ABSTRACT This study analyses the impact of female political empowerment on European countries’ welfare policies. Following a spatial econometric approach, the results reveal the presence of a spatial dependence across countries and a consistent gender effect. In particular, the descriptive representation seems to favour a higher distribution of resources to sectors in which women are disproportionately

ABSTRACT This paper proposes a new estimation procedure for the first-order spatial autoregressive (SAR) model, where the disturbance term also follows a first-order autoregression and its innovations may be heteroscedastic. The estimation procedure is based on the principle of indirect inference that matches the ordinary least squares estimator of the two SAR coefficients (one in the outcome equation

ABSTRACT This paper studies the integration of regional goods markets in Russia over the period 2001–19, analysing the law of one price. The analysis involves all pairs of country’s regions, which provides a comprehensive spatial pattern of market integration. The region pairs are classified as belonging to one of four groups: perfectly integrated, conditionally integrated, not integrated but tending

ABSTRACT This paper develops a simple model of spatial sorting where the least productive entrepreneurs are drawn to the large core region. This is an unusual feature. The literature on spatial sorting typically shows how the most productive individuals and firms agglomerate to the core. However, our model is consistent with empirical evidence that reveals that large agglomerations also attract the

ABSTRACT This paper studies productivity spillovers from colleagues and co-authors simultaneously in computer science accounting for both quantity and quality of peers. For the identification of colleague spillovers, we model colleagues’ mobility behaviours and use the estimated staying colleagues to instrument for the actual colleagues. For the identification of co-author spillovers, we exploit the

ABSTRACT The economy can be conceived as a complex system characterized by interconnected multilayer structures with a spatial dimension. At each layer, different types of decisions or interactions take place involving international or interregional trading partners at the macro-level; institutions, markets and industries at the meso-level; and individual firms and households at the micro-level. Within

ABSTRACT We exploit temporal and spatial correlation in a cross-border merger and acquisition (M&A) database with worldwide coverage to show that firms’ M&A choices are significantly influenced by experience effects related to knowledge accumulation. Our empirical strategy rests on the assumption that experience effects are expected to be at play in M&A directed toward culturally contiguous countries

ABSTRACT This paper investigates the extent and determinants of business cycle synchronization among the US states during the period 2002–11. Phase synchronization is not measured based on one national reference series, but rather is assessed using pairwise synchronization indicators computed over the business cycles of all US state pairs. The analysis is based on a natural and intuitive measure of

(2020). RSA Awards Notice. Spatial Economic Analysis: Vol. 15, No. 4, pp. 505-505.

ABSTRACT Recent empirical findings highlight how economic geography is important in understanding various political outcomes. However, these results are typically based on single elections or referendums. This article overcomes the weaknesses of such data by identifying and analysing the long-term structure and evolution of fundamental political ideologies in Switzerland. The results assess the existence

ABSTRACT We analyse business performance by using a unique data set of the universe of Italian local business units. We investigate the pattern of both productivity and profitability by adopting a decomposition technique to document spatial variation across urban and non-urban areas. Aggregate evidence indicates that an urban–non-urban productivity divide exists, but this premium vanishes with respect

ABSTRACT This paper explores the use of simulations in policy decision-making in the Brazilian State of São Paulo in fighting the COVID-19 pandemic. We propose a methodology for assessing the daily economic costs of control strategies for mitigating the effects of coronavirus. The method is based on the partial hypothetical extraction approach to input–output systems. Simulated daily scenarios based

ABSTRACT Using a spatial general equilibrium model, this paper investigates the resilience of European Union regions under three alternative recessionary shocks, each activating different economic adjustments and mechanisms. We measure the vulnerability, resistance and recoverability of regions and identify key regional features affecting the ability of regions to withstand and recover from unexpected

ABSTRACT The study explores the geographical pattern of the accommodation industry in the Italian insular region of Sicily, focusing on the determinants of the risk of market exit. We adopt a standard framework of business survival analysis where agglomeration economies play an important role. We then extend the analysis by considering the role of geography to explore whether the risk of market exit

ABSTRACT We present an extension of the generalized RAS (GRAS) technique to a multi-regional (MR) or multi-national setting. The framework is applicable to updating/regionalizing/balancing any partitioned matrix that needs to conform to new row sums, column sums and additional non-overlapping aggregation constraints. The technique, which we refer to as MR-GRAS, also handles non-exhaustive constraints

ABSTRACT In an election, the vote shares by party for a given subdivision of a territory form a compositional vector (positive components adding up to 1). Conventional multiple linear regression models are not adapted to explain this composition due to the constraint on the sum of the components and the potential spatial autocorrelation across territorial units. We develop a simultaneous spatial autoregressive

