Philip Hans Franses and Richard Paap
- Published in print:
- 2004
- Published Online:
- August 2004
- ISBN:
- 9780199242023
- eISBN:
- 9780191601286
- Item type:
- book
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/019924202X.001.0001
- Subject:
- Economics and Finance, Econometrics
This book considers periodic time series models for seasonal data, characterized by parameters that differ across the seasons, and focuses on their usefulness for out-of-sample forecasting. Providing ...
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This book considers periodic time series models for seasonal data, characterized by parameters that differ across the seasons, and focuses on their usefulness for out-of-sample forecasting. Providing an up-to-date survey of the recent developments in periodic time series, the book presents a large number of empirical results. The first part of the book deals with model selection, diagnostic checking, and forecasting of univariate periodic autoregressive models. It discusses tests for periodic integration, and provides an extensive discussion of the role of deterministic regressors in testing for periodic integration and in forecasting. The second part discusses multivariate periodic autoregressive models. It provides an overview of periodic cointegration models, including single-equation type tests and a full-system approach based on generalized method of moments. All methods are illustrated with extensive examples, and the book will be invaluable to advanced graduate students and researchers in econometrics and to practitioners looking for an understanding of how to approach seasonal data.Less
This book considers periodic time series models for seasonal data, characterized by parameters that differ across the seasons, and focuses on their usefulness for out-of-sample forecasting. Providing an up-to-date survey of the recent developments in periodic time series, the book presents a large number of empirical results. The first part of the book deals with model selection, diagnostic checking, and forecasting of univariate periodic autoregressive models. It discusses tests for periodic integration, and provides an extensive discussion of the role of deterministic regressors in testing for periodic integration and in forecasting. The second part discusses multivariate periodic autoregressive models. It provides an overview of periodic cointegration models, including single-equation type tests and a full-system approach based on generalized method of moments. All methods are illustrated with extensive examples, and the book will be invaluable to advanced graduate students and researchers in econometrics and to practitioners looking for an understanding of how to approach seasonal data.
Paul Whiteley, Patrick Seyd, and Antony Billinghurst
- Published in print:
- 2006
- Published Online:
- September 2006
- ISBN:
- 9780199242825
- eISBN:
- 9780191604140
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0199242828.003.0008
- Subject:
- Political Science, UK Politics
This chapter examines the political prospects of the Liberal Democrat Party. The big question is whether or not it can replace its rivals as the second, or even the first, party of British electoral ...
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This chapter examines the political prospects of the Liberal Democrat Party. The big question is whether or not it can replace its rivals as the second, or even the first, party of British electoral politics. It begins with an analysis of the necessary conditions for the Liberal Democrats to replace one of the other parties as the second party of British politics. This leads into an examination of the likelihood that these conditions will be met in the foreseeable future. The evidence suggests that the party has a real opportunity to break the existing two-party hegemony at a general election in 2009 or 2010.Less
This chapter examines the political prospects of the Liberal Democrat Party. The big question is whether or not it can replace its rivals as the second, or even the first, party of British electoral politics. It begins with an analysis of the necessary conditions for the Liberal Democrats to replace one of the other parties as the second party of British politics. This leads into an examination of the likelihood that these conditions will be met in the foreseeable future. The evidence suggests that the party has a real opportunity to break the existing two-party hegemony at a general election in 2009 or 2010.
Anthony Garratt, Kevin Lee, M. Hashem Pesaran, and Yongcheol Shin
- Published in print:
- 2006
- Published Online:
- September 2006
- ISBN:
- 9780199296859
- eISBN:
- 9780191603853
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0199296855.003.0011
- Subject:
- Economics and Finance, Econometrics
This chapter is concerned with forecasting and prediction based on the UK model. It elaborates on the notion of probability forecasting, which provides a useful means of conveying the uncertainties ...
