This book focuses on structural changes and economic modeling. It presents papers describing how to model structural changes, as well as those introducing improvements to the existing before-structural-changes models, making it easier to later on combine these models with techniques describing structural changes. The book also includes related theoretical developments and practical applications of the resulting techniques to economic problems. Most traditional mathematical models of economic processes describe how the corresponding quantities change with time. However, in addition to such relatively smooth numerical changes, economical phenomena often undergo more drastic structural change. Describing such structural changes is not easy, but it is vital if we want to have a more adequate description of economic phenomena – and thus, more accurate and more reliable predictions and a better understanding on how best to influence the economic situation.

Econometric models are made up of assumptions which never exactly match reality. Among the most contested ones is the requirement that the coefficients of an econometric model remain stable over time. Recent years have therefore seen numerous attempts to test for it or to model possible structural change when it can no longer be ignored. This collection of papers from Empirical Economics mirrors part of this development. The point of departure of most studies in this volume is the standard linear regression model Yt = x;fJt + U (t = I, ... , 1), t where notation is obvious and where the index t emphasises the fact that structural change is mostly discussed and encountered in a time series context. It is much less of a problem for cross section data, although many tests apply there as well. The null hypothesis of most tests for structural change is that fJt = fJo for all t, i.e. that the same regression applies to all time periods in the sample and that the disturbances u are well behaved. The well known Chow test for instance assumes t that there is a single structural shift at a known point in time, i.e. that fJt = fJo (t

This volume focuses on recent developments in the use of structural econometric models in empirical economics. The first part looks at recent developments in the estimation of dynamic discrete choice models. The second part looks at recent advances in the area empirical matching models.

This book aims to fill the gap between panel data econometrics textbooks, and the latest development on 'big data', especially large-dimensional panel data econometrics. It introduces important research questions in large panels, including testing for cross-sectional dependence, estimation of factor-augmented panel data models, structural breaks in panels and group patterns in panels. To tackle these high dimensional issues, some techniques used in Machine Learning approaches are also illustrated. Moreover, the Monte Carlo experiments, and empirical examples are also utilised to show how to implement these new inference methods. Large-Dimensional Panel Data Econometrics: Testing, Estimation and Structural Changes also introduces new research questions and results in recent literature in this field.

Specially selected from The New Palgrave Dictionary of Economics 2nd edition, each article within this compendium covers the fundamental themes within the discipline and is written by a leading practitioner in the field. A handy reference tool.

This book presents an original theoretical treatment of the problems of maintaining full employment in a multisector economic system

This book offers a theoretically novel way of approaching the knowledge economy, combining analysis of the works of Schumpeter and Kuznets and suggesting fresh conclusions. Francesco Quataro is an up and coming young scholar whose research with Cristiano Antonelli has been widely published in journals.

This book presents recent research on predictive econometrics and big data. Gathering edited papers presented at the 11th International Conference of the Thailand Econometric Society (TES2018), held in Chiang Mai, Thailand, on January 10-12, 2018, its main focus is on predictive techniques – which directly aim at predicting economic phenomena; and big data techniques – which enable us to handle the enormous amounts of data generated by modern computers in a reasonable time. The book also discusses the applications of more traditional statistical techniques to econometric problems. Econometrics is a branch of economics that employs mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. It is therefore important to develop data processing techniques that explicitly focus on prediction. The more data we have, the better our predictions will be. As such, these techniques are essential to our ability to process huge amounts of available data.

Studies that integrate scientific, technological, and economic dimensions of industrial ecology and material flows. The use of economic modeling techniques in industrial ecology research provides distinct advantages over the customary approach, which focuses on the physical description of material flows. The thirteen chapters of Economics of Industrial Ecology integrate the natural science and technological dimensions of industrial ecology with a rigorous economic approach and by doing so contribute to the advancement of this emerging field. Using a variety of modeling techniques (including econometric, partial and general equilibrium, and input-output models) and applying them to a wide range of materials, economic sectors, and countries, these studies analyze the driving forces behind material flows and structural changes in order to offer guidance for economically and socially feasible policy solutions. After a survey of concepts and relevant research that provides a useful background for the chapters that follow, the book presents historical analyses of structural change from statistical and decomposition approaches; a range of models that predict structural change on the national and regional scale under different policy scenarios; two models that can be used to analyze waste management and recycling operations; and, adopting the perspective of local scale, an analysis of the dynamics of eco-industrial parks in Denmark and the Netherlands. The book concludes with a discussion of the policy implications of an economic approach to industrial ecology.

This study provides a comprehensive overview of Korea’s macroeconomic growth and structural change since World War II, and traces some of the roots of development to the colonial period. The authors explore in detail colonial development, changing national income patterns, relative price shifts, sources of aggregate growth, and sources of sectoral structural change, comparing them with other countries.