Spatial econometrics

Marketing has historically been entangled with the study of geography, which has become a very popular focus in the marketing literature nowadays. However, spatially-oriented perspectives in marketing tend to rest on a conceptual divide between place-oriented and space-oriented thinking, thus inhibiting the production of more eclectic and creative spatial knowledge. This conceptual paper endeavours to overcome this dichotomy by rethinking spatiality in terms of boundedness, openness, functionality and expressivity. Marketing science models typically assume that responses of one entity (firm or consumer) are unrelated to responses of other entities. In contrast, models constructed using tools from spatial statistics allow for cross-sectional and longitudinal correlations among responses to be explicitly modelled by locating entities on some type of map. By generalizing the notion of a map to include demographic and psychometric representations, spatial models can capture a variety of effects (spatial lags, spatial autocorrelation, and spatial drift) that impact firm or consumer decision behaviour. Research Objective: The paper presents discussion on marketing science applications of spatial models and important research opportunities for future industry 6.0.

The existence of high correlations between two or more exogenous variables in regression can lead to a serious multicolinearity problem. Multicollinearity influences the ordinary least squares estimator in producing inefficient estimates. Based on the aforementioned, application of ridge regression to obtain ridge parameter that will produce efficient estimates in the presence of multicollinearity becomes necessary. Several authors have studied modalities of setting ridge parameters that will give best estimates of the model parameters. This research work examined the ridge parameter estimation techniques of Alkhamisi ridge estimator, which has already been examined in different forms and in various types by some authors. However, the concept of various kinds of ridge estimators was introduced into the classification of Alkhamisi ridge parameter; this now resulted in proposing 228 new ridge parameters. The existing and proposed ridge estimators (228) were compared through Monte Carlo simulation experiment 1000 times on a linear regression model with three (3) exogenous variables

The existence of high correlations between two or more exogenous variables in regression can lead to a serious multicolinearity problem. Multicollinearity influences the ordinary least squares estimator in producing inefficient estimates. Based on the aforementioned, application of ridge regression to obtain ridge parameter that will produce efficient estimates in the presence of multicollinearity becomes necessary. Several authors have studied modalities of setting ridge parameters that will give best estimates of the model parameters. This research work examined the ridge parameter estimation techniques of Alkhamisi ridge estimator, which has already been examined in different forms and in various types by some authors. However, the concept of various kinds of ridge estimators was introduced into the classification of Alkhamisi ridge parameter; this now resulted in proposing 228 new ridge parameters. The existing and proposed ridge estimators (228) were compared through Monte Carlo simulation experiment 1000 times on a linear regression model with three (3) exogenous variables

This paper investigates the presence of sigma and beta convergence between the Polish subregions over 1995–2006. We verify for the absolute convergence, as well as for the convergence conditioned on the stock of physical capital, human capital and the size of the central city, these being emphasised in the literature as important factors of regional growth. We also test for the presence of spatial effects in the determination of regional growth rates. In line with research from other countries, we observe a sigma divergence and unconditional beta divergence rather than convergence of income across Polish subregions. Conditional convergence is observed only between the regions around cities of similar size. Large agglomerations in particular increase their economic advantage over peripheral regions during dynamic growth periods in the Polish economy, while during periods of economic slowdown the human capital stock proves significant in determining regional growth.

plus other regional and macroeconomic Thomas M. Fullerton, Jr. variables. Predictive accuracy is analyzed using in-sample model simulations. Results Finance, indicate that narrowing yield spreads, real peso appreciation, and oil price declines are

Forest land use is often associated with the protection of water resources from contamination and the reduced cost of drinking water supply. This study attempted to measure the value of the forest on the quality of water resources from a contingent market, namely drinking water supply, by estimating variations in drinking water costs as a function of variations in land uses. Spatial correlations were taken into account because of the use of different geographical scales (i.e., water service area and land uses) and the potential existence of organizational and technological spillovers between water services. We found a significant negative effect of forest land use on water costs. We found no evidence of spatial spillovers concerning the management regime but did find that organizational choices (i.e., grouping of municipalities within a water service) and factors related to the scarcity of resources in neighboring water services have an impact on water costs.

