Spatial econometrics

This paper tries to assess the possible existence of excess of capacity for the Spanish port infrastructures. In order to do this, we estimate a cost function system considering the existence of demand uncertainty of cargo and passengers for port authorities. We find that, in order to fulfil the regularity conditions of the cost function system, we have to specify both demands as uncertain. The results show the importance of passenger variability in terms of demand of variable inputs and the use of quasi-fixed input. We also demonstrate the excess of capacity from the calculation of the shadow price of the quasi-fixed input after controlling demand uncertainty. Finally, some factors as the size of the port authorities' hinterland, the relative specialization in containerised general cargo or passengers, the size of ports, the profitability rate or port regulation are considered as determinants of this excess of capacity.

While air pollution is widely recognized as a factor affecting the real estate market, gaps remain in understanding spatial dependencies, valuation biases, and heterogeneous effects of air pollution on housing markets. Traditional OLS models often overestimate its impact by ignoring spatial spillovers and endogeneity, while limited research explores how Two-Stage Least Squares (2SLS) improves marginal willingness to pay (MWTP) estimation. This study applies spatial econometric models (SLM, SEM) and 2SLS to assess air pollution's impact on housing prices in Thailand. The results confirm significant price reductions, with OLS overestimating the marginal implicit price (MIP) compared to spatial models. The average MIP per house is 39,838 THB ($1,138), varying across models, while the estimated Compensating Surplus (CS) averages 568,078 THB ($16,578) per household, reflecting the economic burden of air pollution. The Hausman test confirms endogeneity, while the Hansen J-Test validates instrumental variables (industrial facility density, rainfall). These findings highlight substantial economic losses from air pollution, emphasizing the need for spatially aware valuation techniques in real estate pricing and policymaking.

The paper introduces for the most frequently used three-dimensional panel data sets several random e ects model speci cations. It derives appropriate estimation methods for the balanced and unbalanced cases and deals with some extensions as well. An application is also presented where the bilateral trade of 20 EU countries is analysed for the period [2001][2002][2003][2004][2005][2006]. The di erences between the xed and random e ects speci cations are highlighted through this empirical exercise.

With the application of Robust Regression Method, this paper attempts to estimate the production function for manufacturing industries of Nepal. In this endeavour, the production function for Furniture and Pharmaceutical industries have been estimated using cross-section data of the Census of Manufacturing Establishment (CME) 2011/2012. The coefficients of log-linear form of Cobb-Douglas (C-D) production function reveal that the selected manufacturing industries are operating with decreasing returns to scales. The labour coefficients of both industries are found to be statistically insignificant. Negative labour coefficient of Pharmaceutical Industry indicates capital intensive nature of the production and minimal contribution of labour inputs. Although positive and significant, capital coefficients indicate both industries were running with decreasing returns to capital inputs. Total Factor Productivity (TFP) representing the state of technology and factors other than labour and capital found to be instrumental and significant for both the industries.

Aims: We evaluated the effects of the COVID-19 pandemic on hospital admission and quality of care for acute coronary syndrome.

Methods and results: Data for all patients admitted to hospital care for acute coronary syndromes in Slovenia (nationwide cohort) between 2014 and 2021 were obtained by merging the national hospital database, national medicines reimbursement database and population mortality registry using unique identifying numbers. Using interrupted time series analysis, we assessed the impact of the COVID-19 pandemic on hospital admission rates and quality of care (in-hospital and 30-day mortality, reperfusion and secondary preventive medication uptake). Data were fitted to segmented regression models with March 2020 as the breakpoint. Data on 21 001 patients were included (7057 ST-elevation myocardial infarction (STEMI), 7649 non-ST elevation myocardial infarction (NSTEMI) and 6295 unstable angina). Hospital admissions for STEMI remained stable (92 patients; +1 patient per month, p=0.783), whereas the pandemic was associated with a significant reduction in NSTEMI (81 patients; −21 patients per month, p=0.015) and unstable angina admissions (47 patients; −28 patients per month, p=0.025). In patients with STEMI, the pandemic did not affect reperfusion rates (0.29%, (95% CI) −1.5% to 2.1%, p=0.755) or in-hospital mortality (0.1%, (95% CI) −0.9% to 1.1%, p=0.815), but was associated with a significant negative trend for secondary preventive medication uptake (−0.12%, (95% CI) −0.23% to −0.01%, p=0.034).

