Preprint, August 2005

1994

2005

Abstract: A frequent criticism of unit root tests concerns the poor power and size properties that many of such tests exhibit. However, the past decade or so intensive research has been conducted to alleviate these problems and great advances have been made. The present paper provides a selective survey of recent contributions to improve upon both size and power of unit root tests and in so doing the approach of using rigorous statistical optimality criteria in the development of such tests is stressed.

Economics Letters, 2007

Econometric Theory, 1995

In the context of testing for a unit root in a univariate time series, the convention is to ignore information in related time series. This paper shows that this convention is quite costly, as large power gains can be achieved by including correlated stationary covariates in the regression equation. The paper derives the asymptotic distribution of ordinary least squares (OLS)

2013

We revisit estimation and computation of the Dickey Fuller (DF) and DFtype tests. Firstly, we show that the usual one step approach, based on the ”DF autoregression”, is likely to be subject to misspecification. Secondly, we clarify a neglected two step approach for estimation of the DF test. (In fact, we introduce a new two step DF autoregression.) This method is always correctly specified and efficient under the circumstances. However, it is either neglected or misused in unit root testing literature. The commonly employed hybrid of the (correct) two step method is shown to be inefficient, even asymptotically. Finally, we further improve/robustify the proposed two step method by employing the missing initial observations. Our finally proposed method is to be used in unit root testing, since it is a new DF autoregression that retains the missing observations.

2023

In recent years, policymakers, academics, and practitioners have increasingly called for the development of global governance mechanisms for artificial intelligence (AI). This paper considers the prospects for these calls in light of two other geopolitical trends: digital sovereignty and digital expansionism. While calls for global AI governance promote the surrender of some state sovereignty over AI, digital sovereignty and expansionism seek to secure greater state control over digital technologies. To demystify the tensions between these trends and their potential consequences, we undertake a case analysis of digital sovereignty and digital expansionism in China, the European Union, and the United States. We argue that the extraterritoriality embedded in these three actors' policies and escalatory competitive narratives, particularly those from the US, will likely undermine substantive global AI governance cooperation. However, nascent areas of alignment or compromise, notably in data governance and technical standards, could prove fruitful starting points for building trust in multilateral fora, such as the G20 or United Nations.

Revue Roumaine d'Histoire de l'Art. Série Beaux-Arts, 2023