The vast relevance of applications of spatial regression models has recently captured the interest of Economics and Agriculture, in the sense of better understanding the spatial behavior of the region under study, in the different forms of approaches. It is interesting to understand why some regions show greater variability than others, and why some forms of regional development are better explained. It is up to the researcher to understand, explore, and organize a series of observations, so that it is possible to make predictions, diagnoses, and recommendations to public policy managers and regional development agents. The municipalities' Gross Domestic Product (Gdp) has driven studies involving spatial information. The objective of this study was to analyze the Gdp of the municipalities in Paraná-Brazil, in 2018, regarding soybean yield, corn yield, pig production, and the tax on the circulation of goods, through different approaches of spatial regression models. SAR and CAR models are global models, while the GWR model is considered a local one. Three spatial analysis models were used to perform this study: Spatial Autoregressive (SAR), Conditional Autoregressive (CAR), and Geographically Weighted Regression (GWR). The results were compared using the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Cross-Validation Criterion (CVC), and the descriptive graphic of residual diagnoses-Worm Plot. The best result obtained was for the GWR model, which best explained the GDP of the state of Paraná-Brazil in terms of its covariates.

This paper examines the main factors behind the regional location of foreign direct investment (FDI) in Spain, at both the aggregate and sectoral levels, over the 1996-2013 period. To do so, a panel spatial Durbin model, which allows to unveil patterns of substitution or complementarity in FDI across regions, is estimated. Our findings reveal that inward FDI in one region is complementary to that in neighboring regions, a conclusion that is consistent with a complex vertical FDI strategy. Besides, they tend to confirm the hypotheses that FDI exhibits some inertia and is attracted by regions with (a) large market size, (b) large surrounding-market potential, and (c) high levels of human capital and wages. However, the results cast some doubts on the role played by infrastructure, R&D and regional differences in taxes as key elements in attracting FDI.

En este trabajo se analiza el efecto del grado de urbanización sobre el nivel de pobreza. Nuestro modelo teórico sugiere una relación funcional en forma de U entre el nivel de urbanización y la pobreza. La urbanización contribuye a la reducción de la pobreza, pero a niveles mucho más altos, la urbanización conduce a aumento de la pobreza. Empíricamente, se estima el "nivel óptimo" de la urbanización mediante el uso de: (i) un enfoque de variables instrumentales utilizando el método generalizado de momentos, y (ii) un enfoque de análisis de panel dinámico.

This work is located among the surveys related to the rental market to estimate the impact of variables, which should be urban and natural using the methodology of hedonic prices in the formation of rental prices in the north and south of Recife. With a database of 269 observations provided by the largest real estate company in the in the region. Then, it is shown that the most suitable models for this research are really the spatial models, especially the rental price formation. Among the amenities chosen to compose the model, the positive impact of the distance to consumer, especially when referring to the useful area and furniture.

Whilst a great deal of e¤ort has been dedicated to identi…cation of agglomeration e¤ects on labour productivity, the measurement of spatial productivity spillovers is a question that has been addressed only occasionally along the New Economic Geography literature. We estimate agglomeration effects, nonetheless conditioned to the possible existence of spatial productivity spillovers across Spanish municipalities in year 2001. To this respect, we …nd that agglomeration e¤ects are in the same order of magnitude than those ✩ This paper was produced in the framework of MICRO-DYN (www.microdyn.eu), an international research project funded by the EU Sixth Framework Programme (www.cordis.lu) with socio-economic sciences and humanities (). This publication re ‡ects only the author's views, the European Community is not liable for any use that may be made of the information contained therein.

The foreign direct investment (FDI) strategy has imbued India’s once stagnant industrial sector with capital and job opportunity. However, as India’s GDP grows ever larger, there is a concern that the growth within the country is not evenly distributed and may in fact exacerbate current economic disparities. This paper seeks to look at potential avenues poorer states can take to attract FDI if they choose to as a method to stay competitive within the country. Our hypothesis is that measures such as power rating (as a proxy for infrastructure), literacy, and minimum wage would be highly significant related to inward FDI.

 Este trabalho tem como objetivo verificar a existência do efeito transbordamento de tecnologia do setor agropecuário entre os municípios da região Norte, bem como analisar os determinantes do valor de produção do setor em 2006. Para esse fim, foram utilizados métodos derivados da econometria espacial. Os resultados obtidos mostraram que no setor agropecuário da região Norte a variável mão-de-obra possui maior impacto sobre o valor de produção e que não existe transbordamento de tecnologia entre os municípios. Este pode ser explicado pela baixa densidade rodoviária na região e pela distância existente entre os estabelecimentos que não permitem a disseminação e compartilhamento de tecnologia. Contudo, verificou-se a existência de dependência espacial no termo de erro na agropecuária nortista.

