Duo Qin
- Published in print:
- 1997
- Published Online:
- November 2003
- ISBN:
- 9780198292876
- eISBN:
- 9780191596803
- Item type:
- book
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0198292872.001.0001
- Subject:
- Economics and Finance, History of Economic Thought, Econometrics
This book traces the formation of econometric theory during the period 1930–1960. It focuses upon the process of how econometrics was formed from mathematical and scientific processes in order to ...
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This book traces the formation of econometric theory during the period 1930–1960. It focuses upon the process of how econometrics was formed from mathematical and scientific processes in order to analyse economic problems. The book deals with the advances that were achieved as well as the problems that arose in the course of the practice of econometrics as a discipline. Duo Qin examines the history of econometrics in terms of the basic issues in econometric modelling: the probability foundations, estimation, identification, testing, and model construction and specification. The book describes chronologically how these issues were formalized. Duo Qin argues that, while the probability revolution in econometrics in the early 1940s laid the basis for the systematization of econometric theory, it was actually an incomplete revolution, and its incompleteness underlay various problems and failures that occurred in applying the newly established theory to modelling practice. Model construction and hypothesis testing remained problematic because the basic problem of induction in econometrics was not properly formalized and solved. The book thus links early econometric history with many issues of interest to contemporary developments in econometrics. The story is told from the econometric perspective instead of the usual perspective in the history of economic thought (i.e. presenting the story either according to different schools or economic issues), and this approach is clearly reflected in the classification of the chapters.Less
This book traces the formation of econometric theory during the period 1930–1960. It focuses upon the process of how econometrics was formed from mathematical and scientific processes in order to analyse economic problems. The book deals with the advances that were achieved as well as the problems that arose in the course of the practice of econometrics as a discipline. Duo Qin examines the history of econometrics in terms of the basic issues in econometric modelling: the probability foundations, estimation, identification, testing, and model construction and specification. The book describes chronologically how these issues were formalized. Duo Qin argues that, while the probability revolution in econometrics in the early 1940s laid the basis for the systematization of econometric theory, it was actually an incomplete revolution, and its incompleteness underlay various problems and failures that occurred in applying the newly established theory to modelling practice. Model construction and hypothesis testing remained problematic because the basic problem of induction in econometrics was not properly formalized and solved. The book thus links early econometric history with many issues of interest to contemporary developments in econometrics. The story is told from the econometric perspective instead of the usual perspective in the history of economic thought (i.e. presenting the story either according to different schools or economic issues), and this approach is clearly reflected in the classification of the chapters.
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.
Manuel Arellano
- Published in print:
- 2003
- Published Online:
- July 2005
- ISBN:
- 9780199245284
- eISBN:
- 9780191602481
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0199245282.003.0001
- Subject:
- Economics and Finance, Econometrics
This introductory chapter begins with a brief discussion on how the term ‘panel data’ is applied to a wide range of situations in econometrics. It describes the two main objectives of this volume: ...
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This introductory chapter begins with a brief discussion on how the term ‘panel data’ is applied to a wide range of situations in econometrics. It describes the two main objectives of this volume: the analysis of econometric models with non-exogenous explanatory variables, and the problem of distinguishing empirically between dynamic responses and unobserved heterogeneity in panel data models. An overview of the three parts of this volume is presented.Less
This introductory chapter begins with a brief discussion on how the term ‘panel data’ is applied to a wide range of situations in econometrics. It describes the two main objectives of this volume: the analysis of econometric models with non-exogenous explanatory variables, and the problem of distinguishing empirically between dynamic responses and unobserved heterogeneity in panel data models. An overview of the three parts of this volume is presented.
David F. Hendry
- Published in print:
- 1995
- Published Online:
- November 2003
- ISBN:
- 9780198283164
- eISBN:
- 9780191596384
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0198283164.003.0001
- Subject:
- Economics and Finance, Econometrics
Econometric modelling of economic time series requires discovering sustainable and interpretable relationships between observed economic variables. Critical and constructive aspects are ...
