公司金融研究中的內(nèi)生性問題

1、公司金融中的內(nèi)生性問題：處理方法與進展連玉君中山大學 嶺南學院電郵： 主頁： 微博： 2013年4月2日 提綱公司金融中的內(nèi)生性問題：如此之多！內(nèi)生性問題的來源遺漏變量 (模型設(shè)定偏誤)衡量偏誤(變量的衡量)聯(lián)立方程組 (雙向因果)內(nèi)生性問題的處理方法IV-GMM面板數(shù)據(jù)模型(Panel Data)Heckman 選擇模型、Treatment effect 模型倍分法 (DID)、傾向得分匹配分析 (PSM)自然實驗：斷點回歸設(shè)計 (RDD)投稿時，我怕被問及審稿時，我樂于問及“內(nèi)生性問題”最新課程介紹: 公司金融中的內(nèi)生性問題：如此之多!一些值得考慮的問題相關(guān)關(guān)系 因果關(guān)系？自然實驗一些潛伏

2、著內(nèi)生問題的研究主題資本結(jié)構(gòu)、投資行為、現(xiàn)金持有、公司價值(Tobins Q )股權(quán)結(jié)構(gòu)與公司價值 (maybe偽回歸)經(jīng)營績效與社會責任 (因果關(guān)系不明朗)投資-現(xiàn)金流敏感性 (衡量偏誤)股權(quán)激勵、內(nèi)部控制 (self-selection)建立政治關(guān)聯(lián)有助于改善公司業(yè)績嗎？ (self-selection)交叉上市具有治理效應(yīng)嗎？ (self-selection)最新課程介紹: 內(nèi)生性：在回歸分析中，干擾項和解釋變量相關(guān)回顧：確保估計量具有一致性的條件隨機抽樣 滿秩 外生 內(nèi)生性的后果統(tǒng)計角度而言：OLS (MLE) 估計結(jié)果有偏 (不是我們想要的結(jié)果)實踐角度而言：經(jīng)驗結(jié)果存在多種可能的解

3、釋 (并非“因果”推斷) 審稿人可以提出多種可能導致你的實證結(jié)果的解釋何謂內(nèi)生性？ 多數(shù)人的處理方法:擺 Pose !最新課程介紹: 內(nèi)生性問題的可能來源互為因果資本結(jié)構(gòu)、投資行為、現(xiàn)金持有、Tobins Q 遺漏變量理論分析和前期文獻中提到的重要變量自我選擇偏誤衡量偏誤Fazzari et al. (1988, JEL): 投資-現(xiàn)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

4、|， Erickson and Whited (2000) |JPE|，Alti (2003) |JF|最新課程介紹: 評論：多數(shù)情況下，遺漏變量是我們的 |無奈之舉|更多的情況下，我們都表現(xiàn)為 |過度自信| 或 |掩耳盜鈴| 解決方法：盡量使用“豐滿”一點的模型(要熟悉相關(guān)理論和文獻)IV or GMM (如何找？)遺漏變量Omitted Variable bias: 簡介？最新課程介紹: 房租的決定因素Q1: 是否存在內(nèi)生性問題？A1: 有可能，政策變量可能被遺漏了.Q2: 怎么辦？A1: IV, 家庭收入 eA2: IV, 地區(qū)虛擬變量 d1, d2, d3, 遺漏變量Omitted V

5、ariable bias: 一個例子最新課程介紹: Stata commands: eivreg | sem | logitem | simex | cme | Ewreg | XTEWreg衡量偏誤Measurement Error (ME): 簡介最新課程介紹: 融資約束假說與投資-現(xiàn)金流敏感性Fazzari et al. (1988) |JEL|，Kaplan and Zingales (1997) |QJE|，F(xiàn)azzari et al. (2000) |QJE|，Kaplan and Zingales (2000) |QJE|，Erickson and Whited (2000) |