This paper estimates water price elasticity and examines spatial patterns of urban water management variables in 70 localities of more than 2 500 inhabitants of the six northern border Mexican states. By using ordinary least squares, spatial econometrics, Lagrange Multipliers, and exploratory spatial data analysis techniques, four variables were analyzed: water price (P), a Non-revenue water index (NRWI), total urban water connections, and water billed volume (BV). In accordance with the literature, we found that water demand is price sensitive but inelastic. Then price as an instrument for controlling water consumption does not offer an efficient alternative for reducing it, as water price increases would have to rise very high to reflect changes in consumption habits. Instead, it could be just a revenue-raising tool. Our findings also confirm a significant spatial autocorrelation in P and the NRWI. More interestingly, we found robust spatial effects on BV. This result implies that the performance of urban water utilities is determined by its counterparts' performance in the region. Given the results and characteristics of water resources in the region, we argue that management policies must consider a regional approach to be effective.

This paper estimates water price elasticity and examines spatial patterns of urban water management variables in 70 localities of more than 2 500 inhabitants of the six northern border Mexican states. By using ordinary least squares, spatial econometrics, Lagrange Multipliers, and exploratory spatial data analysis techniques, four variables were analyzed: water price (P), a Non-revenue water index (NRWI), total urban water connections, and water billed volume (BV). In accordance with the literature, we found that water demand is price sensitive but inelastic. Then price as an instrument for controlling water consumption does not offer an efficient alternative for reducing it, as water price increases would have to rise very high to reflect changes in consumption habits. Instead, it could be just a revenue-raising tool. Our findings also confirm a significant spatial autocorrelation in P and the NRWI. More interestingly, we found robust spatial effects on BV. This result implies that...

Indonesia adopted a strategic long-term development plan targeting to achieve a green and everlasting Indonesia through implementing various environmental policies. One of the mandatory matters for governments is to continue environmental control by constructing Environmental Quality Indexes (EQI). This study focuses on the relationship between regional output or real Regional GDP, level of population density, and the government expenditure on environment quality on EQI in 34 provinces in Indonesia by the time period 2015 to 2019 using a spatial panel data approach. Within the context of spatial modeling, the interaction between provinces depends on their geographical location and condition. Using the geographic information system (GIS) and stata attributes, the coordinates and distances can be mapped and then defined for observation units in space via the spatial weight matrix used. From the perspective of spatial geography, this paper verifies the spatial dependence of Indonesia's Environmental Quality Index (EQI). Pesaran's CD test indicates the spatial effect on the model and SAR with random effect can be considered a better-fitting spatial panel regression model. The results of the econometric spatial panel using SAR panel with random effect analysis show that Indonesia's EQI in the provinces was dependent on the spatial. It was also found that regional GDP has a significant and negative effect on EQI and population density has a negative and significant effect on EQI. While fiscal policy on the environmental area on improving environmental quality did not pass a significance test. Thus, it is recommended to look for ways to promote green growth in the country.

Indonesia adopted a strategic long-term development plan (2005-2025) targeting to achieve a green and everlasting Indonesia through implementing various environmental policies. One of the mandatory matters for governments is to continue environmental control by constructing Environmental Quality Indexes (EQI). This study focuses on the relationship between regional output or real Regional GDP, level of population density, and the government expenditure on environment quality on EQI in 34 provinces in Indonesia by the time period 2015 to 2019 using a spatial panel data approach. Within the context of spatial modeling, the interaction between provinces depends on their geographical location and condition. Using the geographic information system (GIS) and stata attributes, the coordinates and distances can be mapped and then defined for observation units in space via the spatial weight matrix used. From the perspective of spatial geography, this paper verifies the spatial dependence of...

This paper employs individual firm data in order to check the existence of industryspatial effects alongside other microeconomic determinants of R&D investment. Spatial proximity is defined by a measure of firms' industry distance based on trade intensity between sectors. The spatial model specified here refers to the combined spatial autoregressive model with autoregressive disturbances (SARAR). In modelling the outcome for each location as dependent on a weighted average of the outcomes of other locations, outcomes are determined simultaneously. The results of the spatial two stage least square estimation suggest that in their R&D decision firms benefit from spillovers originating from neighbouring industries.