Conclusion: In Slovenia, hospital admissions for STEMI remained stable throughout the COVID-19 pandemic, but NSTEMI and unstable angina admissions dropped significantly. While mortality and reperfusion rates were not affected, the pandemic was associated with a continual negative time trend for the uptake of secondary preventive medication.

Missing data problems are often best tackled by taking into consideration specificities of the data structure and data generating process. In this doctoral dissertation, I present a thorough study of two specific problems. The first problem is one of regression analysis with misaligned data; that is, when the geographic location of the dependent variable and that of some independent variable do not coincide. The misaligned independent variable is rainfall, and it can be successfully modeled as a Gaussian random field, which makes identification possible. In the second problem, the missing independent variable a categorical. In that case, I am able to train a machine learning algorithm which predicts the missing variable. A common theme throughout is the tension between efficiency and robustness. Both missing data problems studied herein arise from the merging of separate sources of data.Economic

We propose Sparse Boosting (the SparseL 2 Boost algorithm), a variant on boosting with the squared error loss. SparseL 2 Boost yields sparser solutions than the previously proposed L 2 Boosting by minimizing some penalized L 2 -loss functions, the FPE model selection criteria, through smallstep gradient descent. Although boosting may give already relatively sparse solutions, for example corresponding to the soft-thresholding estimator in orthogonal linear models, there is sometimes a desire for more sparseness to increase prediction accuracy and ability for better variable selection: such goals can be achieved with SparseL 2 Boost. We prove an equivalence of SparseL 2 Boost to Breiman's nonnegative garrote estimator for orthogonal linear models and demonstrate the generic nature of SparseL 2 Boost for nonparametric interaction modeling. For an automatic selection of the tuning parameter in SparseL 2 Boost we propose to employ the gMDL model selection criterion which can also be used for early stopping of L 2 Boosting. Consequently, we can select between SparseL 2 Boost and L 2 Boosting by comparing their gMDL scores.

Abstract: Fires in forest areas are considered an important threat to the Andean Region and the Amazon rainforest. In Colombia, fire is used to expand the agricultural frontier (including illicit crops) which results in deforestation. Given the importance of avoiding deforestation and to control coca expansion, this paper aims to: 1) understand the relationship between fires and deforestation, coca and deforestation and hence coca and fires; 2) examine the potential of using fire data from remote sensing and socio-economic variables to predict the occurrence of new coca fields in forest areas in Colombia. The analysis was undertaken over a ten year period (2000-2010) at a municipality level in two areas with high coca dynamics (Central Region and Putumayo – Caquetá) using Pearson correlation and three different models: a Linear Probability model, a Logit model and a Probit model. The results show that there is a positive relationship between fire and deforestation. Although in gener...

El propósito de este trabajo es analizar la relación entre convergencia tradicional y espacial del ingreso según la concentración regional de la producción agrícola de México, destacando los efectos propiciados por el cambio del modelo de desarrollo y gestión, mediante la liberalización y privatización de la economía con su incorporación al TLCAN y su comparación con el periodo 1970-2004. Se identifican y delimitan las regiones agrícolas a las que se aplica la medición econométrica de las hipótesis de convergencia tradicional, espacial y de la concentración económica. Los resultados confirman la tendencia a la disparidad del ingreso de esas regiones y el papel de la concentración económica como determinante de su comportamiento, asociado a la política de apertura de la economía mexicana.

