公司金融中的内生性问题：处理方法与进展连玉君中山大学 岭南学院电邮：arlionn163.com2015年5月9日 山东大学峦撬轴佐啪逝邻揍滚己绩永杠范州擞辑咙砧瞳货衰倚培格撅蛇材聘箍瞄嘱公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展 提纲公司金融中的内生性问题：如此之多！内生性问题的来源遗漏变量 (模型设定偏误)衡量偏误(变量的衡量)联立方程组 (双向因果)内生性问题的处理方法IV-GMM面板数据模型(Panel Data)Heckman 选择模型、Treatment effect 模型倍分法 (DID)、倾向得分匹配分析 (PSM)自然实验：断点回归设计 (RDD)结构方程模型 (SEM)投稿时，我怕被问及审稿时，我乐于问及“内内生生性性问问题题”森辰盯刑兜着鲤裸逞矮获暂钵苦湃纫臻伶婪拇掺是诉揍弦果勿乳甘供痊甄公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展公司金融中的内生性问题：如此之多!一些值得考虑的问题相关关系 因果关系？自然实验一些潜伏着内生问题的研究主题资本结构、投资行为、现金持有、公司价值(Tobins Q )股权结构与公司价值 (maybe伪回归)经营绩效与社会责任 (因果关系不明朗)投资-现金流敏感性 (衡量偏误)股权激励、内部控制 (self-selection)建立政治关联有助于改善公司业绩吗？ (self-selection)交叉上市具有治理效应吗？ (self-selection)撬萝冷获办财废制赤印忿惟遁凝吧蛆睁卸妨姬姑助系清蔑柞郭气四瞄方抑公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展内生性：在回归分析中，干扰项和解释变量相关回顾：确保估计量具有一致性的条件随机抽样 满秩 外生 内生性的后果统计角度而言：OLS (MLE) 估计结果有偏 (不是我们想要的结果)实践角度而言：经验结果存在多种可能的解释 (并非“因果”推断) 审稿人可以提出多种可能导致你的实证结果的解释何谓内生性？ 多数人的处理方法:摆 Pose !脯梁虽告绢晤祟圾搽冒凛挞爵澎乙银呐袜尉查晒乔跺跪吃糖锈底朗噪镀绎公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展内生性问题的可能来源互为因果资本结构、投资行为、现金持有、Tobins Q 遗漏变量理论分析和前期文献中提到的重要变量自我选择偏误衡量偏误Fazzari et al. (1988, JEL): 投资-现金流敏感性 Refs：Fazzari et al. (1988) |JEL|，Kaplan and Zingales (1997) |QJE|， Fazzari et al. (2000) |QJE|，Kaplan and Zingales (2000) |QJE|， Erickson and Whited (2000) |JPE|，Alti (2003) |JF|诊冀驰剁弯疟布眼舌涂型错巩豪抗鹊挎吕励嗡葵施尔墨墙迪嗽巴滔铲卷疚公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展评论：多数情况下，遗漏变量是我们的 |无奈之举|更多的情况下，我们都表现为 |过度自信| 或 |掩耳盗铃| 解决方法：尽量使用“丰满”一点的模型(要熟悉相关理论和文献)IV or GMM (如何找？)遗漏变量Omitted Variable bias: 简介？淳暇研蜂院择校驶僧桐传棚威萨绎匙炔逐烦哗成乔砂梳验嫉补劲矽丘雍学公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展房租的决定因素Q1: 是否存在内生性问题？A1: 有可能，政策变量可能被遗漏了.Q2: 怎么办？A1: IV, 家庭收入 IncomeA2: IV, 地区虚拟变量 d1, d2, d3, 遗漏变量Omitted Variable bias: 一个例子防观岔瓷逸邹沫钢践唱捏穆宣扯仁割茄辜榨龋属缴亨密停涅风平洋溪万猩公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展 Stata commands: eivreg | sem | logitem | simex | cme | Ewreg | XTEWreg衡量偏误Measurement Error (ME): 简介涟场憎晒鸡淋浓钞滤秘院绅著楼貉混谗砖俏晚抗痊槛午限苫慷陌殴颤仑办公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展融资约束假说与投资-现金流敏感性Fazzari et al. (1988) |JEL|，Kaplan and Zingales (1997) |QJE|，Fazzari et al. (2000) |QJE|，Kaplan and Zingales (2000) |QJE|，Erickson and Whited (2000) |JPE|，Alti (2003) |JF|, Erickson and Whited (2012) |RFS|T. Whited 的处理方法: Higher Order Moments GMM (HGMM) | Signs Estimator (SigE)Erickson and Whited(2012) |RFS| Average q v.s. Marginal q对比了 HGMM, Dynamic Panel Data, IV 提出了 Minimum Distance Technique (Stata codes)Stata commands: | Ewreg | XTEWreg | 衡量偏误Measurement Error (ME): 一场争论诬瀑场掐提忿室膜躲黑英里里凭羚倦诡踞景赎齿柒瘪摹廷戌狡早稿饭粮泣公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展研究设计和模型设定：从根源上理清内生性问题工具变量法与GMM估计(IV-GMM)面板数据模型 (Panel Data Models)Heckman 选择模型、Treatment effect 模型倍分法 (DID)倾向得分匹配分析 (PSM)断点回归设计 (RDD)结构方程模型（SEM）内生性问题的处理方法狡李讹她餐欧洛姓颊乔召吗再蜜制筋池拒玲氧斤笋余纪蛰阵石卞照灾渐斑公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展模型设定理论依据前期文献中普遍使用的模型设定控制变量的选取关键指标的界定和衡量方法(自控能力、文化、父母健康、公司业绩)数据类型(线性回归、离散选择、计数模型、面板)离群值的处理结构变化排他性解释(均值回复与动态权衡、11合一的事件研究)稳健性检验(结论的适用范围、结果的敏感性)碘厄颈窜提勃再址虎丝绿恩跑唆魏萍校捅氖磋沤洱躇欣青豪踞高欧兼玫宜公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展IV-GMM 估计 y = a + X + ZIV：假设 Corr(Z, ) = 0，一夫一妻2SLS：假设 Corr(Z, ) = 0，一夫多妻第一阶段的回归只是在分配 Z1, Z2 的与 X 之间关系的权重GMMEZ1 = 0, EZ2 = 0, Stata commands: ivregress | ivreg2 | gmm 磋惑译婉赠袭急汹新缉状宅效珊疵豢零依戍码秩狼缨韭楞袁躁迈携察短陀公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展xOLS2SLSw1w2w3GMMIVw1w2w3侍特嘉煮有底杏硅袒亚怜擂蝴南舆上梭蜕鹃兵韦蛊审郴战瞅瓤逞播铰咨状公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展IV2SLSStage1: reg X on Z, get X_hatStata2: reg Y on X_hat, get This is wrong!正确设定: ivregress 2sls y x1 x2 (x3 x4 = z1 z2 z3)IV-2SLS 估计臆憎想岿滚是浴澳叶谱崎勇戏烤玲旨保泞装漠辕肉梳去丙苗尤嫂卧翟扩迷公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展Moment Condition (MC, 矩条件)样本矩条件(SMC)目标函数GMM 估计Lars Peter Hansen置爵漫酷腿巳侗双煽煌反扣渴荷柄添失徒间扦旗蓖投兆遥冤校剧宙模望砷公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展固定效应模型Fixed Effects Model (FE)模型设定 ai : CEO 特征, 公司文化等Stata commands: xtreg, fe | xi: regress i.id舔唯聊霄头云辐盈泥脾避败烃街刚毁陡误埋滴埂街贷皮衣魔儡艇噎臼钡顺公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展OLS估计的问题FE估计的基本思想一阶差分变换: 组内去心变换：固定效应模型Fixed Effects Model (FE)？站锅盯溯浓希簧蔫澜恬倍芬拟袄免立集呻梯语黍啪唁仙荣辨灭朵淬捞奥讹公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展应用Flannery and Rangan (2006) |JFE|，资本结构的动态调整Lemmon et al. (2008) |JF|，资本结构的动态调整Malmendier et al.(2011) |JF|，经理人特征(早期经历)与财务决策Graham et al.(2012) |RFS|，经理人特征与高管薪酬叶德珠 等(2012) |经济经济研究研究|，国家文化与居民消费行为Petersen(2009) |RFS|，面板模型中标准误的估计固定效应模型Fixed Effects Model (FE)砷汰襄遍吏繁梭岁宰王殊奶昨盛溉丫题栓拜沈乒稼庶案败湃裙儿焊刁玻毗公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展动态面板模型Dynamic Panel Data Models模型设定 (1) | 资本结构、投资行为、现金持有 (2) | 递归特征 (3) | 一阶差分,可以去除个体效应 | OLS, FE 估计量都是有偏的，要采用 GMM | IVs for yit1: ？ | OLS, FE 估计量都是有偏的，要采用 GMMStata commands: xtabond | xtdpdsys | xtdpd | xtlsdvc | xtregdhp | xtabond2？豺漫汾魏振角旷校尤渍忧颂佩需溺性炭齐模鼻液妈砧坡莲宗柄摧二绿稀纬公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展应用Aghion et al.(2009) |JM|，汇率波动、金融发展与生产率(规范)Brown et al.(2009) |JF|，金融创新与企业成长(规范)Wintoki et al.(2012) |JFE|，非常细致地探讨了公司治理中的内生性问题，对各种动态面板估计方法进行了非常深入的对比分析(综合)Flannery and Hankins(2013) |JCF|，综述:公司金融中的动态面板估计方法动态面板模型Dynamic Panel Data Models碴衰舰尿咀腾狰盆锻脚委蔫各妊谱神幕坍逞叭全凰剐谈骡季四栗壶讶例茧公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展长差分估计法(long-difference, LD)Hahn et al.(2007) |JE|，适用于 T 较小，y 持续性较强的动态面板Huang and Ritter(2009) |JFQA|，应用：资本结构调整速度估算Han-Phillips dynamic panel data modelHan and Phillips(2010) |ET|，Linear Dynamic Panel Data Regression 适用于y 持续性较强的动态面板，Panel Unit Root Test分位数动态面板模型 (Quantile Dynamic Panel Data)Galvao(2011) |ET|，Quantile regression for dynamic panel data面板VAR模型 (Panel VAR models)Holtz-Eakin et al.(1988) |Etrica|；Arellano and Bond(1991) |RES| ；Love and Zicchino(2006) |QREF|Stata commands: xtregdhp | gmm | pvar | pvar2 | xtvar动态面板模型Dynamic Panel Data Models：进展烛崔概宿脉芜缨陪该豺痪番翼盈守败形媚骏报拜诣辱俺拉袱丈妮她衅挠醉公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展Lee, L.-f., J. Yu, 2010, A spatial dynamic panel data model with both time and individual fixed effects, Econometric Theory, 26 (02), pp. 564-597.Yu, J., R. de Jong, L.-f. Lee, 2012, Estimation for spatial dynamic panel data with fixed effects: The case of spatial cointegration, Journal of Econometrics, 167 (1), pp. 16-37.Lee, L.-f., J. Yu, 2010, Some recent developments in spatial panel data models, Regional Science and Urban Economics, 40 (5), pp. 255-271. (综述)Yu, J., L.-f. Lee, 2012, Convergence: A spatial dynamic panel data approach, Global Journal of Economics, 1 (1), pp. forthcoming. (应用：经济收敛)Lee, L.-f., J. Yu, 2011, Estimation of spatial panels, Now Publishers Inc. (Book)空间动态面板模型Spatial Dynamic Panel Data Models援哑漂急禁臆氯莫朽斡奎棠嘴饲观俏漱姨咱筛肖他企饭骡秋纤馒撂冷迈珍公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展倍分法Difference-In-Difference (DID)房地产调控政策(限价)有效吗？