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Econometric modelling of economic time series requires discovering sustainable and interpretable relationships between observed economic variables. Critical and constructive aspects are distinguished, and the roles of theories, instruments, and evidence discussed. A simple statistical mechanism, which could generate data with many of the salient features of observed time series, is analysed. An inconsistency between that and models fitted to the observed data, highlights the ease of critical evaluation, as against the difficulty of constructive progress. The concept of an empirical model is introduced.Less
Econometric modelling of economic time series requires discovering sustainable and interpretable relationships between observed economic variables. Critical and constructive aspects are distinguished, and the roles of theories, instruments, and evidence discussed. A simple statistical mechanism, which could generate data with many of the salient features of observed time series, is analysed. An inconsistency between that and models fitted to the observed data, highlights the ease of critical evaluation, as against the difficulty of constructive progress. The concept of an empirical model is introduced.
Qin Duo
- Published in print:
- 1997
- Published Online:
- November 2003
- ISBN:
- 9780198292876
- eISBN:
- 9780191596803
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0198292872.003.0006
- Subject:
- Economics and Finance, History of Economic Thought, Econometrics
Addresses the issue of testing, and reveals some intrinsic problems pertaining to hypothesis testing beneath the achievements of formalizing econometrics. Theory verification through applied studies ...
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Addresses the issue of testing, and reveals some intrinsic problems pertaining to hypothesis testing beneath the achievements of formalizing econometrics. Theory verification through applied studies forms one of the main motives for formalizing methods of model estimation and identification, and the statistical theory of hypothesis testing was accepted without much dispute quite early as the technical vehicle to fulfil this desire. However, during the adoption of the theory into econometrics in the 1940s and 1950s, the achievable domain of verification turned out to be considerably reduced, as testing in econometrics proper gradually dwindled into part of the modelling procedure and pertained to model evaluation using statistical testing tools; in the applied field, empirical modellers took on the task of discriminating between and verifying economic theories against the model results, and carried this out in an ad hoc and often non‐sequitur manner. Describes how the desire to test diverged into model evaluation in econometric theory on the one hand, and economic theory verification in practice on the other, as econometric testing theory took shape. The story begins with the early period prior to the formative movement in the first section of the chapter; the following section looks at the period in which the theme of hypothesis testing was introduced, and the first test emerged in econometrics; the last two sections report, respectively, on how model testing in applied econometrics and test design in theoretical econometrics developed and moved apart.Less
Addresses the issue of testing, and reveals some intrinsic problems pertaining to hypothesis testing beneath the achievements of formalizing econometrics. Theory verification through applied studies forms one of the main motives for formalizing methods of model estimation and identification, and the statistical theory of hypothesis testing was accepted without much dispute quite early as the technical vehicle to fulfil this desire. However, during the adoption of the theory into econometrics in the 1940s and 1950s, the achievable domain of verification turned out to be considerably reduced, as testing in econometrics proper gradually dwindled into part of the modelling procedure and pertained to model evaluation using statistical testing tools; in the applied field, empirical modellers took on the task of discriminating between and verifying economic theories against the model results, and carried this out in an ad hoc and often non‐sequitur manner. Describes how the desire to test diverged into model evaluation in econometric theory on the one hand, and economic theory verification in practice on the other, as econometric testing theory took shape. The story begins with the early period prior to the formative movement in the first section of the chapter; the following section looks at the period in which the theme of hypothesis testing was introduced, and the first test emerged in econometrics; the last two sections report, respectively, on how model testing in applied econometrics and test design in theoretical econometrics developed and moved apart.
Qin Duo
- Published in print:
- 1997
- Published Online:
- November 2003
- ISBN:
- 9780198292876
- eISBN:
- 9780191596803
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0198292872.003.0002
- Subject:
- Economics and Finance, History of Economic Thought, Econometrics
Records the fundamental event of the probability revolution in econometrics. Focuses upon how probability theory was brought into econometrics in relation to the main econometric modelling issues, ...
