Monitoring international migration flows in Europe. Towards a statistical data base combining data from different sources

The paper reviews techniques developed in demography, geography and statistics that are useful for bridging the gap between available data on international migration flows and the information required for policy making and research. The basic idea of the paper is as follows: to establish a coherent and consistent data base that contains sufficiently detailed, up-to-date and accurate information, data from several sources should be combined. That raises issues of definition and measurement, and of how to combine data from different origins properly. The issues may be tackled more easily if the statistics that are being compiled are viewed as different outcomes or manifestations of underlying stochastic processes governing migration. The link between the processes and their outcomes is described by models, the parameters of which must be estimated from the available data. That may be done within the context of socio-demographic accounting. The paper discusses the experience of the U.S. Bureau of the Census in combining migration data from several sources. It also summarizes the many efforts in Europe to establish a coherent and consistent data base on international migration. The paper was written at IIASA. It is part of the Migration Estimation Study, which is a collaborative IIASA-University of Groningen project, funded by the Netherlands Organization for Scientific Research (NWO). The project aims at developing techniques to obtain improved estimates of international migration flows by country of origin and country of destination

Defections From The Inner Circle: Social Exchange, Reciprocity, And The Diffusion Of Board Independence In Us Corporations

This study seeks to reconcile traditional sociological views of the corporate board as an instrument of elite cohesion with recent evidence of greater board activism and control over top management. We propose that CEO-directors may typically support fellow CEOs by impeding increased board control over management but that CEO-directors may also foster this change if they have experienced it in their own corporation. Drawing on social exchange theory, we develop and test the argument that these CEO-directors may experience a reversal in the basis for generalized social exchange with other top managers from one of deference and support to one of independence and control. Using data from a large sample of major U.S. corporations over a recent ten-year period, we show (1) how CEO-directors ''defect'' from the network of mutually supportive corporate leaders, (2) how defections have diffused across organizations and over time, and (3) how this has contributed to increased board control, as measured by changes in board structure, diversification strategy, and contingent compensation. We also provide evidence that a social exchange perspective can explain the diffusion of these changes better than more conventional perspectives on network diffusion that emphasize imitation or learning.Business Administratio

ESTIMATION OF COST ALLOCATION COEFFICIENTS AT THE FARM LEVEL USING AN ENTROPY APPROACH

This paper aims to estimate the farm cost allocation coefficients from whole farm input costs. An entropy approach was developed under a Tobit formulation and was applied to a sample of farms from the 2004 FADN data base for Alentejo region, Southern Portugal. A Generalized Maximum Entropy model and Cross Generalized Entropy model were developed to the sample conditions and were tested. Model results were assessed in terms of their precision and estimation power and were compared with observed data. The entropy approach showed to be a flexible and valid tool to estimate incomplete information, namely regarding farm costs. Keywords: Generalized maximum entropy; costs; estimation; Alentejo, FADN

The Importance of Being Clustered: Uncluttering the Trends of Statistics from 1970 to 2015

In this paper we retrace the recent history of statistics by analyzing all the papers published in five prestigious statistical journals since 1970, namely: Annals of Statistics, Biometrika, Journal of the American Statistical Association, Journal of the Royal Statistical Society, series B and Statistical Science. The aim is to construct a kind of "taxonomy" of the statistical papers by organizing and by clustering them in main themes. In this sense being identified in a cluster means being important enough to be uncluttered in the vast and interconnected world of the statistical research. Since the main statistical research topics naturally born, evolve or die during time, we will also develop a dynamic clustering strategy, where a group in a time period is allowed to migrate or to merge into different groups in the following one. Results show that statistics is a very dynamic and evolving science, stimulated by the rise of new research questions and types of data

Biproportional Techniques in Input-Output Analysis: Table Updating and Structural Analysis

This paper is dedicated to the contributions of Sir Richard Stone, Michael Bacharach, and Philip Israilevich. It starts out with a brief history of biproportional techniques and related matrix balancing algorithms. We then discuss the RAS algorithm developed by Sir Richard Stone and others. We follow that by evaluating the interpretability of the product of the adjustment parameters, generally known as R and S. We then move on to discuss the various formal formulations of other biproportional approaches and discuss what defines an algorithm as “biproportionalâ€. After mentioning a number of competing optimization algorithms that cannot fall under the rubric of being biproportional, we reflect upon how some of their features have been included into the biproportional setting (the ability to fix the value of interior cells of the matrix being adjusted and of incorporating data reliability into the algorithm). We wind up the paper by pointing out some areas that could use further investigation.Input-Output Economics; RAS; data raking; iterative proportional fitting; estimating missing data