1,721,156 research outputs found
Portfolio diversification based on stochastic dominance under incomplete probability information
Full text linkIdentifying efficient portfolio diversification strategies subject to stochastic dominance (SD) criteria usually assumes that the state-space of future asset returns can be captured by a fixed sample of equally probable historical returns. This paper relaxes this assumption by developing SD criteria under incomplete information on state probabilities. Specifically, we identify portfolios that dominate a given benchmark for any state probabilities in a given set. The proposed approach is applied to analyze if industrial diversification can be utilized to outperform the market portfolio. The results from this application demonstrate that the use of set-valued state probabilities can help to improve out-of-sample performance of SD-based portfolio optimization
Misallocation of labor and capital in Finland’s business sector
No full textMisallocation of labor and capital has attracted considerable interest in economics, however, there is little empirical evidence from Finland’s business sector. This project examined misallocation by applying modern methods of economics and statistics to the register data of Statistics Finland on business enterprises in Finland.
The main results of the study can be summarized as follows: 1) The current allocation of resources is far from optimal from a societal point of view. 2) The efficiency of resource allocation between companies deteriorated during the study period 2000-2018. 3) Misallocation of labor correlates statistically significantly with the characteristics of enterprises such as the age, size, equity-debt ratio, and foreign ownership. 4) The majority of the companies considered operate capital intensively than would be efficient from a societal perspective.
Based on the results, more efficient allocation of resources to high-productivity firms could significantly increase productivity. Although startups are, on average, more productive than exiting firms, many startups are unable to take advantage of the competitive advantage due to high productivity to expand their operation. On the other hand, the results suggest that the allocation of labor input across firms is less efficient than the allocation of capital, especially for startups and small firms. Increasing labor mobility and wage competition could be practical means to improve the allocation of labor across firms.This publication is part of the implementation of the Government Plan for Analysis, Assessment and Research (tietokayttoon.fi). The content is the responsibility of the producers of the information and does not necessarily represent the view of the Government
Stochastic Nonparametric Envelopment of Data: Combining Virtues of SFA and DEA in a Unified Framework
Full text linkThe literature of productive efficiency analysis is divided into two main branches: the parametric Stochastic Frontier Analysis (SFA) and nonparametric Data Envelopment Analysis (DEA). This paper attempts to combine the virtues of both approaches in a unified framework. We follow the SFA literature and introduce a stochastic component decomposed into idiosyncratic error and technical inefficiency components imposing the standard SFA assumptions. In contrast to the SFA, we do not make any prior assumptions about the functional form of the deterministic production function. In this respect, we follow the nonparametric route of DEA that only imposes free disposability, convexity, and some specification of returns to scale. From the postulated class of production functions, the proposed method identifies the production function with the best empirical fit to the data. The resulting function will always take a piece-wise linear form analogous to the DEA frontiers. We discuss the practical implementation of the method and illustrate its potential by means empirical examples.Productivity Analysis,
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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