Suppose you estimated the following model with a time-series data of corn yields (in bu/acre) from a single county: Corn Yield_t=_0+_1 Prec_t+_2 Time_t+_t where Prec is the annual precipitation (inch). The Gretl output is Model 1: OLS, using observations 1989-2013 (T = 25) Dependent variable: corn_yield Coefficient Std. Error t-ratio p-value const 2234.55 1307.82 1.7086 0.1016 prec 0.0871372 0.0341095 2.5546 0.0181 ** time 1.13244 0.651029 1.7395 0.0959 * Mean dependent var 90.22400 S.D. dependent var 26.83948 Sum squared resid 12656.05 S.E. of regression 23.98489 R-squared 0.267954 Adjusted R-squared 0.201404 F(2, 22) 4.026371 P-value(F) 0.032354 Log-likelihood 113.3111 Akaike criterion 232.6223 Schwarz criterion 236.2789 Hannan-Quinn 233.6365 rho 0.258139 Durbin-Watson 1.308130 Durbin-Watson statistic = 1.30813 p-value = 0.020907 For each of the explanatory variables in your model provide a carefully worded interpretation of the meaning of the estimated coefficient, and discuss whether or not it is statistically significant at the 5% significance level. (2 points)