ABSTRACT To understand the links between Big Data and economic development is to focus on the knowledge that may be created from Big Data and the knowledge workers who can produce and use this knowledge to maximum economic impact. Using location quotients, this paper finds that the current geographical concentration of employees with skills to generate value from Big Data means that economic opportunities

ABSTRACT The neighborhood inequality (NI) index measures aspects of spatial inequality in the distribution of incomes within a city. It is a population average of the normalized income gap between each individual’s income (observed at a given location in the city) and the incomes of the neighbours located within a certain distance range. The approach overcomes the modifiable areal units problem affecting

ABSTRACT This paper reflects on regional perspectives in a post-growth world, taking the case of population loss as an example. Building on existing knowledge and illustrating with descriptive examples, three aspects of population loss that bear further study are highlighted: its ubiquity, dynamism and geography. The paper closes by emphasizing the importance of researching, thinking about and engaging

ABSTRACT The objective in this special issue is twofold. First, it emphasizes the importance of comprehending that, the global impacts of climate change notwithstanding, there are salient region-specific impacts that vary across space. Second, given this observation, it is shown how rigorous modelling of the connections between climate change and (1) land-use changes, (2) forestry, (3) infrastructure

ABSTRACT This paper characterizes the value of biodiversity and ecosystem resilience by formalizing a stochastic dynamic bioeconomic model of pollinator diversity under climate changes, with an application to oil rapeseed production in the Stockholm region of Sweden. It studies the optimal provision of semi-natural habitat for two different pollinator bee species: bumble bees and solitary wild bees

ABSTRACT In economic development there are often regions that share similar socioeconomic characteristics, and econometrics models on such regions tend to produce similar covariate effect estimates. This paper proposes a Bayesian clustered regression for spatially dependent data in order to detect clusters in covariate effects. The proposed method is based on the Dirichlet process, which provides a

ABSTRACT This paper analyses the empirical functioning of the regional labour market in Italy (21 Italian regions over the period 1995–2015). Starting from centralized union bargaining, it derives a micro-founded theoretical long-run relationship between the nominal wage per worker and average labour productivity. The long-run equation is then empirically verified using cointegration analysis, controlling

ABSTRACT Global Positioning System (GPS) devices afford the opportunity to collect accurate data on unit movements from temporal and spatial perspectives. With a special focus on GPS technology in travel surveys, this paper proposes: (1) two algorithms for the pre-processing of GPS data in order to deal with outlier identification and missing data imputation; (2) a clustering approach to recover the

ABSTRACT This paper assesses the diaspora effects of the Italian mass emigration of the late 19th-early 20th centuries on exports of Italian regions in the 2000s. We find statistically significant elasticities of exports to overseas economies on average higher than those estimated for European countries. The variability of the results across categories of exports provides indirect evidence on the presence

ABSTRACT When a regression analysis is performed on a variable that exhibits some form of spatial dependence, Gauss–Markov assumptions about the exogeneity of regressors and independence amongst error terms may be violated. If this is the case and no information is available about the location of units, point estimators and standard error estimators are typically heavily biased. The paper proposes

ABSTRACT This paper investigates the role of spatial dependence, spatial heterogeneity and spatial scale in principal component analysis for geographically distributed data. It considers spatial heterogeneity by adopting geographically weighted principal component analysis at a fine spatial resolution. Moreover, it focuses on dependence by introducing a novel approach based on spatial filtering. These

ABSTRACT The relationship between land values, climate and landscape diversity is investigated for a region of the Mediterranean where climate impacts are expected to be particularly severe. The Ricardian approach is applied, and spatial correlation and endogenous selection of farm type are accounted for. The analysis is at the farm level, and it is completely geocoded. It is found that farmland value

ABSTRACT This editorial summarizes the papers published in issue 15(2) so as to raise the bar in applied spatial economic research and highlight new trends. The first paper combines a conditionally autoregressive process from the spatial statistics literature with a spatial Durbin error model from the spatial econometrics literature. The second paper feeds a multistage and multilevel data envelopment

ABSTRACT A main channel through which climate change is expected to affect the economy is the agricultural sector. Large spatial variability in these impacts and high levels of uncertainty in climate change projections create methodological challenges for assessing the consequences this sector could face. Crop emulators based on econometric fixed-effects models that can closely reproduce biophysical

ABSTRACT This paper studies the effect of income transfers on the distribution of economic activity through a modified FE model. The model incorporates some key features of the Dutch disease literature: sectorial mobility and non-tradable goods. If foreign competition is high (high trade openness), transfers could cause a Dutch disease in the short and long runs. For intermediate levels of foreign

ABSTRACT Spatial general equilibrium (SGE) theory and macroeconomic theory have developed in isolation. This paper explores some implications of SGE theory for the aggregate supply of GDP in terms of spatial differences in total factor productivity (TFP) and amenities. We show, inter alia, that if internal labor mobility is imperfect, local productivity shocks may adversely affect GDP if they occur