Pub Date : 2023-11-10DOI: 10.1080/17421772.2023.2271519
Santiago Truffa, Alexis Montecinos
ABSTRACTWe study how cities’ amenities and limited housing supply contribute to aggregate wage inequality and affect housing prices through the sorting of heterogeneous skilled workers. We develop a general equilibrium model where workers differ along a continuum of skills and compete for limited housing. Our analysis suggests that spatial sorting accounts for 7.5% of the aggregate wage dispersion, increases average housing prices by 20–40% in constrained cities, and makes the economy 1.9% more productive. In addition, we evaluate a place-based policy that aims to expand the supply of houses in 1% of constrained cities and find that it improves aggregate productivity between 0.2% and 0.4%. However, the place-based policy has the unintended consequence of aggravating aggregate wage inequality by the same magnitude.KEYWORDS: labour sortinginequalityhousingplace-based policiesJEL: D44D58F16J24R13 ACKNOWLEDGEMENTSWe are extremely grateful to Ernesto Dal Bó, William Fuchs and John Morgan for their support. We also thank Scott Baker, Victor Couture, Cecile Gaubert, Rui de Figueiredo, William Grieser, William Hardin, Enrico Moretti, Gonzalo Maturana, Steve Tadelis, Joachim Voth, Reed Walker, Zhonghua Wu and Noam Yuchtman, as well as numerous seminar and conference participants, for their helpful discussions and comments. We would also like to thank Diogo Duarte who contributed to this project on an earlier version. This paper was originally part of Santiago Truffa’s PhD dissertation titled ‘Essays in urban economics’.DISCLOSURE STATEMENTNo potential conflict of interest was reported by the authors.Notes1 In this study we will focus on wage and housing price inequality. In particular, since we are able to compute wages at the individual level, we can analyse both between- and within-city inequality. When we refer to aggregate inequality, we mean the total variance of all individual wages.2 Shapiro (Citation200Citation6), Glaeser and Gottlieb (Citation2008), Couture (Citation2015), Albouy et al. (Citation2016) and Albouy (Citation2016) have empirically shown the importance of amenities in accounting for sorting patterns. We build on this literature, and we quantify the trade-off between amenities versus restrictions on the housing supply. Related literature has explored the sorting of heterogeneous firms (Behrens et al., Citation2014; Gaubert, Citation2018; Serrato & Zidar, Citation2016) to study the welfare implications of taxes and firm incentives. We complement this literature by focusing on the worker side. Further work is required to join these two threads in the literature.3 Frameworks that divide the workforce into discrete categories are empirically sensitive since the results depend on dichotomous definitions of what type of worker qualifies for each type of category. Indeed, Baum-Snow et al. (Citation2018) show that if we change the definition of high-skilled worker to a worker with some college education, some of the results shown by Diamond (C
摘要本文通过对异质技术工人的分类，研究了城市的便利设施和有限的住房供应如何导致总工资不平等并影响房价。我们开发了一个一般均衡模型，其中工人在连续的技能上存在差异，并为有限的住房而竞争。我们的分析表明，空间分类占总工资差异的7.5%，在受限制的城市中，平均房价上涨了20-40%，并使经济生产力提高了1.9%。此外，我们评估了一项基于地方的政策，该政策旨在扩大1%受限城市的住房供应，并发现它提高了0.2%至0.4%的总生产率。然而，基于地点的政策产生了意想不到的后果，即在同样程度上加剧了总体工资不平等。关键词:劳动分类不平等住房基于地方的政策我们非常感谢Ernesto Dal Bó， William Fuchs和John Morgan的支持。我们还要感谢Scott Baker、Victor Couture、Cecile Gaubert、Rui de Figueiredo、William Grieser、William Hardin、Enrico Moretti、Gonzalo Maturana、Steve Tadelis、Joachim Voth、Reed Walker、Zhonghua Wu和Noam Yuchtman以及众多研讨会和会议参与者的宝贵讨论和意见。我们还要感谢Diogo Duarte，他为这个项目的早期版本做出了贡献。这篇论文最初是圣地亚哥·特鲁法博士论文《城市经济学论文》的一部分。声明作者未报告潜在的利益冲突。注1在本研究中，我们将关注工资和房价不平等。特别是，由于我们能够计算个人水平的工资，我们可以分析城市之间和城市内部的不平等。当我们提到总体不平等时，我们指的是所有个体工资的总方差Shapiro (Citation200Citation6)、Glaeser和Gottlieb (Citation2008)、Couture (Citation2015)、Albouy等人(Citation2016)和Albouy (Citation2016)已经从经验上证明了舒适度对分类模式的重要性。我们以这些文献为基础，量化了便利设施与住房供应限制之间的权衡。相关文献探讨了异质性企业的分类(Behrens et al.， Citation2014;•高柏,Citation2018;Serrato & Zidar, Citation2016)研究税收和企业激励对福利的影响。我们通过关注工人方面来补充这些文献。需要进一步的工作来连接这两个线程在文献中将劳动力划分为离散类别的框架在经验上是敏感的，因为结果依赖于哪种类型的工人符合每种类别的二分定义。事实上，Baum-Snow等人(Citation2018)表明，如果我们将高技能工人的定义更改为具有大学学历的工人，Diamond (Citation2016)所显示的一些结果将不再成立为了做到这一点，我们参考了最近用竞标战来模拟房地产市场的文献。详见《汉与奇》(Citation2015)一个值得注意的例外是Kline和Moretti (Citation2014)，他们开发了一种方法来估计他们的总体效应与Costinot和Vogel (Citation2010)类似，我们假设Ai(s，σ)>0是二次可微且严格对数超模的，以捕捉高技能工人在更复杂的任务中具有比较优势的想法。这一特征部分补偿了我们有一个共同的集聚弹性和不区分低技能和高技能工人的弹性的事实注意，Li(s，σ)=vi(s)1{Mi(s)=σ}，其中1是一个指示函数。另外，请注意Bi=Vi(s¯)根据Albrecht等人(Citation2016)的假设，我们假设Bi和Si足够大，使得访问特定卖家的买家到达率遵循参数为θi.10的连续泊松过程(9)中的偏好是文献中常用的齐次偏好U=Tailog (xi)的单调变换。因此，在式(9).11的单调变换下，该效用表示的所有性质都保持不变事实上，这与Bacolod等人(Citation2009)所显示的人才的实证分布是一致的。尽管我们看到不同城市在高技能工人和低技能工人的比例上存在差异，但我们仍然观察到，在各个水平的人才中，工人的数量都是正的。此外，如果我们将注意力限制在两个城市，我们可以证明，对于任何一对不重叠的技能分布，这种配置永远不会处于均衡状态，因为高技能城市中技能最低的工人总是有动机搬到技能最高的低技能城市。我们在网上补充资料的附录中介绍了这两个城市的病例。
