资本集聚、税收互动与纵向税收竞争

依据2003—2007年中国26个省区269个城市的面板数据,通过构造3维误差成分结构的空间计量模型,以及工具变量两步sys-GMM估计、双重固定效应法和多重空间权重矩阵设置,本文发现政府层级之间存在显著的纵向税收外部性。这种互补性质的策略互动影响不同于西方理论考虑的具有充分和稳定税收管辖权的各级政府会由于共享税基产生交互影响,而是上级政府基于政治和行政权威,面向辖内下级政府实施的具有利维坦特征的税收驱赶和"挤压"影响,是一种纵向政府层级间的"税收竞争"。     

“绿色悖论”之谜:地方政府竞争视角的解读

文章利用中国2000—2011年省级面板数据,以地方政府竞争为切入点,基于地理邻接、地理距离和经济距离三种空间权重矩阵,构造动态空间面板模型检验了环境规制对碳排放的影响。研究显示:就纯粹的环境规制而言,本地区和相邻地区的环境规制能有效遏制碳排放,且环境规制的空间策略互动表现为"竞争向上"型;而在地方政府竞争的影响下,本地区和相邻地区的环境规制则显著促进了碳排放,引发环境规制竞争的"逐底效应"和"绿色悖论"现象。因此,为了有效规避"绿色悖论"现象,必须从匡正地方政府竞争行为入手,改革"中国式分权"下的激励机制,完善环境绩效考核制度与监督体系。     

财政分权下地方政府卫生支出的竞争行为研究

分权体制框架下地级市政府在制定医疗卫生支出决策时往往会受到相邻城市相关策略的影响,从而引发城市间政府卫生支出的策略互动行为.文章选取了2007?2013年中国283个城市面板数据,运用动态空间面板模型检验了分权体制下地市级政府卫生支出的策略互动行为,并揭示出财政分权及其城市间空间策略互动对政府卫生支出的影响.研究发现,地市级政府在政府卫生支出上存在显著的互补型策略互动,这种效应在地理距离相近的同省区城市间更为显著.进一步分析发现,财政分权促进了政府卫生服务供给;而无论是短期还是长期,地市级政府间财政分权的策略互动对政府卫生支出产生明显的抑制作用,从而较好地解释了政府卫生支出比重徘徊不前的原因.由此,积极利用竞争、激励机制以及实现财政体制安排的优化变革来引导政府的卫生服务供给将是重要的政策选择.     

地方财政支出跨境溢出效应的估计及其对区域一体化的影响——基于长江三角洲城市群的实证研究

地理位置的相邻性、经济规模的相似性以及城市化水平的相似性等空间因素对一个区域内各地方的财政支出及其结构有着不容忽视的影响,直接决定着区域一体化的进程和路径。文章在理论上刻画了相邻地区之间财政支出及其结构的空间外溢效应形成机制,并以跨行政区划区域一体化的典型案例——长江三角洲城市群16个核心城市为样本,计算了地理空间和经济空间的权重矩阵,估计了各地方财政总支出的跨境溢出效应,结果发现,相邻地区的财政支出每增加1%,本地区的财政支出增加0.64%-0.72%。文章还进一步估计了各地方生产性支出的空间外溢效应及其对区域一体化的影响,以及教科文卫、社会福利等民生项目支出的空间外溢效应,为地方政府如何合作治理以推进跨行政区划的区域一体化进程提供更为细致的路径选择和突破口,扫除行政区划和地方利益所导致的一体化发展障碍。     

地方政府建设开发区:左顾右盼的选择?

开发区重复建设、无序扩张是长期以来困扰中国经济持续健康发展的重要问题.文章基于2004?2014年100个城市数据,采用空间面板模型,以国家级经开区为例从空间策略互动视角考察了地方政府热衷推动开发区建设的行为动机.研究发现:(1)中国地市级政府在建设开发区上会充分参考"邻居"城市的行为作出自身决策,并且这种空间效应在地理距离相近的同级城市间更为显著.具体而言,如果地理邻近城市平均建设10个新的开发区,本市往往会相应建立5个开发区.(2)相对东部来说,中西部城市间在建设开发区上的空间策略互动更强,并受到经济发展水平、产业结构、基础设施、人力资本等因素的影响.(3)进一步的经验检验表明,财政分权和中央政府主导下的政绩考核带动了地方政府招商引资的空间竞争,强化了地方政府推动建设开发区上的策略互动.文章的研究发现在一定程度上反映和解释了"开发区热"的本质特征,揭示了地方政府合作困境的根源.由此,应从政绩考核体制、财税体制、地方债务管理体制等方面采取有效的改革措施,严格控制地方政府过度建设开发区的盲目竞争行为.     