Stata commands: diff | did3 | regress20092011Difference 广州(限价)16,00020,000 4,000 东莞(不限价)12,00017,000 5,000 Difference-1,000磕炙痞凡毙搪烘歇噬赵辩舜镊笔扶削待浅枣糖那虾同殊示菠帜溯髓哲辩篆公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展关键问题配对样本的选择：二者随时间自然变化的部分应相同PSM + DID面板数据：多次调控(Treat)倍分法Difference-In-Difference (DID)屉辜钝各逃壁稚缕嚎象宴皱圾漠熄跨凛弃夷扭喘记建烁挥俱知稽醒椎处摧公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展倍分法Difference-In-Difference (DID)应用Cooper et al. (2005) |JF|，基金更名行为的影响Villalonga (2004) |FM|，多元化经营，DID，HeckmanChhaochharia and Grinstein (2009) |JF|，萨班斯法案与 CEO 薪酬Frsard (2010) |JF|，产品市场竞争与现金持有Black and Kim (2012) |JF|, 董事会结构与公司价值, DID, 2SLS, 3SLS都房已鹏乡毋琳看汗押锑峡阶德拷榨班攻勇块滋远截殴店嘴格障鸟谆勘奈公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展倾向得分匹配分析Propensity Score Matching Method (PSM) 为何要配对？ 传统匹配方法：多维(规模、行业、盈利能力)PSM：Logit 模型，多维 一维 PS 值Stata commands: teffects | pscore | psmatch2 | nnmatch | psmatch | diff | psmatch | ccmatch | cem袖髓剂剪缨旱握卒斌关僵询顽扭卡款质累雨贞漏之卿旺业盒主典佑闭谢撵公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展非股权激励非股权激励 公司公司基本思路：股权激励公司股权激励公司匹配公司匹配公司匹配指标: Propensity Score (PS 值) Logit(Size, Industry, ROA, Leverage, Ownership, .) PS 值 降维：多维 一维倾向得分匹配分析Propensity Score Matching Method (PSM) 怂咕得腋账捶碘脾白动恤谣烩土闻植瓢庐氯行尽切婿遣注欧绰诅浅笔裳糜公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展最近邻匹配半径匹配核匹配用所有 Control 组公司的加权平均 虚构出一个配对公司C1TC2倾向得分匹配分析Propensity Score Matching Method (PSM) 鸣墅谷刨无享悸耗丛炬义泊愤坪棵茵磨膀观终馒猛瓢枚蛰建电髓犹现夜概公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展应用Cooper et al. (2005) |JF|，基金更名行为的影响Hellmann et al. (2008) |RFS|，银企关系Campello et al. (2010) |JFE|，金融危机中 CFO 如何应对Faulkender and Yang (2010) |JFE|，经理人薪酬激励Michaely and Roberts (2012) |RFS|，私营企业的股利支付行为倾向得分匹配分析Propensity Score Matching Method (PSM) 销脊脚低穷瑚关散独芥彪髓竟族雅舜泰粟曳诱尿每描幕需恳胀君涸莹磕纱公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展自选择模型Self-Selection Models问题的根源：被解释变量(y)中经常包含缺漏值Case I: 随机缺漏Case II: 非随机缺漏(无法观察到)例如, y = 公司的研发支出；高管的在职消费；公司的游说支出模型设定(Heckman selection model)回归方程选择方程: y is observed only if 郸赴婴而灵拱寄毁吴吱庄悍豌骄巾冬够啡屏块忍嘲共梭夯尖涝更消脸损擒公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展处理效应模型Treatment Effect Models模型设定：解释变量中包含一个内生的 0/1 变量Stata commands: etregress | heckman | ivprobit | cmp| itreatreg | mtreatreg | etpoisson | treatoprobit| etpoisson 全眨否逼疾靡搏霸巴宝锰锑驳少猿宠宜骗惯饲棍糠测脏煮兜嫌弹篮蛀杆毛公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展应用Laeven and Levine (2007) |RFS|，多元化折价Gompers et al. (2010) |RFS|，双重股权公司Ayyagari et al. (2010) |RFS| , 非正规融资，中国Ross (2010) |RFS| , 主导银行效应Core and Guay (2001) |JFE|，股权激励Lee and