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This chapter is concerned with forecasting and prediction based on the UK model. It elaborates on the notion of probability forecasting, which provides a useful means of conveying the uncertainties surrounding forecasts obtained from the model. It illustrates the usefulness of probability forecasts with reference to the Bank of England’s inflation targets and the UK’s growth prospects.Less
This chapter is concerned with forecasting and prediction based on the UK model. It elaborates on the notion of probability forecasting, which provides a useful means of conveying the uncertainties surrounding forecasts obtained from the model. It illustrates the usefulness of probability forecasts with reference to the Bank of England’s inflation targets and the UK’s growth prospects.
Anthony Garratt, Kevin Lee, M. Hashem Pesaran, and Yongcheol Shin
- Published in print:
- 2006
- Published Online:
- September 2006
- ISBN:
- 9780199296859
- eISBN:
- 9780191603853
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0199296855.003.0007
- Subject:
- Economics and Finance, Econometrics
This chapter provides an introduction to the interpretation and estimation of probability forecasts, which is considered to be a particularly useful method for presenting forecasts and ...
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This chapter provides an introduction to the interpretation and estimation of probability forecasts, which is considered to be a particularly useful method for presenting forecasts and decision-making. It shows how probability forecasts can accommodate stochastic uncertainty, parameter uncertainty, and model uncertainty. Practical guidance on their computation is provided.Less
This chapter provides an introduction to the interpretation and estimation of probability forecasts, which is considered to be a particularly useful method for presenting forecasts and decision-making. It shows how probability forecasts can accommodate stochastic uncertainty, parameter uncertainty, and model uncertainty. Practical guidance on their computation is provided.
Lawrence R. Klein (ed.)
- Published in print:
- 1991
- Published Online:
- October 2011
- ISBN:
- 9780195057720
- eISBN:
- 9780199854967
- Item type:
- book
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195057720.001.0001
- Subject:
- Economics and Finance, Econometrics
One of the most important, and visible, things economists do is to forecast what will happen in the economy in the future. Each year, a number of different groups in the United States use their own ...
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One of the most important, and visible, things economists do is to forecast what will happen in the economy in the future. Each year, a number of different groups in the United States use their own econometric models to forecast what will happen to the economy in the coming year. Some economic forecasts are more accurate than others. This book consists of chapters comparing the different models now being used. It is organized topically rather than by model. The contributors include: Roger Brimmer, Ray Fair, Bert Hickman, F. Gerard Adams, and Albert Ando. The editor provides an introduction to the volume.Less
One of the most important, and visible, things economists do is to forecast what will happen in the economy in the future. Each year, a number of different groups in the United States use their own econometric models to forecast what will happen to the economy in the coming year. Some economic forecasts are more accurate than others. This book consists of chapters comparing the different models now being used. It is organized topically rather than by model. The contributors include: Roger Brimmer, Ray Fair, Bert Hickman, F. Gerard Adams, and Albert Ando. The editor provides an introduction to the volume.
John Kay
- Published in print:
- 1996
- Published Online:
- November 2003
- ISBN:
- 9780198292227
- eISBN:
- 9780191596520
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0198292228.003.0002
- Subject:
- Economics and Finance, Microeconomics
Using data on previous forecasts, this widely influential 1995 FT article criticizes the reliability and usefulness of economic forecasts. Contrary to the widespread belief that economists always ...
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Using data on previous forecasts, this widely influential 1995 FT article criticizes the reliability and usefulness of economic forecasts. Contrary to the widespread belief that economists always disagree, it shows that economic forecasts typically fall into quite a narrow range, but that the range rarely includes the outcome.Less
Using data on previous forecasts, this widely influential 1995 FT article criticizes the reliability and usefulness of economic forecasts. Contrary to the widespread belief that economists always disagree, it shows that economic forecasts typically fall into quite a narrow range, but that the range rarely includes the outcome.
Anthony Garratt, Kevin Lee, M. Hashem Pesaran, and Yongcheol Shin
- Published in print:
- 2006
- Published Online:
- September 2006
- ISBN:
- 9780199296859
- eISBN:
- 9780191603853
- Item type:
- book
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0199296855.001.0001
- Subject:
- Economics and Finance, Econometrics
This book provides a comprehensive description of the state-of-the-art in macroeconometric modelling and describes the ‘long-run structural modelling approach’ applied to the modelling of national ...