{"title":"On the geography of inequality: labour sorting in general equilibrium","authors":"Santiago Truffa, Alexis Montecinos","doi":"10.1080/17421772.2023.2271519","DOIUrl":"https://doi.org/10.1080/17421772.2023.2271519","url":null,"abstract":"ABSTRACTWe study how cities’ amenities and limited housing supply contribute to aggregate wage inequality and affect housing prices through the sorting of heterogeneous skilled workers. We develop a general equilibrium model where workers differ along a continuum of skills and compete for limited housing. Our analysis suggests that spatial sorting accounts for 7.5% of the aggregate wage dispersion, increases average housing prices by 20–40% in constrained cities, and makes the economy 1.9% more productive. In addition, we evaluate a place-based policy that aims to expand the supply of houses in 1% of constrained cities and find that it improves aggregate productivity between 0.2% and 0.4%. However, the place-based policy has the unintended consequence of aggravating aggregate wage inequality by the same magnitude.KEYWORDS: labour sortinginequalityhousingplace-based policiesJEL: D44D58F16J24R13 ACKNOWLEDGEMENTSWe are extremely grateful to Ernesto Dal Bó, William Fuchs and John Morgan for their support. We also thank Scott Baker, Victor Couture, Cecile Gaubert, Rui de Figueiredo, William Grieser, William Hardin, Enrico Moretti, Gonzalo Maturana, Steve Tadelis, Joachim Voth, Reed Walker, Zhonghua Wu and Noam Yuchtman, as well as numerous seminar and conference participants, for their helpful discussions and comments. We would also like to thank Diogo Duarte who contributed to this project on an earlier version. This paper was originally part of Santiago Truffa’s PhD dissertation titled ‘Essays in urban economics’.DISCLOSURE STATEMENTNo potential conflict of interest was reported by the authors.Notes1 In this study we will focus on wage and housing price inequality. In particular, since we are able to compute wages at the individual level, we can analyse both between- and within-city inequality. When we refer to aggregate inequality, we mean the total variance of all individual wages.2 Shapiro (Citation200Citation6), Glaeser and Gottlieb (Citation2008), Couture (Citation2015), Albouy et al. (Citation2016) and Albouy (Citation2016) have empirically shown the importance of amenities in accounting for sorting patterns. We build on this literature, and we quantify the trade-off between amenities versus restrictions on the housing supply. Related literature has explored the sorting of heterogeneous firms (Behrens et al., Citation2014; Gaubert, Citation2018; Serrato & Zidar, Citation2016) to study the welfare implications of taxes and firm incentives. We complement this literature by focusing on the worker side. Further work is required to join these two threads in the literature.3 Frameworks that divide the workforce into discrete categories are empirically sensitive since the results depend on dichotomous definitions of what type of worker qualifies for each type of category. Indeed, Baum-Snow et al. (Citation2018) show that if we change the definition of high-skilled worker to a worker with some college education, some of the results shown by Diamond (C","PeriodicalId":47008,"journal":{"name":"Spatial Economic Analysis","volume":"121 29","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135138018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-09DOI: 10.1080/17421772.2023.2256810
Malabika Koley, Anil K. Bera
ABSTRACT The spatial Durbin model (SDM) is one of the most widely used models in spatial econometrics. It originated as a generalisation of the spatial error model (SEM) under a non-linear parametric restriction (see Anselin (1988, pp. 110–111)). This restriction should be tested to select an appropriate model between SDM and SEM. Perhaps, due to the complexity of executing a test for a non-linear hypothesis, this restriction is rarely tested in practice, though see Burridge (1981), Mur and Angulo (2006) and LeSage and Pace (2009, p. 164). This paper considers an alternative linear hypothesis to test the suitability of the SDM. To achieve this, we first use Rao’s score (RS) testing principle and then Bera and Yoon (1993)’s methodology to robustify the original RS tests. The robust tests that require only ordinary least squares (OLS) estimation are able to identify the specific source(s) of departure(s) from the baseline linear regression model. An extensive Monte Carlo study provides evidence that our suggested tests possess excellent finite sample properties, both in terms of size and power. Our empirical illustrations, with two real data sets, attest that the tests developed in this paper could be very useful in judging the suitability of the SDM for the spatial data in hand.