This work investigates the determinants of health care expenditures, such as drug prescriptions, inpatient care, and outpatient care, of the resident population of the Region of Friuli Venezia Giulia (Italy). The phenomenon of interest is examined here by considering a cross-sectional register-based dataset on individual expenditures exhibiting a cross-classified hierarchical structure. In fact, patients (about 1,000,000) are grouped by general practitioners and municipalities. Does the evidence in individual data analyses support the results of the micro and macroeconomic literature? The adoption of disaggregated data allows us to disentangle the role of the micro and macroeconomic determinants of the expenditures. Moreover, the degree of interdependence between neighbouring municipalities is measured by accounting for the spatial correlation in the error convolution. A feasible two-stage Heckit method has to be adapted to encompass the zero inflation issue, to consider the hierarchical structure of data and to study the spatial di↵usion process of the expenditures in the sample selection model framework. The main results on the determinants of health care expenditures at the macro-level are confirmed in our analysis on disaggregated data. On the contrary, however, the substitution e↵ect, which is typically observed in aggregated data, has not been confirmed by the present research. Moreover, the selection process appears to be relevant in drug prescriptions and outpatient care expenditures Luca Grassetti (orcid.org/0000-0003-1997-8001) and Laura Rizzi (orcid.

Bu çalışmanın amacı Türkiye'deki sağlık harcamalarının turizm gelirleri ve BIST Sağlık Endeksinde yer alan şirketlerin hisse değerleri üzerine etkisini araştırmaktır. Bu amaçla çalışmada BIST'te faaliyet gösteren dört sağlık şirketinin sağlık harcamaları, hisse fiyatları ile ülke turizm gelirlerinin Nisan 2011-Temmuz 2021 dönemi aylık verileri ARDL eşbütünleşme yöntemiyle analiz edilmiştir. Analiz sonucunda; eşbütünleşme testi ile her iki modelde de değişkenler arasında eşbütünleşik ilişki olduğu sonucu ortaya çıkmıştır. Ayrıca uzun ve kısa dönemli katsayı tahminci sonuçlarına göre sağlık harcamaları hacmindeki genişlemenin sektördeki firmaların hisse değerlerine olumlu katkı sağladığı, sağlık harcamaları değişkenindeki artışın turizm gelirleri üzerinde azaltıcı bir etkiye neden olduğu görülmektedir.

This paper analyzes the dynamics of economic convergence in ECOWAS countries over the period 1991-2019. The methodological approach is based on fixed-effects panel model including a lagged endogenous variable. The results support an absolute beta-convergence process. Spatial interaction term is also significant, showing that countries tend to cluster spatially according to their economic performance. These results suggest that geographical proximity should be considered as an asset for promoting the enlargement of national markets through the mobility of production factors and the reduction of growth disparities.

This paper investigates factors that determine the average income growth and net migration rates in Swedish municipalities during the period 1981 to 1999. The main issue is to test the hypothesis that, conditional on a set of other possible determinants of regional growth, the growth rate in one municipality is a¤ected by the growth rates in its neighboring municipalities. We also test the hypothesis of conditional convergence, that is, the hypothesis that initially 'poorer' regions tend to grow faster than initially 'richer' regions conditional on the other explanatory variables in the model. We …nd a positive correlation between net migration rates in neighboring municipalities, which suggests that net migration tend to 'spill over' to neighboring municipalities. When it comes to average income growth, our results indicate spatial dependence in the error terms during the 1980's. Such dependence is important in the sense that it indicates that shocks into the system not only a¤ect the municipality where the shock has its origin but spread across the country. In addition, and in contrast to previous empirical …ndings based on Swedish data, we do not …nd any clear evidence in favour of the hypothesis of conditional convergence. Instead, our results predict conditional divergence between municipalities located in the Stockholm region throughout the period and also for municipalities outside the Stockholm region during the 1990's. K e y w or ds : Sp a tial e¤ ec ts, c on d ition al c on ve rge n ce , reg ion al grow th , n e t m i gratio n .

This paper explores the potential of using the Moran's I statistic to detect complementary bidding on public contracts. The test is applied to data concerning the so-called Swedish asphalt cartel, which was discovered in 2001. Using information on submitted bids and procurement characteristics for both the cartel period (1995)(1996)(1997)(1998)(1999)(2000)(2001) and the post-cartel period (2003)(2004)(2005)(2006)(2007)(2008)(2009), the Moran's I correctly predicts complementary bidding behavior for linear and quadratic specifications when such behavior is likely to exist, and rejects such behavior when it's unlikely to be present. Remarkably, the Moran's I also correctly indicates and rejects complementary bidding on the basis of information on the separate bids alone.

