Wage differentials between Permanent and Temporal Contracts: Further Evidence

The main objective of this paper is to estimate wage differentials between permanent and temporal workers for different qualification levels and decompose such differentials to see which factors contribute more to explain them. The data we use is the "Encuesta de Estructura Salarial", a survey carried out in 1995 in all countries of the European Union, which contains very detailed information on wages and other characteristics for about 180.000 workers. The empirical results indicate that (a) the wage gap between permanent and temporal workers increases with qualification and it is smaller for females than for males, (b) when decomposing average wage differentials for each qualification level, we observe that the vast majority of such differential is explainedby differences in characteristics, and in particular by differences in tenure and occupation. With respect to differences in returns, our results indicate that the returns to tenure are higher for temporal workres relative to permanent workers for both males and females and for every qualification level. Returns to occupation are higher for permanent than for temporal workers, and the differenceis particularly high for females.

Music-Theoretic Estimation of Chords and Keys from Audio

This paper proposes a new method for local key and chord estimation from audio signals. This method relies primarily on principles from music theory, and does not require any training on a corpus of labelled audio files. A harmonic content of the musical piece is first extracted by computing a set of chroma vectors. A set of chord/key pairs is selected for every frame by correlation with fixed chord and key templates. An acyclic harmonic graph is constructed with these pairs as vertices, using a musical distance to weigh its edges. Finally, the sequences of chords and keys are obtained by finding the best path in the graph using dynamic programming. The proposed method allows a mutual chord and key estimation. It is evaluated on a corpus composed of Beatles songs for both the local key estimation and chord recognition tasks, as well as a larger corpus composed of songs taken from the Billboard dataset.