Econometrics and economic statistics

As conceived by the founders of the Econometric Society, econometrics is a field that uses economic theory and statistical methods to address empirical problems in economics.

This monograph deals with spatially dependent nonstationary time series in a way accessible to both time series econometricians wanting to understand spatial econometics, and spatial econometricians lacking a grounding in time series analysis.

All manner of models are used to describe, simulate, extrapolate, and ultimately understand the function of dynamic systems.

Kryptowährungen haben die Finanzwelt revolutioniert – doch jetzt stehen sie vor einem neuen Wendepunkt: der Einbindung Künstlicher Intelligenz.

This book presents the Multiple Criteria Decision Making (MCDM) paradigm for modelling agricultural decision-making in three parts.

This full-color book provides a compendium of stimulating facts about the states, presented graphically, and covering a wide array of topics including demographic, economic, environmental, health, and crime variables.

This accessible textbook introduces the foundations of applied econometrics and statistics for undergraduate students.

In response to the damage caused by a growth-led global economy, researchers across the world started investigating the association between environmental pollution and its possible determinants using different models and techniques.

The Handbook is a definitive reference source and teaching aid for econometricians.

An Introduction to Wavelets and Other Filtering Methods in Finance and Economics presents a unified view of filtering techniques with a special focus on wavelet analysis in finance and economics.

The need to understand how to design and set up an investigative experiment is nearly universal to all students in engineering, applied technology and science, as well as many of the social sciences.

In seinem Werk 'Zur Psychologie des Geldes, Zur Psychologie der Frauen & Philosophie der Mode' erforscht Georg Simmel die tiefgreifenden psychologischen Aspekte von Geld, Frauen und Mode.

Central banks and other policymaking institutions use causal hypotheses to justify macroeconomic policy decisions to the public and public institutions.

Central banks and other policymaking institutions use causal hypotheses to justify macroeconomic policy decisions to the public and public institutions.

This book is about doing microeconometrics, defined by Cameron and Trivedi as "e;the analysis of individual-level data on the economic behavior of individuals or firms using regression methods applied to cross-section and panel data"e; with R.

This textbook is a comprehensive guide to machine learning and artificial intelligence tailored for students in business and economics.

The growth rate of national income has fluctuated widely in the United States since 1929.

For courses in Statistical Methods for the Social Sciences .

This book surveys what executives who make decisions based on forecasts and professionals responsible for forecasts should know about forecasting.

This book surveys what executives who make decisions based on forecasts and professionals responsible for forecasts should know about forecasting.

The concept of equilibrium plays a central role in various applied sciences, such as physics (especially, mechanics), economics, engineering, transportation, sociology, chemistry, biology and other fields.

This book aims to explore how to automate, innovate, design, and deploy emerging technologies in actuarial work transformations for the insurance and finance sector.

Research on forecasting methods has made important progress over recent years and these developments are brought together in the Handbook of Economic Forecasting.

Over the last 30 years the practice and use of game theory has changed dramatically, yet textbooks continue to present game theory with algebraic formalism and toy models.

The explosive growth in computational power over the past several decades offers new tools and opportunities for economists.

'Overall, the book is highly technical, including full mathematical proofs of the results stated.

This book explores new topics in modern research on empirical corporate finance and applied accounting, especially the econometric analysis of microdata.

Ebook: Using Statistics In Economics

This textbook provides the foundation for a course that takes PhD students in empirical accounting research from the very basics of statistics, data analysis, and causal inference up to the point at which they conduct their own research.

Bayesian Statistical Methods: With Applications to Machine Learning provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis.

The goals of this new, second edition of this book are to develop the skills and an appreciation for the richness and versatility of modern time series analysis as a tool for analyzing dependent data.

Cornerstones in Quantitative Empirical Methods - Volume I: Foundations provides a complete, self-contained path from first principles to modern statistical inference, giving a comprehensive technical foundation for understanding and analyzing data problems using quantitative methods.

Cornerstones in Quantitative Empirical Methods - Volume I: Foundations provides a complete, self-contained path from first principles to modern statistical inference, giving a comprehensive technical foundation for understanding and analyzing data problems using quantitative methods.

This book discusses the financial impact of Artificial Intelligence (AI) on the finance and business sectors.

A plethora of empirical studies on corporate finance do not yield clear results, making it difficult to draw consistent conclusions.

The goals of this new, second edition of this book are to develop the skills and an appreciation for the richness and versatility of modern time series analysis as a tool for analyzing dependent data.

This book discusses the financial impact of Artificial Intelligence (AI) on the finance and business sectors.

A plethora of empirical studies on corporate finance do not yield clear results, making it difficult to draw consistent conclusions.

Bayesian Statistical Methods: With Applications to Machine Learning provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis.

Multivariate Statistics and Machine Learning is a hands-on textbook providing an in-depth guide to multivariate statistics and select machine learning topics using R and Python software.

Multivariate Statistics and Machine Learning is a hands-on textbook providing an in-depth guide to multivariate statistics and select machine learning topics using R and Python software.