{"title":"To use, or not to use the spatial Durbin model? – that is the question","authors":"Malabika Koley, Anil K. Bera","doi":"10.1080/17421772.2023.2256810","DOIUrl":"https://doi.org/10.1080/17421772.2023.2256810","url":null,"abstract":"ABSTRACT The spatial Durbin model (SDM) is one of the most widely used models in spatial econometrics. It originated as a generalisation of the spatial error model (SEM) under a non-linear parametric restriction (see Anselin (1988, pp. 110–111)). This restriction should be tested to select an appropriate model between SDM and SEM. Perhaps, due to the complexity of executing a test for a non-linear hypothesis, this restriction is rarely tested in practice, though see Burridge (1981), Mur and Angulo (2006) and LeSage and Pace (2009, p. 164). This paper considers an alternative linear hypothesis to test the suitability of the SDM. To achieve this, we first use Rao’s score (RS) testing principle and then Bera and Yoon (1993)’s methodology to robustify the original RS tests. The robust tests that require only ordinary least squares (OLS) estimation are able to identify the specific source(s) of departure(s) from the baseline linear regression model. An extensive Monte Carlo study provides evidence that our suggested tests possess excellent finite sample properties, both in terms of size and power. Our empirical illustrations, with two real data sets, attest that the tests developed in this paper could be very useful in judging the suitability of the SDM for the spatial data in hand.","PeriodicalId":47008,"journal":{"name":"Spatial Economic Analysis","volume":" 35","pages":"30 - 56"},"PeriodicalIF":0.0,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135241073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-23DOI: 10.1080/17421772.2023.2264344
Jeffrey Clemens, John Kearns, Beatrice Lee, Stan Veuger
ABSTRACTWe analyse whether US federal aid to state and local governments impacted economic activity through either direct or cross-state spillover effects during the COVID-19 pandemic. Deploying an instrumental-variables framework rooted in the funding advantage of states that are over-represented in Congress, we find that federal assistance had significantly less impact on state and local government employment, as well as broader measures of economic activity, than estimates from prior crisis responses would imply. The modest employment impacts we find stem largely from the direct effect of states’ own aid allocation, as opposed to spillovers across state lines. These findings point to an important role for variations in fiscal policy transmission mechanisms, namely that cross-state spillovers are less likely to be important when some of the key mechanisms for such spillovers, like robust interjurisdictional supply chains and patterns of consumption, are muted or shut down.KEYWORDS: COVID-19employmentfiscal federalismfiscal policyspatial macroeconomicsspilloversJEL: E6H5H7 ACKNOWLEDGEMENTThis article is based on the following working paper:Clemens, Jeffrey, John Kearns, Beatrice Lee, and Stan Veuger. ‘Spatial Spillovers and the Effects of Fiscal Stimulus: Evidence from Pandemic-Era Federal Aid for State and Local Governments.’ AEI Economics Working Paper 2022-14.DISCLOSURE STATEMENTNo potential conflict of interest was reported by the author(s).Notes1 These four pieces of legislation are the March 2020 Families First Coronavirus Response Act (FFCRA) and Coronavirus Aid, Relief, and Economic Security (CARES) Act, the December 2020 Response and Relief Act (RRA) of 2021 and the March 2021 American Rescue Plan Act (ARPA) of 2021.2 Nakamura and Steinsson (Citation2014), as well as Ramey (Citation2016, Citation2019) and Chodorow-Reich (Citation2020), provide frameworks for interpretation of the different estimates in these literatures.3 We use data from the CRFB’s COVID-19 Money Tracker as of August 19th, 2021.4 As in Clemens and Veuger (Citation2021), ‘[w]e obtain information on the distribution of transit funds for the RRA and ARPA from the US Federal Transit Administration (Citation2021a, Citation2021b). Data on the allocation of ARPA assistance to non-public schools come from the US Office of Elementary and Secondary Education (Citation2021). We obtain estimates of ARPA section 9817 matching increases from Chidambaram and Musumeci (Citation2021). We approximate the allocation of ARPA section 9819 federal matching funds for uncompensated care using FY2021 estimates of federal disproportionate share hospital allotments by state from the Medicaid and Chip Payment Access Commission (Citation2021).’ The Coronavirus Capital Projects Fund outlined in ARPA is distributed according to guidance from the United States Department of the Treasury (Citation2021a).5 Congressional representation per million residents is calculated as #ofRepresentativess+#ofSenato
