Endogeneity analysis and Compare the OLS and IV/2SLS coefficient

I. Anti-takeover Provisions and Firm Value (Endogeneity Correction) [40 points]:

In this assignment as a financial analyst, you are trying to examine how a company’s anti-takeover provisions would ultimately affect its value. There appears to be consensus regarding the effect of anti-takeover provisions on firm value among academia, investors, policy makers/regulators and the popular media. On one hand, more anti-takeover provisions may help enhance firm value by protecting managers against the odds of losing their jobs and/or compensations due to takeovers, thereby motivating managerial dedication to value-increasing decisions without worrying about job security. On the other hand, more anti-takeover provisions insulate underperforming managers from the discipline of the corporate control market, therefore leading to managerial pursuit of private benefits at the sacrifice of shareholder value. Your job is to disentangle these two competing arguments/hypotheses and draw conclusions from the econometric analyses, after controlling for endogeneity. 

Run SAS regression analyses including testing and correcting for endogeneity and interpret the outputs in the same manner as we discussed in class. The dependent variable is Tobin’s q (“q”) – the conventional measure of firm value, and the explanatory variable of interest is a firm’s total number of anti-takeover provisions implemented (“gindex”). The instrument for “gindex” is the average gindex of all firms in the same industry as the sample firm for each year (“gindex_mean”). Definitions for all variables are provided in the Excel spreadsheet “Variable Definitions”. The sample firms include S&P 1500 companies during 2003-2005:

1. Download “Board_IV_Final.sas” SAS program file and “Board.xlsx” Excel spreadsheet from D2L and save both in the folder “H:\fin419”. 

2. Run the OLS regression of q (market to book value of assets) on gindex (the total number of anti-takeover provisions adopted by a firm, also called “G-Index” or “Governance-Index”), after controlling for all control variables used in a similar manner as in our prior class. 

3. Comment on the SAS regression output including

a. Coefficient estimates on the explanatory variables (the sign and magnitude that indicates the economic significance) and statistical significance (t-stat & p-value)

b. Overall fit and validity of the model: F-stat and its p-value

c. Goodness of fit of the model: R2 and Adjusted R2.

4. Run the IV/2SLS regression of q on gindex and the control variables, where using industry average gindex (“gindex_mean”) as the instrument for gindex. 

5. What is the endogeneity problem you face here? Explain the sources/reasons for the endogeneity.

6. Comment on the IV/2SLS regression output including coefficient estimates on the explanatory variables (the sign and magnitude that indicates the economic significance) and statistical significance (t-stat & p-value).

7. Comment on the Endogeneity test result using the PORC QLIM procedure (at the end of the output).

8. Compare the OLS and IV/2SLS coefficient estimates & statistical significance using either the PROC SYSLIN or PROC QLIM procedure.

II. Board of Directors and Corporate Innovation [10 points]:

2.2 If you were the referee for a paper that examines the relationship between various board of directors characteristics and firms’ innovation output (e.g., patents, new products, R&D). After controlling for various observable macro, industry and year effects, firm financial, accounting factors, executive characteristics, board characteristics etc. (i.e., controlled for anything you can think of that are relevant), the authors find that busy directors have a negative and significant impact on firms’ innovation output. Busy directors are defined as the percentage of directors on a firm’s board that hold at least three (>=3) outside directorships on other firms’ boards. The authors interpret their findings as being consistent with the notion that busy directors, whose time and efforts are in limited supply, are stretched out than non-busy directors and thus are lax in monitoring and advising firms’ innovation activity. 

a) To establish the causality from busy directors to innovation, what is the econometric issue the authors should address? 

b) How would you design your study to address the issue – be as specific as possible? 

c) What instrument(s) would you use if you were conducting this study and using instrumental variables estimation to address the problem?