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Records the fundamental event of the probability revolution in econometrics. Focuses upon how probability theory was brought into econometrics in relation to the main econometric modelling issues, such as estimation, identification, and testing, and shows that this laid the basis for the formalization of those issues, which is reported in later chapters. The first section sketches the eve of the probability revolution. An introduction to probability methods follows in the second section, and the third section is dedicated to the ‘Haavelmo revolution’: the thorough adoption of probability theory in econometrics. The following section turns to alternative approaches to the adoption of probability theory, and the final section discusses the after‐effect and especially the incompleteness of the probability revolution.Less
Records the fundamental event of the probability revolution in econometrics. Focuses upon how probability theory was brought into econometrics in relation to the main econometric modelling issues, such as estimation, identification, and testing, and shows that this laid the basis for the formalization of those issues, which is reported in later chapters. The first section sketches the eve of the probability revolution. An introduction to probability methods follows in the second section, and the third section is dedicated to the ‘Haavelmo revolution’: the thorough adoption of probability theory in econometrics. The following section turns to alternative approaches to the adoption of probability theory, and the final section discusses the after‐effect and especially the incompleteness of the probability revolution.
Qin Duo
- Published in print:
- 1997
- Published Online:
- November 2003
- ISBN:
- 9780198292876
- eISBN:
- 9780191596803
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0198292872.003.0003
- Subject:
- Economics and Finance, History of Economic Thought, Econometrics
This chapter recounts the evolution of econometric models up to the 1940s, discussing the common criteria and principles used for model choice, and the generalization of model construction as ...
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This chapter recounts the evolution of econometric models up to the 1940s, discussing the common criteria and principles used for model choice, and the generalization of model construction as econometrics focused on the structural modelling procedure. The first section reviews the pre‐model period, and the second looks at the emergence of models and the structural method of model construction. The initial generalization (formalization) efforts of the model‐building strategy and criteria are dealt with in the third section. Concludes with the establishment of the structural modelling procedure (the maturity of simultaneous‐equations model formulation).Less
This chapter recounts the evolution of econometric models up to the 1940s, discussing the common criteria and principles used for model choice, and the generalization of model construction as econometrics focused on the structural modelling procedure. The first section reviews the pre‐model period, and the second looks at the emergence of models and the structural method of model construction. The initial generalization (formalization) efforts of the model‐building strategy and criteria are dealt with in the third section. Concludes with the establishment of the structural modelling procedure (the maturity of simultaneous‐equations model formulation).
Qin Duo
- Published in print:
- 1997
- Published Online:
- November 2003
- ISBN:
- 9780198292876
- eISBN:
- 9780191596803
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0198292872.003.0007
- Subject:
- Economics and Finance, History of Economic Thought, Econometrics
Looks at problems associated with econometric model construction for the period immediately after the formative phase, and tries to link up the previous chapters and to show what has been left ...
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Looks at problems associated with econometric model construction for the period immediately after the formative phase, and tries to link up the previous chapters and to show what has been left unsolved in the formation of econometrics. The structural modelling procedure explained only how to estimate and identify a priori given structural models, while many of the empirical studies involved searching for the appropriate structural models from the given data. This mismatch of the two sides gave rise to many problems and disputes, mostly in connection with the roles that modellers attributed to individual tools of testing, identification, and estimation in the integrated process of empirical model construction, as the procedure and the associated techniques spread and formed the core of orthodox econometrics. Revisits the issue of model construction with particular respect to the roles of testing, identification, and estimation, depicting how controversies arose as econometricians were swung back to more data‐based positions, away from the emphasis on a priori considerations; back to statistical results, away from reliance on economic theory; and back to dynamics, away from concerns over contemporaneous interdependency. The first section looks at modelling issues associated with hypothesis testing; the second examines problems about model formulation with respect to identification; the third turns to the estimation aspect of modelling; and the fourth leads the discourse to the focal issue of the probability approach underlying established econometrics by illustrating that most of the problems could be viewed as due to the incompleteness of the probability approach (as suggested in Chapter 1).Less
Looks at problems associated with econometric model construction for the period immediately after the formative phase, and tries to link up the previous chapters and to show what has been left unsolved in the formation of econometrics. The structural modelling procedure explained only how to estimate and identify a priori given structural models, while many of the empirical studies involved searching for the appropriate structural models from the given data. This mismatch of the two sides gave rise to many problems and disputes, mostly in connection with the roles that modellers attributed to individual tools of testing, identification, and estimation in the integrated process of empirical model construction, as the procedure and the associated techniques spread and formed the core of orthodox econometrics. Revisits the issue of model construction with particular respect to the roles of testing, identification, and estimation, depicting how controversies arose as econometricians were swung back to more data‐based positions, away from the emphasis on a priori considerations; back to statistical results, away from reliance on economic theory; and back to dynamics, away from concerns over contemporaneous interdependency. The first section looks at modelling issues associated with hypothesis testing; the second examines problems about model formulation with respect to identification; the third turns to the estimation aspect of modelling; and the fourth leads the discourse to the focal issue of the probability approach underlying established econometrics by illustrating that most of the problems could be viewed as due to the incompleteness of the probability approach (as suggested in Chapter 1).
