1,721,083 research outputs found
Advances in the statistical modeling of spatial interaction data
No full textAn abstract is not availabl
Socio-economic impacts of tourism in the European Union - A pilot estimation framework based on Tourism Satellite Accounts
Full text linkThe tourism sector has been indicated by the European Commission as one of the 14 strategic industries to build a stronger single market for Europe’s recovery after the COVID-19 pandemic shock. Despite the importance of tourism, the data describing its socioeconomic impact are still limited and fragmented. The direct economic impact of tourism is appraised through the Tourism Satellite Account (TSA) framework compiled by National Statistical Institutes under the coordination of Eurostat.
TSA data have an unrealized potential to evaluate not only direct, but also indirect and induced effect of tourism on the economy. This report documents a pilot study coordinated by the JRC in collaboration with Eurostat and DG GROW carrying two main tasks: (i) the collation and harmonization of TSA data from different EU countries, and (ii) their combination with input-output tables to estimate the direct and indirect economic impact of tourism in terms of total consumption, value added and employment. The methodology is applied to a sample of 10 EU countries, and the results are compared with estimates provided by official statistics and other sources.
This study demonstrates that TSA data can be harnessed to assess the socioeconomic contribution of tourism and support EU policy in a more complete and systematic way. However, the study also identified issues in the availability, completeness and consistency of TSA data, from which suggestions to improve TSA data production, dissemination and publication are drawn
The German East-West divide in knowledge production: an application to nanomaterial patenting
No full textResearch and development (R&D) in the field of nanomaterials is expected to be a major driver of innovation and economic growth. In this respect, many countries, as national systems of innovation, have established support programs offering subsidies for industry- and government-funded R&D. Consequently, it is of great interest to understand which factors facilitate the creation of new technological knowledge. The existing literature has typically addressed this question by employing a knowledge production function based on firm-, regional- or even country-level data. Estimating the effects for the entire national system of innovation, however, implicitly assumes poolability of regional data. We apply our reasoning to Germany, which has well-known – and wide – regional disparities, for example between the East and the West. Based on analyses at the level of NUTS-3 regions, we find different knowledge production functions for the East and the West. Moreover, we investigate how our results are affected by the adoption of alternative aggregation levels. Our findings have implications for further research in the field, that is, a careful evaluation of poolability and aggregation is required before estimating knowledge production functions at the regional level. Policy considerations are offered as well
Spatial econometric interaction modelling
No full textThe present book is concerned with spatial interaction modelling. In particular, it aims
to illustrate, through a collection of methodological and empirical studies, how
estimation approaches in this field recently developed, by including the tools typical of
spatial statistics and spatial econometrics (Anselin 1988; Cressie 1993; Arbia 2006,
2014), into what LeSage and Pace (2009) deemed as ‘spatial econometric interaction
models’.
It is no surprise to scientists and practitioners in regional science, planning,
demography or economics that spatial interaction models (or gravity models, following
the traditional Newtonian denomination, still popular in fields like international trade)
still are, after a long time, some of the most widely used analytical tools in studying
interactions between social and economic agents observed in space. Spatial interaction
indeed underlies most processes involving individual choices in regional economics,
and can apply to all economic agents (firms, workers or households, public entities,
etc.).
Although spatial interaction models originated at the end of the 19th century
following the Newtonian paradigm relating two masses and the distance between them
(for a more detailed review, see Sen and Smith 1995), they now have solid theoretical
economic foundations grounded on probabilistic theory, discrete choice modelling and
entropy maximization. The works of, among others, Stewart (1941), Isard (1960) and
Wilson (1970) during the 20th century provided such foundations, and allowed to see
spatial interaction models not just as mechanical tools for empirical analysis, but also
as a framework for theoretical and structural analyses (see, e.g., Baltagi and Egger
2015; Egger and Tarlea 2015).
A spatial interaction model describes the movement of people, items or information
(the list of possible applications is long) between generic spatial units. We can loosely
write it as a multiplicative model of the type:
( ), ij i j ij T kO D f d a b = (1)
where Tij is the flow (physical or not) moving from unit i to unit j, k is a proportionality
constant, Oi and Dj are sets of potentially different variables (e.g., population, income,
jobs) measured at the origin and the destination, respectively, and dij is the distance
(possibly measured according to different metrics) between units i and j. The latter is
solely an example of different types of deterrence variables accounting for factors
which impede or favour pairwise interaction. Different functional forms – most
frequently power or exponential – have been tested over the years to model the effect
of distance on spatial interaction. The parameters , and those involved by the
deterrence functions need to be properly estimated.