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This book provides a comprehensive description of the state-of-the-art in macroeconometric modelling and describes the ‘long-run structural modelling approach’ applied to the modelling of national economies in a global context. The first part of the book discusses the ways in which economic theory and econometric analysis can be brought together to construct a macroeconometric model, in which the long-run relationships are consistent with economic theory and where the short-run dynamics have an interpretation. The discussion considers theoretical as well as practical considerations involved in the model building process, and gives an overview of the econometric methods covering cointegrating VAR analysis and probability forecasting. The second part of the book is devoted to the practical detail of estimating a long-run structural macroeconometric model and is illustrated through various global and national examples, including a step-by-step description of the development of a model of the UK economy. The third part discusses the interpretation and use of long-run structural macroeconometric models, describing the use of the UK model along with illustrations of the modelling approach in investigating regional interdependencies in a global macroeconometric model and other specified issues in a global or national macroeconometric context. Throughout, the book emphasizes the use of macroeconometric modelling in the real world and provides sufficient detail, including discussion of data collection and computer programmes employed, for the techniques that are introduced to be replicated or applied in new contexts.Less
This book provides a comprehensive description of the state-of-the-art in macroeconometric modelling and describes the ‘long-run structural modelling approach’ applied to the modelling of national economies in a global context. The first part of the book discusses the ways in which economic theory and econometric analysis can be brought together to construct a macroeconometric model, in which the long-run relationships are consistent with economic theory and where the short-run dynamics have an interpretation. The discussion considers theoretical as well as practical considerations involved in the model building process, and gives an overview of the econometric methods covering cointegrating VAR analysis and probability forecasting. The second part of the book is devoted to the practical detail of estimating a long-run structural macroeconometric model and is illustrated through various global and national examples, including a step-by-step description of the development of a model of the UK economy. The third part discusses the interpretation and use of long-run structural macroeconometric models, describing the use of the UK model along with illustrations of the modelling approach in investigating regional interdependencies in a global macroeconometric model and other specified issues in a global or national macroeconometric context. Throughout, the book emphasizes the use of macroeconometric modelling in the real world and provides sufficient detail, including discussion of data collection and computer programmes employed, for the techniques that are introduced to be replicated or applied in new contexts.
Sarah Holden and Jack VanDerhei
- Published in print:
- 2006
- Published Online:
- September 2006
- ISBN:
- 9780199204656
- eISBN:
- 9780191603822
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0199204659.003.0003
- Subject:
- Economics and Finance, Financial Economics
As defined contribution plans are increasingly being offered as the primary employer-sponsored pension, it is of interest to ask whether these accumulations are likely to yield sufficient retirement ...
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As defined contribution plans are increasingly being offered as the primary employer-sponsored pension, it is of interest to ask whether these accumulations are likely to yield sufficient retirement income. This chapter uses a projection model to explore alternative future scenarios for retirees who had 401(k) plans available to them over their full working careers. It also assesses the impact of ‘catch-up’ contributions, saving through an individual retirement account when an employer does not offer a 401(k) plan, and changing retirement ages.Less
As defined contribution plans are increasingly being offered as the primary employer-sponsored pension, it is of interest to ask whether these accumulations are likely to yield sufficient retirement income. This chapter uses a projection model to explore alternative future scenarios for retirees who had 401(k) plans available to them over their full working careers. It also assesses the impact of ‘catch-up’ contributions, saving through an individual retirement account when an employer does not offer a 401(k) plan, and changing retirement ages.
Scott H. Frey
- Published in print:
- 2010
- Published Online:
- January 2011
- ISBN:
- 9780195395273
- eISBN:
- 9780199863518
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195395273.003.0013
- Subject:
- Neuroscience, Sensory and Motor Systems
The ability to forecast the likely consequences of our actions accurately is an important component of adaptive behavior that has been approached from several distinct theoretical perspectives. ...
