A researcher wants to estimate the price elasticity of demand for cars in the states of Washington, Oklahoma, Arkansas, Louisiana, and New York for the year 2017. For this, she uses the sample of car owners, measured state-wise by the number of car registrations at the end of 2017. To remove simultaneity between the per capita quantity demanded of cars (Qars) and the price of cars (Pars), she uses two instruments, namely state sales tax on cars (Stax;, measured by the sales tax levied on cars in that state) and local sales tax on cars (Ltax;, measured by the statewise average of the local sales tax levied on cars). She also uses statewise income level of the car owners (Inc₁, measured by the average household income of car owners in that state) as an exogenous regressor. She wants to test whether the instruments are exogenous or not, for which she uses the overidentifying restrictions test. The regression ATSLS of the estimated two stage least squares residual (u; ), on the instruments and the exogenous variable included is: ATSLS = 1.81 +1.94Stax; +1.82Ltax; +2.68Inc;. (0.6) (1.34) (1.25) (0.94) Standard errors are given in parentheses. The researcher wants to test the hypothesis that the effect of Stax;, on ATSLS ui is not significant. The test statistic associated with the test the researcher wants to conduct is 1.45. ATSLS The researcher also wants to test the hypothesis that the effect of Ltax;, on u¡ is not significant. The test statistic associated with this test is 1.46. (Round your answers to two decimal places.) Suppose the estimated correlation between the two test statistics calculated by the researcher (Pt₁t₂) is 0.65. The researcher wants to test the hypothesis that Stax; and Ltax; are not jointly significant. The test statistic associated with the test the researcher wants to conduct is (Round your answer to two decimal places.)