{"title":"Spatial spillovers and the effects of fiscal stimulus: evidence from pandemic-era federal aid for state and local governments","authors":"Jeffrey Clemens, John Kearns, Beatrice Lee, Stan Veuger","doi":"10.1080/17421772.2023.2264344","DOIUrl":"https://doi.org/10.1080/17421772.2023.2264344","url":null,"abstract":"ABSTRACTWe analyse whether US federal aid to state and local governments impacted economic activity through either direct or cross-state spillover effects during the COVID-19 pandemic. Deploying an instrumental-variables framework rooted in the funding advantage of states that are over-represented in Congress, we find that federal assistance had significantly less impact on state and local government employment, as well as broader measures of economic activity, than estimates from prior crisis responses would imply. The modest employment impacts we find stem largely from the direct effect of states’ own aid allocation, as opposed to spillovers across state lines. These findings point to an important role for variations in fiscal policy transmission mechanisms, namely that cross-state spillovers are less likely to be important when some of the key mechanisms for such spillovers, like robust interjurisdictional supply chains and patterns of consumption, are muted or shut down.KEYWORDS: COVID-19employmentfiscal federalismfiscal policyspatial macroeconomicsspilloversJEL: E6H5H7 ACKNOWLEDGEMENTThis article is based on the following working paper:Clemens, Jeffrey, John Kearns, Beatrice Lee, and Stan Veuger. ‘Spatial Spillovers and the Effects of Fiscal Stimulus: Evidence from Pandemic-Era Federal Aid for State and Local Governments.’ AEI Economics Working Paper 2022-14.DISCLOSURE STATEMENTNo potential conflict of interest was reported by the author(s).Notes1 These four pieces of legislation are the March 2020 Families First Coronavirus Response Act (FFCRA) and Coronavirus Aid, Relief, and Economic Security (CARES) Act, the December 2020 Response and Relief Act (RRA) of 2021 and the March 2021 American Rescue Plan Act (ARPA) of 2021.2 Nakamura and Steinsson (Citation2014), as well as Ramey (Citation2016, Citation2019) and Chodorow-Reich (Citation2020), provide frameworks for interpretation of the different estimates in these literatures.3 We use data from the CRFB’s COVID-19 Money Tracker as of August 19th, 2021.4 As in Clemens and Veuger (Citation2021), ‘[w]e obtain information on the distribution of transit funds for the RRA and ARPA from the US Federal Transit Administration (Citation2021a, Citation2021b). Data on the allocation of ARPA assistance to non-public schools come from the US Office of Elementary and Secondary Education (Citation2021). We obtain estimates of ARPA section 9817 matching increases from Chidambaram and Musumeci (Citation2021). We approximate the allocation of ARPA section 9819 federal matching funds for uncompensated care using FY2021 estimates of federal disproportionate share hospital allotments by state from the Medicaid and Chip Payment Access Commission (Citation2021).’ The Coronavirus Capital Projects Fund outlined in ARPA is distributed according to guidance from the United States Department of the Treasury (Citation2021a).5 Congressional representation per million residents is calculated as #ofRepresentativess+#ofSenato","PeriodicalId":47008,"journal":{"name":"Spatial Economic Analysis","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135368192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-20DOI: 10.1080/17421772.2023.2254817
Philipp Otto, Osman Doğan, Süleyman Taşpınar
