Identifying spatial interactions in the presence of spatial error autocorrelation: An application to land use spillovers

Spatial spillovers—interaction effects among neighboring agents in space—are a common characteristic of a variety of processes that are of interest to environmental and resource economists. Empirical identification of these interactions is challenging, however, due to the endogenous nature of the interactions and the inevitable unobserved spatial correlation that, if uncontrolled, can result in spurious estimates of the interaction parameters. Traditional spatial econometric models rely on maintained assumptions that impose separate structures for the spatial error and interaction processes and thus are insufficient for solving this identification problem. To identify spatial land use spillovers in a hedonic model of residential housing values, we pursue an alternative approach by exploiting a natural experiment in the data. We use exogenous physical land features that impose a direct constraint on residential development on some, but not all, of the land that falls within our study region and use this to construct a “partial population identifier.” We find that this estimation strategy solves the endogeneity problem and reduces spatial error autocorrelation, but does not fully eliminate it. Estimation of the model using a more restricted sample in combination with the partial population identification strategy is successful in eliminating the remaining spatial error autocorrelation. We conclude that less restrictive approaches to controlling for unobserved spatial correlation, such as the natural experiment pursued here, may provide a superior alternative to identifying spatial spillovers.     

Analyzing long-term average adjustment of financial ratios with spatial interactions

The aim of this paper is to put forward a beta convergence model using spatial interaction to evaluate the dynamics of financial ratios. We overcome some of the limitations that come from the traditional partial adjustment model by relating both models. We show that the parameters of the two models may be connected. As an example, we discuss the case of a large sample of medium to high-tech industrial small and medium enterprises (SMEs) located along the Spanish Mediterranean coast. Our findings support the existence of a long-term average adjustment process in the financial ratios of this set of companies which depends on the characteristics of the firms in their neighborhood.     

Testing stochastic income convergence in seasonal heterogeneous panels

In this paper we introduce a seasonal version of the Solow–Swan growth model and acquire an empirical income convergence equation. We take this equation as a basis to investigate whether income convergence exists in an OECD sample. To do this, we propose the test statistics under various asymptotic properties for some of the seasonal frequencies in the context of nonstationary heterogeneous panels. Critical values and moments of our statistics are generated and their finite sample performances are examined via Monte Carlo simulations.     

Testing for Granger causality in heterogeneous mixed panels

In this paper, we propose a simple Granger causality procedure based on Meta analysis in heterogeneous mixed panels. Firstly, we examine the finite sample properties of the causality test through Monte Carlo experiments for panels characterized by both cross-section independency and cross-section dependency. Then, we apply the procedure for investigating the export led growth hypothesis in a panel data of twenty OECD countries.     

Testing slope homogeneity in large panels with serial correlation

Pesaran and Yamagata (Pesaran, M.H., Yamagata, T., Testing slope homogeneity in large panels, Journal of Econometrics 142, 50–93, 2008) propose a test for slope homogeneity in large panels, which has become very popular in the literature. However, the test cannot deal with the practically relevant case of heteroskedastic and/serially correlated errors. The present note proposes a generalized test that accommodates both features.     

On PPP,unit roots and panels

In this paper we use a combination of time series unit root and cointegration analysis and the Bai and Ng (Econometrica 72:1127–1187, 2004) factor model approach to assess the purchasing power parity hypothesis for four real exchange rate panels. Our main findings are twofold: First, we find robust evidence for nonstationary common components in the real exchange rate panels and hence no evidence for PPP. Second, the presence of nonstationary common components is consistent with rejections of the unit root null hypothesis when applying a battery of first and second generation panel unit root tests, which are known to be adversely affected in the presence of common nonstationary components.     

A simple test for nonstationarity in mixed panels with incidental trends

Ng (2008) shows how the cross-sectional variance of the observed panel data can be used to construct a simple test for the proportion of non-stationary units. However, in the case with incidental trends the test is distorted. The present note shows how the distortions can be substantially reduced by the use of bias-adjustment. It also investigates the local power of the bias-adjusted test, which is shown to suffer from the same incidental trends problem previously only documented for conventional t$t$-tests.     

