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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.
Contemporary Apprenticeship Reforms and Reconfigurations
INAP, the International Network on Innovative Apprenticeship has steadily grown to incorporate researchers from all over the world. In 2019 it's 8th international conference hosted by Konstanz University, Germany, points to various issues linked to contemporary apprenticeship reforms and reconfigurations, which indicates the need for apprenticeships to deliver on its promise of workplace skills and for it to evolve and also to change as the world economies develop. Apprenticeship is a model of work and training, which has benefits for many different types of economies and societies. Specific areas of research are represented in Konstanz by the following topics and from different countries' perspectives: - Governance and Stakeholders - Teaching and Learning - Academisation in Apprenticeships - Diversity and Inclusiveness - Internationalisation and Transfer of VET Services - Future Work: New Employment Patterns - Future Work: Industry 4.0 - School to Work Transition and Youth Employment - Modern Fields of TVET Research and Practice
Apprenticeship in a Globalised World
In April 2013, the International Network on Innovative Apprenticeship (INAP) hosted its fifth international conference in Johannesburg, South Africa, in co-operation with the International Labor Organization (ILO), bringing together researchers, policy makers, and practitioners from 34 nations. The title of the conference - "Apprenticeship in a Globalized World: Premises, Promises and Pitfalls" - points out the need for apprenticeship to deliver on its promise of workplace skills and for it to develop and change as world economies develop. An international exchange of ideas among researchers from all over the world is necessary to identify cases of good practice and facilitate the transfer o...
Econometrics
What is Econometrics The field of econometrics involves the utilization of statistical techniques to analyze economic data with the objective of providing empirical evidence to economic relationships. More specifically, it refers to "the quantitative analysis of actual economic phenomena based on the concurrent development of theory and observation, related by appropriate methods of inference." In a textbook that provides an introduction to economics, econometrics is described as a tool that enables economists to "sift through mountains of data to extract simple relationships." In the field of econometrics, Jan Tinbergen is identified as one of the two founding fathers. That other individual...
Mostly Harmless Econometrics
In addition to econometric essentials, this book covers important new extensions as well as how to get standard errors right. The authors explain why fancier econometric techniques are typically unnecessary and even dangerous.
Smoothing Techniques
The author has attempted to present a book that provides a non-technical introduction into the area of non-parametric density and regression function estimation. The application of these methods is discussed in terms of the S computing environment. Smoothing in high dimensions faces the problem of data sparseness. A principal feature of smoothing, the averaging of data points in a prescribed neighborhood, is not really practicable in dimensions greater than three if we have just one hundred data points. Additive models provide a way out of this dilemma; but, for their interactiveness and recursiveness, they require highly effective algorithms. For this purpose, the method of WARPing (Weighted Averaging using Rounded Points) is described in great detail.