ABSTRACTGeo-referenced data are characterised by an inherent spatial dependence due to geographical proximity. In this paper, we introduce a dynamic spatiotemporal autoregressive conditional heteroscedasticity (ARCH) process to describe the effects of (i) the log-squared time-lagged outcome variable, the temporal effect, (ii) the spatial lag of the log-squared outcome variable, the spatial effect, and (iii) the spatiotemporal effect on the volatility of an outcome variable. We derive a generalised method of moments (GMM) estimator based on the linear and quadratic moment conditions. We show the consistency and asymptotic normality of the GMM estimator. After studying the finite-sample performance in simulations, the model is demonstrated by analysing monthly log-returns of condominium prices in Berlin from 1995 to 2015, for which we found significant volatility spillovers.Preprint: This paper is based on the preprint arXiv:2202.13856KEYWORDS: Spatial ARCHGMMvolatility clusteringvolatilityhouse price returnslocal real-estate marketJEL: C13C23P25R31 DISCLOSURE STATEMENTNo potential conflict of interest was reported by the author(s).Notes1 Note that the matrix equation ABC=D, where D, A, B, and C are suitable matrices, can be expressed as vec(D)=(C′⊗A)vec(B), where vec(B) denotes the vectorisation of the matrix B (Abadir & Magnus, Citation2005, p. 282). This property can be applied to (U1∗,U2∗,…,UT−1∗)=(U1,U2,…,UT)FT,T−1 by setting D=(U1∗,U2∗,…,UT−1∗), C=FT,T−1, B=(U1,U2,…,UT) and A=In.2 In applying Lemma 1 in the Appendix in the supplemental data online, we use the fact that tr(A′B)=vec′(A)vec(B)=vec′(B)vec(A), where A and B are any two N×N matrices.3 The explicit forms of D1N and D2N are given in Section C of the Appendix.4 Note that when t=1, we may simply use H1=c1((In−1T−1∑h=1T−1Ah)Y0∗−1T−1∑r=1T−1(∑h=0T−r−1Ah)S−1(Xrβ0+αr,01n)).5 Note that when T is large, μ~0=(μ0+μϵ1n) can be estimated by μ~ˆN=1T∑t=1T(ϑˆt−1n1n′ϑˆt1n).
{"title":"Dynamic spatiotemporal ARCH models","authors":"Philipp Otto, Osman Doğan, Süleyman Taşpınar","doi":"10.1080/17421772.2023.2254817","DOIUrl":"https://doi.org/10.1080/17421772.2023.2254817","url":null,"abstract":"ABSTRACTGeo-referenced data are characterised by an inherent spatial dependence due to geographical proximity. In this paper, we introduce a dynamic spatiotemporal autoregressive conditional heteroscedasticity (ARCH) process to describe the effects of (i) the log-squared time-lagged outcome variable, the temporal effect, (ii) the spatial lag of the log-squared outcome variable, the spatial effect, and (iii) the spatiotemporal effect on the volatility of an outcome variable. We derive a generalised method of moments (GMM) estimator based on the linear and quadratic moment conditions. We show the consistency and asymptotic normality of the GMM estimator. After studying the finite-sample performance in simulations, the model is demonstrated by analysing monthly log-returns of condominium prices in Berlin from 1995 to 2015, for which we found significant volatility spillovers.Preprint: This paper is based on the preprint arXiv:2202.13856KEYWORDS: Spatial ARCHGMMvolatility clusteringvolatilityhouse price returnslocal real-estate marketJEL: C13C23P25R31 DISCLOSURE STATEMENTNo potential conflict of interest was reported by the author(s).Notes1 Note that the matrix equation ABC=D, where D, A, B, and C are suitable matrices, can be expressed as vec(D)=(C′⊗A)vec(B), where vec(B) denotes the vectorisation of the matrix B (Abadir & Magnus, Citation2005, p. 282). This property can be applied to (U1∗,U2∗,…,UT−1∗)=(U1,U2,…,UT)FT,T−1 by setting D=(U1∗,U2∗,…,UT−1∗), C=FT,T−1, B=(U1,U2,…,UT) and A=In.2 In applying Lemma 1 in the Appendix in the supplemental data online, we use the fact that tr(A′B)=vec′(A)vec(B)=vec′(B)vec(A), where A and B are any two N×N matrices.3 The explicit forms of D1N and D2N are given in Section C of the Appendix.4 Note that when t=1, we may simply use H1=c1((In−1T−1∑h=1T−1Ah)Y0∗−1T−1∑r=1T−1(∑h=0T−r−1Ah)S−1(Xrβ0+αr,01n)).5 Note that when T is large, μ~0=(μ0+μϵ1n) can be estimated by μ~ˆN=1T∑t=1T(ϑˆt−1n1n′ϑˆt1n).","PeriodicalId":47008,"journal":{"name":"Spatial Economic Analysis","volume":"166 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135569233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-09DOI: 10.1080/17421772.2023.2261464
Xudong Chen, Bihong Huang, Yantuan Yu
ABSTRACTThis study examines the impacts of political competition on eco-efficiency. We first develop a theoretical model in which local government officials compete against each other to maximise their own political score. We find that after an initial stage of decline, eco-efficiency eventually turns upwards, once environmental performance becomes a meaningful component of local government officials’ annual assessment. Eco-efficiency also exhibits a pattern of convergence. Lastly, the level of political competition is found to be negatively correlated with eco-efficiency. For the empirical analysis, we use a data envelopment analysis (DEA) model to compute the eco-efficiency level for 191 Chinese cities from 2003 to 2015. Our empirical evidence presents a ‘U’-shape pattern in the trend of eco-efficiency and identifies two peer effects that work in opposite directions: the incentivising effect arising from higher performing neighbours, and the disincentivising effect when a city outperforms