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To answer the following questions, use the annual Compustat data from January 1, 2015 to December 31, 2020 using the WRDS platform. Provide your solutions in the Excel file, posted on Canvas, in the corresponding worksheets. Part 1: Regression Analysis 1. As a starting point, create a clean database by (i) removing the negative or missing observations for total assets and sales, and (ii) dropping utility (SIC codes between 4900 and 4949) and financial firms (SIC codes betwen 6000 and 6999). Before downloading the data, you first need to read all the following questions to understand what variables you need to download from WRDS Compustat database in addition to total assets and sales. Note that in the first part of the assignment, our goal is to construct appropriate variables and run a few regression models using the compustat sample. In the second part of the assignment, our goal is to construct a series of financial ratios that are often used by the finance community to assess the viability and soundness of a firm, again using the Compustat sample. 2. The first regression model examines how different firm characteristics affect new investment. The regression model is as follows: Iit=0+1MBit+2CashFlowit+3Sizeit+4SalesGrowtit+5REit+it where Iit, the new investment, consists of capital expenditures plus research and development (R\&D) expenses plus acquisitions minus sale of property, plant, and equipment (PP\&E) minus amortization and depreciation, all scaled by total assets. MBit is the firm's market-to-book ratio which we learned in class how to construct. CashFlow it is the firm's cash flow scaled by total assets. Cash flow is defined as income before extraordinary items plus depreciation plus deferred taxes (if available). Size it i is the natural logarithm of total assets. SalesGrowth hit is the percent change in sales from one year to another year. REit is the retained earnings scaled by total assets. Lastly, it is the regression's error term. When you are constructing the regression variables, make sure you set missing values of sale of PP\&E, R\&D, and acquisitions to zero. Also, do not forget to winsorize all the variables at the 1% and the 99% of their empirical distribution. Now that you have constructed all the variables, estimate the above regression and provide the regression analysis estimates. More importantly, provide an interpretation of all the estimated coefficients. 3. Repeat the same regression model given in Equation (1) but this time add the lag of new investment (lag of Iit ) to the control variables and rerun the regression. Compare the estimates of the coefficients to those from the previous question. What do you observe? Also, what is your interpretation of the coefficient of the lag of new investment? 4. In the second regression, we are looking at firm value. If not the most important, firm value is one of the critical measures that investors analyze and track over time. A fundamental question in the finance world is to understand what factors affect firm value. In this question, we run a regression of firm value on a set of firm characteristics to examine what factors matter for firm value and whether they have a positive or negative effect on the value. The common proxy for firm value used in the finance literature is Tobin's Q that we learned in class how to construct. With that in mind, run the following regression: TQit=0+1Sizeit+2Levit+3ROAit+4Invit+5Divit+6Ageit+it where the dependent variable, TQit, is Tobin's Q which is used as a proxy for firm value. Size it it is the natural logarithm of total assets. Levit is the book leverage ratio defined as total debt (the sum of short-term debt and long-term debt) scaled by total assets. ROAit is defined as operating income before depreciation scaled by total assets. This ratio provides a measure of firm profitability. Inv it is the sum of investment in physical capital and R&D, scaled by total assets. Divit is a dummy variable which is 1 if the firm pays dividends in a given year and zero otherwise. Lastly, Ageit is the natural logarithm of one plus the number of years the firm has been listed in the Compustat database. After estimating this regression, provide a complete interpretation of the estimated coefficients. What firm characteristics increase firm value and what factors decrease it? To answer the following questions, use the annual Compustat data from January 1, 2015 to December 31, 2020 using the WRDS platform. Provide your solutions in the Excel file, posted on Canvas, in the corresponding worksheets. Part 1: Regression Analysis 1. As a starting point, create a clean database by (i) removing the negative or missing observations for total assets and sales, and (ii) dropping utility (SIC codes between 4900 and 4949) and financial firms (SIC codes betwen 6000 and 6999). Before downloading the data, you first need to read all the following questions to understand what variables you need to download from WRDS Compustat database in addition to total assets and sales. Note that in the first part of the assignment, our goal is to construct appropriate variables and run a few regression models using the compustat sample. In the second part of the assignment, our goal is to construct a series of financial ratios that are often used by the finance community to assess the viability and soundness of a firm, again using the Compustat sample. 2. The first regression model examines how different firm characteristics affect new investment. The regression model is as follows: Iit=0+1MBit+2CashFlowit+3Sizeit+4SalesGrowtit+5REit+it where Iit, the new investment, consists of capital expenditures plus research and development (R\&D) expenses plus acquisitions minus sale of property, plant, and equipment (PP\&E) minus amortization and depreciation, all scaled by total assets. MBit is the firm's market-to-book ratio which we learned in class how to construct. CashFlow it is the firm's cash flow scaled by total assets. Cash flow is defined as income before extraordinary items plus depreciation plus deferred taxes (if available). Size it i is the natural logarithm of total assets. SalesGrowth hit is the percent change in sales from one year to another year. REit is the retained earnings scaled by total assets. Lastly, it is the regression's error term. When you are constructing the regression variables, make sure you set missing values of sale of PP\&E, R\&D, and acquisitions to zero. Also, do not forget to winsorize all the variables at the 1% and the 99% of their empirical distribution. Now that you have constructed all the variables, estimate the above regression and provide the regression analysis estimates. More importantly, provide an interpretation of all the estimated coefficients. 3. Repeat the same regression model given in Equation (1) but this time add the lag of new investment (lag of Iit ) to the control variables and rerun the regression. Compare the estimates of the coefficients to those from the previous question. What do you observe? Also, what is your interpretation of the coefficient of the lag of new investment? 4. In the second regression, we are looking at firm value. If not the most important, firm value is one of the critical measures that investors analyze and track over time. A fundamental question in the finance world is to understand what factors affect firm value. In this question, we run a regression of firm value on a set of firm characteristics to examine what factors matter for firm value and whether they have a positive or negative effect on the value. The common proxy for firm value used in the finance literature is Tobin's Q that we learned in class how to construct. With that in mind, run the following regression: TQit=0+1Sizeit+2Levit+3ROAit+4Invit+5Divit+6Ageit+it where the dependent variable, TQit, is Tobin's Q which is used as a proxy for firm value. Size it it is the natural logarithm of total assets. Levit is the book leverage ratio defined as total debt (the sum of short-term debt and long-term debt) scaled by total assets. ROAit is defined as operating income before depreciation scaled by total assets. This ratio provides a measure of firm profitability. Inv it is the sum of investment in physical capital and R&D, scaled by total assets. Divit is a dummy variable which is 1 if the firm pays dividends in a given year and zero otherwise. Lastly, Ageit is the natural logarithm of one plus the number of years the firm has been listed in the Compustat database. After estimating this regression, provide a complete interpretation of the estimated coefficients. What firm characteristics increase firm value and what factors decrease it