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The ability to forecast the likely consequences of our actions accurately is an important component of adaptive behavior that has been approached from several distinct theoretical perspectives. Relatively little, however, is known about the neural mechanisms involved in generating these predictions. This chapter focuses on recent work concerning the prospective selection of grasping actions. Even in the complete absence of movement, results suggest that determining how to engage an object with the hands or a recently mastered tool increases activity in parietal and premotor areas known to participate in the sensorimotor control of grasp. One possibility is that these brain regions, along with the cerebellum, are involved in generating long-range forecasts of the sensory consequences of movements when motor commands are inhibited. The chapter considers modifications to putative feedforward mechanisms involved in motor control that might extend their temporal range, and the potential implications of this hypothesis for our understanding the relationship between affordance perception and motor imagery.Less
The ability to forecast the likely consequences of our actions accurately is an important component of adaptive behavior that has been approached from several distinct theoretical perspectives. Relatively little, however, is known about the neural mechanisms involved in generating these predictions. This chapter focuses on recent work concerning the prospective selection of grasping actions. Even in the complete absence of movement, results suggest that determining how to engage an object with the hands or a recently mastered tool increases activity in parietal and premotor areas known to participate in the sensorimotor control of grasp. One possibility is that these brain regions, along with the cerebellum, are involved in generating long-range forecasts of the sensory consequences of movements when motor commands are inhibited. The chapter considers modifications to putative feedforward mechanisms involved in motor control that might extend their temporal range, and the potential implications of this hypothesis for our understanding the relationship between affordance perception and motor imagery.
Blake LeBaron
- Published in print:
- 2013
- Published Online:
- October 2017
- ISBN:
- 9780691155234
- eISBN:
- 9781400846450
- Item type:
- chapter
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691155234.003.0006
- Subject:
- Economics and Finance, Macro- and Monetary Economics
This chapter focuses on heterogeneous gain learning and long swings in asset prices. Many asset prices deviate from their fundamental values, yielding potential long-run predictability. Asset price ...
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This chapter focuses on heterogeneous gain learning and long swings in asset prices. Many asset prices deviate from their fundamental values, yielding potential long-run predictability. Asset price swings can be both short or long in duration, and their time series shows few regular patterns when one analyzes their long-range behavior. This chapter considers an underparameterized learning model with heterogeneous gain parameters and traders using differing perspectives on history. It first provides an overview of the basic model and some benchmark simulation runs before discussing the output of the model compared to actual financial time series. It then describes a range of internal mechanisms of the agents and forecasts in use and how wealth moves across them over time. It shows that learning algorithms appear to be behaving in a predictable fashion, and that interesting dynamics come from how agent wealth selects rules over time. The chapter concludes by addressing some questions for researchers working on learning in financial markets.Less
This chapter focuses on heterogeneous gain learning and long swings in asset prices. Many asset prices deviate from their fundamental values, yielding potential long-run predictability. Asset price swings can be both short or long in duration, and their time series shows few regular patterns when one analyzes their long-range behavior. This chapter considers an underparameterized learning model with heterogeneous gain parameters and traders using differing perspectives on history. It first provides an overview of the basic model and some benchmark simulation runs before discussing the output of the model compared to actual financial time series. It then describes a range of internal mechanisms of the agents and forecasts in use and how wealth moves across them over time. It shows that learning algorithms appear to be behaving in a predictable fashion, and that interesting dynamics come from how agent wealth selects rules over time. The chapter concludes by addressing some questions for researchers working on learning in financial markets.
Agustín Maravall
- Published in print:
- 1999
- Published Online:
- November 2003
- ISBN:
- 9780198292111
- eISBN:
- 9780191596537
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0198292112.003.0015
- Subject:
- Economics and Finance, Macro- and Monetary Economics, Microeconomics
Agustin Maravall provides an account of the statistical methodology used in analysing the present situation and predicting the short‐term future. The analysis of the present consists of removing ...
