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The Nobel Memorial Prize for Robert F. Engle

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Engle's footsteps range widely. His major contributions include early work on band-spectral regression, development and unification of the theory of model specification tests (particularly Lagrange multiplier tests), clarification of the meaning of econometric exogeneity and its relationship to causality, and his later stunningly influential work on common trend modeling (cointegration) and volatility modeling (ARCH, short for AutoRegressive Conditional Heteroskedasticity). More generally, Engle's cumulative work is a fine example of best-practice applied time-series econometrics: he identifies important dynamic economic phenomena, formulates precise and interesting questions about those phenomena, constructs sophisticated yet simple econometric models for measurement and testing, and consistently obtains results of widespread substantive interest in scientific, policy, and financial communities. Although many of Engle's contributions are fundamental, I will focus largely on the two most important: the theory and application of cointegration, and the theory and application of dynamic volatility models. Moreover, I will discuss much more extensively Engle's volatility models and their role in financial econometrics, for several reasons. First, Engle's Nobel citation was explicitly for methods of analyzing economic time series with time-varying volatility (ARCH), whereas Granger's was for for methods of analyzing economic time series with common trends (cointegration). Second, the credit for creating the ARCH model goes exclusively to Engle, whereas the original cointegration idea was Granger's, notwithstanding Engle's powerful and well-known contributions to the development. Third, volatility models are a key part of the financial econometrics theme that defines Engle's broader contributions, whereas cointegration has found wider application in macroeconomics than in finance. Last and not least, David Hendry's insightful companion review of Granger's work, also in this issue of the Scandinavian Journal, discusses the origins and development of cointegration in great depth. In this brief and selective review, I attempt a description of what happened and why) as a popular American talk show host puts it). My approach has been intentionally to avoid writing a long review, as several extensive surveys of the relevant literatures already exist. In addition, I have de-emphasized technical aspects, focusing in stead on the intuition, importance, and nuances of the work. In Section 2, I discuss cointegration in the context of Engle's previous and subsequent work, which facilitates the extraction of interesting and long-running themes, several of which feature prominently in Engle's volatility models. I discuss the basic ARCH model in Section 3, and I discuss variations, extensions and applications in Section 4. I conclude in Section 5.
Title: The Nobel Memorial Prize for Robert F. Engle
Description:
Engle's footsteps range widely.
His major contributions include early work on band-spectral regression, development and unification of the theory of model specification tests (particularly Lagrange multiplier tests), clarification of the meaning of econometric exogeneity and its relationship to causality, and his later stunningly influential work on common trend modeling (cointegration) and volatility modeling (ARCH, short for AutoRegressive Conditional Heteroskedasticity).
More generally, Engle's cumulative work is a fine example of best-practice applied time-series econometrics: he identifies important dynamic economic phenomena, formulates precise and interesting questions about those phenomena, constructs sophisticated yet simple econometric models for measurement and testing, and consistently obtains results of widespread substantive interest in scientific, policy, and financial communities.
Although many of Engle's contributions are fundamental, I will focus largely on the two most important: the theory and application of cointegration, and the theory and application of dynamic volatility models.
Moreover, I will discuss much more extensively Engle's volatility models and their role in financial econometrics, for several reasons.
First, Engle's Nobel citation was explicitly for methods of analyzing economic time series with time-varying volatility (ARCH), whereas Granger's was for for methods of analyzing economic time series with common trends (cointegration).
Second, the credit for creating the ARCH model goes exclusively to Engle, whereas the original cointegration idea was Granger's, notwithstanding Engle's powerful and well-known contributions to the development.
Third, volatility models are a key part of the financial econometrics theme that defines Engle's broader contributions, whereas cointegration has found wider application in macroeconomics than in finance.
Last and not least, David Hendry's insightful companion review of Granger's work, also in this issue of the Scandinavian Journal, discusses the origins and development of cointegration in great depth.
In this brief and selective review, I attempt a description of what happened and why) as a popular American talk show host puts it).
My approach has been intentionally to avoid writing a long review, as several extensive surveys of the relevant literatures already exist.
In addition, I have de-emphasized technical aspects, focusing in stead on the intuition, importance, and nuances of the work.
In Section 2, I discuss cointegration in the context of Engle's previous and subsequent work, which facilitates the extraction of interesting and long-running themes, several of which feature prominently in Engle's volatility models.
I discuss the basic ARCH model in Section 3, and I discuss variations, extensions and applications in Section 4.
I conclude in Section 5.

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