The work of Card and Krueger has cast doubt on the nature of the relationship between the minimum wage and teenage employment in the United States. The earlier 'consensus' finding of a small but statistically significant negative effect was based on time series data whereas Card and Krueger's findings are based mainly on cross-section data. In this article, we re-examine the time series relationship between minimum wage and teenage employment. We find that previous models break down due to their inability to capture changes in the trend, cyclical and seasonal components of teenage employment. We propose an alternative approach in which these components are treated as stochastic components and which contains the traditional, deterministic approach as a special case. The model when estimated up to 1979 accurately predicts what happens to teenage employment subsequently, when the minimum wage was frozen after 1981 and then increased quite substantially in the early 1990s. Moreover, we find that there is a significant, negative effect of
ADInternational audienceWe examine the dependence between the volatility of the prices of the carbon dioxide “CO2” emissions with the volatility of one of their fundamental components, the energy prices. The dependence between the returns will be approached by a particular class of copula, the SCAR (Stochastic Autoregressive) Copulas, which is a time varying copula that was first introduced by Hafner and Manner (2012) [1] in which the parameter driving the dynamic of the copula follows a stochastic autoregressive process. The standard likelihood method will be used together with EIS (Efficient Importance Sampling) method, to evaluate the integral with a large dimension in the expression of the likelihood function. The main result suggests that the dynamics of the dependence between the volatility of the CO2 emission prices and the volatility of energy returns, coal, natural gas and Brent oil prices, do vary over time, although not much in stable periods but rise noticeably during the period of crisis and turmoils
ACL-2International audienceThis study examines the volatility and correlation and their relationships among the euro/US dollar exchange rates, the S&P500 equity indices, and the prices of WTI crude oil and the precious metals (gold, silver, and platinum) over the period 2005 to 2012. Our model links the univariate volatilities with the correlations via a hidden stochastic decision tree. The ensuing Hidden Markov Decision Tree (HMDT) model is in fact an extension of the Hidden Markov Model (HMM) introduced by Jordan et al. (1997). The architecture of this model is the opposite that of the classical deterministic approach based on a binary decision tree and, it allows a probabilistic vision of the relationship between univariate volatility and correlation. Our results are categorized into three groups, namely (1) exchange rates and oil, (2) S&P500 indices, and (3) precious metals. A switching dynamics is seen to characterize the volatilities, while, in the case of the correlations, the series switch from one regime to another, this movement touching a peak during the period of the Subprime crisis in the US, and again during the days following the Tohoku earthquake in Japan. Our findings show that the relationships between volatility and correlation are dependent upon the nature of the series considered, sometimes corresponding to those found in econometric studies, according to which correlation increases in bear markets, at other times differing from them
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