地方政府“土地引资”背景下的FDI挤入挤出效应研究

文章基于税收优惠空间缩小条件下地方政府为追求经济增长而将“土地引资”作为重要招商手段的现实背景,根据中国2004-2007年259个地级及以上城市数据,从理论和实证两个层面系统研究了地方政府“土地引资”行为对FDI与国内投资之间关系的附加影响.(1)理论分析表明,在最大化本地产出的目标下,地方政府有激励压低工业地价并给予高效率企业更多优惠,这种干预行为有可能会放大FDI对国内投资的挤入或挤出效应.(2)实证结果显示,样本期内“土地引资”有效地刺激了当地总投资规模增长.在全国,“土地引资”强化了FDI的挤入效应.在城市群层面,FDI在发达城市有较大的挤入效应,“土地引资”的影响作用不明显;在发展水平居中的城市,政府“土地引资”效果最显著,强化了FDI的挤入作用.在其他城市,“土地引资”及FDI对国内投资比重的影响不显著.     

中国FDI区域分布决定因素的动态演变与地理溢出程度——基于空间面板数据的实证研究

外商直接投资(Foreign Direct Investment,简称FDI)的空间依赖性已得到越来越多文献的证实,但FDI区位选择决定因素实证研究方面,大多数文献都忽略了这种空间依赖性,直接导致模型估计结果无法令人信服。文章利用最新发展的空间面板数据模型研究中国区域FDI决定因素的动态演变,在模型中纳入空间效应后,发现:①模型的估计结果比OLS估计更为稳健;②吸引FDI的传统因素依然存在,但作用已弱化,然而新经济地理所揭示的贸易成本、集聚效应等传导机制的作用日益凸现;③相邻省份的空间溢出效应显著地影响FDI的区域分布,一省FDI的增加对相邻地区FDI流入有正向影响。     

城市首位度与经济增长

利用空间面板德宾(Durbin)模型分析了城市首位度对经济增长的影响,并选择使用不同的空间权重矩阵进行检验。结果表明:城市首位度对经济增长不存在非线性关系;本地城市首位度、相邻地区经济发展水平的提高对当地经济增长都具有正向影响;在不同空间权重矩阵下,相邻地区城市首位度的提高对本地区经济增长效应不同,可能存在正向或者负向影响,但是随着使用的空间矩阵所体现的区域之间互动依赖关系增强之后,相邻地区城市首位度的提高对本地区经济增长具有正向影响并且数值稳定。     

为资本而赛跑?——城市马拉松赛事吸引FDI的实证研究

"稳外资"已经成为当前政府经济工作的一大重点,而积极有为的地方政府对于吸引FDI具有重要意义,但政府是否积极有为难以在短期内被外来投资者全面观察和准确识别到.为此,文章将举办马拉松赛事视为地方政府向外界传递"有为政府"形象的信号机制和竞争FDI的手段,并基于2009–2018年中国286个地级以上城市的面板数据,探索了城市马拉松赛事对于吸引FDI的影响.研究发现:(1)举办马拉松赛事显著促进了FDI的流入,平均而言,城市每举办一场全程马拉松赛事能够使FDI相应增加约16％;(2)举办马拉松赛事的"引资效应"在市场规模较大、政府财力较雄厚的举办城市更为明显.文章不但拓展了我们对于地方政府竞争策略以及FDI流入决定因素的理解,而且也启发城市政府应在市场发展和财力保障的基础上,积极建设成"有为政府",通过举办大型体育赛事以吸引外资流入,从而促进高质量的开放型经济发展.     

