J 1 1.(a) Consider a two equation model:y₁ = αz, + uty, B₁2, +B₂x, +U₂t; t=1,2,..., Twhere y, and z, are endogenous variables, x, is an exogenous variable,u₁, and u₂, are serially uncorrelated disturbances with zero means, variancesof and o and covariance ₁2 for all t.Write down the reduced form corresponding to y and z. Suggest a method ofestimation of the reduced form parameters, which will give unbiased andconsistent estimators.

In this problem, we are dealing with a two-equation model involving endogenous variables and an…

Answered: Consider a two equation model: y₁ = az,…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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1:.V A moodle.unizwa.edu.om الوقت المتبقي 0:32:35 ا Q1. [6 points] : From the following data set [2 3. 6. 6 11 16 1 find correlation coefficients 2. Estimate the simple linear regression model 3. Find the predicted value of y when x-10 Q2. [6 points] The weekly wages workmen are normally distributed around a mean of R.O. 70 with a SD. of R.O. S. Find the probability of workers whose weekly wages will be @ between R.O. 69 and R.O. 72, (mless than R.O. 69, (m) Find the value of K such that P(X K) =0.34 00 01 02 03 04 os 06 07 0160 0199 oss7 .0675 0714 O753 0910 0948 1064 .1141 O 179 04154 os1915 .1217 -1255 .1293 .1.368 .1406 1443 .1460 .1517 .1700 2014 1591 1626 .1736 .1772 2123 .1879 .1950 2291 2190 2224 2549 1985 2019 2088 2157 2324 2357 2422 2704 2734 2309 24 2517 0.7 2580 2611 2910 2642 2939 3212 2673 2764 3051 2794 2023 3106 2995 3264 3131 3365 3589 3599 3621 3830 2967 3023 3078 0.9 3159 3236 3115 3340 3531 3413 1. 3643 1234 10 3430 3461 3465 3554 3577 3665 36 7on 379 3749 349 3770…
justify the reasons for the in1.Econometrics deals with the measurement of economic relationships which are stochastic or random. The simplest form of economic relationships between two variables X and Y can be represented by: ; where are regression parameters and the stochastic disturbance term Justify the reasons for the insertion of U-term in the modelsertion of of u (error term) in the model Y=a+bX+u?
10. In a partially destroyed laboratory record relating to correlation data, the following results are legible o,² = 9, Regression equations 8X- 10Y + 66 = 0, 40X– 18Y = 214. What were (a) the mean values of X and Y , (b) , , (c) the co-efficient of correlation between X and Y ?
A student working on a summer internship in the economic research department of a large corporation studied the relation between sales of a product (Y, in million dollars) and population (X, in million persons) inthefirm's50marketingdistricts.The normal error regression model was employed. The student first wished to test whether or not a linear association between Y and X existed. The student accessed a simple linear regression program and obtained the following information on the regression coefficients. The student concluded from these results that there is a linear association between Y and X. Is the conclusion warranted? What is the implied level of significance?
1a)
2. Consider the simple linear regression Yi = Bo + B1r, +E, (a) Derive the weighted least squares estimators for 30 and B1. (b) Express the weighted least squares estimator for B1 in terms of the centered variables y; - G and z; – Fu, where ỹu, and E, are the weighted means.
3) Consider a simple linear regression model Y = Bo + B₁x + €, where Y is the response variable, x is the explanatory variable and € is the random error. Suppose we have n observations (x₁, Y₁), ..., (xn, Yn) on x and Y. Write down the assumptions about the random errors €1,..., En.
6) A company manufactures some thermocouples with the following voltage vs. temperature data: T ('C) V (mV) 20 30 40 50 60 75 100 1.02 1.53 2.05 2.55 3.07 3.56 4.05 The company claims that the voltage output is linear with temperature in this range. Test company's claim by (a) Giving the calibration equation (b) Calculating the correlation coefficient
5. Consider the following two simple regression models: Model I : Y, = B,+B,X, +H, Model II : Y,=a, +a, (X,- X)+v, (1) Derive the estimators for B, and a,. Are they the same? (2) Derive the estimators for B, and a, . Are they the same?
14. Interpret the following values : (i) Product moment coefficient of correlation is 0. (ii) Regression coefficient of y on x is – 1-75. (iii) Coefficient of rank correlation = 1.
Suppose Y; are the fitted y-values for in a maximum-likelihood linear regression model and Y; are the observed values, i = 1,2,... Show that E(Y: - Ý;) = 0 i=1
If var(X) = var(Y) = σ², cov(X,Y)= and 2Y-3 find the correlation between 2X+3

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