Qin Duo
- Published in print:
- 1997
- Published Online:
- November 2003
- ISBN:
- 9780198292876
- eISBN:
- 9780191596803
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0198292872.003.0004
- Subject:
- Economics and Finance, History of Economic Thought, Econometrics
Narrates the process of how estimation was formalized. Estimation can be seen as the genesis of econometrics, since finding estimates for coefficients of economically meaningful relationships has ...
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Narrates the process of how estimation was formalized. Estimation can be seen as the genesis of econometrics, since finding estimates for coefficients of economically meaningful relationships has always been the central motive and fulfilment of applied modelling activities. The process therefore became separated out as one of the basic steps along with model construction, identification, and testing. Subsequent research activities in estimation were confined to technical development of new optimal estimators for increasingly complicated model forms. The first section of the chapter describes the early developments in estimation methods centring around the least squares (LS) principle; how this led to the maximum‐likelihood (ML) method in a simultaneous‐equations system is the content of the second section; the third section turns to look at special problems in the context of time‐series analysis; other developments concerning errors‐in‐variables models are summed up in the fourth section; and the final completion of basic estimation theory in orthodox econometrics takes up the final section.Less
Narrates the process of how estimation was formalized. Estimation can be seen as the genesis of econometrics, since finding estimates for coefficients of economically meaningful relationships has always been the central motive and fulfilment of applied modelling activities. The process therefore became separated out as one of the basic steps along with model construction, identification, and testing. Subsequent research activities in estimation were confined to technical development of new optimal estimators for increasingly complicated model forms. The first section of the chapter describes the early developments in estimation methods centring around the least squares (LS) principle; how this led to the maximum‐likelihood (ML) method in a simultaneous‐equations system is the content of the second section; the third section turns to look at special problems in the context of time‐series analysis; other developments concerning errors‐in‐variables models are summed up in the fourth section; and the final completion of basic estimation theory in orthodox econometrics takes up the final section.
David F. Hendry
- Published in print:
- 1995
- Published Online:
- November 2003
- ISBN:
- 9780198283164
- eISBN:
- 9780191596384
- Item type:
- book
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0198283164.001.0001
- Subject:
- Economics and Finance, Econometrics
This systematic and integrated framework for econometric modelling is organized in terms of three levels of knowledge: probability, estimation, and modelling. All necessary concepts of econometrics ...
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This systematic and integrated framework for econometric modelling is organized in terms of three levels of knowledge: probability, estimation, and modelling. All necessary concepts of econometrics (including exogeneity and encompassing), models, processes, estimators, and inference procedures (centred on maximum likelihood) are discussed with solved examples and exercises. Practical problems in empirical modelling, such as model discovery, evaluation, and data mining are addressed, and illustrated using the software system PcGive. Background analyses cover matrix algebra, probability theory, multiple regression, stationary and non‐stationary stochastic processes, asymptotic distribution theory, Monte Carlo methods, numerical optimization, and macro‐econometric models. The reader will master the theory and practice of modelling non‐stationary (cointegrated) economic time series, based on a rigorous theory of reduction.Less
This systematic and integrated framework for econometric modelling is organized in terms of three levels of knowledge: probability, estimation, and modelling. All necessary concepts of econometrics (including exogeneity and encompassing), models, processes, estimators, and inference procedures (centred on maximum likelihood) are discussed with solved examples and exercises. Practical problems in empirical modelling, such as model discovery, evaluation, and data mining are addressed, and illustrated using the software system PcGive. Background analyses cover matrix algebra, probability theory, multiple regression, stationary and non‐stationary stochastic processes, asymptotic distribution theory, Monte Carlo methods, numerical optimization, and macro‐econometric models. The reader will master the theory and practice of modelling non‐stationary (cointegrated) economic time series, based on a rigorous theory of reduction.