区域一体化对城市土地绿色利用效率的影响

文章基于地理空间一体化、经济空间一体化以及社会空间一体化三个维度建构区域一体化发展水平测度指标体系,通过熵值法测算区域一体化发展水平综合指数。选取2003—2020年中国30个省级面板数据,实证检验区域一体化对城市土地绿色利用效率的影响。研究发现：区域一体化发展有利于提升城市土地绿色利用效率,已成为优化国内城市土地绿色利用效率的关键引擎。中介效应检验结果表明,区域一体化不仅能直接促进城市土地绿色利用效率提高,还可经由人力资本效应与产业结构效应间接提升对城市土地绿色利用效率。据此,应当全面推进区域一体化发展,完善区域一体化基础设施建设,推动社会经济生态友好型发展,实现区域一体化与可持续发展战略共赢。     

Mixed logit estimation of willingness to pay distributions: a comparison of models in preference and WTP space using data from a health-related choice experiment

Different approaches to modelling the distribution of WTP are compared using stated preference data on Tanzanian Clinical Officers’ job choices and mixed logit models. The standard approach of specifying the distributions of the coefficients and deriving WTP as the ratio of two coefficients (estimation in preference space) is compared to specifying the distributions for WTP directly at the estimation stage (estimation in WTP space). The models in preference space fit the data better than the corresponding models in WTP space although the difference between the best fitting models in the two estimation regimes is minimal. Moreover, the willingness to pay estimates derived from the preference space models turn out to be very high for many of the job attributes. The results suggest that sensitivity testing using a variety of model specifications, including estimation in WTP space, is recommended when using mixed logit models to estimate willingness to pay distributions.     

Environmental amenities and agricultural land values: a hedonic model using geographic information systems data

Remote agricultural lands, which include wildlife habitat, angling opportunities and scenic vistas, command higher prices per hectare in Wyoming than those whose landscape is dominated by agricultural production. Geographic information systems (GIS) data are used to measure recreational and scenic amenities associated with rural land. A hedonic price model is specified with GIS measures. It is used to estimate the impact of amenity and agricultural production land characteristics on price per acre for a sample of Wyoming agricultural parcels. Results indicate that the specification performed well across several functional forms. The sampled land prices are explained by the level of both environmental amenities as well as production attributes. Statistically significant amenity variables included scenic view, elk habitat, sport fishery productivity and distance to town. This analysis permits a better estimation of environmental amenity values from hedonic techniques. Improved estimation of amenity values is vital for policies aimed at open space preservation, using agricultural conservation easements and land use conflict resolution.     

The role of unemployment in wage determination: further evidence on the wage curve from Turkey

This paper presents an empirical estimation of the correlation between wages and regional unemployment rates in Turkey, more specifically it explores the role of regional unemployment rates in wage determination. The analysis builds upon a series of recent empirical studies on the wage-unemployment relationship, now commonly known as ‘the wage curve’, a downward sloping curve in wage-unemployment space. The existing studies are for most part in advanced market economies, while this paper presents one of the few attempts at a wage curve analysis within the context of a developing market economy. A cross-sectional estimation of micro level individual wage data for the Turkish labour market in 1994, suggest a statistically significant negative correlation between wages and regional unemployment rates. Separate regressions for men and women, however, show a wage curve to exist only in the male labour market. The study also presents the results on other variables of wage determination such as returns to schooling, returns to age, job tenure, gender, industrial and occupational affiliation of the worker, economic sector and union status.     

Simultaneous-equation estimation with no instrumental variables

For a single equation in a system of linear equations, estimation by instrumental variables is the standard approach. In practice, however, it is often difficult to find valid instruments. This letter outlines a maximum-likelihood method that does not require instrumental variables; it is applied to the estimation of a demand function and an Engel curve.     

Semiparametric Estimation of Simultaneous-Equation Microeconometric Models with Index Restrictions

This article introduces semiparametric methods for the estimation of simultaneous-equation microeconometric models with index restrictions. The methods are motivated by a semiparametric minimum-distance procedure, which unifies the estimation of both regression-type and linear or nonlinear simultaneous-equation models without emphasis on the construction of instrumental variables. Single-equation and systematic estimation methods and optimal weighting procedures are considered. The estimators are √ n -consistent and asymptotically normal. For the estimation of nonparametric regression and some sample selection models where the variances of disturbances are functions of the same indices, the optimal weighted estimator attains Chamberlain's efficient bound for models with conditional moment restrictions. The weighted estimator is shown to be optimal within a class of semiparametric instrumental variables estimators.
JEL classification numbers: C14, C24, C34.     