This paper measures the accuracy of using regional cycles to identify national business cycle turning points in the U.S. with the Markov Switching Panel (MSP) model. Based on the MSP model, it is determined that regional cycles are highly capable of identifying national business cycle turning points in the U.S., but the duration of recessions of regional cycles are longer than those of national business cycles.

This study explores the effect of province-specific temperature and precipitation, which are expressed as deviancies of temperature and precipitation from historical data using the spatial Mankiw, Romer, and Weil (MRW) growth model. Performing a panel data set of 34 provinces covering the period from 2006 to 2022, this study predicts the nonlinear impact of climate change on per capita real output growth. We also show the inverted U-shaped curve from persistent changes in the temperature and precipitation on per capita real output growth either above or below its historical data. In the absenteeism of mitigation strategies, we found that an insistent increase in the average temperature or precipitation per year diminishes per capita real output growth. This study also explores climate change's spatial impacts on economic growth performance through spatial lambda and rho parameters. We discovered the significant provincial spillover effect of climate change on economic growth. We also identify that increasing temperature and precipitation in provincial neighbors further decreased economic growth. Furthermore, this study conducts a robustness test by employing an open economy to meet the consistency of the baseline model. We reconfirm the empirical results of the baseline model.

Specification of a model is one of the most fundamental problems in econometrics. In practice, specification tests are generally carried out in a piecemeal fashion, for example, testing the presence of one-effect at a time ignoring the potential presence of other forms of misspecification. Many of the suggested tests in the literature require estimation of complex models and even then those tests cannot account for multiple forms of departures from the model under the null hypothesis. Using Bera and Yoon (Econom Theory 9(04):649-658, 1993) general test principle and a spatial panel model framework, we first propose an overall test for ''all'' possible misspecification. Then, we derive adjusted Rao's score tests for random effect, serial correlation, spatial lag and spatial error, which can identify the definite cause(s) of rejection of the basic model and thus aiding in the steps for model revision. For empirical researchers, our suggested procedures provide simple strategies for model specification search employing only the ordinary least squares residuals from a standard linear panel regression. Through an extensive simulation study, we evaluate the finite sample performance of our suggested tests and some of the existing procedures. We find that our proposed tests have good finite sample properties both in terms of size and power. Finally, to illustrate the usefulness of our procedures, we provide an empirical application of our test strategy in the context of the convergence theory of incomes of different economies, which is a widely studied empirical problem in macro-economic growth theory. Our empirical illustration reveals the problems in using and interpreting unadjusted tests, and demonstrates how these problems are rectified in using our proposed adjusted tests.

Methodological and empirical literature offers several possibilities how to model migration flows. The main goal of this paper is to compare two different specifications of spatial econometric models of migration flows (spatial error model and first-order spatial autoregressive model) employing three different ways of handling the intraregional flows (setting them to zero; eliminating them; adding a separate intercept term for these observations as well as a set of explanatory variables). Our empirical analysis is based on internal migration flows among the Slovak districts (territorial level LAU-1) using 2009-2013 data. The results suggest that different models offer similar estimates, however few differences can be observed.

This study explores disparity in regional development in Russia and in Canada and role of geography in their development. In the first chapter analysis of the role of geographic, economic, and institutional factors in economic growth over 1996-2004 is presented. Additionally the issue of the interregional spatial interaction is analyzed, which is studied in the framework of the new economic geography. The second chapter devoted to the development of Canadian provinces and analyzes factors of provincial differences along with factors of migration in Canada over the period of 1991-2001.

This analysis focuses on studying whether four significant trends in Latin America may be important determinants of FDI. The trends explored are: increased financial liberalization, improvements in the quality of institutions, shifts towards leftist governments, and increased dependence on exports of natural resources. To test whether these trends can be considered as significant incentives or deterrents to FDI in the Latin American region, this empirical analysis uses a baseline model that includes a set of control variables identified in previous empirical analyses as important determinants of FDI in a panel framework. This study also addresses for endogeneity and incorporates spatial econometric techniques to account for the possibility that FDI inflows in one country may be dependent on the FDI inflows of nearby countries. The main robust findings are that financial liberalization, mineral exports and leftist politics have a significant effect on net FDI. While financial liberalization and mineral exports can be considered as incentives to FDI, the movement towards the left is a deterrent.

