A researcher is interested in nding out how the past average daily values of the stock prices of a firm A determine the current average daily value of its stock price. Let pt (measured in dollars) denote the average daily value of the stock price of firm Aat time t. The researcher collects data on the average daily values of the stock prices of the last quarter of 2017, Le, I: 1, 2,..., 90 and estimates the following autoregressive model with 1 lag of Pt: A _ pt: 2.12 +1.07p,_1, R2 = 0.512, SER= 13.14. (1.12) (0.43) The standard errors are given in parentheses. Suppose that the actual average daily value of the stock price on January 2, 2018 was $504.48 and the average daily value of the stock price on December 31, 2017 was $445.12. The forecast error in the estimation of the average daily value of the stock price on January 2, 2018 will be $ 26.08 . (Round your answer to two decimal places.) Suppose that the researcher wants to check the causal effect of p,_1 on the current average daily value of the stock price, p,. Let A denote the population slope coefficient on pt_1. The tstatistic associated with the hypothesis 1 = 0 is 2.49'. (Round your answer to two decimal places.) V At the 5% signicance level, the researcher will reject the hypothesis of no causal effect of pt_1 on p) Suppose the researcher now estimates the following AR(2) model by adding a second lag of the average daily value of the stock price (Pt 2): A _ p,=2.31+1.08p,_1+0.97p,_2,R2 = 0.518, SER= 13.2. (1.17) (1.04) (0.74) The standard errors are given in parentheses. Let ,62 denote the population slope coefficient on pt_2. The tstatistic associated with the hypothesis z = 0 is |:. (Round your answer to two decimal places.) At the 5% signicance level, the researcher will V the hypothesis of no causal effect of pt_2 on Pt