Bootstrap LM tests for higher-order spatial effects in spatial linear regression models

This paper first extends the methodology of Yang (J Econom 185:33–59, 2015) to allow for non-normality and/or unknown heteroskedasticity in obtaining asymptotically refined critical values for the LM-type tests through bootstrap. Bootstrap refinements in critical values require the LM test statistics to be asymptotically pivotal under the null hypothesis, and for this we provide a set of general methods for constructing LM and robust LM tests. We then give detailed treatments for two general higher-order spatial linear regression models: namely the \(\mathtt{SARAR}(p,q)\) model and the \(\mathtt{MESS}(p,q)\) model, by providing a complete set of non-normality robust LM and bootstrap LM tests for higher-order spatial effects, and a complete set of LM and bootstrap LM tests robust against both unknown heteroskedasticity and non-normality. Monte Carlo experiments are run, and results show an excellent performance of the bootstrap LM-type tests.     

Second-order polynomial spatial error model. Global and local spatial dependence in unemployment in Andalusia

This paper analyses a second-order polynomial spatial structure in the residues of a regression model. We propose a new specification that captures spatial dependence on two different levels, adding a new autoregressive cycle to the errors of the classical spatial error model (SEM). The inference problems of the parameters are solved by means of maximum likelihood estimation. The model is confirmed to identify two spatial structures of spatial dependence, global and local, by an empirical application in the analysis of municipal unemployment in the Spanish region of Andalusia. Finally, Monte Carlo is implemented to evaluate the performance of this strategy in a context of finite size samples.     

Using spatial microsimulation to account for demographic and spatial factors in environmental benefit transfer

This paper presents a simulation-based modelling approach for estimating total visitor numbers and amenity values for prospective non-priced open-access outdoor recreation sites. To begin, the geographic extent of the market for recreation at a policy site is estimated using data from a similar study site. The population residing within this geographic area is simulated using a spatial microsimulation model and GIS techniques and an individual-level ‘visitor arrival function’ is then transferred across this simulated population. This allows the latent demand for visits to the policy site by each simulated individual to be predicted and summed, providing an estimate of the total potential demand for recreation at the site. Combining this with an economic value measure of a visit provides an estimate of the potential amenity value of the policy site. The approach is applied to Moyode Wood, a small-scale forest in the West of Ireland, and estimates the potential total economic value of recreation at €0.4 million for the site. The research represents the first time that spatial microsimulation has been used in environmental benefit transfer and shows how it can be used to control for differences in demographic and spatial factors between study and policy sites. It also demonstrates how individual-level single-site travel cost models estimated using on-site survey data can be used to predict demand at alternative policy sites.     

Important overlooked IVs in spatial models

Spatial models often contain additional endogenous variables as regressors. The complete system determining these variables is typically not known to the researcher, and so maximum likelihood or Bayesian estimation methods are precluded. This leaves instrumental variable estimation. In all likelihood, the system may contain certain forms of nonlinearities. These nonlinearities might arise because of endogenous weighting matrices, functional form differences in the endogenous variables, etc. The existence of such nonlinearities strongly suggests the use of nonlinear forms of the instruments. Issues of this sort were pointed out in Kelejian and Piras (Spatial econometrics, Elsevier, Amsterdam, 2017) and Kelejian (Lett Spat Resour Sci 9(1):113–136, 2016). However, thus far Monte Carlo results relating to efficiencies gained by the use of nonlinear instrumental variables are not available. This is unfortunate because these efficiencies can be quite extensive. The purpose of this paper is to fill this void.     

Structural unempolyment in Australia

This paper examines whether structural unemployment increased in Australia over the last two decades. A simple regression model has been considered for testing the hypothesis of increase in unemployment of several segment of the labour force over time. Six dimensions of the labour force, namely age, sex, region, duration of unemployment, occupation and industry, have been taken into account. Analysis of the regression results reveals that the structural unemployment problem is substantial with respect to age, sex, duration of unemployment occupation and industry. Regarding region the evidence for structural symptom is not very strong.     

