CEMFI

About: CEMFI is a based out in . It is known for research contribution in the topics: Unemployment & Estimator. The organization has 71 authors who have published 499 publications receiving 46553 citations. The organization is also known as: Center for Monetary and Financial Studies.

Assessing the equalizing force of mobility using short panels: France 1990-2000

Abstract: In this paper, we document whether and how much the equalizing force of earnings mobility has changed in France in the 1990s. For this purpose, we use a representative three-year panel, the French Labour Force Survey. We develop a model of earnings dynamics that combines a flexible specification of marginal earnings distributions (to fit the large cross-sectional dimension of the data) with a tight parametric representation of the dynamics (adapted to the short timeseries dimension). Log earnings are modelled as the sum of a deterministic component, an individual fixed effect and a transitory component which is assumed first-order Markov. The transition probability of the transitory component is modelled as a one-parameter Plackett copula. We estimate this model using a sequential EM algorithm. We exploit the estimated model to study employment/earnings inequality in France over the 1990-2002 period. We show that, in phase with business cycle fluctuations (a recession in 1993 and two peaks in 1990 and 2000), earnings mobility decreases when cross-section inequality and unemployment risk increase. We simulate individual earnings trajectories and compute present values of lifetime earnings for various horizons. Inequality presents a hump-shaped evolution over the period, with a 9% increase between 1990 and 1995 and a decrease afterwards. Accounting for unemployment yields an increase of 11%. Moreover, this increase is persistent, as it translates into a 12% increase in the variance of log present values. The ratio of inequality in present values to inequality in one-year earnings, a natural measure of immobility or of the persistence of inequality, remains remarkably constant over the business cycle.

Normality tests for latent variables

Abstract: We exploit the rationale behind the Expectation Maximization algorithm to derive simple to implement and interpret LM normality tests for the innovations of the latent variables in linear state space models against generalized hyperbolic alternatives, including symmetric and asymmetric Student ts. We decompose our tests into third and fourth moment components, and obtain one‐sided likelihood ratio analogues, whose asymptotic distribution we provide. When we apply our tests to a common trend model which combines the expenditure and income versions of US aggregate real output to improve its measurement, we reject normality if the sample period extends beyond the Great Moderation. Cointegration gross domestic product gross domestic income kurtosis Kuhn–Tucker test skewness supremum test Wiener–Kolmogorov–Kalman smoother C32 C52 E01

Growth, Inequality, and Poverty : A Robust Relationship?

Abstract: An extensive literature on poverty traps suggests that high levels of poverty deter growth. However, a seemingly basic implication of the underlying theoretical models, namely that countries suffering from higher levels of poverty should grow less rapidly, has remained untested. A parallel literature has suggested a variety of mechanisms through which inequality may affect growth in opposing directions. Because inequality and poverty are different aspects of the income distribution, inequality can also affect growth through poverty, an indirect channel that has not been explicitly analyzed. This paper contributes to fill both gaps. Using a large cross-country panel data set, it estimates a reduced-form growth equation adding both inequality and poverty to an otherwise standard set of growth determinants. Given inequality, the correlation of growth with poverty is consistently negative. In contrast, given poverty, the correlation of growth with inequality can be positive or negative, depending on the empirical specification and econometric approach used. Yet, the indirect effect of inequality on growth through its correlation with poverty is robustly negative. Closer inspection shows that these results are driven by the sample observations featuring high (but not extremely high) poverty rates. These empirical findings are consistent with the predictions from an analytical framework with learning-by-doing and knowledge spillovers, in which consumers cannot save and invest if their initial endowment is below a minimum consumption level.