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Agustin Maravall provides an account of the statistical methodology used in analysing the present situation and predicting the short‐term future. The analysis of the present consists of removing seasonality and trend which increase the variability of the data. He then discusses short‐term forecasting and argues that overall, stochastic model‐based forecasting has now become standard and that the usual processes employed have to be extended to multi‐variate settings and that non‐linear extensions will be important. One of Maravall's principle focuses is on seasonal adjustment and while arguing that model‐based signal extraction with ARIMA type modes will continue to predominate, he regrets the widespread practice of issuing data that has already been seasonally corrected. He concludes by giving an example to illustrate his contention that short‐term methods may well be highly unreliable for long term analysis.Less
Agustin Maravall provides an account of the statistical methodology used in analysing the present situation and predicting the short‐term future. The analysis of the present consists of removing seasonality and trend which increase the variability of the data. He then discusses short‐term forecasting and argues that overall, stochastic model‐based forecasting has now become standard and that the usual processes employed have to be extended to multi‐variate settings and that non‐linear extensions will be important. One of Maravall's principle focuses is on seasonal adjustment and while arguing that model‐based signal extraction with ARIMA type modes will continue to predominate, he regrets the widespread practice of issuing data that has already been seasonally corrected. He concludes by giving an example to illustrate his contention that short‐term methods may well be highly unreliable for long term analysis.
Timo Teräsvirta, Dag Tjøstheim, and W. J. Granger
- Published in print:
- 2010
- Published Online:
- May 2011
- ISBN:
- 9780199587148
- eISBN:
- 9780191595387
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199587148.003.0014
- Subject:
- Economics and Finance, Econometrics
A major purpose of nonlinear models is forecasting. This often requires numerical techniques, and a few alternatives are considered. There are also cases in which analytical forecasts are available, ...
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A major purpose of nonlinear models is forecasting. This often requires numerical techniques, and a few alternatives are considered. There are also cases in which analytical forecasts are available, and some of them are shown as examples. Measuring forecast accuracy is given some consideration. This includes comparing forecasts from different models using statistical tests. Published studies comparing between forecasts from linear and nonlinear models in order to assess the usefulness of nonlinear models are discussed.Less
A major purpose of nonlinear models is forecasting. This often requires numerical techniques, and a few alternatives are considered. There are also cases in which analytical forecasts are available, and some of them are shown as examples. Measuring forecast accuracy is given some consideration. This includes comparing forecasts from different models using statistical tests. Published studies comparing between forecasts from linear and nonlinear models in order to assess the usefulness of nonlinear models are discussed.
Jamie L. Pietruska
- Published in print:
- 2017
- Published Online:
- May 2018
- ISBN:
- 9780226475004
- eISBN:
- 9780226509150
- Item type:
- book
- Publisher:
- University of Chicago Press
- DOI:
- 10.7208/chicago/9780226509150.001.0001
- Subject:
- History, American History: 19th Century
This book is a history of forecasting in the United States from the 1860s to the 1920s that examines how methods of prediction and ideas about predictability changed as Americans reckoned with new ...
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This book is a history of forecasting in the United States from the 1860s to the 1920s that examines how methods of prediction and ideas about predictability changed as Americans reckoned with new uncertainties in post-Civil War economy and culture and debated whether it was possible to predict the future with any degree of certainty. The book examines crop forecasting, weather forecasting, economic forecasting, utopian literature, and fortune-telling and considers forecasts as forms of knowledge production and tools for risk management. The book’s main argument revises the historical interpretation of the late nineteenth and early twentieth centuries as a “search for order” by demonstrating that a search for predictability yielded the opposite: acceptance of the uncertainties of twentieth-century economic and cultural life. It demonstrates how routinized forecasts of everyday life became ubiquitous in a late-nineteenth-century culture of prediction, revising scholarly accounts that locate the origins of professional forecasting in the Cold War. The book also uncovers rural origins of modern bureaucratic rationality in the histories of crop and weather forecasting, both of which depended on large-scale government information networks that are an overlooked example of the size and reach of the nineteenth-century American state. The book emphasizes controversies over forecasts’ meaning and value, contests over forecasters’ authority and expertise, and epistemic debates over the nature of forecasting itself.Less
This book is a history of forecasting in the United States from the 1860s to the 1920s that examines how methods of prediction and ideas about predictability changed as Americans reckoned with new uncertainties in post-Civil War economy and culture and debated whether it was possible to predict the future with any degree of certainty. The book examines crop forecasting, weather forecasting, economic forecasting, utopian literature, and fortune-telling and considers forecasts as forms of knowledge production and tools for risk management. The book’s main argument revises the historical interpretation of the late nineteenth and early twentieth centuries as a “search for order” by demonstrating that a search for predictability yielded the opposite: acceptance of the uncertainties of twentieth-century economic and cultural life. It demonstrates how routinized forecasts of everyday life became ubiquitous in a late-nineteenth-century culture of prediction, revising scholarly accounts that locate the origins of professional forecasting in the Cold War. The book also uncovers rural origins of modern bureaucratic rationality in the histories of crop and weather forecasting, both of which depended on large-scale government information networks that are an overlooked example of the size and reach of the nineteenth-century American state. The book emphasizes controversies over forecasts’ meaning and value, contests over forecasters’ authority and expertise, and epistemic debates over the nature of forecasting itself.
