysis and provides case studies to understand the practical implementations of the models.This book will be a great reference manual that covers a whole gamut of analytical techniques that are useful for students, research scholars and practitioners of economics, environmental studies, development studies, sociology, South Asian studies and public policy, among others.

This book leverages statistical analysis, data mining, and machine learning techniques to address managerial and socioeconomic problems. With the advent of modern technologies, massive amount of data, especially big data, proliferate from business transactions and users. Consequently, there is an ever-increasing demand for analyzing the data and gaining valuable insights. This book comprises 15 chapters: the first ten chapters cover methods from Statistics and Econometrics, while the next five chapters delve into selected Machine Learning techniques. By bringing together the expertise of eminent researchers from reputed universities worldwide, this volume provides a cohesive guide to understanding and applying data science methodologies to real-world problems.The book assumes basic knowledge of probability and statistics. Each chapter presents a blend of theoretical insights and practical case studies, ensuring that readers not only learn the techniques but also see their relevance and implementation in real-world scenarios. The chapters not only cover the theoretical underpinnings in a student-friendly language but also provide step-by-step guides for implementation using various software tools such as R, Python, Matlab, and SPSS. This is to instill confidence in the reader to apply such techniques to real-life problems. The book is designed for a broad spectrum of readership - empirical economists, business analysts, and post-graduate students aiming to learn and practice data science. Moreover, the book is designed in such a way that it can be used as a practical reference book for one semester-long Data Science course.

This book is a collection of 20 chapters on chosen topics from cross-section and panel data econometrics.