Santosh Acharya's Blog

Abstract  Inflation is taken as a secret form of taxing people, thus in literature it is also known as an indirect form of tax. This has been tested by using the secondary data since 1975 to 2010 on government tax revenue (GTAX) and national consumer price index (NCPI) of Nepal. Initially, ADF test, then Granger Causality and finally OLS has been conducted. Granger Causality has suggested that NCPI causes GTAX which helped later to consider NCPI as an independent variable and GTAX as a dependent variable. After conducting OLS test it is found that NCPI impacts GTAX directly (Acharya, 2014).  Key Words : Inflation, Tax, Granger Causality and OLS.  Reference: Acharya, S. (2014). Inflation is a hidden form of tax in Nepal: Granger Causality test. Khwopa Journal , 1 (1), 61–75.

Consider the nonlinear equation f(x)=4x 2 –exp(x). Write a Fortran program that uses the Golden Section Search Method to find the solution accurate to within 10 -6 for the nonlinear equation on [4,8].  Sauce Code: Program  Assignmentq2 implicit none real:: f real::x, r, q1, q2,a, b, tol=1.0e-6 !Define Interval and Function f(x) = 4*x**2-exp(x) a=4 b=8 print*, "a", a, "b", b !Evaluation of the function at the end point r=(sqrt(5.0)-1)/2 q1=b-r*(b-a) q2=a+r*(b-a)  print*, "q1",q1, "q2", q2  ! Creating Loop !if ((b-a)<=tol) stop do while ((b-a)>tol)      !if(f(a)*f(b)<=0) then      if(f(a)*f(q2)<=0) then          b=q2          q2=q1          q1=b-r*(b-a)      else          a=q1          q1=q2          q2=a+r*(b-a) ...

 Question: Solve the following system of linear equations using Gaussian Elimination using Fortran. x 1 + x 2 - x 3 + x 4 - x 5 = 2 2x 1 + 2 x 2 + x 3 - x 4 + x 5 = 4 3x 1 + x 2 -3 x 3 -2x 4 + 3 x 5 = 8 4x 1 + x 2 - x 3 +4 x 4 -5x 5 =16 16x 1 -x 2 + x 3 - x 4 - x 5 =32   Solution: program main implicit none integer, parameter :: n=5 double precision:: a(n,n), b(n), x(n) integer:: i,j ! matrix A   data (a(1,i), i=1,5) /  1.0,  1.0,  -1.0, 1.0, -1.0 /   data (a(2,i), i=1,5) /  2.0,  2.0,  1.0, -1.0, 1.0 /   data (a(3,i), i=1,5) /  3.0,  1.0,  -3.0, -2.0, 3.0 /   data (a(4,i), i=1,5) /  4.0,  1.0,  -1.0, 4.0, -5.0 /   data (a(5,i), i=1,5) /  16.0, -1.0, 1.0, -1.0, -1.0 / ! matrix b   data (b(i),   i=1,5) /  2.0, 4.0, 8.0, 16.0, 32.0 / ! print a header and the original equations   write (*,200)   do i=1,n      write ...