Francis X. Diebold and Glenn D. Rudebusch
- Published in print:
- 2013
- Published Online:
- October 2017
- ISBN:
- 9780691146805
- eISBN:
- 9781400845415
- Item type:
- chapter
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691146805.003.0001
- Subject:
- Economics and Finance, History of Economic Thought
This chapter introduces some important conceptual, descriptive, and theoretical considerations regarding nominal government bond yield curves. Conceptually, just what is it that are we trying to ...
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This chapter introduces some important conceptual, descriptive, and theoretical considerations regarding nominal government bond yield curves. Conceptually, just what is it that are we trying to measure? How can we best understand many bond yields at many maturities over many years? Descriptively, how do yield curves tend to behave? Can we obtain simple yet accurate dynamic characterizations and forecasts? Theoretically, what governs and restricts yield curve shape and evolution? Can we relate yield curves to macroeconomic fundamentals and central bank behavior? The discussions cover three interest rate curves, zero-coupon yields, yield curve facts, yield curve factors, and yield curve questions.Less
This chapter introduces some important conceptual, descriptive, and theoretical considerations regarding nominal government bond yield curves. Conceptually, just what is it that are we trying to measure? How can we best understand many bond yields at many maturities over many years? Descriptively, how do yield curves tend to behave? Can we obtain simple yet accurate dynamic characterizations and forecasts? Theoretically, what governs and restricts yield curve shape and evolution? Can we relate yield curves to macroeconomic fundamentals and central bank behavior? The discussions cover three interest rate curves, zero-coupon yields, yield curve facts, yield curve factors, and yield curve questions.
Francis X. Diebold and Glenn D. Rudebusch
- Published in print:
- 2013
- Published Online:
- October 2017
- ISBN:
- 9780691146805
- eISBN:
- 9781400845415
- Item type:
- chapter
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691146805.003.0002
- Subject:
- Economics and Finance, History of Economic Thought
This chapter starts with static in the cross section, then proceeds quickly to dynamic Nelson–Siegel modeling, with all its nuances and opportunities. Among other things, it emphasizes the model's ...
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This chapter starts with static in the cross section, then proceeds quickly to dynamic Nelson–Siegel modeling, with all its nuances and opportunities. Among other things, it emphasizes the model's state-space structure, generalizes it to the multicountry context, and highlights aspects of its use in risk management and forecasting.Less
This chapter starts with static in the cross section, then proceeds quickly to dynamic Nelson–Siegel modeling, with all its nuances and opportunities. Among other things, it emphasizes the model's state-space structure, generalizes it to the multicountry context, and highlights aspects of its use in risk management and forecasting.
E. Philip Howrey
- Published in print:
- 1991
- Published Online:
- October 2011
- ISBN:
- 9780195057720
- eISBN:
- 9780199854967
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195057720.003.0008
- Subject:
- Economics and Finance, Econometrics
Econometric forecasters continually seek ways to increase forecast accuracy. As new data are released, the residuals of forecasting models are examined for evidence of structural change and equations ...