Tax competition and spillover models offer ambiguous predictions concerning the economic impact of tax havens on non-tax havens. The implications of tax havens for less developed countries (LDCs), in particular, are not well understood and are little studied. This paper investigates the impact of tax havens on non-tax haven countries in terms of foreign direct investment (FDI). We investigate the importance of agglomeration effects by accounting for the level of FDI inflows as well as the role of geography by measuring proximity to the nearest tax haven. Our analysis yields several interesting findings. First, using panel data for 142 countries, we find evidence of positive spillovers from tax havens to nearby LDCs, but not to nearby developed countries. Second, restricting our panel to LDCs, we find the positive effect of tax haven FDI on LDCs to be robust. Third, we find that geographic distance matters for financial flows: LDCs which are the closest to a nearby tax haven benefit the most in terms of FDI inflows. This result is robust to including a lag of the dependent variable and accounting for spatial interdependence of FDI. We conclude that tax haven activity has beneficial implications for FDI inflows of nearby LDCs.

This analysis considers whether spatial interdependence is an important determinant of foreign direct investment (FDI) in Latin America. Two types of spatial interdependence are explored: 1) surrounding market potential and 2) spatial autocorrelation of FDI. Using a sample of 17 Latin American countries, with observations from 1986 to 2006, we find that spatial interdependence matters for world net FDI in the region. Surrounding market potential has a positive effect on FDI of significant magnitude, but there is no evidence that FDI is spatially autocorrelated. Other contributors to FDI in this analysis include governance, specifically control of corruption, and exports of raw materials. We find differences in contributors to American FDI in the region. When considering only American FDI, we find that FDI is spatially autocorrelated, and that surrounding market potential is not significant when the spatially lagged dependent variable is included in the model.

El texto que se presenta representa un esfuerzo empírico de aplicación de Técnicas de Análisis Regional para los municipios del estado de Quintana Roo con la variable Producto Interno Bruto. El periodo de análisis que se eligió fue 2003-2008, la razón de ello es que sólo hay datos disponibles y actualizados de PIB por municipio para dicho periodo. El análisis se realizó con el software TAREA de ILPES-CEPAL. Los resultados constituyen un importante aporte para los especialistas en planeación del desarrollo regional.

his study explores the spatial distribution of manufacturing in Colombia through the lenses of Marshallian and New Economic Geography theories on industrial localisation. Employing spatial econometric methods with geo-referenced data reveals that industrial presence at the municipal level is positively impacted by the service sector connections and population density. Additionally, a panel data analysis suggests that traditional manufacturing hubs benefit from unobservable fixed effects, enhancing the persistence of initial locational advantages. These findings underscore the ongoing spatial concentration of manufacturing, influenced by both historical industrial activities and contemporary urban factors.

Transportation infrastructure plays an important role in regional economic development both in the stimulation of growth and as a response to output expansion. However, measuring these effects quantitatively has been a challenge due to the complicated impact mechanisms of transportation infrastructure. This complication is due to two reasons: first, regional impacts of transportation infrastructure are achieved through a mechanism that involves both a demand influence through the variation of transportation price and a supply influence implemented through the variation of transportation cost; second, impacts of transportation are usually evaluated in a regional context where the presence of unobserved local or regional variables may give rise to spatial autocorrelation. As a result, impact analysis may become biased and spurious. This study develops a new method called Spatial Econometric Computable General Equilibrium (SECGE) model, which integrates both spatial econometrics with equilibrium modeling techniques to improve the effectiveness of impact analysis on transportation infrastructure. This study differs from previous studies in the following three aspects: First, through a spatial autocorrelation test, the presence of spatial dependence is observed and confirmed among the elasticities of factor substitution in the US. To deal with spatial dependence, spatial panel econometric techniques are introduced to estimate the elasticity of factor substitution of different sectors for the Constant Elasticity of Substitution (CES) production function with consideration of spatial direct and indirect effects. and traditional OLS estimates. Although the differences are relatively small in this aggregate case study, implications for more sensitive disaggregated regional models are clear.