its competitors. Both peer effects lead to convergence in eco-efficiency, and our spatial econometric modeling analysis suggests that the net peer effect is significantly positive. We also find evidence of political competition reducing eco-efficiency, as predicted in the theoretical model. Our findings are robust to alternative measures of eco-efficiency.KEYWORDS: peer effectpolitical competitioneco-efficiencyspatial analysisChinaJEL: C61C67Q56R15 DISCLOSURE STATEMENTNo potential conflict of interest was reported by the authors.Notes1 This body of research, known as the environmental Kuznets curve (EKC) literature, has been enormously influential. The work by Grossman and Krueger (Citation1995) is widely regarded as one of the earliest attempts at EKC hypotheses. For an extensive overview of theoretical studies and empirical evidence regarding EKC, see Kaika and Zervas (Citation2013).2 The term ‘eco-efficiency’ is a concept and philosophy geared toward sustainability, combining ecological and economic efficiency.3 The pollution haven hypothesis was first developed by Pethig (Citation1976) and McGuire (Citation1982), and later improved by Copeland and Taylor (Citation1994) and Levinson and Taylor (Citation2008), among others.4 For example, in its National 10th Five-Year Plan (2001–05), released in 2001, the central government for the first time added environmental protection and pollution reduction to its list of ‘national strategic goals’, and set a target to reduce pollutant discharges by 10% by the end of 2005. Under the new regulation framework, each province was assigned a specific target, and the provincial government officials were to be evaluated on, among other things, how well these targets were met. However, little improvement in environmental quality has been observed in China based on data between 1998 and 2008, because the pollution mandates imposed by the central government have triggered strategic polluting responses from the provinces (Cai et
{"title":"Peer effect, political competition and eco-efficiency: evidence from city-level data in China","authors":"Xudong Chen, Bihong Huang, Yantuan Yu","doi":"10.1080/17421772.2023.2261464","DOIUrl":"https://doi.org/10.1080/17421772.2023.2261464","url":null,"abstract":"ABSTRACTThis study examines the impacts of political competition on eco-efficiency. We first develop a theoretical model in which local government officials compete against each other to maximise their own political score. We find that after an initial stage of decline, eco-efficiency eventually turns upwards, once environmental performance becomes a meaningful component of local government officials’ annual assessment. Eco-efficiency also exhibits a pattern of convergence. Lastly, the level of political competition is found to be negatively correlated with eco-efficiency. For the empirical analysis, we use a data envelopment analysis (DEA) model to compute the eco-efficiency level for 191 Chinese cities from 2003 to 2015. Our empirical evidence presents a ‘U’-shape pattern in the trend of eco-efficiency and identifies two peer effects that work in opposite directions: the incentivising effect arising from higher performing neighbours, and the disincentivising effect when a city outperforms its competitors. Both peer effects lead to convergence in eco-efficiency, and our spatial econometric modeling analysis suggests that the net peer effect is significantly positive. We also find evidence of political competition reducing eco-efficiency, as predicted in the theoretical model. Our findings are robust to alternative measures of eco-efficiency.KEYWORDS: peer effectpolitical competitioneco-efficiencyspatial analysisChinaJEL: C61C67Q56R15 DISCLOSURE STATEMENTNo potential conflict of interest was reported by the authors.Notes1 This body of research, known as the environmental Kuznets curve (EKC) literature, has been enormously influential. The work by Grossman and Krueger (Citation1995) is widely regarded as one of the earliest attempts at EKC hypotheses. For an extensive overview of theoretical studies and empirical evidence regarding EKC, see Kaika and Zervas (Citation2013).2 The term ‘eco-efficiency’ is a concept and philosophy geared toward sustainability, combining ecological and economic efficiency.3 The pollution haven hypothesis was first developed by Pethig (Citation1976) and McGuire (Citation1982), and later improved by Copeland and Taylor (Citation1994) and Levinson and Taylor (Citation2008), among others.4 For example, in its National 10th Five-Year Plan (2001–05), released in 2001, the central government for the first time added environmental protection and pollution reduction to its list of ‘national