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Econometric forecasters continually seek ways to increase forecast accuracy. As new data are released, the residuals of forecasting models are examined for evidence of structural change and equations are modified if necessary. Several of the participants in the Model Comparison Seminar have recently investigated alternative methods for using monthly data in a systematic way to adjust forecasts produced by quarterly models. These initial studies are reviewed in this chapter and some illustrative results are presented. It begins with a review of some of the implications of temporal aggregation for the specification and estimation of models and their use in economic forecasting. This review is intended to provide motivation for the use of high-frequency (monthly) data in forecasting economic aggregates, as well as to indicate some of the difficulties that are involved. The chapter concludes with a presentation of some illustrative results obtained using the Michigan Quarterly Econometric Model of the United States economy.Less
Econometric forecasters continually seek ways to increase forecast accuracy. As new data are released, the residuals of forecasting models are examined for evidence of structural change and equations are modified if necessary. Several of the participants in the Model Comparison Seminar have recently investigated alternative methods for using monthly data in a systematic way to adjust forecasts produced by quarterly models. These initial studies are reviewed in this chapter and some illustrative results are presented. It begins with a review of some of the implications of temporal aggregation for the specification and estimation of models and their use in economic forecasting. This review is intended to provide motivation for the use of high-frequency (monthly) data in forecasting economic aggregates, as well as to indicate some of the difficulties that are involved. The chapter concludes with a presentation of some illustrative results obtained using the Michigan Quarterly Econometric Model of the United States economy.
Roman Frydman and Michael D. Goldberg
- Published in print:
- 2013
- Published Online:
- October 2017
- ISBN:
- 9780691155234
- eISBN:
- 9781400846450
- Item type:
- chapter
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691155234.003.0007
- Subject:
- Economics and Finance, Macro- and Monetary Economics
This chapter considers an alternative approach to economic analysis, Imperfect Knowledge Economics (IKE), and introduces a model of asset prices and risk that has explicit mathematical ...
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This chapter considers an alternative approach to economic analysis, Imperfect Knowledge Economics (IKE), and introduces a model of asset prices and risk that has explicit mathematical microfoundations and yet remains open to nonroutine change. The IKE model consists of representations of individuals' preferences, forecasting behavior, constraints, and decision rules in terms of a set of causal (often called “informational”) variables, which portray the influence of economic policy, institutions, and other features of the social context. It also entails an aggregation rule and processes for the informational variables. The chapter examines irregular swings in asset prices and their relationship to financial risk. It also presents an IKE account of asset price swings before concluding with an analysis of contingent predictions of long swings and their compatibility with rationality.Less
This chapter considers an alternative approach to economic analysis, Imperfect Knowledge Economics (IKE), and introduces a model of asset prices and risk that has explicit mathematical microfoundations and yet remains open to nonroutine change. The IKE model consists of representations of individuals' preferences, forecasting behavior, constraints, and decision rules in terms of a set of causal (often called “informational”) variables, which portray the influence of economic policy, institutions, and other features of the social context. It also entails an aggregation rule and processes for the informational variables. The chapter examines irregular swings in asset prices and their relationship to financial risk. It also presents an IKE account of asset price swings before concluding with an analysis of contingent predictions of long swings and their compatibility with rationality.
Andrew J. Patton and Allan Timmermann
- Published in print:
- 2010
- Published Online:
- May 2010
- ISBN:
- 9780199549498
- eISBN:
- 9780191720567
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199549498.003.0010
- Subject:
- Economics and Finance, Econometrics
This chapter discusses properties of optimal forecasts under general loss functions, and proposes an interesting change of measure under which minimum mean square error forecast properties can be ...
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This chapter discusses properties of optimal forecasts under general loss functions, and proposes an interesting change of measure under which minimum mean square error forecast properties can be recovered. The outline of this chapter is as follows. Section 2 establishes properties of optimal forecasts under general known loss functions. Section 3 contains the change of measure result, and Section 4 presents empirical illustrations of the results. Section 5 concludes.Less
This chapter discusses properties of optimal forecasts under general loss functions, and proposes an interesting change of measure under which minimum mean square error forecast properties can be recovered. The outline of this chapter is as follows. Section 2 establishes properties of optimal forecasts under general known loss functions. Section 3 contains the change of measure result, and Section 4 presents empirical illustrations of the results. Section 5 concludes.
