nep-geo New Economics Papers
on Economic Geography
Issue of 2013‒12‒20
ten papers chosen by
Andreas Koch
Institute for Applied Economic Research

  1. Do more distant collaborations have more citation impact? By Nomaler; Frenken; Heimeriks
  2. A new framework for the US city size distribution: Empirical evidence and theory By Ramos, Arturo; Sanz-Gracia, Fernando; González-Val, Rafael
  3. Spatial Price Differentiation and Regional Market Power. The Case of Food-Retailing in Austria By Dieter Pennerstorfer; Franz Sinabell
  4. Knowledge Spillovers in Neoclassical Growth Model: an extension with Public Sector By Álvarez, Inmaculada; Barbero, Javier
  5. Proximity and Stratification in European Scientific Research Collaboration Networks: A Policy Perspective By Hoekman; Frenken
  6. ‘Small Area Social Indicators for the Indigenous Population: Synthetic data methodology for creating small area estimates of Indigenous disadvantage’ By Yogi Vidyattama; Robert Tanton; Nicholas Biddle
  7. "On the Decomposition of Regional Stabilization and Redistribution " By Masayoshi Hayashi
  8. GMM Estimation of Spatial Autoregressive Models with Autoregressive and Heteroskedastic Disturbances By Osman Dogan; Suleyman Taspinar
  9. Heteroskedasticity of Unknown Form in Spatial Autoregressive Models with Moving Average Disturbance Term By Osman Dogan
  10. Cointegration Testing in Panel VAR Models Under Partial Identification and Spatial Dependence By Arturas Juodis