Essa tese busca analisar as questoes espaciais de saude nos municipios brasileiros. Dessa forma, o artigo 1 investiga as evidencias de ciclos eleitorais e partidarios e interacao espacial nas despesas com saude e saneamento. O modelo de painel dinâmico espacial propiciou observar se ocorre o aumento das despesas com saude e saneamento nos anos de eleicao municipal e quais os partidos que mais gastam com saude e saneamento. Identificou que o padrao dessas despesas e influenciado pelo comportamento das despesas nos municipios vizinhos. Nota-se a presenca do efeito spillovers, pois os governantes reduzem suas despesas com saude e saneamento ao observarem que os vizinhos aumentam as despesas. O artigo 2 analisa as questoes espaciais da Estrategia Saude da Familia (ESF) capazes de influenciar a taxa de mortalidade infantil e de criancas de 1 a 4 anos nos municipios brasileiros entre 1998 e 2012. A estimacao se da por dados por painel espacial. Como resultado, observa-se a presenca dos ef...

Resumen: Comparamos dos de las estadísticas espaciales más robustas que reporta la literatura contemporánea para analizar patrones locacionales de firmas: las funciones K-plana y K-en red. Estas funciones generan valores que, en determinadas condiciones, permiten conocer la estructura espacial básica de la localización de las variables objeto de análisis, pudiéndose incorporar medidas de significancia estadística acerca de la aglomeración/dispersión/aleatoriedad locacional, tanto en espacios euclidianos como en ...

We compare two of the most robust spatial statistics reported in the contemporary literature to analyze locational patterns of firms: the K-planar and the K-network functions. These functions generate values that, under certain conditions, provide insights into the basic spatial structure of the location of the variables under analysis. Both functions are able to incorporate measures of statistical significance on the agglomeration/dispersion/randomness of locational patterns. The K-planar function does it in Euclidian spaces while ...

Resumen: Entre 1999 y 2007, el análisis de la brecha de género del voto en Argentina revela dinámicas complejas y regionalizadas. Si bien en el nivel nacional las diferencias de voto entre mujeres y hombres no son cuantitativamente significativas, emergen patrones específicos vinculados a contextos geográficos particulares. Las mujeres muestran una inclinación hacia fuerzas políticas moderadas con valores republicanos, como las representadas por la Alianza de De la Rúa en 1999 y las candidaturas de Elisa Carrió en 2003 y 2007, con un sesgo femenino notable en regiones como el área pampeana y la Región Metropolitana de Buenos Aires. Estos hallazgos evidencian la inexistencia de un patrón uniforme de la brecha de género y confirman la presencia de heterogeneidad espacial en algunas candidaturas. Esto sugiere que la brecha de género del voto responde a efectos contextuales de tipo geográfico, en parte vinculados al proceso de territorialización política. La incorporación de herramientas de análisis espacial local permite captar estas heterogeneidades y destaca la importancia de considerar los contextos subnacionales en los estudios del comportamiento electoral.

Operating Francis turbines over extended range is often hindered by the flow instabilities developed downstream the runner, in the draft tube cone. The unsteady pressure field induced by flow instabilities leads to pressure fluctuations. The paper presents the experimental investigations of the unsteady pressure field generated by flow instabilities into a draft tube of the Francis turbine over extended operating range. In situ measurements are performed without and with air injection in order to assess the control method. The unsteady pressure is recorded in five locations on the draft tube cone wall. As a result, the Fourier spectra are obtained without and with air injection in order to identify the fundamental frequency and associated amplitude. In this case, the air injection improves significantly the dynamic behavior at 0.7Q BEP while for operating points at lower discharge (around 0.5Q BEP ) the dynamic behavior is deteriorated.

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.

Bankruptcy and insolvency risk analysis with all their respective methodologies and techniques are well covered topics in the literature. Investigating companies operating in very dynamic or specific industries from an insolvency risk point of view using traditional tool packs may become rather cumbersome for various reasons. The purpose of this paper is to suggest a much simplified and relatively straightforward method using SAS System software, as well as discussing some potential pitfalls.

