We think you have liked this presentation. If you wish to download it, please recommend it to your friends in any social system. Share buttons are a little bit lower. Thank you!
Presentation is loading. Please wait.
Published byCarson Hyles
Modified about 1 year ago
Cross Equation Constraints
Stone-Geary Utility Function Linear expenditure system U= (q 1 - 1 ) (q 2 - 2 ) – + =1 – and are expenditure shares (above subsistence) – i subsistence quantity of good I
Stone-Geary Utility Function q 1 = 1 + ( /p 1 )(M - p 1 1 - p 2 2 ) –M is money income –p i is price of good i q 2 = 2 + ( /p 2 )(M - p 1 1 - p 2 2 )
Stone-Geary Utility Function q 1 = 1 (1- )+ (M/p 1 )- (p 2 /p 1 ) 2 q 1 = a 0 + a 1 (M/p 1 ) + a 2 (p 2 /p 1 ) + 1 q 2 = 2 + (M/p 2 )- (p 1 /p 2 ) 1 q 2 = b 0 + b 1 (M/p 2 ) + b 2 (p 1 /p 2 ) + 2
Stone-Geary Utility Function Constraints –a 1 + b 1 = 1 –a 2 = b 0 –a 0 = b 2 q 1 = a 0 + a 1 (M/p 1 ) + a 2 (p 2 /p 1 ) + 1 q 2 = b 0 + b 1 (M/p 2 ) + b 2 (p 1 /p 2 ) + 2
Constraints in Stata Constraint define # “condition” –example 1: constraint define 1 var1=var2 coefficient on var1 equals coefficient on var2 –example 2: constraint define 2 [q1]constant = [q2]var3 constant in q1 equation equals coefficient on var3 in q2 equation
Seemingly Unrelated Regressions in Stata SUREG ([eqname1]: depvar1 indvar11 indvar12…, noconstant) ([eqname2]: depvar2 indvar21 indvar22…, noconstant), constraint(constraint numbers) –eqname is optional –noconstant is optional –constraint(.) is optional
Seemingly Unrelated Regressions in Stata SUREG ([q1]: q1 M/p 1 p 2/1 ) ([q2]: q2 M/p 2 p 1/2 ) test [q1]constant = [q2] p 1/2 constraint define 2 [q1]constant=[q2] p 1/2 SUREG ([q1]: q1 M/p 1 p 2/1 ) ([q2]: q2 M/p 2 p 1/2 ), constraint(2)
4.6: Cramer’s Rule. Cramer’s Rule - 2 x 2 ● Cramer’s Rule relies on determinants. ● Consider the system below with variables x and y:
Do Now 4 Find the equation of a line through the points (7, -2) and (3, -1).
Goods and Financial Markets Together: The IS-LM Model.
Polynomial Functions and Their Graphs. Definition of a Polynomial Function Let n be a nonnegative integer and let a n, a n- 1,…, a 2, a 1, a 0, be real.
Solving Quadratic Equations by Completing the Square.
Section 3.4 Objectives: Find function values Use the vertical line test Define increasing, decreasing and constant functions Interpret Domain and Range.
Reporting Results, and choosing a functional form. Hill et al chapter 6.
Polynomial Inequalities in One Variable Let P(x) be any polynomial. Then P(x) 0 are called polynomial inequalities. To solve polynomial inequalities: Use.
Further Inference in the Multiple Regression Model Hill et al Chapter 8.
Section P.1 – Graphs and Models. How to Graph xy Make a table to graph y = x Use your knowledge of relations and functions.
Ordered pairs ( x, y ) as solutions to Linear Equations Here are some examples of Linear Equations. The variables have ones as their exponents. They create.
POLYNOMIAL FUNCTIONS A POLYNOMIAL is a monomial or a sum of monomials. A POLYNOMIAL IN ONE VARIABLE is a polynomial that contains only one variable. Example:
A Brief Introduction to Spatial Regression Eugene Brusilovskiy.
Linear Equation in One Variable. A linear equation in one variable is an equation that can be written in the form ax + b = 0 Where a 0 For example: 5x.
Worked examples and exercises are in the text STROUD PROGRAMME 25 SECOND-ORDER DIFFERENTIAL EQUATIONS.
EXAMPLE 1 Find the number of solutions or zeros a. How many solutions does the equation x 3 + 5x 2 + 4x + 20 = 0 have? SOLUTION Because x 3 + 5x 2 + 4x.
Michael R. Baye, Managerial Economics and Business Strategy, 3e. ©The McGraw-Hill Companies, Inc., 1999 Managerial Economics & Business Strategy Chapter.
Heteroskedasticity Hill et al Chapter 11. Predicting food expenditure Are we likely to be better at predicting food expenditure at: –low incomes; –high.
Beatrice Venturi1 Economic Faculty STABILITY AND DINAMICAL SYSTEMS prof. Beatrice Venturi.
One method of graphing a linear equation is to construct a table of values. Example: Consider the equation y = 2x + 3 xy When x = 0, y =
The IF function Bernard Liengme. Objectives To know how to: Construct a condition using the comparison operators =, >=, >, ; Construct a formula using.
Variables on Both Sides of the Equation Moving terms When a one step equation is solved, essentially the constants are sorted to one side of the.
Graphing Linear Equations By: Christine Berg Edited By: VTHamilton.
Notes 6.6 Fundamental Theorem of Algebra. If P(x) is a polynomial with degree n >1 with complex coefficients, then P(x) = 0 has at least one complex root.
3.4 Linear Programming 10/31/2008. Optimization: finding the solution that is either a minimum or maximum.
Regression Analysis: A statistical procedure used to find relationships among a set of variables.
Theoretical foundation for demand analysis Consumers equilibrium : Cardinal Utility: Law of Diminishing marginal Utility Law of equimarginal Principle.
Linear Correlation and Regression Using the TI-83 or TI-84.
ARCH (Auto-Regressive Conditional Heteroscedasticity) An approach to modelling time-varying variance of a time series. ( t 2 : conditional variance ) Mostly.
© 2016 SlidePlayer.com Inc. All rights reserved.