Efficient spatial competition

Game-theoretic models of spatial competition usually assume that firms set prices after their choices of locations. Rather than make this assumption, this paper uses the core to model the competition between the firms. Two conditions are shown to be sufficient for efficient spatial competition. The first is that the firms' location choices satisfy a no-externalities condition. The second is that the second-stage game satisfy a separable-value condition, namely that the value (gains from trade) can be created on a buyer-by-buyer basis. This approach yields two further benefits. First, efficient location can be stable in situations with arbitrary distributions of buyers, arbitrary willingness-to-pay functions, and completely general location spaces. Second, efficiency in location games can be shown to be related to the Second Welfare Theorem.     

Social interactions in small groups

Abstract.  In the well‐known 'critical mass' model of social interactions, aggregate behaviour exhibits multiple equilibria if the influence of group behaviour on individual behaviour exceeds some fairly high threshold. I demonstrate that this property depends on an implicit assumption that the relevant social group is large (infinite). With small (finite) social groups, the same model exhibits multiplicity whenever group behaviour exerts any influence. The range of equilibrium group behaviour depends on the size of the social group as well as its strength of influence. Brief applications on youth smoking and retirement planning demonstrate the implications of these results for applied work. JEL classification: Z13, D00     

Threshold effects of financial status on the cost frontiers of financial institutions in nondynamic panels

This article applies Hansen's (1999, 2000) threshold regression model to estimate translog cost frontiers in the hope of shedding light on the banking industry's production processes and the extent of its Technical Efficiency (TE). The threshold technique allows for the existence of multiple technologies of production, distinguished by an exogenous threshold variable. Strong evidence of multiple technologies is found in the industry irrespective of which financial indicator, as constructed by factor analysis, defines the threshold variable. Cost savings and scale economies among the various underlying technologies are compared herein. We also highlight the differences between the threshold results and the conventional cost frontier.     

Using PDA consistency checks to increase the precision of profits and sales measurement in panels

Personalized Digital Assistants (PDAs) and other forms of hardware needed to collect survey data electronically have become more affordable and powerful in recent years, leading to their use in a number of surveys in developing countries. Simple use of these devices can offer the prospect of more timely data entry and greater accuracy in guiding respondents through skip patterns. Further benefits are possible through the use of more complex consistency checks. We use PDAs to measure sales and profits for microenterprises, which are notoriously noisy. Consistency checks in the cross-section compare sales and profits, while those in the panel query responses which result in large changes from one period to the next. Cross-sectional checks also served as a second prompt in the case of missing profits. These checks do succeed in reducing the standard deviation and in increasing the correlation of the observations for which corrections are made. However, we find that the vast majority of large changes in enterprise sales and profits are confirmed by firm owners as genuine, highlighting the volatility of income in this sector. As a result, the overall impact of these consistency checks on the full sample is rather limited, suggesting that while such checks are useful if computerized forms of data collection are being used, the consistency checks per se are not a strong reason for using computerized data collection in collecting firm profits and sales.     

长期增长过程的“结构性加速”与“结构性减速”:一种解释

立足于Mitchell和Maddison的历史统计数据库,本文对发达国家增长因素进行了分析,阐释了以下事实,即1970年代以后发达国家经济增长的减速,与生产率增长的减速密切相关,而生产率的减速是由于产业结构服务化这种系统性因素造成的。为此,本文提出了长期增长过程中"结构性加速"与"结构性减速"的观点。这种观点一方面系统化和清晰化了人们关于长期增长趋势的认识,另一方面在"结构性加速"向"结构性减速"过渡期间的经济问题也更容易得到解释和预测。未来几十年,中国经济结构的服务化趋势逐渐增强,"结构性加速"向"结构性减速"转换及相应问题将会凸显。相对于其他理论而言,这种观点对于中国的工业化和城市化问题可能具有更强、更直观的解释能力。     

Equilibria in systems of social interactions

In this paper, we establish existence and uniqueness results for equilibria in systems with an infinite number of agents and with local and global social interactions. We also examine the structure of the equilibrium distribution and derive a “Markov”property for the equilibrium distribution of a class of spatially homogeneous systems.