strategic goals’, and set a target to reduce pollutant discharges by 10% by the end of 2005. Under the new regulation framework, each province was assigned a specific target, and the provincial government officials were to be evaluated on, among other things, how well these targets were met. However, little improvement in environmental quality has been observed in China based on data between 1998 and 2008, because the pollution mandates imposed by the central government have triggered strategic polluting responses from the provinces (Cai et ","PeriodicalId":47008,"journal":{"name":"Spatial Economic Analysis","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135142197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-27DOI: 10.1080/17421772.2023.2252691
Paul Elhorst, Ugo Fratesi, Maria Abreu, Pedro Amaral, Steven Bond-Smith, Coro Chasco, Luisa Corrado, Jan Ditzen, Daniel Felsenstein, Franz Fuerst, Vassilis Monastiriotis, Francesco Quatraro, Dimitrios Tsiotas, Jihai Yu
This editorial summarises the papers in issue 18(4) (2023). The first paper investigates attitudes towards civic engagement in relation to living closer to individuals with the same social status. The second paper develops a Bayesian estimator of a dynamic multivariate spatial ordered probit (DMSOP) model. The third paper examines the impact of drug-related activities on violent crime. The fourth paper web-scrapes data from individual firms to provide a better understanding of the determinants of innovation. The fifth paper tests the forecasting performance in post-crises years of spatial dynamic panel data (SDPD) models reformulated in first-differences. The sixth paper applies a count-data econometric model to explain early-stage (GE) business creation. The seventh paper examines patient migration flows among cantons and hospitals using a gravity model extended with spatial lags and a hospital efficiency score as an explanatory variable. The eighth paper studies whether the decision to migrate to pursue a tertiary education negatively affects student achievement at the university level as migration distance increases.
{"title":"Raising the bar (final)","authors":"Paul Elhorst, Ugo Fratesi, Maria Abreu, Pedro Amaral, Steven Bond-Smith, Coro Chasco, Luisa Corrado, Jan Ditzen, Daniel Felsenstein, Franz Fuerst, Vassilis Monastiriotis, Francesco Quatraro, Dimitrios Tsiotas, Jihai Yu","doi":"10.1080/17421772.2023.2252691","DOIUrl":"https://doi.org/10.1080/17421772.2023.2252691","url":null,"abstract":"This editorial summarises the papers in issue 18(4) (2023). The first paper investigates attitudes towards civic engagement in relation to living closer to individuals with the same social status. The second paper develops a Bayesian estimator of a dynamic multivariate spatial ordered probit (DMSOP) model. The third paper examines the impact of drug-related activities on violent crime. The fourth paper web-scrapes data from individual firms to provide a better understanding of the determinants of innovation. The fifth paper tests the forecasting performance in post-crises years of spatial dynamic panel data (SDPD) models reformulated in first-differences. The sixth paper applies a count-data econometric model to explain early-stage (GE) business creation. The seventh paper examines patient migration flows among cantons and hospitals using a gravity model extended with spatial lags and a hospital efficiency score as an explanatory variable. The eighth paper studies whether the decision to migrate to pursue a tertiary education negatively affects student achievement at the university level as migration distance increases.","PeriodicalId":47008,"journal":{"name":"Spatial Economic Analysis","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135537774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-06DOI: 10.1080/17421772.2023.2237067
Markus J. Fülle, Philipp Otto
ABSTRACT Spatial GARCH models, like all other spatial econometric models, require the definition of a suitable weight matrix. This matrix implies a certain structure for spatial interactions. GARCH-type models are often applied to financial data because the conditional variance, which can be translated as financial risks, is easy to interpret. However, when it comes to instantaneous/spatial interactions, the proximity between observations has to be determined. Thus, we introduce an estimation procedure for spatial GARCH models under unknown locations employing the proximity in a covariate space. We use one-year stock returns of companies listed in the Dow Jones Global Titans 50 index as an empirical illustration. Financial stability is most relevant for determining similar firms concerning stock return volatility.
