In this paper, we study partial identification of the distribution of treatment effects of a binary treatment for ideal randomized experiments, ideal randomized experiments with a known value of a dependence measure, and for data satisfying the selection-on-observables assumption respectively....

In this paper, we first re-visit the inference problem for interval identified parameters originally studied in Imbens and Manski (2004) and later extended in Stoye (2008). We take the general criterion function approach and establish a new confidence interval that is asymptotically valid under...

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...

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 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...

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...

Evaluating the treatment of missing values by SAS 6.12, the first target group is considered to be an uninitiated person like a physician who is doing his first real research in the frame of his doctoral thesis. Such a physician will easily come to wrong conclusions as the treatment of missing...

The present state of world economy urges managers to look for new methods, which can help to start the economic growth. To achieve this goal, managers use standard as well as new procedures. The fundamental prerequisite of the efficient decision-making processes are actual and right information....

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...

In machine learning and data science literature, clustering is the task of dividing the observations (data points) into several categories in such a way that data points falling into one group are being dissimilar than the data points falling to the other groups such that the variation within a...