On the positive correlation between income inequality and unemployment

Several empirical studies in the literature have documented the existence of a positive correlation between income inequalitiy and unemployment. I provide a theoretical framework under which this correlation can be better understood. The analysis is based on a dynamic job search under uncertainty. I start by proving the uniqueness of a stationary distribution of wages in the economy. Drawing upon this distribution, I provide a general expression for the Gini coefficient of income inequality. The expression has the advantage of not requiring a particular specification of the distribution of wage offers. Next, I show how the Gini coefficient varies as a function of the parameters of the model, and how it can be expected to be positively correlated with the rate of unemployment. Two examples are offered. The first, of a technical nature, to show that the convergence of the measures implied by the underlying Markov process can fail in some cases. The second, to provide a quantitative assessment of the model and of the mechanism linking unemployment and inequality.

A search-theoretic explanation for the negative correlation between labor income and impatience

Lawrance (1991) has shown, through the estimation of consumption Euler equations, that subjective rates of impatience (time preference) in the U.S. are three to Öve percentage points higher for households with lower average labor incomes than for those with higher labor income. From a theoretical perspective, the sign of this correlation in a job-search model seems at Örst to be undetermined, since more impatient workers tend to accept wage o§ers that less impatient workers would not, thereby remaining less time unemployed. The main result of this paper is showing that, regardless of the existence of e§ects of opposite sign, and independently of the particular speciÖcations of the givens of the model, less impatient workers always end up, in the long run, with a higher average income. The result is based on the (unique) invariant Markov distribution of wages associated with the dynamic optimization problem solved by the consumers. An example is provided to illustrate the method.

Analysis of contagion from the constant conditional correlation model with Markov regime switching

Over the last decades, the analysis of the transmissions of international nancial events has become the subject of many academic studies focused on multivariate volatility models volatility. The goal of this study is to evaluate the nancial contagion between stock market returns. The econometric approach employed was originally presented by Pelletier (2006), named Regime Switching Dynamic Correlation (RSDC). This methodology involves the combination of Constant Conditional Correlation Model (CCC) proposed by Bollerslev (1990) with Markov Regime Switching Model suggested by Hamilton and Susmel (1994). A modi cation was made in the original RSDC model, the introduction of the GJR-GARCH model formulated in Glosten, Jagannathan e Runkle (1993), on the equation of the conditional univariate variances to allow asymmetric e ects in volatility be captured. The database was built with the series of daily closing stock market indices in the United States (SP500), United Kingdom (FTSE100), Brazil (IBOVESPA) and South Korea (KOSPI) for the period from 02/01/2003 to 09/20/2012. Throughout the work the methodology was compared with others most widespread in the literature, and the model RSDC with two regimes was de ned as the most appropriate for the selected sample. The set of results provide evidence for the existence of nancial contagion between markets of the four countries considering the de nition of nancial contagion from the World Bank called very restrictive. Such a conclusion should be evaluated carefully considering the wide diversity of de nitions of contagion in the literature.

Speculative bubbles and contagion: analysis of volatility’s clusters during the DotCom bubble based on the dynamic conditional correlation model

Revendo a definição e determinação de bolhas especulativas no contexto de contágio, este estudo analisa a bolha do DotCom nos mercados acionistas americanos e europeus usando o modelo de correlação condicional dinâmica (DCC) proposto por Engle e Sheppard (2001) como uma explicação econométrica e, por outro lado, as finanças comportamentais como uma explicação psicológica. Contágio é definido, neste contexto, como a quebra estatística nos DCC’s estimados, medidos através das alterações das suas médias e medianas. Surpreendentemente, o contágio é menor durante bolhas de preços, sendo que o resultado principal indica a presença de contágio entre os diferentes índices dos dois continentes e demonstra a presença de alterações estruturais durante a crise financeira.

Speculative bubbles and contagion: analysis of volatility's clusters during the DotCom bubble based on the dynamic conditional correlation model

Reviewing the de nition and measurement of speculative bubbles in context of contagion, this paper analyses the DotCom bubble in American and European equity markets using the dynamic conditional correlation (DCC) model proposed by (Engle and Sheppard 2001) as on one hand as an econometrics explanation and on the other hand the behavioral nance as an psychological explanation. Contagion is de ned in this context as the statistical break in the computed DCCs as measured by the shifts in their means and medians. Even it is astonishing, that the contagion is lower during price bubbles, the main nding indicates the presence of contagion in the di¤erent indices among those two continents and proves the presence of structural changes during nancial crisis