Minimum Divergence,Generalized Empirical Likelihoods,and Higher Order Expansions

This article studies the minimum divergence (MD) class of estimators for econometric models specified through moment restrictions. We show that MD estimators can be obtained as solutions to a tractable lower dimensional optimization problem. This problem is similar to the one solved by the generalized empirical likelihood estimators of Newey and Smith (2004 Newey , W. K. , Smith , R. J. ( 2004 ). Higher order properties of GMM and Generalized Empirical Likelihood estimators . Econometrica 72 : 219 – 255 .[Crossref], [Web of Science ®] , [Google Scholar]), but it is equivalent to it only for a subclass of divergences. The MD framework provides a coherent testing theory: tests for overidentification and parametric restrictions in this framework can be interpreted as semiparametric versions of Pearson-type goodness of fit tests. The higher order properties of MD estimators are also studied and it is shown that MD estimators that have the same higher order bias as the empirical likelihood (EL) estimator also share the same higher order mean square error and are all higher order efficient. We identify members of the MD class that are not only higher order efficient, but also, unlike the EL estimator, well behaved when the moment restrictions are misspecified.     

广义矩估计的延伸——广义经验似然估计

从广义矩估计(GMM)到广义经验似然估计(GEL)的发展,是由于GMM估计量小样本性质的不足,促使人们寻求方法的改进和拓展。通过必要的证明和推导,详细解析GEL类估计量(包括EL,ET,CUE)的逻辑关系和数理结构,认识GEL的内在本质,并运用随机模拟方法证实了在小样本场合GEL类估计量比GMM估计量具有更小的估计偏差和均方误差,即GEL类估计改进了GMM估计的小样本性质。     

GMM inference in spatial autoregressive models

In this study, we investigate the finite sample properties of the optimal generalized method of moments estimator (OGMME) for a spatial econometric model with a first-order spatial autoregressive process in the dependent variable and the disturbance term (for short SARAR(1, 1)). We show that the estimated asymptotic standard errors for spatial autoregressive parameters can be substantially smaller than their empirical counterparts. Hence, we extend the finite sample variance correction methodology of Windmeijer (2005 Windmeijer, F. (2005). A finite sample correction for the variance of linear efficient two-step GMM estimators. Journal of Econometrics 126(1):25–51.[Crossref], [Web of Science ®] , [Google Scholar]) to the OGMME for the SARAR(1, 1) model. Results from simulation studies indicate that the correction method improves the variance estimates in small samples and leads to more accurate inference for the spatial autoregressive parameters. For the same model, we compare the finite sample properties of various test statistics for linear restrictions on autoregressive parameters. These tests include the standard asymptotic Wald test based on various GMMEs, a bootstrapped version of the Wald test, two versions of the C(α) test, the standard Lagrange multiplier (LM) test, the minimum chi-square test (MC), and two versions of the generalized method of moments (GMM) criterion test. Finally, we study the finite sample properties of effects estimators that show how changes in explanatory variables impact the dependent variable.     

Markov-switching BILINEAR − GARCH models: Structure and estimation

Markov-switching (MS) models are becoming increasingly popular as efficient tools of modeling various phenomena in different disciplines, in particular for non Gaussian time series. In this articlept", we propose a broad class of Markov-switching BILINEAR–GARCH processes (MS ? BLGARCH hereafter) obtained by adding to a MS ? GARCH model one or more interaction components between the observed series and its volatility process. This parameterization offers remarkably rich dynamics and complex behavior for modeling and forecasting financial time-series data which exhibit structural changes. In these models, the parameters of conditional variance are allowed to vary according to some latent time-homogeneous Markov chain with finite state space or “regimes.” The main aim of this new model is to capture asymmetric and hence purported to be able to capture leverage effect characterized by the negativity of the correlation between returns shocks and subsequent shocks in volatility patterns in different regimes. So, first, some basic structural properties of this new model including sufficient conditions ensuring the existence of stationary, causal, ergodic solutions, and moments properties are given. Second, since the second-order structure provides a useful information to identify an appropriate time-series model, we derive the expression of the covariance function of for MS ? BLGARCH and for its powers. As a consequence, we find that the second (resp. higher)-order structure is similar to some linear processes, and hence MS ? BLGARCH (resp. its powers) admit an ARMA representation. This finding allows us for parameter estimation via GMM procedure proved by a Monte Carlo study and applied to foreign exchange rate of the Algerian Dinar against the single European currency.     

