Description
With a focus on practical applications, this book delves into the fundamental concepts, methods, and techniques of statistical inference, estimation, prediction, and econometric modeling. It begins by laying the foundation of statistical inference, covering topics such as the role of statistics in economic analysis, types of data and measurement scales, sampling methods, and probability concepts.
From there, the book explores estimation and prediction techniques, examining point and interval estimation, hypothesis testing, linear regression, and model selection. It then delves into the realm of time series analysis, focusing on the stationarity of time series data, ARIMA models, forecasting techniques, and seasonal and non-seasonal models.
To further enhance understanding of economic phenomena, the book covers econometric models, including ordinary least squares (OLS) estimation, generalized least squares (GLS) estimation, instrumental variables (IV) estimation, maximum likelihood estimation (MLE), and Bayesian estimation. It also examines limited dependent variable models, such as binary choice models, multinomial choice models, and ordered choice models.
With a focus on practical applications, the book provides valuable insights into forecasting economic and financial variables, exploring time series forecasting methods, structural econometric models, Bayesian forecasting, and the evaluation and combination of forecasts. It also covers causal inference and impact evaluation techniques, including randomized controlled trials, observational studies, propensity score matching, regression discontinuity design, and instrumental variables methods.
Our journey concludes with an exploration of the frontiers of econometrics, examining recent developments in econometric theory, emerging applications of econometrics, and the challenges and opportunities that lie ahead. We also discuss the ethical considerations and future directions of econometrics, highlighting its vital role in informing economic policy and decision-making.
Written in a clear, engaging, and accessible style, this book provides a comprehensive and enjoyable learning experience for readers seeking to master the art of statistical inference and econometric modeling. With its emphasis on real-world examples and contextually relevant content, this guide is an invaluable resource for economists, data scientists, and anyone seeking to make informed decisions based on data.
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Language : English
Dimensions : 6 x 9 inches
Pages : 201 pages
Pasquale De Marco stands as a prolific author whose literary prowess knows no bounds. With a passion for storytelling that transcends genres, he has made a name for himself as a versatile writer with the extraordinary ability to captivate readers across diverse literary landscapes. His journey as an author is marked by an insatiable curiosity, a love for the written word, and a relentless commitment to sharing knowledge and experiences with the world.
Pasquale De Marco collaborates with a dedicated team of ghostreaders who assist him in evaluating and editing the manuscripts. His collaborators are not only skilled professionals but also avid readers who purchase and read books as a personal hobby. This unique blend of creativity allows Pasquale to push the boundaries of traditional publishing, making literature more accessible and diverse.
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