6、JPE|，Alti (2003) |JF|, Erickson and Whited (2012) |RFS|T. Whited 的處理方法: Higher Order Moments GMM (HGMM) | Signs Estimator (SigE)Erickson and Whited(2012) |RFS| Average q v.s. Marginal q對比了 HGMM, Dynamic Panel Data, IV 提出了 Minimum Distance Technique (Stata codes)Stata commands: | Ewreg | XTEWreg | 衡量

7、偏誤Measurement Error (ME): 一場爭論最新課程介紹: 工具變量法與GMM估計(IV-GMM)面板數(shù)據(jù)模型 (Panel Data Models)Heckman 選擇模型、Treatment effect 模型倍分法 (DID)傾向得分匹配分析 (PSM)斷點回歸設(shè)計 (RDD)結(jié)構(gòu)方程模型（SEM）內(nèi)生性問題的處理方法最新課程介紹: IV-GMM 估計 y = a + X + ZIV：假設(shè) Corr(Z, ) = 0，一夫一妻2SLS：假設(shè) Corr(Z, ) = 0，一夫多妻第一階段的回歸只是在分配 Z1, Z2 的與 X 之間關(guān)系的權(quán)重GMMEZ1 = 0, EZ2

8、= 0, Stata commands: ivregress | ivreg2 | gmm 最新課程介紹: xOLS2SLSw1w2w3GMMIVw1w2w3最新課程介紹: IV2SLSStage1: reg X on Z, get X_hatStata2: reg Y on X_hat, get IV-2SLS 估計最新課程介紹: Moment Condition (MC, 矩條件)樣本矩條件(SMC)目標函數(shù)GMM 估計Lars Peter Hansen最新課程介紹: 固定效應(yīng)模型Fixed Effects Model (FE)模型設(shè)定 ai : CEO 特征, 公司文化等Stata co

9、mmands: xtreg, fe | xi: regress i.id最新課程介紹: OLS估計的問題FE估計的基本思想一階差分變換: 組內(nèi)去心變換：固定效應(yīng)模型Fixed Effects Model (FE)？最新課程介紹: 應(yīng)用Flannery and Rangan (2006) |JFE|，資本結(jié)構(gòu)的動態(tài)調(diào)整Lemmon et al. (2008) |JF|，資本結(jié)構(gòu)的動態(tài)調(diào)整Malmendier et al.(2011) |JF|，經(jīng)理人特征(早期經(jīng)歷)與財務(wù)決策Graham et al.(2012) |RFS|，經(jīng)理人特征與高管薪酬葉德珠 等(2012) |經(jīng)濟研究|，國家文化與居

10、民消費行為Petersen(2009) |RFS|，面板模型中標準誤的估計固定效應(yīng)模型Fixed Effects Model (FE)最新課程介紹: 動態(tài)面板模型Dynamic Panel Data Models模型設(shè)定 (1) | 資本結(jié)構(gòu)、投資行為、現(xiàn)金持有 (2) | 遞歸特征 (3) | 一階差分,可以去除個體效應(yīng) | OLS, FE 估計量都是有偏的，要采用 GMM | IVs for yit1: ？ | OLS, FE 估計量都是有偏的，要采用 GMMStata commands: xtabond | xtdpdsys | xtdpd | xtlsdvc | xtregdhp |

11、xtabond2？最新課程介紹: 應(yīng)用Aghion et al.(2009) |JM|，匯率波動、金融發(fā)展與生產(chǎn)率(規(guī)范)Brown et al.(2009) |JF|，金融創(chuàng)新與企業(yè)成長(規(guī)范)Wintoki et al.(2012) |JFE|，非常細致地探討了公司治理中的內(nèi)生性問題，對各種動態(tài)面板估計方法進行了非常深入的對比分析(綜合)Flannery and Hankins(2013) |JCF|，綜述:公司金融中的動態(tài)面板估計方法動態(tài)面板模型Dynamic Panel Data Models最新課程介紹: 長差分估計法(long-difference, LD)Hahn et al.(