Masulis (2009) |JFE|，二次发行Masulis and Mobbs (2011) |JF|， 独立董事市场处理效应模型Treatment Effect Models充售乞悸诬兄餐让见丧瘪掷计忘随冯梁德被穿庆掳讨厨寿晒猩撤尉集悼胜公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展断点回归设计 Regression Discontinuity Designs (RDD)RDD: 接近于自然实验的研究方法Stata commands: | rd | rdrobust | rdcv粒惦礁激颜碌漓孺届吉躇住孵清做崭等提粱乔悔栏烛邀苏蚜爸招鲍壬守搀公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展RDDSource: Lee and Lemieux (2010, |JEL|, Figure. 1)却楚厨互铬形逆崩曹比蒂棺碌世税吴朴设巷娱宏但屯谆澈兢戚廷窒鸟畸茎公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展惮札椿哦秃德颅选沽浩箱钓雄霞迹媒扩舟毗缝铜患媚棚室萨帖股住废酶糟公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展Notes: 横轴为驱动变量 上一届选举中执政党与在野党票数比重之差 纵轴为结果变量 下一届选举中执政党获得的选票比重Source: Lee and Lemieux (2010, |JEL|, Figure. 7)橡漳洞赂端蔬榴廊阐入勒鞘延捎锈纪缸妮帘侍裁喂回赚氰酪涩坏盒跑器撂公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展断点回归设计 Regression Discontinuity Designs (RDD)应用Chava and Roberts (2008) |JF|，债务契约与投资行为Roberts and Sufi (2009) |JF|，控制权与资本结构Iliev (2010) |JF|，萨班斯法案对融资成本、盈余管理和股价的影响Garmaise and Natividad (2010) |RFS|，信息不对称与融资成本Cuat et al.(2010) |NBER|，公司治理与股东价值(股东年会投票数据)Baker et al.(2011) |JFE|，参考价格与兼并收购行为党琉疥尊及庭侠倒判榨浑血患亏桑赢越椽弹享窝竿扛厉竟揣啄仿纠匹卡夯公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展对于实证分析的建议清晰界定你所研究的问题(重要的、有意义的)数据总是有缺陷的，要通过巧妙的研究设计来保证统计推断的可靠性e.g. Fazzari et al. (1988), 投资-现金流敏感性 融资约束假说方法的实现不是问题，关键在于要选择合适的方法研究设计：制度背景的深刻理解(很重要！)内生性问题的来源与后果(避免摆 Pose)采用何种方法能够恰当地进行统计推断 (多种方法的配合使用)特殊的事件、特殊的数据：尽量接近于自然实验贺滴弗磁汰昏颇踏彝颇灶兑佃晚晴玲葫缝带司朵撅慈宵扔饿尿臼蕾咎唤宣公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展让我们的实证研究实证研究更接近于自然实验自然实验 特蜜扶赠细勾吕楞珠伐茄菲晴垦贫梆耘囱瞻香榷垂莎蜘忿靡寸砍扩比牌驹公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展附内生性问题综述Wintoki et al. (2008)；Coles et al. (2007)； Tucker (2011)；Lee (2005)Roberts and Whited (2011)；Imbens and Wooldridge (2009)Imbens and Lemieux(2008) JE, RDDLee and Lemieux(2010) JEL, RDD相关模型和方法的Stata实现过程及范例IV-GMM估计：Stata高级视频 B4_IV_GMM静态面板数据模型和动态面板数据模型：Stata高级视频 B7_Panel面板门槛模型：Stata学术论文视频 (说明书)Hansen_1999(附带Stata命令 xtthres)倾向得分匹配分析PSM：Stata学术论文视频 (说明书) Lian_2012_PSM古花铬享滋亮亏紊霞谨臀桶傍达疵返抑案音蛹亦袍激邢劫煞彩戌森埠嚣粟公司金融中的内生性问题处理方法与进展公司金融中的内生性问题处理方法与进展参考文献Aghion, P, Bacchetta P, Ranciere R, Rogoff K (2009). Exchange rate volatility and productivity growth: The role of financial development. Journal of Monetary Economics, 56 (4): 494-513.Alti, A (2003). 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