Such a simple specification is described as an unconstrained model, because it does
not fix the total number of outgoing or incoming flows (the marginal sums of the origindestination
matrix). Singly- or doubly-constrained model specifications impose such
limitations by including sets of balancing factors, which are nonlinear constraints
requiring iterative calibration (Wilson 1970). Constrained approaches, which are often
seen as the correct way of estimating the model, are, however, only seldom used in
applied work, mostly because of the computational complexity involved.
Although spatial interaction models have been used for decades by researchers and
practitioners in many fields, several authors have shown a renewed interest in them
over the last 10–15 years, both with regards to the theoretical foundations and to the
estimation approaches the latter being greatly facilitated by the wider computing power
availability. The contributions by Anderson and van Wincoop (2003, 2004) pushed the
envelope in trade-related research by proposing a theory-consistent interpretation of the
balancing factors, relabelled as multilateral resistance terms. Santos Silva and Tenreyro
(2006) provided a stepping stone in the discussion on the estimation of spatial
interaction (and in general multiplicative) models. They suggested that, because of
Jensen’s inequality and of overdispersion, these models should not be estimated in their
loglinear transformation, but rather using the count data (such as the Poisson)
regressions framework. The pseudo-maximum likelihood estimator proposed by the
authors is now one of the most commonly used estimation approaches. Further studies
focus on further issues in complementing the above groundbreaking studies. Burger et
al. (2009) reviewed alternative estimation approaches focusing on the cases of excess
zeros; Baltagi and Egger (2015) proposed a quantile regression approach; Egger (2005),
Baier and Bergstrand (2009) and Egger and Staub (2015) proposed estimators for the
cross-sectional model, while Egger and Pfaffermayr (2003) discussed panel estimation
issues. Many more studies of recent publication coul
Accessibility, equity and efficiency. Challenges for Transport and Public Services
Full text linkIn this book, leading researchers from around the world show the importance of accessibility in contemporary issues such as rural depopulation, investments in public services and public transport, and transport infrastructure investments in Europe. The trade-offs between accessibility, economic development and equity are comprehensively examined, and a variety of approaches to measuring accessibility and equality presented. The book’s interdisciplinary contributions also provide different geographical contexts, from the US to various European and developing countries, and cover ex ante and ex post evaluation of transport investment. Improving transport accessibility is a main objective in transport policy and planning in developed and developing countries all over the world. Investment is motivated by the need to develop and/or reduce spatial or social inequalities. However, the economic and equity implications of investments in transport are not straightforward. The concepts of accessibility and equity can be defined and operationalised in many different ways, influencing outcomes and conclusions. Moreover, equity and efficiency goals are often conflicting. Accessibility models not only help to explain spatial and transport patterns in developed and developing countries, but are also powerful tools to explain the equity and efficiency impacts of urban and transport policies and projects. This state-of-the-art overview of the accessibility-economic efficiency-equity relationship will appeal to researchers as well as transport and urban planners interested in accessibility issues and transport/regional developments
Spatial Early Warning Signals to Assess Economic Resilience
No full textImproving the resilience of economies to crises is of societal and policy interest. In this article, we complement the regional economics literature on resistance and recovery facets of resilience by instead exploring signals for loss of resilience prior to crises. In particular, we adapt spatiotemporal indicators from the ecological literature to spatially disaggregated unemployment data to assess the resilience of the economy of France. Key questions are whether more information about the resilience of the system can be gained by considering the spatial dimension, and whether the indicators can be used as a detection method of impending economic crises. This approach reveals that a spatially disaggregated principal components analysis enables to capture of signals of critical slowing down and to assess which specific region or groups of regions dominate the unemployment dynamics, which represents critical information that is missed when using nonspatial early warning signals. We find that different regions dominate the signal before or after a crisis. This resembles response diversity as seen in ecosystems. The spatial early warning signal, Moran’s I, is found to increase prior to the moments of economic crises. These findings suggest that the spatial characteristics of a country’s unemployment are crucial to assess a country’s resilience
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
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