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Papers and proceedings of a regional seminar organized in collaboration with the research and information system for the non-aligned and other developing countries (RIS) New Delhi, 27 February to 1 March 1989.
A textbook for a graduate or final-year undergraduate course in tourism studies that might also find interest among researchers and practitioners who want to apply recent developments in econometric modeling and forecasting to tourism demand analysis. Song and Witt (both management in the service sector, U. of Surrey, Britain) begin with the fundamentals of tourism demand analysis, and the problems of traditional modeling and forecasting. Then they explore the general- to-specific approach, the time-varying parameter model, and the panel- data approach. Annotation copyrighted by Book News, Inc., Portland, OR
This is the first outcome of our effort in ASIAN LINK PROJECT to construct the econometric models of Asian developing countries and analyze their inter-dependence with major trading partners, the United States and Japan. The model we present here is called Asian Link System. The countries in this system include Korea, Taiwan, Hong Kong, China, the Philippines, Thailand, Malaysia, Singapore, Indonesia, Japan and the United States. They are covered by national models. The rest of the world is divided into several regions and treated by simple proto-type models. The main characteristics of Asian Link System are to deal with the inter-dependent relations between Asian developing countries on the one hand and Japan and United States on the other hand. Here are presented these national models and the Asian Link System with the underlying statistical data, so that any econometrician can re-estimate our models and check the results of our research work. Nowadays most articles and books in econometrics report only the final results or conclusions of research so that no other econometrician can re-calculate or re examine the findings. This is very serious in the empirical research, because as theorists may make mistakes, positive economists do commit errors or miss some possible considerations. Unless statiscal data are offered, other econometricians cannot make suggestions or improve the models. This is the main reason why empirical research in econometrics or applied econometrics are not making substantial progress in recent years.
This book is a sequel to our first report of ASIAN LINK PROJECT in 1985: Econometric Models of Asian LINK, Springer-Verlag, Tokyo - Berlin - New York. Now the scope is expanded to Asian-Pacific Countries in coverage, so that this monograph presents the econometric models of Japan, the United States, Canada, China, Korea, Taiwan, Hong Kong, Thailand, the Philippines, Malaysia, Singa pore, Indonesia, Australia and the European Community. We are particularly happy to have included the excellent models of Australia and Canada whose economies are essential parts of the Asian-Pacific Economic Community. Most of those models were presented at the Workshop of Asian Link Project held in Bandung, Indonesia at the time of the Second Convention of the East Asian Eco nomic Association, 1990. Those models have been up-dated since then, and several other important models were added. Unlike our previous book, we have not tried here to link these national models as a regional or global model in any way, ex cept for the model by S. Kinoshita which offers a regional linkage for Pacific-basin economies by linking the US, Japan, Canada, the European Community coun tries as a group, Asian NIEs (Korea, Hong Kong, Taiwan), ASEAN (Indonesia, Malaysia, the Philippines, Singapore) and East Asian economies. As we argued in our previous publication, we tried to publish these econometric models again with the statistical data as much as we could, so as to enable the reader examine the estimation and performance of the models by himself.
This insightful and timely volume provides a succinct, expert-led introduction to the latest developments in advanced econometric methodologies in the context of tourism demand modelling and forecasting. Written by a plethora of worldwide experts on this topic, this book offers a comprehensive approach to tourism econometrics. Accurate demand forecasts are crucial to decision-making in the tourism industry and this book provides real-life tourism applications and the corresponding R code alongside theoretical foundations, in order to enhance understanding and practice amongst its readers. The methodologies introduced include general to specific modelling, cointegration, vector autoregression, time-varying parameter modelling, spatiotemporal econometric models, mixed-frequency forecasting, hybrid forecasting models, forecasting combination techniques, density forecasting, judgemental forecasting, scenario forecasting under crisis, and web-based tourism forecasting. Embellished with insightful figures and tables throughout, this book is an invaluable resource for those using advanced econometric methodologies in their studies and research, including both undergraduate and postgraduate students, researchers, and practitioners.