Alfred Maizels, Robert Bacon, and George Mavrotas
- Published in print:
- 1997
- Published Online:
- October 2011
- ISBN:
- 9780198233381
- eISBN:
- 9780191678981
- Item type:
- book
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780198233381.001.0001
- Subject:
- Economics and Finance, Development, Growth, and Environmental
The collapse in commodity prices since 1980 has been a major cause of the economic crisis in a large number of developing countries. This book investigates whether the commodity-producing countries, ...
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The collapse in commodity prices since 1980 has been a major cause of the economic crisis in a large number of developing countries. This book investigates whether the commodity-producing countries, by joint action, could have prevented the price collapse by appropriate supply management. The analysis is focused on the markets for the tropical beverage crops: coffee, cocoa, and tea. Using new econometric models for each market, the impact of alternative supply management schemes on supply, consumption, prices, and export earnings is simulated for the later 1980s. The results indicate that supply management by producing countries would, indeed, have been a viable alternative to the ‘free market’ approach favoured by the developed countries. This has important implications for current international commodity policy, and, in particular, for future joint action by producing countries to overcome persistent commodity surpluses as a complement to needed diversification.Less
The collapse in commodity prices since 1980 has been a major cause of the economic crisis in a large number of developing countries. This book investigates whether the commodity-producing countries, by joint action, could have prevented the price collapse by appropriate supply management. The analysis is focused on the markets for the tropical beverage crops: coffee, cocoa, and tea. Using new econometric models for each market, the impact of alternative supply management schemes on supply, consumption, prices, and export earnings is simulated for the later 1980s. The results indicate that supply management by producing countries would, indeed, have been a viable alternative to the ‘free market’ approach favoured by the developed countries. This has important implications for current international commodity policy, and, in particular, for future joint action by producing countries to overcome persistent commodity surpluses as a complement to needed diversification.
R. Jeffery Green, Bert G. Hickman, E. Philip Howrey, Saul H. Hymans, and Michael R. Donihue
- Published in print:
- 1991
- Published Online:
- October 2011
- ISBN:
- 9780195057720
- eISBN:
- 9780199854967
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195057720.003.0004
- Subject:
- Economics and Finance, Econometrics
This chapter discusses the methodology of IS-LM and AD-AS system reduction and illustrates its application to three U.S. econometric models: the Hickman-Coen (HC) Annual Growth Model, the Indiana ...
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This chapter discusses the methodology of IS-LM and AD-AS system reduction and illustrates its application to three U.S. econometric models: the Hickman-Coen (HC) Annual Growth Model, the Indiana University Econometric Model (EMUS), and the University of Michigan's Quarterly Econometric Model (MQEM). Bert Hickman compares the estimation of the short-run IS, LM, and AS locuses by partial simulation techniques and full-model comparative-static experiments. In the next section, M.N. Green measures the short- and long-run elasticities of the IS, LM, AD, and AS locuses of the Indiana Model by partial simulation methods. In the third section, E. Philip Howrey, Saul Hymans, and Michael Donihue illustrate the use of IS-LM analysis to interpret macroeconometric model simulations in a detailed examination of the responses of the MQEM model to a fiscal shock over a ten-year horizon. The final section offers some concluding observations on the usefulness of the general approach.Less
This chapter discusses the methodology of IS-LM and AD-AS system reduction and illustrates its application to three U.S. econometric models: the Hickman-Coen (HC) Annual Growth Model, the Indiana University Econometric Model (EMUS), and the University of Michigan's Quarterly Econometric Model (MQEM). Bert Hickman compares the estimation of the short-run IS, LM, and AS locuses by partial simulation techniques and full-model comparative-static experiments. In the next section, M.N. Green measures the short- and long-run elasticities of the IS, LM, AD, and AS locuses of the Indiana Model by partial simulation methods. In the third section, E. Philip Howrey, Saul Hymans, and Michael Donihue illustrate the use of IS-LM analysis to interpret macroeconometric model simulations in a detailed examination of the responses of the MQEM model to a fiscal shock over a ten-year horizon. The final section offers some concluding observations on the usefulness of the general approach.