12、2007) |JE|，適用于 T 較小，y 持續(xù)性較強的動態(tài)面板Huang and Ritter(2009) |JFQA|，應(yīng)用：資本結(jié)構(gòu)調(diào)整速度估算Han-Phillips dynamic panel data modelHan and Phillips(2010) |ET|，Linear Dynamic Panel Data Regression 適用于y 持續(xù)性較強的動態(tài)面板，Panel Unit Root Test分位數(shù)動態(tài)面板模型 (Quantile Dynamic Panel Data)Galvao(2011) |ET|，Quantile regression for dynami

13、c 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動態(tài)面板模型Dynamic Panel Data Models：進展最新課程介紹: Lee, L.-f., J. Yu, 2010, A spatial dynamic panel data model with both ti

14、me 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 development

15、s in spatial panel data models, Regional Science and Urban Economics, 40 (5), pp. 255-271. (綜述)Yu, J., L.-f. Lee, 2012, Convergence: A spatial dynamic panel data approach, Global Journal of Economics, 1 (1), pp. ing. (應(yīng)用：經(jīng)濟收斂)Lee, L.-f., J. Yu, 2011, Estimation of spatial panels, Now Publishers Inc.

16、 (Book)空間動態(tài)面板模型Spatial Dynamic Panel Data Models最新課程介紹: 倍分法Difference-In-Difference (DID)房地產(chǎn)調(diào)控政策(限價)有效嗎？Stata commands: diff | did3 | regress20092011Difference 廣州(限價)16,00020,000 4,000 東莞(不限價)12,00017,000 5,000 Difference-1,000最新課程介紹: 關(guān)鍵問題配對樣本的選擇：二者隨時間自然變化的部分應(yīng)相同PSM + DID面板數(shù)據(jù)：多次調(diào)控(Treat)倍分法Difference

17、-In-Difference (DID)最新課程介紹: 倍分法Difference-In-Difference (DID)應(yīng)用Cooper et al. (2005) |JF|，基金更名行為的影響Villalonga (2004) |FM|，多元化經(jīng)營，DID，HeckmanChhaochharia and Grinstein (2009) |JF|，薩班斯法案與 CEO 薪酬Frsard (2010) |JF|，產(chǎn)品市場競爭與現(xiàn)金持有Black and Kim (2012) |JF|, 董事會結(jié)構(gòu)與公司價值, DID, 2SLS, 3SLS最新課程介紹: 傾向得分匹配分析Propensity

18、 Score Matching Method (PSM) 為何要配對？ 傳統(tǒng)匹配方法：多維(規(guī)模、行業(yè)、盈利能力)PSM：Logit 模型，多維 一維 PS 值Stata commands: pscore | psmatch2 | nnmatch | psmatch最新課程介紹: 非股權(quán)激勵 公司基本思路：股權(quán)激勵公司匹配公司匹配指標: Propensity Score (PS 值) Logit(Size, Industry, ROA, Leverage, Ownership, .) PS 值 降維：多維 一維傾向得分匹配分析Propensity Score Matching Method (

19、PSM) 最新課程介紹: 最近鄰匹配半徑匹配核匹配用所有 Control 組公司的加權(quán)平均 虛構(gòu)出一個配對公司C1TC2傾向得分匹配分析Propensity Score Matching Method (PSM) 最新課程介紹: 應(yīng)用Cooper et al. (2005) |JF|，基金更名行為的影響Hellmann et al. (2008) |RFS|，銀企關(guān)系Campello et al. (2010) |JFE|，金融危機中 CFO 如何應(yīng)對Faulkender and Yang (2010) |JFE|，經(jīng)理人薪酬激勵Michaely and Roberts (2012) |RFS

20、|，私營企業(yè)的股利支付行為傾向得分匹配分析Propensity Score Matching Method (PSM) 最新課程介紹: 自選擇模型Self-Selection Models問題的根源：被解釋變量(y)中經(jīng)常包含缺漏值Case I: 隨機缺漏Case II: 非隨機缺漏(無法觀察到)例如, y = 公司的研發(fā)支出；高管的在職消費；公司的游說支出模型設(shè)定(Heckman selection model)回歸方程選擇方程: y is observed only if 最新課程介紹: 處理效應(yīng)模型Treatment Effect Models模型設(shè)定：解釋變量中包含一個內(nèi)生的 0/1