This study investigates the ex post impact of the Beijing-Shanghai high speed rail (BJHSR) on housing values. A dataset including 1016 housing communities from the 22 cities along the BJHSR line are analyzed in the tradition of the hedonic pricing model using three estimation procedures: a robust ordinary-least square regression, a Box-Cox transformation technique and a spatial econometric model. After controlling for physical characteristics of housing property, neighboring environment and locational accessibility, the study finds that the establishment of the BJHSR service has a considerable regional impact (including local effects and spillover effects) on housing values in medium and small cities but a negligible impact in larger capital cities. This may be the results of the competitive nature of housing market in Chinese capital cities.

The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein.

Este trabajo pretende investigar como se comporta un modelo de crecimiento del empleo en un territorio geograficamente cerrado considerando tanto su vertiente espacial, y el efecto de rebosamiento espacial de la variable endogena de empleo, como su vertiente temporal considerando el comportamiento de las variables empleo y recursos en diferentes ejercicios economicos sucesivos. Esto ultimo permite incorporar el efecto de relacion temporal entre las variables permitiendo derivar otros indicadores temporales que segun el modelo faciliten una explicacion del comportamiento del empleo en el tiempo. Para evaluar el modelo se ha tomado como piloto una subcomarca de acentuado caracter rural de Palencia, y se ha utilizado la modelacion SUR Espacial.

When same authorities belonging to a same level of government derive their receipts from a mobile tax base, a competition mechanism takes place among them that triggers externalities. Likewise, when di¤erent layers of decision-makers exert their taxing power upon a common base, the choices made by one tier a¤ect the receipts that the other governments can collect. Generally speaking, the decisions made by one government a¤ect the tax revenue that can be collected by the decisionmakers belonging to the same tier of government or by stacked jurisdictions : externalities arise, the existence and the magnitude of which are closely related to the nature of the tax, to the mobility of the base and to the distribution of tax competence among decisionmakers. This paper proposes a model where both horizontal and vertical interactions take place. Uncertainty concerning the base, that is, the amount of capital likely to be invested, is introduced and a generalization of taxation schemes is provided in order to assess the robustness of traditional analyses results in a more general and realistic scheme. The analysis shows that horizontal and vertical externalities point towards opposite directions : while horizontal competition leads to ine¢ ciently low rates, the common pool problem arising from the stacking of decisionmakers taxing a same base gives rise to a phenomenon of over-taxation. The paper aims at …nding out whether the combination of both externalities yields higher or lower global tax rates than the one that would emerge in a unique government case. It turns that an excessively high level of taxation emerges. Nevertheless, the vertical tax externality is lessened with respect to the vertical competition case : the global tax rate sets at an intermediary level so that the outcome is brought closer to the social optimum issue.

The modifiable areal unit problem refers to the modifications of any statistical analysis when changing the scale of observation (e.g. from region to countries) or the aggregation criterion (e.g. different partitions of one country at a given scale). In a previous work (Arbia in Spatial data configuration in the statistical analysis of regional economics and related problems, Kluwer, Dordrecht 1989), we analyzed the effects of the modifiable areal unit problem on statistical analysis without referring to any specific random field. The quoted work concentrated on the modification of the first and second order properties of a random field. In this paper we reanalyse the same problem by looking specifically at the effects of MAUP on linear spatial econometric models looking in particular at the SARAR (1,1) model. A previous version of this paper was presented at the North American Meetings of the Regional Science Association International (RSAI) sponsored by the North American Regional Science Association (NARSC), Denver, November 10-13, 2010. We wish to thank all participants for the comments received in that occasion.

The standard approaches used in the empirical literature to test economic convergence-divergence between countries and regions are all grounded on the Mankiw-Romer-Weil and Barro-Sala-i-Martin contributions that led to the celebrated b-convergence model. Such a model, however, presents strong limitations related to the fact that it compares two situations in two different moments of time rather than monitoring the entire time path of the regional GDP. This is a major drawback because very different situations may lead to the same results in terms of the speed of convergence and this may cause problems in interpreting the results and in using them when programming regional politics and when targeting spatial re-equilibrating resources. This paper reviews some of the approaches proposed in the literature that seek to overcome this obstacle and aim to capture the full dynamics of the economic convergence process. Four approaches are reviewed. The first is based on the theory of space-t...

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

In the present article we propose a spatial micro econometric approach for studying the geographical concentration of economic activities. We analyse the incentives to use this approach rather than the traditional one based on regional aggregates. As an example, we present our prototypical theoretic model -to be seen as a continuous space version of Krugman's concentration model -that includes birth, survival and growth components. We present a numerical estimation of the birth model for a set of data referring to the concentration of the manufacturing industries in the San Marino Republic.