F. Gerard Adams and Lawrence R. Klein
- Published in print:
- 1991
- Published Online:
- October 2011
- ISBN:
- 9780195057720
- eISBN:
- 9780199854967
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195057720.003.0002
- Subject:
- Economics and Finance, Econometrics
This chapter focuses on the response of the various econometric models to a number of alternatively specified external shocks. Altogether, 11 model groups supplied simulation results for the model ...
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This chapter focuses on the response of the various econometric models to a number of alternatively specified external shocks. Altogether, 11 model groups supplied simulation results for the model comparisons. These groups represent a cross section of the currently active model operators and forecasters. They run from the now traditional Keynesian to the monetarist and the rational expectations approaches. The participating model groups and the special characteristics of their models are listed in the chapter. Early in the meetings of the model comparison seminar, the philosophy of model comparisons was a topic of some extensive discussion. The approach was to compare alternative “disturbed” model solutions to a base solution. Each model operator was instructed to prepare a so-called “tracking solution” that would approximately reproduce history over the period 1975 to 1984.Less
This chapter focuses on the response of the various econometric models to a number of alternatively specified external shocks. Altogether, 11 model groups supplied simulation results for the model comparisons. These groups represent a cross section of the currently active model operators and forecasters. They run from the now traditional Keynesian to the monetarist and the rational expectations approaches. The participating model groups and the special characteristics of their models are listed in the chapter. Early in the meetings of the model comparison seminar, the philosophy of model comparisons was a topic of some extensive discussion. The approach was to compare alternative “disturbed” model solutions to a base solution. Each model operator was instructed to prepare a so-called “tracking solution” that would approximately reproduce history over the period 1975 to 1984.
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.
Qin Duo
- Published in print:
- 1997
- Published Online:
- November 2003
- ISBN:
- 9780198292876
- eISBN:
- 9780191596803
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0198292872.003.0005
- Subject:
- Economics and Finance, History of Economic Thought, Econometrics
Narrates the process of how identification was formalized in econometrics. The issue of identification stemmed from the quest to know the attainability of economically meaningful relationships from ...
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Narrates the process of how identification was formalized in econometrics. The issue of identification stemmed from the quest to know the attainability of economically meaningful relationships from statistical analysis of economic data in early estimation attempts. It arose out of the ‘correspondence’ problems ‘between economic activity, the data that activity generates, the theoretical economic model and the estimated relationship’ (Morgan, 1990). When identification theory was eventually formalized, its purpose became focused on the conditions under which a certain set of values of structural parameters could be uniquely determined from the data among all the permissible sets embodied in a mathematically complete theoretical model, usually composed of a simultaneous‐equations system. These conditions are most commonly known as the order and rank conditions in the context of linear, simultaneous‐equations models in present‐day econometrics textbooks. The emergence of identification theory played a key role in the formal establishment of the structural approach of orthodox econometrics through its links to model testing and model specification. Traces the formalization of identification theory around two interwoven themes: how the identification problem was perceived and described in connection with the other issues in econometric modelling; and how the problem was formalized and tackled with mathematical and statistical means. The first section outlines the early appearance of the identification problem and some ad hoc solutions for particular cases and model forms before the mid‐1930s; the second centres upon the initial systematic work on the issue around 1940; the third is devoted to the contribution of the Cowles group; and the completion of the theoretical framework and its overlaps with other modelling issues form the subject of the last section.Less
Narrates the process of how identification was formalized in econometrics. The issue of identification stemmed from the quest to know the attainability of economically meaningful relationships from statistical analysis of economic data in early estimation attempts. It arose out of the ‘correspondence’ problems ‘between economic activity, the data that activity generates, the theoretical economic model and the estimated relationship’ (Morgan, 1990). When identification theory was eventually formalized, its purpose became focused on the conditions under which a certain set of values of structural parameters could be uniquely determined from the data among all the permissible sets embodied in a mathematically complete theoretical model, usually composed of a simultaneous‐equations system. These conditions are most commonly known as the order and rank conditions in the context of linear, simultaneous‐equations models in present‐day econometrics textbooks. The emergence of identification theory played a key role in the formal establishment of the structural approach of orthodox econometrics through its links to model testing and model specification. Traces the formalization of identification theory around two interwoven themes: how the identification problem was perceived and described in connection with the other issues in econometric modelling; and how the problem was formalized and tackled with mathematical and statistical means. The first section outlines the early appearance of the identification problem and some ad hoc solutions for particular cases and model forms before the mid‐1930s; the second centres upon the initial systematic work on the issue around 1940; the third is devoted to the contribution of the Cowles group; and the completion of the theoretical framework and its overlaps with other modelling issues form the subject of the last section.
