... growth, improving economic development. In sum, technological innovation can improve ecological efficiency by reducing resource input, reducing environmental pollution, and improving economic output. This paper uses the super‐efficiency model, the spatial econometric method, and panel threshold model...

... inflows between the countries in our sample, suggesting that an increase in FDI inflows in a host country is likely to stimulate FDI inflows of its neighbours. FDI statutory corporate tax rate panel data spatial econometrics JEL classification: C23, E62, F21, H25 Due to multiple expected...

... of new forest planting in the coming decades under policy or market scenarios that incentivize improved forest productivity or certain ecosystem services provided by intensively managed systems (e.g., carbon sequestration). plantation forest land-use change spatial econometrics forest management...

... spatial smoothing extreme value theory Gaussian spatial process spatial econometrics Adverse selection and moral hazard are common concerns when designing insurance products ( Ramirez and Shonkwiler 2017 ). Area-yield insurance can avoid the problems of moral hazard and transactions costs arising from...

...Virgilio Gómez-Rubio; Francisco Palmí-Perales Bayesian inference Disease mapping Integrated nested Laplace approximation Markov chain Monte Carlo methods Spatial econometrics Consejería de Educación, Cultura y Deportes PPIC-2014-001-P Fondo Europeo de Desarrollo Regional 10.13039...

... and the estimator can be easily implemented using pre‐programmed estimators available in most statistical packages. We provide an application of our method using the Add Health database. Homophily Network formation Random fields Spatial econometrics Note that the function h ij ( W m , − ij...

... concludes with policy recommendations that arise from our spatial analysis. Bayesian spatial probit sustainable technology adoption spatial econometrics Sustainable intensification is becoming increasingly important, which mainly stems from the recognition that the current growth path in agricultural...

..., such as the k‐means algorithm Forgy, (1965) extended to allow for covariates in the model; see, in particular, Lin and Ng ( 2012 ) and Bonhomme and Manresa (2015) , and also Ando and Bai (2016) . Our approach also has potential application in the area of spatial econometrics. Given the equivalence between...

... density may reinforce this effect. We use spatial econometrics to explain arable land rents in northern Germany based on 2010 agricultural census data. The results indicate that increasing biogas density is associated with a significant rise in the rental rates of arable land only in regions with high...

... growth and enhance competitiveness in Europe. infrastructure transport regional growth regional spillovers global growth opportunities ORBIS data spatial econometrics F23 F43 H4 H54 H76 R4 R53 Global growth opportunities matter for local business. They provide scope for firms to expand...

..., and [ g i l , r ] = 0 otherwise. Because municipalities are either adjacent or not, g i l , r = g l i , r , which satisfies reciprocity in the networking literature, and, as in the spatial econometrics literature, we assume that g i i , r = 0...

... play a role. spatial econometrics EU Rural Development Policy rurality indicators O18 Q01 R58 This article is aimed at assessing the relevance of space in influencing the allocation of the Rural Development Policy (RDP) expenditure at ‘local’ level, that is, across about 1,300 European Union (EU...

... model. Second, we have implemented a hybrid spatial interpolator that accounts both for systematic and probabilistic climate variation. In the Ricardian approach climate variables are typically generated with less complex interpolators. Third, we take an explicit spatial econometric approach that allows...

...-scale farming spatial econometrics urban-rural fringe Q28 Q15 R14 Concerns about permanent conversion of agricultural land to other uses have prompted the adoption of farmland conservation policies across the United States and Canada ( Duke and Lynch 2006 ; Deaton and Vyn 2010 ; Kline...

... new products in a social network it is essential to identify influential individuals whose product recommendations influence the consumption choices of their peers. In this study, we use spatial econometric methods to determine how individuals revise their preferences for product attributes when...

... change spatial econometrics sample selection generalised method of moments estimation I3 Q18 C50 Recently, Deschênes and Greenstone (2007) introduced the idea of utilising year-to-year fluctuations in weather (which can be considered as random) to improve the estimates of Ricardian models...

... when considering the impact that the final consumers’ location has on production). We assume that the profit function of a hog producer is given by: (1) Hog production Land availability Manure application regulation Agglomeration economies Spatial econometrics Q10 Q53 R12 Empirical evidence...

... for the spatial econometric model. Improved data availability has allowed us to add further and more recent variables to the spatial models, thereby integrating additional aspects into the analysis. In this study, the factors influencing the decision to convert to organic farming are related to two kinds...

... concludes. Proofs of results are given in the Appendix . Hausman test Panel data Random effects estimator Spatial econometrics Within estimator In their seminal paper, Kapoor et al. (2007) concentrate on the random effects model, assuming that the explanatory variables and the unit‐specific error...

... rather than assume that NEG will be successful at a low level of spatial aggregation. New economic geography urban economics spatial econometrics panel data non-nested rivals C21 C31 C33 O18 R12 R31 The New Economic Geography (NEG) has made a major contribution to economic geography theory...