  1. By: Nomaler; Frenken; Heimeriks
    Abstract: Internationally co-authored papers are known to have more citation impact than nationally co-authored paper, on average. However, the question of whether there are systematic differences between pairs of collaborating countries in terms of the citation impact of their joint output, has remained unanswered. On the basis of all scientific papers published in 2000 and co-authored by two or more European countries, we show that citation impact increases with the geographical distance between the collaborating counties.
    Keywords: citation impact, collaborations, distance, country effects
    Date: 2013–11
  2. By: Ramos, Arturo; Sanz-Gracia, Fernando; González-Val, Rafael
    Abstract: We study the US city size distribution using the Census places data, without size restriction, for the period (1900-2010). Also, we use the recently introduced US City Clustering Algorithm (CCA) data for 1991 and 2000. We compare the lognormal, two distributions named after Ioannides and Skouras (2013) and the double Pareto lognormal with two newly introduced distributions. The empirical results are overwhelming: One of the new distributions widely outperform any of the previously used density functions for each type of data. We also develop a theory which generates the new distributions based on the standard geometric Brownian motion for the population in the short term. We propose some extensions of the theory in order to deal with the long term empirical features.
    Keywords: US city size distribution, population thresholds, lower and upper tail, new statistical distributions
    JEL: C13 C16 R00
    Date: 2013–12–13
  3. By: Dieter Pennerstorfer (WIFO); Franz Sinabell (WIFO)
    Abstract: A small number of firms have a large market share in the Austrian food retailing market. Market concentration has been growing over the last years which has raised concerns about market power. Previous studies on price setting behaviour in the food retailing market were at the national level and regional price setting has not yet been analysed. We use a panel data set of over 2,000 households with monthly food purchasing data and the number of outlets of the nine biggest food retailers in 120 districts to explore regional price setting behaviour. The analysis shows that only a small number of retailers seem to regionally differentiate prices extensively. It cannot be confirmed that spatial price differentiation is a way to exert market power in the Austrian food retailing market.
    Keywords: Market power, Food retailing, Spatial price differentiation, Austria
    Date: 2013–12–12
  4. By: Álvarez, Inmaculada (Departamento de Análisis Económico (Teoría e Historia Económica). Universidad Autónoma de Madrid.); Barbero, Javier (Departamento de Análisis Económico (Teoría e Historia Económica). Universidad Autónoma de Madrid.)
    Abstract: We propose a framework to analyze convergence between regions, incorporating the public sector and technological knowledge spillovers in the context of a Neoclassical Growth Model. Secondly, we apply novel estimation methods pertaining to the spatial econometrics literature introducing a spatial autoregressive panel data model based on instrumental variables estimation. Additionally, we introduce marginal effects associated with changing explanatory variables. Our model makes it possible to analyze, in terms of convergence, the results obtained in Spanish regions with the policies implemented during the period 1980-2007. The results support the idea that investments in physical, private and public capital, as well as in education have a positive effect on regional development and cohesion. Therefore, we can conclude that it is possible to obtain better results for regional convergence with higher rates of public investment. We also obtain interesting results that confirm the existence of spillover effects in economic growth and public policies, identifying their magnitude and significance.
    Keywords: speed of convergence; growth models; public policies.
    JEL: E13 H54 O41
    Date: 2013–12
  5. By: Hoekman; Frenken
    Abstract: In this chapter we introduce a framework to understand the geography of scientific research collaboration with an emphasis on empirical studies that evaluate the policy efforts to create a ‘European Research Area’ (ERA). We argue that the geography of scientific research collaboration follows a logic of proximity that provides researchers with solutions to the problem of coordination, and a logic of stratification that provides researchers with differential means to engage in collaboration. The policy efforts to create ERA can then be understood as strategic policy interventions at the European level that affect the form and nature of both structuring principles. More specifically, the aim of reducing ‘fragmentation of research activities, programmes and policies’ affects the importance of several forms of proximity vis-à-vis each other, while the promotion of ‘research excellence’ results in new forms of network stratification at multiple spatial scales. We provide an overview of recent empirical findings to illustrate these claims, and discuss potential implications for future ERA policies.
    Keywords: collaboration, science, geography, proximity, stratification, Europe
    Date: 2013–11
  6. By: Yogi Vidyattama (NATSEM, University of Canberra); Robert Tanton (NATSEM, University of Canberra); Nicholas Biddle (CAEPR, Australian National University (ANU))
    Abstract: The lack of data on how the social condition of Indigenous people varies throughout Australia has created difficulties in allocating government and community programs across Indigenous communities. In the past, spatial microsimulation has been used to derive small area estimates to overcome such difficulties. However, for previous applications, a record unit file from a survey dataset has always been available on which to conduct the spatial microsimulation. For the case of indigenous disadvantage, this record unit file was not available due to the scarcity of the Indigenous population in Australia, and concerns from the ABS about confidentialising the file. This study offers a solution to this problem by proposing the building of a synthetic unit record file with observations that sum to the population totals from the actual survey file. A spatial microsimulation approach is then applied to this synthetic unit record file and the results are validated.
    Keywords: Wellbeing, synthetic data, spatial microsimulation, Indigenous people, wellbeing
    JEL: C15 C63 I31 J15
    Date: 2013–12
  7. By: Masayoshi Hayashi (Faculty of Economics, The University of Tokyo)
    Abstract:    This study proposes decomposition and estimation methods that can be applied to analyze both regional stabilization and redistribution. The method proposed herein follows the approach taken by Shorrocks (1982), and applies it to per-capita level quantities of the relevant variables rather than the log-linear quantities used by Asdrubali et al. (1996) for regional stabilization and the normalized per-capita quantities used by Bayoumi and Masson (1995) for regional redistribution. I directly calculate the proportional contributions to the decomposition and bootstrap their confidence intervals rather than indirectly obtain them as OLS estimates from the artificial regressions by Asdrubali et al. (1996). I then apply the proposed method to Japanese prefectural accounts data so that we can compare the presented analysis with those in previous studies. Furthermore, I also apply the method to municipal budgetary data in Japan in order to demonstrate its usefulness.
    Date: 2013–12
  8. By: Osman Dogan (Ph.D. Program in Economics, City University of New York Graduate Center); Suleyman Taspinar (Ph.D. Program in Economics, City University of New York Graduate Center)
    Abstract: We consider a spatial econometric model containing a spatial lag in the dependent variable and the disturbance term with an unknown form of heteroskedasticity in innovations. We first prove that the maximum likelihood (ML) estimator for spatial autoregressive models is generally inconsistent when heteroskedasticity is not taken into account in the estimation. We show that the necessary condition for the consistency of the ML estimator of spatial autoregressive parameters depends on the structure of the spatial weight matrices. Then, we extend the robust generalized method of moment (GMM) estimation approach in Lin and Lee (2010) for the spatial model allowing for a spatial lag not only in the dependent variable but also in the disturbance term. We show the consistency of the robust GMM estimator and determine its asymptotic distribution. Finally, through a comprehensive Monte Carlo simulation, we compare finite sample properties of the robust GMM estimator with other estimators proposed in the literature.
    Keywords: spatial autoregressive models, unknown heteroskedasticity, robustness, GMM, asymptotics, MLE
    JEL: C13 C21 C31
    Date: 2013–12–16
  9. By: Osman Dogan (Ph.D. Program in Economics, City University of New York Graduate Center)
    Abstract: In this study, we investigate the necessary condition for the consistency of the maximum like- lihood estimator (MLE) of spatial models that have a spatial moving average process in the disturbance term (for short SARMA(1,1)). We show that the maximum likelihood estimator (MLE) of the spatial autoregressive and spatial moving average parameters is generally incon- sistent when heteroskedasticity is not considered in the estimation. The necessary condition for the consistency of the MLE depends on the structure of the spatial weight matrices. We also show that the inconsistency of the spatial autoregressive and spatial moving average parameters contaminates the MLE of the parameters of the exogenous variables. A Monte Carlo simulation study provides evaluation of the performance of the MLE in the presence of heteroskedastic innovations. The simulation results indicate that the MLE imposes substantial amount of bias on both autoregressive and moving average parameters. However, they also show that the MLE imposes almost no bias on the parameters of the exogenous variables in moderate sample sizes.
    Keywords: spatial dependence, spatial moving average, spatial autoregressive, maximum likelihood estimator, MLE, asymptotics, heteroskedasticity, SARMA(1,1)
    JEL: C13 C21 C31
    Date: 2013–12–16
  10. By: Arturas Juodis
    Abstract: This paper considers the Panel Vector Autoregressive Models of order 1 (PVAR(1)) with possibly spatially dependent error terms. We propose a simple Method of Moments based cointegration test using the rank test of Kleibergen and Paap (2006) for fixed number of time observations. The test is shown to be robust to spatial dependence, cross-sectional and time series heteroscedasticity as well as unbalanced panels. The main novelty of our approach is that we fully exploit the "weakness" of the Anderson and Hsiao (1982) moment conditions in construction of the new test. The finite-sample performance of the proposed test statistic is investigated using the simulated data. The results show that for most scenarios the method performs well in terms of both size and power. The proposed test is applied to employment and wage equations using Spanish firm data of Alonso-Borrego and Arellano (1999) and the results show little evidence for cointegration.
    Date: 2013–10–03

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