Econometric Modeling provides a new and stimulating introduction to econometrics, focusing on modeling. The key issue confronting empirical economics is to establish sustainable relationships that are both supported by data and interpretable from economic theory. The unified likelihood-based approach of this book gives students the required statistical foundations of estimation and inference, and leads to a thorough understanding of econometric techniques. David Hendry and Bent Nielsen introduce modeling for a range of situations, including binary data sets, multiple regression, and cointegrated systems. In each setting, a statistical model is constructed to explain the observed variation in the data, with estimation and inference based on the likelihood function. Substantive issues are always addressed, showing how both statistical and economic assumptions can be tested and empirical results interpreted. Important empirical problems such as structural breaks, forecasting, and model selection are covered, and Monte Carlo simulation is explained and applied. Econometric Modeling is a self-contained introduction for advanced undergraduate or graduate students. Throughout, data illustrate and motivate the approach, and are available for computer-based teaching. Technical issues from probability theory and statistical theory are introduced only as needed. Nevertheless, the approach is rigorous, emphasizing the coherent formulation, estimation, and evaluation of econometric models relevant for empirical research.
This important book consists of surveys of high-frequency financial data analysis and econometric forecasting, written by pioneers in these areas including Nobel laureate Lawrence Klein. Some of the chapters were presented as tutorials to an audience in the Econometric Forecasting and High-Frequency Data Analysis Workshop at the Institute for Mathematical Science, National University of Singapore in May 2006. They will be of interest to researchers working in macroeconometrics as well as financial econometrics. Moreover, readers will find these chapters useful as a guide to the literature as well as suggestions for future research. Sample Chapter(s). Foreword (32 KB). Chapter 1: Forecast Uncertainty, Its Representation and Evaluation* (97 KB). Contents: Forecasting Uncertainty, Its Representation and Evaluation (K F Wallis); The University of Pennsylvania Models for High-Frequency Macroeconomic Modeling (L R Klein & S Ozmucur); Forecasting Seasonal Time Series (P H Franses); Car and Affine Processes (C Gourieroux); Multivariate Time Series Analysis and Forecasting (M Deistler). Readership: Professionals and researchers in econometric forecasting and financial data analysis.
How to interpret and evaluate economic forecasts and the uncertainties inherent in them.
A comprehensive and integrated approach to economic forecasting problems Economic forecasting involves choosing simple yet robust models to best approximate highly complex and evolving data-generating processes. This poses unique challenges for researchers in a host of practical forecasting situations, from forecasting budget deficits and assessing financial risk to predicting inflation and stock market returns. Economic Forecasting presents a comprehensive, unified approach to assessing the costs and benefits of different methods currently available to forecasters. This text approaches forecasting problems from the perspective of decision theory and estimation, and demonstrates the profound implications of this approach for how we understand variable selection, estimation, and combination methods for forecasting models, and how we evaluate the resulting forecasts. Both Bayesian and non-Bayesian methods are covered in depth, as are a range of cutting-edge techniques for producing point, interval, and density forecasts. The book features detailed presentations and empirical examples of a range of forecasting methods and shows how to generate forecasts in the presence of large-dimensional sets of predictor variables. The authors pay special attention to how estimation error, model uncertainty, and model instability affect forecasting performance. Presents a comprehensive and integrated approach to assessing the strengths and weaknesses of different forecasting methods Approaches forecasting from a decision theoretic and estimation perspective Covers Bayesian modeling, including methods for generating density forecasts Discusses model selection methods as well as forecast combinations Covers a large range of nonlinear prediction models, including regime switching models, threshold autoregressions, and models with time-varying volatility Features numerous empirical examples Examines the latest advances in forecast evaluation Essential for practitioners and students alike
As real estate forms a significant part of the asset portfolios of most investors and lenders, it is crucial that analysts and institutions employ sound techniques for modelling and forecasting the performance of real estate assets. Assuming no prior knowledge of econometrics, this book introduces and explains a broad range of quantitative techniques that are relevant for the analysis of real estate data. It includes numerous detailed examples, giving readers the confidence they need to estimate and interpret their own models. Throughout, the book emphasises how various statistical techniques may be used for forecasting and shows how forecasts can be evaluated. Written by a highly experienced teacher of econometrics and a senior real estate professional, both of whom are widely known for their research, Real Estate Modelling and Forecasting is the first book to provide a practical introduction to the econometric analysis of real estate for students and practitioners.