1,720,956 research outputs found
Housing Market Shocks in Italy: a GVAR Approach
Get PDFIn this paper, we use a Global Vector Autoregression (GVAR) model to assess the spatio-temporal mechanism of house price spillovers, also known as “ripple effect”, among 93 Italian provincial housing markets, over the period 2004 − 2016. In order to better capture the local housing market dynamics, we use data not only on house prices but also on transaction volumes. In particular, we focus on estimating, to what extent, exogenous shocks, interpreted as negative housing demand shocks, arising from 10 Italian regional capitals, impact on their house prices and sales and how these shocks spill over to neighbours housing markets. The negative housing market demand shock hitting the GVAR model is identified by using theory-driven sign restrictions. The spatio-temporal analysis carried through impulse response functions shows that there is evidence of a “ripple effect” mainly occurring through transaction volumes
Climate risk and investment in equities in Europe: a Panel SVAR approach
Get PDFIn this study, we use data on European stocks to construct a green-minus-brown portfolio hedging climate risk and to evaluate its performance in terms of cumulative expected and unexpected returns. More specifically, we estimate a Structural Panel VAR fitted to one month return and realized volatility computed for 40 constituents of a green portfolio (i.e., the low carbon emission portfolio monitored by Refinitiv) and for 41 constituents of a brown portfolio (underlying the Oil&Gas and Utilities industry sectors of the STOXX Europe 600). The common shocks underlying the cross-sectional averages, interpreted as portfolio shocks, are retrieved in a first stage
of the analysis and they are used to control for cross-sectional dependence. We compute the historical decomposition (for cumulative returns) in a second stage of the analysis and we find, in line with P ́astor, L., Stambaugh, R. F., & Taylor, L. A. (2022). Dissecting green returns. Journal of Financial Economics, 146 (2), 403–424, an out-performance of the expected component of the brown portfolio relative to the one for the green portfolio, and an out-performance of the green portfolio when we turn our focus on the unexpected component. We also extend the analysis of
P ́astor et al. (2022), assessing, for the top 5 constituents of the green portfolio (e.g., those which are found to have the worst performance in terms of expected return), the role played by idiosyncratic shocks in shaping their out-performance in terms of unexpected component. Finally, after exploiting the non-gaussian time series properties of the financial time series considered for the purpose of statistical identification, we are able to interpret ex post the idiosyncratic shocks in terms of financial leverage and risk aversion
Temperature and Growth: a Panel Mixed Frequency VAR Analysis using NUTS2 data
Get PDFIn this study, we contribute to the existing literature on the impact of temperature on
growth by examining the orthogonalized seasonal effect jointly with the feedback from
economic activity (hence treating the increase in global temperature as anthropogenic)
on a sample of 225 EU NUTS2 regions. For this purpose, we use a Panel Mixed-
Frequency VAR. The empirical findings show, first, a worsening impact of temperature
on growth over the last sub-sample (2000-2019) relative to the full sample analysis
(covering the 1981-2019 time span). Moreover, our findings show that seasonal
temperature effects are not restricted only to the agriculture sector, and we also
find evidence of a heterogeneous impact of seasonal temperature on growth when
we turn our focus on hot and cold regions (using the average EU median annual
temperature as a threshold), rich and poor regions (using the average EU median
income per capita as a threshold) and between competitiveness (using the median
Regional Competitiveness index as a threshold)
Housing market shocks in italy: A GVAR approach
No full textIn this paper, we use a Global Vector Autoregression (GVAR) model to assess the spatio-temporal mechanism of house price spillovers, also known as “ripple effect”, among 93 Italian provincial housing markets, over the period 2004−2016. In order to better capture the local housing market dynamics, we use data not only on house prices but also on transaction volumes. In particular, we focus on estimating, to what extent, exogenous shocks, interpreted as negative housing demand shocks, arising from 10 Italian regional capitals, impact on their house prices and sales and how these shocks spill over to neighbours housing markets. The negative housing market demand shock hitting the GVAR model is identified by using theory-driven sign restrictions. The spatio-temporal analysis carried through impulse response functions shows that there is evidence of a “ripple effect” mainly occurring through transaction volumes
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Get PDF“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
Get PDFWe 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
Get PDFWe 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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