21、變量Stata commands: treatreg | heckman | ivprobit | cmp最新課程介紹: 應(yīng)用Laeven and Levine (2007) |RFS|，多元化折價Gompers et al. (2010) |RFS|，雙重股權(quán)公司Ayyagari et al. (2010) |RFS| , 非正規(guī)融資，中國Ross (2010) |RFS| , 主導銀行效應(yīng)Core and Guay (2001) |JFE|，股權(quán)激勵Lee and Masulis (2009) |JFE|，二次發(fā)行Masulis and Mobbs (2011) |JF|， 獨立董事市場處

22、理效應(yīng)模型Treatment Effect Models最新課程介紹: 斷點回歸設(shè)計 Regression Discontinuity Designs (RDD)RDD: 接近于自然實驗的研究方法Stata commands: | rd |最新課程介紹: RDDSource: Lee and Lemieux (2010, |JEL|, Figure. 1)最新課程介紹: 最新課程介紹: Notes: 橫軸為驅(qū)動變量 上一屆選舉中執(zhí)政黨與在野黨票數(shù)比重之差 縱軸為結(jié)果變量 下一屆選舉中執(zhí)政黨獲得的選票比重Source: Lee and Lemieux (2010, |JEL|, Figure.

23、7)最新課程介紹: 斷點回歸設(shè)計 Regression Discontinuity Designs (RDD)應(yīng)用Chava and Roberts (2008) |JF|，債務(wù)契約與投資行為Roberts and Sufi (2009) |JF|，控制權(quán)與資本結(jié)構(gòu)Iliev (2010) |JF|，薩班斯法案對融資成本、盈余管理和股價的影響Garmaise and Natividad (2010) |RFS|，信息不對稱與融資成本Cuat et al.(2010) |NBER|，公司治理與股東價值(股東年會投票數(shù)據(jù))Baker et al.(2011) |JFE|，參考價格與兼并收購行為最新

24、課程介紹: 對于實證分析的建議清晰界定你所研究的問題(重要的、有意義的)數(shù)據(jù)總是有缺陷的，要通過巧妙的研究設(shè)計來保證統(tǒng)計推斷的可靠性e.g. Fazzari et al. (1988), 投資-現(xiàn)金流敏感性 融資約束假說方法的實現(xiàn)不是問題，關(guān)鍵在于要選擇合適的方法研究設(shè)計：制度背景的深刻理解(很重要！)內(nèi)生性問題的來源與后果(避免擺 Pose)采用何種方法能夠恰當?shù)剡M行統(tǒng)計推斷 (多種方法的配合使用)特殊的事件、特殊的數(shù)據(jù)：盡量接近于自然實驗最新課程介紹: 讓我們的實證研究更接近于自然實驗 附內(nèi)生性問題綜述Wintoki et al. (2008)；Coles et al. (2007)； T

25、ucker (2011)；Lee (2005)Roberts and Whited (2011)；Imbens and Wooldridge (2009)Imbens and Lemieux(2008) JE, RDDLee and Lemieux(2010) JEL, RDD相關(guān)模型和方法的Stata實現(xiàn)過程及范例IV-GMM估計：Stata高級視頻 B4_IV_GMM靜態(tài)面板數(shù)據(jù)模型和動態(tài)面板數(shù)據(jù)模型：Stata高級視頻 B7_Panel面板門檻模型：Stata學術(shù)論文視頻 (說明書)Hansen_1999(附帶Stata命令 xtthres)傾向得分匹配分析PSM：Stata學術(shù)論文視頻

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30、tersen B C (2009). Financing Innovation and Growth: Cash Flow, External Equity, and the 1990s R&D Boom. The Journal of Finance, 64 (1): 151-185.最新課程介紹: 參考文獻Campello, M, Graham J R, Harvey C R (2010). The Real Effects of Financial Constraints: Evidence from a Financial Crisis. Journal of Financial Ec

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