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The editors are pleased to offer the following papers to the reader in recognition and appreciation of the contributions to our literature made by Robert Engle and Sir Clive Granger, winners of the 2003 Nobel Prize in Economics. Please see the previous dedication page of this volume. The basic themes of this part of Volume 20 of Advances in Econometrics are time-varying betas of the capital asset pricing model, analysis of predictive densities of nonlinear models of stock returns, modeling multivariate dynamic correlations, flexible seasonal time series models, estimation of long-memory time series models, the application of the technique of boosting in volatility forecasting, the use of different time scales in Generalized Auto-Regressive Conditional Heteroskedasticity (GARCH) modeling, out-of-sample evaluation of the ‘Fed Model’ in stock price valuation, structural change as an alternative to long memory, the use of smooth transition autoregressions in stochastic volatility modeling, the analysis of the “balancedness” of regressions analyzing Taylor-type rules of the Fed Funds rate, a mixture-of-experts approach for the estimation of stochastic volatility, a modern assessment of Clive's first published paper on sunspot activity, and a new class of models of tail-dependence in time series subject to jumps. Of course, we are also pleased to include Rob's and Clive's remarks on their careers and their views on innovation in econometric theory and practice that were given at the Third Annual Advances in Econometrics Conference held at Louisiana State University, Baton Rouge, on November 5–7, 2004.

Volume 20 of Advances in Econometrics is dedicated to Rob Engle and Sir Clive Granger, winners of the 2003 Nobel Prize in Economics, for their many valuable contributions to the econometrics profession. The Royal Swedish Academy of Sciences cited Rob “for methods of analyzing economic time series with time-varying volatility (ARCH),” while Clive was cited “for methods of analyzing economic time series with common trends (cointegration).” Of course, these citations are meant for public consumption but we specialists in time-series analysis know their contributions go far beyond these brief citations. Consider some of Rob's other contributions to our literature: Aggregation of Time Series, Band Spectrum Regression, Dynamic Factor Models, Exogeneity, Forecasting in the Presence of Cointegration, Seasonal Cointegration, Common Features, ARCH-M, Multivariate GARCH, Analysis of High Frequency Data, and CAViaR. Some of Sir Clive's additional contributions include Spectral Analysis of Economic Time Series, Bilinear Time Series Models, Combination Forecasting, Spurious Regression, Forecasting Transformed Time Series, Causality, Aggregation of Time Series, Long Memory, Extreme Bounds, Multi-Cointegration, and Non-linear Cointegration. No doubt, their Nobel Prizes are richly deserved. And the 48 authors of the two parts of this volume think likewise. They have authored some very fine papers that contribute nicely to the same literature that Rob's and Clive's research helped build.

Volume 20 of Advances in Econometrics is dedicated to Rob Engle and Sir Clive Granger, winners of the 2003 Nobel Prize in Economics, for their many valuable contributions to the econometrics profession. The Royal Swedish Academy of Sciences cited Rob “for methods of analyzing economic time series with time-varying volatility (ARCH)” while Clive was cited “for methods of analyzing economic time series with common trends (cointegration).” Of course, these citations are meant for public consumption but we specialists in time series analysis know their contributions go far beyond these brief citations. Consider some of Rob's other contributions to our literature: Aggregation of Time Series, Band Spectrum Regression, Dynamic Factor Models, Exogeneity, Forecasting in the Presence of Cointegration, Seasonal Cointegration, Common Features, ARCH-M, Multivariate GARCH, Analysis of High Frequency Data, and CAViaR. Some of Sir Clive's additional contributions include Spectral Analysis of Economic Time Series, Bilinear Time Series Models, Combination Forecasting, Spurious Regression, Forecasting Transformed Time Series, Causality, Aggregation of Time Series, Long Memory, Extreme Bounds, Multi-Cointegration, and Non-linear Cointegration. No doubt, their Nobel Prizes are richly deserved. And the 48 authors of the two parts of this volume think likewise. They have authored some very fine papers that contribute nicely to the same literature that Rob's and Clive's research helped build.

Relying on Clive Granger's many and varied contributions to econometric analysis, this paper considers some of the key econometric considerations involved in estimating Taylor-type rules for US data. We focus on the roles of unit roots, cointegration, structural breaks, and non-linearities to make the case that most existing estimates are based on an unbalanced regression. A variety of estimates reveal that neglected cointegration results in the omission of a necessary error correction term and that Federal Reserve (Fed) reactions during the Greenspan era appear to have been asymmetric. We argue that error correction and non-linearities may be one way to estimate Taylor rules over long samples when the underlying policy regime may have changed significantly.

In a brilliant career spanning almost five decades, Sir Clive Granger has made numerous contributions to time series econometrics. This paper reappraises his very first paper, published in 1957 on sunspot numbers.

This paper considers the East India Company’s emergence as a territorial power from the 1760s until the revocation of most of its commercial functions in 1834. While this period has been a key episode for historians of the British Empire and of South Asia, social scientists have struggled with the Company’s ambiguous nature. In this paper, I propose that a profitable way to grasp the Company’s transformation is to consider it as a global strategic action field. This perspective clarifies two key processes in the Company’s transition: the enlargement of its territorial possessions; and the increased exposure of its patrimonial network to intervention from British metropolitan politics. To further suggest the utility of this analytic perspective, I synthesize evidence from various sources, including data concerning the East India Court of Directors and the career histories of Company servants in two of its key administrative regions, Bengal and Madras, during this period of transition.

The East India Company was a hybrid corporation. This hybridity refers to the merchant-state function of the Company, designed as a joint-stock corporate established to trade and make profit, whilst simultaneously exercising public state governance over India. As the Company strived for profits, this was inherently detrimental to ruling a state of people. Its increasing public role alienated both Indians and the British government as it faced increasing criticism. Eventually British state intervention increased until the Company operated as an agent for British imperialism, and its corporate status continued to decline until the Company was replaced by British rule. Ultimately, the legacy of the East India Company represents the incompatibility of private actors taking on state responsibility.

There is now a large, if rather contentious and inconclusive, cross-country empirical literature on the effectiveness of aid in contributing to economic growth. Surprisingly, perhaps, there are very few country studies of aid effectiveness, and none of which we are aware that adopt a time series econometric approach to analyzing the impact of aid on growth. This chapter is an attempt to fill that gap, through a study of Kenya over the period 1964–2002. The core hypothesis underlying our approach is that aid does not have a direct effect on growth, but can have indirect effects through mediating channels. Given the requirements of time series techniques, we focus on two channels for the aid-growth relationship, one through effects on government fiscal relationship (as aid finances public spending) and another through effects on investment (as aid finances public investment). The analysis is no more than indicative but suggests a number of reasons why aid has not been effective in Kenya: reliance on aid loans to finance unanticipated budget deficits, low productivity of public investment and adverse effects of government behavior on private investment. Addressing these deficiencies is necessary if Kenya is to be enabled to utilize aid to improve its poor economic performance.