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The Effect
Extensive code examples in R, Stata, and Python Chapters on overlooked topics in econometrics classes: heterogeneous treatment effects, simulation and power analysis, new cutting-edge methods, and uncomfortable ignored assumptions An easy-to-read conversational tone Up-to-date coverage of methods with fast-moving literatures like difference-in-differences
Causal Inference
An accessible, contemporary introduction to the methods for determining cause and effect in the Social Sciences “Causation versus correlation has been the basis of arguments—economic and otherwise—since the beginning of time. Causal Inference: The Mixtape uses legit real-world examples that I found genuinely thought-provoking. It’s rare that a book prompts readers to expand their outlook; this one did for me.”—Marvin Young (Young MC) Causal inference encompasses the tools that allow social scientists to determine what causes what. In a messy world, causal inference is what helps establish the causes and effects of the actions being studied—for example, the impact (or lack thereof) of increases in the minimum wage on employment, the effects of early childhood education on incarceration later in life, or the influence on economic growth of introducing malaria nets in developing regions. Scott Cunningham introduces students and practitioners to the methods necessary to arrive at meaningful answers to the questions of causation, using a range of modeling techniques and coding instructions for both the R and the Stata programming languages.
The Book of Why
The hugely influential book on how the understanding of causality revolutionized science and the world, by the pioneer of artificial intelligence 'Wonderful ... illuminating and fun to read' Daniel Kahneman, Nobel Prize-winner and author of Thinking, Fast and Slow 'Correlation does not imply causation.' For decades, this mantra was invoked by scientists in order to avoid taking positions as to whether one thing caused another, such as smoking and cancer, or carbon dioxide and global warming. But today, that taboo is dead. The causal revolution, sparked by world-renowned computer scientist Judea Pearl and his colleagues, has cut through a century of confusion and placed cause and effect on a ...
Impact Evaluation
Encompasses the main concepts and approaches of quantitative impact evaluations, used to consider the effectiveness of programmes, policies, projects or interventions. This textbook for economics graduate courses can also serve as a manual for professionals in research institutes, governments, and international organizations.
Thinking Clearly with Data
"This is an intro-level text that teaches how to think clearly and conceptually about quantitative information, emphasizing ideas over technicality and assuming no prior exposure to data analysis, statistics, or quantitative methods. The books four parts present the foundation for quantiative reasoning: correlation and causation; statistical relationships; causal phenomena; and incorporating quantitative information into decision making. Within these parts it covers the array of tools used by social scientists, including regression, inference, experiments, research design, and more, all by explaining the rationale and logic behind such tools rather than focusing only on the technical calculations used for each. New concepts are presented simply, with the help of copious examples, and the books leans towards graphic rather than mathematical representation of data, with any technical material included in appendices"--
Data Analysis for Business, Economics, and Policy
A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data.
Linear Algebra for Economists
This textbook introduces students of economics to the fundamental notions and instruments in linear algebra. Linearity is used as a first approximation to many problems that are studied in different branches of science, including economics and other social sciences. Linear algebra is also the most suitable to teach students what proofs are and how to prove a statement. The proofs that are given in the text are relatively easy to understand and also endow the student with different ways of thinking in making proofs. Theorems for which no proofs are given in the book are illustrated via figures and examples. All notions are illustrated appealing to geometric intuition. The book provides a variety of economic examples using linear algebraic tools. It mainly addresses students in economics who need to build up skills in understanding mathematical reasoning. Students in mathematics and informatics may also be interested in learning about the use of mathematics in economics.
A Practical Introduction to Regression Discontinuity Designs
In this Element, which continues our discussion in Foundations, the authors provide an accessible and practical guide for the analysis and interpretation of Regression Discontinuity (RD) designs that encourages the use of a common set of practices and facilitates the accumulation of RD-based empirical evidence. The focus is on extensions to the canonical sharp RD setup that we discussed in Foundations. The discussion covers (i) the local randomization framework for RD analysis, (ii) the fuzzy RD design where compliance with treatment is imperfect, (iii) RD designs with discrete scores, and (iv) and multi-dimensional RD designs.
Climate Economics
This unique and erudite second edition can be used at three different levels – advanced undergraduate, post-graduate and doctoral. It comprehensively covers the critical issues on the economics of climate change and climate policy features and clearly identifies the specific sections each level of reader should explore. Topics include the costs and benefits of adaptation and mitigation, discounting, uncertainty, policy instruments, and international agreements. Lectures can be combined with exercises, guided reading, or the building and application of an integrated assessment model. The book is accompanied by a website with background material, data, opinion pieces and videos. Although primarily intended for use in the classroom, anyone with an interest in climate policy can use this text as a reference.
Experimetrics
This advanced textbook is an essential guide to discovering new and more illuminating ways to analyse the econometric modelling of experimental data. Peter Moffatt, one of the world's experts in the field, covers a range of techniques: from the familiar, such as treatment testing, to lesser known ones such as finite mixture models and the method of maximum simulated likelihood. The book takes a hands-on approach by explaining STATA commands in detail. In addition, difficult problems inherent in the methodology are addressed, such as the parametric estimation of social preference models, quantal response models, and learning models. An indispensable book for researchers and advanced students in experimental and behavioural economics who want to come to grips with the field of Experimetrics. The companion website www.palgrave.com/moffatt contains: - All data sets (in Stata format) used as examples in the book - An executable Stata 'do-file' containing stata commands and programs used in examples And - An Excel file containing some Excel calculations presented in the text