Phaedra Daipha
- Published in print:
- 2015
- Published Online:
- May 2016
- ISBN:
- 9780226298542
- eISBN:
- 9780226298719
- Item type:
- chapter
- Publisher:
- University of Chicago Press
- DOI:
- 10.7208/chicago/9780226298719.003.0005
- Subject:
- Sociology, Science, Technology and Environment
The chapter begins by outlining NWS efforts to articulate and streamline the management of meteorological risk into a government meteorology. To properly showcase the challenges of actually managing ...
More
The chapter begins by outlining NWS efforts to articulate and streamline the management of meteorological risk into a government meteorology. To properly showcase the challenges of actually managing meteorological risk on the ground, the chapter next launches into a thick description of two missed weather events. The first incident serves as an illustration of the serious repercussions that may arise from a missed hazardous weather forecast even in the absence of any hazardous weather whatsoever. The second incident details the aftermath of a forecast that missed the first snow squalls of the season; a forecast that would have gone unnoticed only a few days later but, on that day, led to hundreds of road accidents and a statewide, five-hour long traffic standstill. The concluding discussion, on the duality of meteorological error, reflects on the essential irresolvability of the “overforecasting versus underforecasting” dilemma and considers its implications for managing risk at the NWS.Less
The chapter begins by outlining NWS efforts to articulate and streamline the management of meteorological risk into a government meteorology. To properly showcase the challenges of actually managing meteorological risk on the ground, the chapter next launches into a thick description of two missed weather events. The first incident serves as an illustration of the serious repercussions that may arise from a missed hazardous weather forecast even in the absence of any hazardous weather whatsoever. The second incident details the aftermath of a forecast that missed the first snow squalls of the season; a forecast that would have gone unnoticed only a few days later but, on that day, led to hundreds of road accidents and a statewide, five-hour long traffic standstill. The concluding discussion, on the duality of meteorological error, reflects on the essential irresolvability of the “overforecasting versus underforecasting” dilemma and considers its implications for managing risk at the NWS.
Phaedra Daipha
- Published in print:
- 2015
- Published Online:
- May 2016
- ISBN:
- 9780226298542
- eISBN:
- 9780226298719
- Item type:
- chapter
- Publisher:
- University of Chicago Press
- DOI:
- 10.7208/chicago/9780226298719.003.0006
- Subject:
- Sociology, Science, Technology and Environment
Turning to the temporal dimensions of meteorological decision-making, this chapter identifies two principles underlying the logic of weather forecasting practice: risk and scale. The former rests on ...
More
Turning to the temporal dimensions of meteorological decision-making, this chapter identifies two principles underlying the logic of weather forecasting practice: risk and scale. The former rests on a demarcation between routine and non-routine operations, while the latter is driven by the fact that the more global the reach of a weather phenomenon the earlier its detection. The joint influence of risk and spatial scale on weather forecasting practice yields four temporal regimes of decision-making: emergency, extended alert, near-term, and longer-term. This rudimentary framework is elaborated through an analysis of its empirical manifestation in summer weather forecasting, winter weather forecasting, short-term forecasting, and long-term forecasting respectively. The analysis complicates dual-process models of cognitive processing by establishing that, in practice, deliberation and heuristics are combined across disparate temporal regimes to produce organizationally sanctioned, skilled decisions.Less
Turning to the temporal dimensions of meteorological decision-making, this chapter identifies two principles underlying the logic of weather forecasting practice: risk and scale. The former rests on a demarcation between routine and non-routine operations, while the latter is driven by the fact that the more global the reach of a weather phenomenon the earlier its detection. The joint influence of risk and spatial scale on weather forecasting practice yields four temporal regimes of decision-making: emergency, extended alert, near-term, and longer-term. This rudimentary framework is elaborated through an analysis of its empirical manifestation in summer weather forecasting, winter weather forecasting, short-term forecasting, and long-term forecasting respectively. The analysis complicates dual-process models of cognitive processing by establishing that, in practice, deliberation and heuristics are combined across disparate temporal regimes to produce organizationally sanctioned, skilled decisions.
