Answer the following questions correctly.

When we derived money demand function in class, we assumed that money demand depends on income and interest rate. Consider an economy that its money demand does not depend on income and is only a function of interest rate. M = L(i) Suppose that the economy is an open economy that is on a flexible exchange rate system. 1. Draw the money demand and supply curves with money demand and supply on x-axis and interest rate on y-axis. [3 marks] 2. Show what happens to money demand and supply curves if income changes. 2 marks] 3. Derive the LM curve. [5 marks] 4. Derive the AD curve. [5 marks]3. Suppose that the wage-setting and price-setting equations are given by W = p-F(u, z) = p (0.75 - u) p = (1+m)w = 1.5w (a) Explain why nominal wages depend on the expected price level. (b) Define the 'natural rate of unemployment' and derive its value, given the wage- and price-setting equations. (c) Now suppose that there is an increase in market concentration in the goods market. How would you expect this increase in concentra- tion to influence the wage-setting and price-setting equations? What would be the effect on the natural rate of unemployment? (d) Briefly comment on the terminology: what is natural about the 'nat- ural rate'?Again consider a researcher who has access to the Boston Home Mortgage Disclosure Act (HMDA) data used by Stock and Watson (2019). The binary variable deny is 1 if the mortgage application was denied and O if the mortgage application was accepted. The variable piratio is the ratio of the applicant's anticipated total monthly loan payments to the applicant's monthly income. Now let the binary variable black be 1 if the applicant is black and O if the applicant is white. Use the estimation results given in the table below to answer the following two questions. Dependent variable: deny Linear Probability Probit Logit 0.559 (0.089) 2.74 5.37 piratio (0.44) (0.96) 0.177 (0.025) 0.71 1.27 black (0.083) (0.15) -0.091 -2.26 -4.13 Constant (0.029) (0.16) 0.35) Sample Size 2380 2380 2380 [15] Use the probit results to predict the denial probability for a white applicant with a payment-to-income ratio of 0.30 ( piratio = 0.30 ). [16] Use the probit results to predict the denial probability for a black applicant with a payment-to-income ratio of 0.30 ( piratio = 0.30 ). What is the difference between the denial probability for this black applicant and the denial probability of the white applicant above