Even casual observation reveals obvious spatial patterns in labor-market outcomes and policies across the developed democracies, and within the European Union particularly. Labor-market policies entail significant cross-border spillovers, so strategic interdependence among developed democracies...

We use the panel data social network analysis program SIENA to estimate the effect of actor reputation derived from past performance on alliance formation, while controlling for other constant actor attributes, and network position. We distinguish between individual reputation based on the past...

The exponential increase in data today derives from the big amount of interactions among consumers that spreads in social media, using mobile devices, IT, localization, historical data in purchase, data owned by companies, behavioral insights and so on through connected online devices and mobile...

We present a new Monte-Carlo methodology to forecast the crude oil production of Norway and the U.K. based on a two-step process, (i) the nonlinear extrapolation of the current/past performances of individual oil fields and (ii) a stochastic model of the frequency of future oil field...

In this paper, we propose a new empirical version of the Fama and French Model based on the Hausman (1978) specification test and aimed at discarding measurement errors in the variables. The proposed empirical framework is general enough to be used for correcting other financial and accounting...

In this paper, we aim at forecasting the stochastic volatility of key financial market variables with the Kalman filter using stochastic models developed by Taylor (1986, 1994) and Nelson (1990). First, we compare a stochastic volatility model relying on the Kalman filter to the conditional...

It is well-known that traditional financial institutions like banks follow procyclical risk strategies (Rajan 2005, 2009, Shin 2009, Jacques 2010) in the sense that they increase their leverage in economic expansions and reduce it in recessions, which leads to a procyclical behaviour for their...

In this study we combine clustering techniques with a moving window algorithm in order to filter financial market data outliers. We apply the algorithm to a set of financial market data which consists of 25 series selected from a larger dataset using a cluster analysis technique taking into...

The paper offers an alternative approach to analyzing stock market time series data. The purpose is to develop descriptive, more intuitive, and closer to reality analogs of the behavior of US stock market prices, as indexed by the S&P500 stock price index covering the period October 2003 to...

This paper studies the dynamics of Mexican inflation by using a wavelet multiresolution analysis on 16 indexes of the Mexican Consumer Price Index. This enables us to estimate the long-term trend, seasonality, and local shocks of the inflation series, even when the series are non-stationary. The...