{"title":"Spatial GARCH models for unknown spatial locations – an application to financial stock returns","authors":"Markus J. Fülle, Philipp Otto","doi":"10.1080/17421772.2023.2237067","DOIUrl":"https://doi.org/10.1080/17421772.2023.2237067","url":null,"abstract":"ABSTRACT Spatial GARCH models, like all other spatial econometric models, require the definition of a suitable weight matrix. This matrix implies a certain structure for spatial interactions. GARCH-type models are often applied to financial data because the conditional variance, which can be translated as financial risks, is easy to interpret. However, when it comes to instantaneous/spatial interactions, the proximity between observations has to be determined. Thus, we introduce an estimation procedure for spatial GARCH models under unknown locations employing the proximity in a covariate space. We use one-year stock returns of companies listed in the Dow Jones Global Titans 50 index as an empirical illustration. Financial stability is most relevant for determining similar firms concerning stock return volatility.","PeriodicalId":47008,"journal":{"name":"Spatial Economic Analysis","volume":" ","pages":"92 - 105"},"PeriodicalIF":2.3,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48614093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-31DOI: 10.1080/17421772.2023.2242897
A. C. Aydinoglu, S. Sisman
{"title":"Comparing modelling performance and evaluating differences of feature importance on defined geographical appraisal zones for mass real estate appraisal","authors":"A. C. Aydinoglu, S. Sisman","doi":"10.1080/17421772.2023.2242897","DOIUrl":"https://doi.org/10.1080/17421772.2023.2242897","url":null,"abstract":"","PeriodicalId":47008,"journal":{"name":"Spatial Economic Analysis","volume":"1 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"60064147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-29DOI: 10.1080/17421772.2023.2235377
David Castells‐Quintana, Paula Herrera-Idárraga, L. Quintero, Guillermo Sinisterra
This paper examines the efficacy of government-mandated mobility restrictions on curbing urban mobility, paying special attention to spatial heterogeneity in lockdown compliance. In particular, it explores the role of cash subsidies disbursed during lockdown as well as socio-economic differences across neighbourhoods to explain their unequal response to mobility restrictions. To do so, it relies on novel data showing changes in movement at highly disaggregated spatial levels in Bogotá, before and during the first wave of the COVID-19 pandemic, matched with data on socio-economic characteristics and non-pharmaceutical interventions implemented in the period of analysis. Findings indicate that the general lockdown imposed in the city significantly reduced mobility (by about 41 percentage points). In terms of the unequal response across locations, the findings indicate that low-income areas with higher population density, informality and overcrowding reacted less to mobility restrictions. In this regard, despite government efforts, the findings indicate that cash subsidies were not sufficient to make compliance easier in low-income neighbourhoods.
{"title":"Unequal response to mobility restrictions: evidence from COVID-19 lockdown in the city of Bogotá","authors":"David Castells‐Quintana, Paula Herrera-Idárraga, L. Quintero, Guillermo Sinisterra","doi":"10.1080/17421772.2023.2235377","DOIUrl":"https://doi.org/10.1080/17421772.2023.2235377","url":null,"abstract":"This paper examines the efficacy of government-mandated mobility restrictions on curbing urban mobility, paying special attention to spatial heterogeneity in lockdown compliance. In particular, it explores the role of cash subsidies disbursed during lockdown as well as socio-economic differences across neighbourhoods to explain their unequal response to mobility restrictions. To do so, it relies on novel data showing changes in movement at highly disaggregated spatial levels in Bogotá, before and during the first wave of the COVID-19 pandemic, matched with data on socio-economic characteristics and non-pharmaceutical interventions implemented in the period of analysis. Findings indicate that the general lockdown imposed in the city significantly reduced mobility (by about 41 percentage points). In terms of the unequal response across locations, the findings indicate that low-income areas with higher population density, informality and overcrowding reacted less to mobility restrictions. In this regard, despite government efforts, the findings indicate that cash subsidies were not sufficient to make compliance easier in low-income neighbourhoods.","PeriodicalId":47008,"journal":{"name":"Spatial Economic Analysis","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45190100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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