A researcher wants to study the unemployment rate in India. He collects yearly data on the unemployment rate in the country for the last 50 years from 1967 to 2017. He then uses an autoregressive model with 4 lags to forecast the one period ahead unemployment rate. The AR(4) model is of the form: Yr =30 +1Yt1"'2Yt2 +3Yt-3 +4Yt-4 + \"t- where Yr is the unemployment rate in the current time period and Y)_,- (i= 1,..., 4) is the unemployment rate in time period t- i. Suppose that the sum of the squared residuals (SSR) of the autoregression is 250.16. The mean squared forecast error (MSFE) estimated using the standard error of the regression is 5.56 . (Round your answer to two decimal places.) The MSFE estimated using the nal prediction error is (Round your answer to two decimal places.) Suppose that P is the proportion of the sample used by the researcher to make out-of sample forecasts. The researcher chooses 40% of the sample size (T) to estimate an out-of sample forecast, .2 such that P: 40% X T. Suppose that the sum of squared pseudo-outofsample forecast errors calculated by the researcher, 2 us, is 143. The pseudo outofsample estimated MSFE is (Round your answer to two decimal places.)