Thomas J. Sargent
- Published in print:
- 2013
- Published Online:
- October 2017
- ISBN:
- 9780691158709
- eISBN:
- 9781400847648
- Item type:
- chapter
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691158709.003.0001
- Subject:
- Economics and Finance, Economic History
This chapter discusses the rational expectations reconstruction of macroeconomics. In particular, it examines how the hypothesis of rational expectations has been used to develop econometric models ...
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This chapter discusses the rational expectations reconstruction of macroeconomics. In particular, it examines how the hypothesis of rational expectations has been used to develop econometric models that take into account that people's behavior patterns will vary systematically with changes in government policies—the rules of the game. The chapter looks at two examples that illustrate the general presumption that the systematic behavior of private agents and the random behavior of market outcomes both will change whenever agents' constraints change, as when government policy or other parts of the environment change. The first example deals with investment decision, and the second concerns the inflationary effects of government deficits. The chapter also considers the implications of the rational expectations approach for the ways in which policymakers and their advisers think about the choices confronting them.Less
This chapter discusses the rational expectations reconstruction of macroeconomics. In particular, it examines how the hypothesis of rational expectations has been used to develop econometric models that take into account that people's behavior patterns will vary systematically with changes in government policies—the rules of the game. The chapter looks at two examples that illustrate the general presumption that the systematic behavior of private agents and the random behavior of market outcomes both will change whenever agents' constraints change, as when government policy or other parts of the environment change. The first example deals with investment decision, and the second concerns the inflationary effects of government deficits. The chapter also considers the implications of the rational expectations approach for the ways in which policymakers and their advisers think about the choices confronting them.
Qin Duo
- Published in print:
- 1997
- Published Online:
- November 2003
- ISBN:
- 9780198292876
- eISBN:
- 9780191596803
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0198292872.003.0008
- Subject:
- Economics and Finance, History of Economic Thought, Econometrics
Mainstream econometric research in the 1960s and the 1970s comprised primarily technical refinements and extensions of the structural modelling procedure. The author, therefore marks an end‐point ...
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Mainstream econometric research in the 1960s and the 1970s comprised primarily technical refinements and extensions of the structural modelling procedure. The author, therefore marks an end‐point around 1960 in the historical study of the formation of econometrics, and asks in this concluding chapter of the book what should and can be learnt from this period of history with respect to present and future econometric research. She has seen during the historical investigation presented that the key points of historic significance are the junctures at which economic thinking and mathematical statistics merged to match economics with data information. In the light of this, she tries to draw some more concrete lessons from these junctures, hoping to provide some useful points, particularly with respect to issues pertinent to present econometric developments. The prime impression of the history is that most important econometric advances have resulted from ingenious interfusion of statistical ideas with economic thinking, in regard to applied problems of interest, with the single most significant event of this sort being, perhaps, the acceptance of probability theory.Less
Mainstream econometric research in the 1960s and the 1970s comprised primarily technical refinements and extensions of the structural modelling procedure. The author, therefore marks an end‐point around 1960 in the historical study of the formation of econometrics, and asks in this concluding chapter of the book what should and can be learnt from this period of history with respect to present and future econometric research. She has seen during the historical investigation presented that the key points of historic significance are the junctures at which economic thinking and mathematical statistics merged to match economics with data information. In the light of this, she tries to draw some more concrete lessons from these junctures, hoping to provide some useful points, particularly with respect to issues pertinent to present econometric developments. The prime impression of the history is that most important econometric advances have resulted from ingenious interfusion of statistical ideas with economic thinking, in regard to applied problems of interest, with the single most significant event of this sort being, perhaps, the acceptance of probability theory.
Roberto S. Mariano and Bryan W. Brown
- Published in print:
- 1991
- Published Online:
- October 2011
- ISBN:
- 9780195057720
- eISBN:
- 9780199854967
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195057720.003.0009
- Subject:
- Economics and Finance, Econometrics
Stochastic simulations of nonlinear dynamic econometric models have been used in various ways in the past. This chapter discusses how stochastic simulations can be exploited to develop appropriate ...