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.

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Regional labour markets in the "Great Recession": The evolution of regional unemployment rates in Germany, France and the United Kingdom in 2009. Contrary to the already encompassing literature on the differentiated effects of the "Great Recession" on states, the article takes a regional economic perspective. The stated research question is "Which factors might explain the spatially unequal development of unemployment rates at the regional level?". Using a cross-section data-set with the percentage point increase of regional unemployment rates between 2008 and 2009 as the dependent variable and a set of regional and national variables as independent variables, a multiple linear regression model is estimated. After detecting spatial autocorrelation for the OLS-estimators, the model is re-estimated and a spatial error model with ML-estimators is computed. It turns out that the share of low-skilled has a significant positive effect on the change of regional unemployment rates. Furthermore, the financial centres showed a significant better resilience than other regional economies. Because of the strong influence of the national variables in these models, separate models are estimated for France and UK. It is shown that the same variables have quite different effects. This questions the existence of a common explanation for regional unemployment dynamics in Europe.

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.

Forest crimes cause significant economic, social and environmental problems. It is declerated that economical reasons are the basic origin of these crimes. This study was performed in 36 forest village located in the Karadere Forest Enterprise area. As a results of the survey applied to 235 forest villagers in the sampling area, the effects of economical conditions of the forest villagers on forest crimes was determined. It was determined that only 9 of 25 economic indicators researched were significantly effective on the forest crimes at this research.

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.

The aim of this work is to identify spatial patterns of economic inequality between the inter micro comprising the northern region of Brazil from 2010. Specifically, we intend to: a) determine the degree of economic inequality intermunicipal for micro, b) check whether there is spatial dependence between the micro and finally, c) identify the relationship between the variables GDP per capita and inequality, between the Municipal Human Development Index (HDI-M) and economic inequality. To achieve the proposed objectives , is used to calculate the degree of inequality Williamson (Williamson coefficient) for micro- and still are used technical analysis of spatial distribution, specifically, Exploratory Spatial Data Analysis (ESDA), along with measures of autocorrelation Moran's I global and local, and their respective indices. The study confirms empirical observations and reveals that in the Northern region of Brazil is a high degree of inequality between the microregions that make...

 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.

O objetivo geral deste trabalho é identificar padrões espaciais de desigualdade econômica intermunicipal entre as microrregiões que compõem a região Norte do Brasil no período de 2010. Especificamente, pretende-se: a) determinar o grau de desigualdade econômica intermunicipal para as microrregiões, b) verificar se existe dependência espacial entre as microrregiões e, por fim, c) identificar o relacionamento entre as variáveis PIB per capita e desigualdade, e entre o Índice de Desenvolvimento Humano Municipal (IDH-M) e desigualdade econômica. Para alcançar os objetivos propostos, é utilizado o cálculo do grau de desigualdade de Williamson (coeficiente de Williamson) para as microrregiões, e ainda, são utilizadas técnicas de análise de distribuição espacial, especificamente, a Análise Exploratória de Dados Espaciais (AEDE), juntamente com as medidas de auto correlação I de Moran global e local, e seus respectivos índices. O estudo confirma observações empíricas e revela que na Região ...

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...

As the experiences of industrialized economies have shown, "intangible capital" such as R&D expenses, patents, copyrights, franchises or licenses, and trademarks, represents a key component of the knowledge of firms that are crucial to their performance. The aim of this paper is to investigate the impact of capital inputs on productivity in Turkish manufacturing industry. Using firm-level data from 2003 to 2012, we compare the impact of tangibles and intangibles, as well as different types of intangibles on productivity. Our findings based on the estimation of a Cobb-Douglas production function by using Generalized Methods of Moments (GMM) and a semi-parametric estimation method proposed by show that firms with increasing level of expenditure for intangible assets experienced an increase in their productivity. In addition, the effect of intangible assets on productivity is especially significant for computer software and patent capital.

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.

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.