中国分行业和总体工资粘性

工资粘性是比价格粘性更加重要的名义刚性,对于分析外生冲击对宏观经济的影响具有至关重要的作用。本文从行业工资粘性的异质性入手,建立多部门DSGE模型并推导出各行业的工资动态方程;通过对行业工资动态方程的结构化GMM估计,得到了我国19个行业的工资粘性,发现各行业的工资粘性存在显著的异质性。本文进一步研究了总体工资粘性的估计问题,发现采用单部门DSGE模型估计总体工资粘性会出现高估的问题,而以各行业工资为权重计算各行业工资粘性的加权中位数可以较好的估计加总工资粘性。     

种麦农户行为选择:来自价格、政策和非农就业的综合响应检验

基于2003-2011年全国农村固定观察点数据,选用扩展Nerlove模型及系统GMM估计方法,引入市场化政策和非农就业水平等变量构建农户小麦动态供给反应模型,探究农户粮食种植决策对价格和非价格因素的反应程度。研究发现：①无论短期还是长期,农户小麦种植对价格始终保持较高的敏感程度。②非农就业在短期内对农户小麦种植直接影响结果不显著,但间接提高了农户对小麦生产成本的敏感程度,这意味着非农就业水平的提高使得生产成本对小麦的负面减产效应显著增加。③市场化政策始终是影响粮食市场价格变动及农户粮食种植决策的重要因素。因此,建议完善对粮食生产的补贴制度,通过杠杆调节冲破生产成本对粮食生产的“桎梏”,同时确定合理的粮食最低收购价水平,科学制定调整幅度,引导农户合理调整种植结构。     

基于财政分权的地方政府科技投入库兹涅茨曲线效应研究

依据2007—2016年中国省级动态面板数据,采用系统GMM估计方法,实证探讨了财政收入分权和支出分权对地方政府科技投入影响的库兹涅茨曲线效应。结果表明：样本考察期内,财政收入分权和支出分权对地方政府科技投入的影响均具有显著的倒“U”形特征,省级财政分权度的提高,显著激励地方政府扩大科技投入规模,而迈过倒“U”形曲线拐点,财政分权对地方政府科技投入的正向激励作用消失,转为负向抑制。系列控制变量中,地区经济发展水平、对外开放程度、政府竞争对地方政府科技投入具有正向激励作用,但政府竞争的影响不显著;而上一年度政府科技投入水平和城镇化水平对地方政府科技投入具有负向抑制作用,但后者的影响不显著。采用财政自给率指标替换财政分权变量进行二次回归,显示研究结果具有良好的稳健性。研究结论可为重新划分央地政府科技投入责任,完善地方官员晋升考核标准,提高财政科技资金使用效率,加大对欠发达地区财政转移支付力度,推动地区间科技投入合作提供决策参考。     

中心城市的溢出效应与城市经济增长——基于中国城市群2000—2012年市级面板数据的经验研究

在城市空间结构高级形态——城市群的框架内,基于 2000—2012 年市级面板数据,研究中心城市发展对外围城市经济增长的溢出或极化效应,结果发现:(1)针对十大城市群 136 个城市的分析证实,中心城市发展对外围城市的经济增长呈现出正向溢出效应;(2)针对不同城市群的分类分析发现,中心城市对外围地区的影响会出现 U形关系,如京津冀城市群中心城市北京的发展在 2007 年之前抑制了外围城市的经济增长,而 2007 年之后转为正向溢出效应;(3)城市群内部结构的异质性也会带来不同的结果,山东半岛城市群济南、青岛的双中心结构对外围城市的共同影响较单个城市更为显著。此外,研究结果还证实以受教育水平衡量的人力资本对以熟练劳动力为主的低端制造业地区的经济发展影响较低,政府规模对市场投资相对不足的中西部地区具有积极影响。     

信用衍生产品对冲、货币市场波动与中国商业银行贷款行为

文章基于信用衍生产品对冲的实质构建理论模型并得到理论结论与推论,利用GMM方法对理论结果进行实证检验。实证研究结果表明,在回购利率互换对冲时,中国银行贷款总额随对冲程度的提升先减后增,与货币市场波动负相关;在存款利率互换对冲时,贷款总额随对冲程度的提升而增大,与货币市场波动正相关;在隔夜利率互换对冲时,贷款总额随对冲程度的提升先增后减,与货币市场波动正相关。实证结果验证了理论模型的正确性,同时也在一定程度上说明2008年美国次贷危机的诱因同样存在于中国商业银行中。