In this paper we aim at identifying stylized facts in order to suggest adequate models of spatial co-agglomeration of industries. We describe a class of spatial statistical methods to be used in the empirical analysis of spatial clusters. Compared to previous contributions using point pattern methods, the main innovation of the present paper is to consider clustering for bivariate (rather than univariate) distributions, which allows uncovering co-agglomeration and repulsion phenomena between the different industrial sectors. Furthermore we present the results of an empirical application of such methods to a set of European Patent Office (EPO) data and we produce a series of empirical evidences referred to the the pair-wise intra-sectoral spatial distribution of patents in Italy in the nineties. In this analysis we are able to identify some distinctive joint patterns of location between patents of different sectors and to propose some possible economic interpretations.

The present issue of Economic Modelling features a selection of papers presented at the 3rd World Conference of the Spatial Econometrics Association, held on July 9-10, 2009 at the Faculty of Economics and Business, University of Barcelona. The purpose of this meeting was to provide a forum where economists, econometricians, geographers, and regional scientists could discuss the development of theoretical tools and sound applications of the discipline of spatial econometrics. Henry Overman, from the London School of Economics, and James LeSage, from Texas State University, gave the plenary speeches. The scientific contributions to the conference spanned a broad range of topics: ranging from applied to theoretical econometrics. This variety of papers offered an insight into the scope for innovative empirical research across different areas in the field spatial econometrics, including also spatial statistics and spatial data analysis. The meeting was attended by more than 100 participants from around the world. All of the papers selected for this special issue have gone through the usual process of peer review for Economic Modelling, and we would like to thank all of the referees for their hard work. The variety of the contributions both in terms of the methodological contribution and in terms of the substantive issues tackled provides a good snapshot of the current development of the discipline and of the future paths along which it will develop in future years. Contributions cover both the topic of static spatial econometrics based on synchronic data and that of dynamic modelling based on spatial panel data. This issue contains nine papers. Four of them refer to static spatial econometrics (namely those written by Arbia et al., Seya, et al., Smirnov and Egan and Yokoi and Ando) while the remaining 5 (namely those by Baltagi et al., Bartkowska and Riedl, Cotteleer and Van Kooten, Hall and Guo and Claeys et al.) conversely take an explicit panel data approach. In what follows we briefly summarize the content of the various contributions to this special issue. Most of the existing literature in spatial econometrics uses data at aggregate level. The paper by Arbia, Espa, Giuliani and Mazzitelli take a different approach and present a methodology based on micro data referring to single individual economic agents. Following such an approach they treat each firm as a point in the space and present a methodology to analyse the regularities in their arrangement using point pattern techniques. In particular they propose a nonparametric approach for the analysis of spatial heterogeneity, based on the so-called inhomogeneous K-function. They present an empirical application of the method to analyse the spatial distribution of 2654 high-tech manufacturing plants in Italy, for the year 2001. The authors assume the economic space to be non-homogenous, and take the pattern of inhomogeneity as an instrument to disentangle spatial heterogeneity from spatial dependence. Along similar lines, Baltagi, Blien and Wolf study individual data distributed in space and discuss the possibility of a dynamic 'wage curve'

This paper presents a comprehensive analysis of informal settlements in Tunja, Colombia, from 2010 to 2022. It examines the historical, social, and economic factors that contribute to these settlements, using various data sources, including development and territorial planning plans, the Agustín Codazzi Geographic Institute, and local government records. The study highlights significant inequalities in access to public services between urban and rural areas, exacerbated by environmental hazards from nearby mines, landfills, and sewage treatment plants. The research employs a descriptive and explanatory approach, detailing the historical context and theoretical frameworks related to agglomeration economics, territorial inequality, and urbanization processes. A historical-deductive method ensures logical consistency in the analysis of data from 2010 to 2022. The study also utilizes georeferencing techniques to present spatial data on service coverage and demographic characteristics, differentiating urban and rural disparities. Findings show that informal settlements in Tunja are predominantly located on the periphery of the city, with significant disparities in service coverage. While urban areas have over 90% coverage of basic services, rural areas lack adequate infrastructure, particularly sewage, gas, and internet services. The study identifies specific settlements, such as Runta and Pirgua, details their access to services and highlights environmental and structural issues.