北京市二手住宅价格影响机制--基于多尺度地理加权回归模型(MGWR)的研究

文章基于多尺度地理加权回归研究北京市2011-2017年二手住宅交易的价格特征,结果表明:①以往基于经典地理加权回归模型的研究可能存在一定的不稳健,而多尺度地理加权回归可以将不同变量对于因变量的影响尺度反映出来,其回归的结果更为可靠。②北京房价对区位因素非常敏感,且存在高度的空间异质性,区位的影响尺度是所有变量中最小的,接近于街道尺度。而卧室数量和到最近地铁站的距离为全局尺度的变量,在空间上的影响较为平稳。到公交站的距离、到小学的距离、建筑结构和装修状况对于房价的影响不显著。其他显著的变量均存在一定的空间异质性,其空间尺度由小到大分别为成交时间、面积、楼龄、楼层、朝向。③区位、朝向、卧室数量、成交时间均正向影响房价,而面积、楼龄、楼层、到地铁站的距离负向影响房价。所有影响因素中区位是影响房价的最主要因素,其次是成交时间朝向。面积成交时间、朝向和到最近地铁站的距离影响较大,所在楼层、卧室数量对于房价的影响较小,而面积和楼龄的影响最弱。     

Gravity model estimation: fixed effects vs. random intercept Poisson pseudo-maximum likelihood

The standard Anderson and van Wincoop gravity model has typically been estimated using a fixed-effects approach. However, a fixed-effects approach has a major drawback: it does not allow for the estimation of exporter- and importer-invariant variables. Thus, at least in a cross-sectional context, economically relevant variables such as exporter and importer gross domestic product are disregarded. We propose a random intercept model to address this gap. For large datasets, this approach not only provides identical estimates like a fixed-effects approach, but also allows for the estimation of exporter- and importer-invariant variables.     

Determinants of long-term growth: New results applying robust estimation and extreme bounds analysis

Two important problems exist in cross-country growth studies: outliers and model uncertainty. Employing Sala-i-Martin’s (1997a,b) data set, we first use robust estimation and analyze to what extent outliers influence OLS regressions. We then use both OLS and robust estimation techniques in applying the Extreme Bounds Analysis (EBA) to deal with the problem of model uncertainty. We find that the use of robust estimation affects the list of variables that are significant determinants of economic growth. Also the magnitude of the impact of these variables differs sometimes under the various approaches.First version received: March 2003 / Final version received: June 2004We like to thank two referees for their very helpful comments on a previous version of this paper. The usual disclaimer applies.     

Short Term Econometric Forecasting and Seasonal Adjustment

Seasonal behaviour in the variables of an econometric model is usually handled in one of two ways—either the data are adjusted prior to estimation, or seasonal binary variables are included in the specification and estimation of the model. Although the literature on the subject is extensive, it is not obvious which of these procedures is best for forecasting. This paper compares the forecasting ability of a small model of the Australian economy for each of the alternative approaches to seasonal adjustment.     

Exchange rates,and fundamental variables: a semi-parametric analysis of binary choice

This study is motivated by the dearth of models that provide good out-of-sample fit for exchange rates. That is, current models of exchange rate behaviour are poor predictors of subsequent currency movements. An attempt is made to determine if the relationship between exchange rates and fundamental variables can help explain the more extreme exchange rate movements (distributional switches). Models are developed that relate fundamental economic variables to the resulting estimates based on the mixture of normal probability distributions. Parametric estimation procedures (Logit and Probit) are compared with a semi-parametric technique, maximum score estimation (MSCORE), which is relatively untested in the field of finance. The fundamental variables of these models include information on trade balances, money supply changes, interest rate changes, real economic growth, relative inflation rates and changes in stock market indexes. Classification results favour MSCORE. Implications of results and improvements in methodology are discussed.