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Stochastic simulations of nonlinear dynamic econometric models have been used in various ways in the past. This chapter discusses how stochastic simulations can be exploited to develop appropriate system-specification tests for nonlinear systems. The approach is through auxiliary regressions of stochastic simulation errors to develop asymptotically valid significance tests of the predictive performance of the model. The first section discusses Adrian Pagan's critique of the use of simulations in testing nonlinear models for misspecification. The related issue of the informational content of multi-period-ahead predictions is also analyzed in this section. The stochastic simulations that it uses to form the prediction-based tests and their basic asymptotic properties are reviewed in the second section. The last section then develops the auxiliary regressions leading to our prediction-based tests.Less
Stochastic simulations of nonlinear dynamic econometric models have been used in various ways in the past. This chapter discusses how stochastic simulations can be exploited to develop appropriate system-specification tests for nonlinear systems. The approach is through auxiliary regressions of stochastic simulation errors to develop asymptotically valid significance tests of the predictive performance of the model. The first section discusses Adrian Pagan's critique of the use of simulations in testing nonlinear models for misspecification. The related issue of the informational content of multi-period-ahead predictions is also analyzed in this section. The stochastic simulations that it uses to form the prediction-based tests and their basic asymptotic properties are reviewed in the second section. The last section then develops the auxiliary regressions leading to our prediction-based tests.
Luc Bauwens, Michel Lubrano, and Jean-François Richard
- Published in print:
- 2000
- Published Online:
- September 2011
- ISBN:
- 9780198773122
- eISBN:
- 9780191695315
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780198773122.003.0003
- Subject:
- Economics and Finance, Econometrics
This chapter examines the application of numerical methods in econometrics and provides some methods useful for Bayesian inference in econometrics. It presents the general principle of Bayesian ...
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This chapter examines the application of numerical methods in econometrics and provides some methods useful for Bayesian inference in econometrics. It presents the general principle of Bayesian analysis of models for which partly analytical results are available. It explains the general principle of partially linear models and discusses the computing principles for the Bayesian analysis of econometric models for which fully analytical posterior or predictive results are not available.Less
This chapter examines the application of numerical methods in econometrics and provides some methods useful for Bayesian inference in econometrics. It presents the general principle of Bayesian analysis of models for which partly analytical results are available. It explains the general principle of partially linear models and discusses the computing principles for the Bayesian analysis of econometric models for which fully analytical posterior or predictive results are not available.
Adams F. Gerard and Joaquin Vial
- Published in print:
- 1991
- Published Online:
- October 2011
- ISBN:
- 9780195057720
- eISBN:
- 9780199854967
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195057720.003.0010
- Subject:
- Economics and Finance, Econometrics
Comparisons of the performance of econometric models serve a number of purposes. These goals motivate the comparisons of econometric models of less developed countries (LDCs) as they have previous ...
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Comparisons of the performance of econometric models serve a number of purposes. These goals motivate the comparisons of econometric models of less developed countries (LDCs) as they have previous model comparison projects dealing with the United States and other industrial countries. The most important goal of the round of LDC model performance comparisons presented in Taiwan in May of 1987 was to get a first idea of the general characteristics of these models and a preliminary diagnostic of their principal strengths and weaknesses. A request to produce a standard set of simulations was sent to a dozen model groups in different countries. The simulations were defined carefully, restricting as much as possible the freedom of individual model builders so as to attain maximum comparability of results. Even so, since model structures and procedures differ, it is not certain that all the simulations are fully comparable.Less
Comparisons of the performance of econometric models serve a number of purposes. These goals motivate the comparisons of econometric models of less developed countries (LDCs) as they have previous model comparison projects dealing with the United States and other industrial countries. The most important goal of the round of LDC model performance comparisons presented in Taiwan in May of 1987 was to get a first idea of the general characteristics of these models and a preliminary diagnostic of their principal strengths and weaknesses. A request to produce a standard set of simulations was sent to a dozen model groups in different countries. The simulations were defined carefully, restricting as much as possible the freedom of individual model builders so as to attain maximum comparability of results. Even so, since model structures and procedures differ, it is not certain that all the simulations are fully comparable.