Reference no: EM131152460

Homework: Elemantary Econometrics

Part 1:

ESSAY- Write your answer in the space provided or on a separate sheet of paper.

1) Earnings functions attempt to find the determinants of earnings, using both continuous and binary variables.

One of the central questions analyzed in this relationship is the returns to education.

(a) Collecting data from 253 individuals, you estimate the following relationship

{ln(Earn_i)}^ = 0.54 +0.083 x Educ, R² = 0.20, SER = 0.445
                         (0.14) (0.011)

where Earn is average hourly earnings and Educ is years of education.

What is the effect of an additional year of schooling?

(b) You incorporate the experience variable into your original regression

{ln(Earn_i)}^ = -0.01 + 0.101 x Educ +0.033 x Exper - 0.0005 x Exper²,
                        (0.16) (0.012)                (0.006)                (0.0001)
R² = 0.34

What is the effect of an additional year of experience for a person who is 40 years old and had 12 years of education? What about for a person who is 60 years old with the same education background?

(c) Test for the significance of each of the coefficients of the added variables. Why has the coefficient on education changed so little? (Think

(d) You expect the variable EDUC to have a positive coefficient. Create and tes the appropriate hypothesis to evaluate this expectation at 5% leveabout omitted variable bias.)

2) Attendance at sports events depends on various factors. Teams typically do not change ticket prices from game to game to attract more spectators to less attractive games. However, there are other marketing tools used, such as fireworks, free hats, etc., for this purpose. You work as a consultant for a sports team, the Los Angeles Dodgers, to help them forecast attendance, so that they can potentially devise strategies for price discrimination. After collecting data over two years for every one of the 162 home games of the 2000 and 2001 season, you run the following regression:

(Attend)^ = 15,005 +201 x Temperat + 465 x DodgNetWin +82 x OppNetWin + 9647 xDFSaSu + 1328 x Drain +1609 x D150m +271 x DDiv - 978 x D2001;

R²=0.416, SER = 6983

where Attend is announced stadium attendance, Temperat it the average temperature on game day, DodgNetWin are the net wins of the Dodgers before the game (wins-losses), OppNetWin is the opposing team's net wins at the end of the previous season, and DFSaSu, Drain, D150m, Ddiv, and D2001 are binary variables, taking a value of 1 if the game was played on a weekend, it rained during that day, the opposing team was within a 150 mile radius, the opposing team plays in the same division as the Dodgers, and the game was played during 2001, respectively.

(a) Interpret the regression results. Do the coefficients have the expected signs?

(b) Excluding the last four binary variables results in the following regression result:

Attend = 14,838 +202 x Temperat + 435 x DodgNetWin + 90 x OppNetWin +10,472 x DFSaSu, R²=0.410, SER = 6925

According to this regression, what is your forecast of the change in attendance if the temperature increases by 30 degrees? Is it likely that people attend more games if the temperature increases? Is it possible that Temperat picks up the effect of an omitted variable?

(c) Assuming that ticket sales depend on prices, what would your policy advice be for the Dodgers to increase attendance?

3) Investigate the following production function estimated for Indian industries, where Q K and L represent production, capital and labor, respectively.

ln(Q) = 0.97 + 0.92 In(L) + 0.12 ln(K) + residual

(a) What are the elasticities of output with respect to labor and capital for each industry?

(b) What are the marginal effects of capital and labor on output?

Part 2:

1. Consider the Romer model. If the percentage of the population engaged in ideas formation (l‾) decreases, what are the short- and long-term impacts of this shift on Y?

2. Consider the following Romer model of economic growth:

Y_t = A_t L_yt

ΔA_t =z‾A_tL_t

 

L_at + L_yt = L‾

 

L_at = l‾L‾

 

a. A₀ = 100, l‾ = 0.1, z‾ = 1/3000 and L‾ = 1,000, what is the growth rate of knowledge in this economy?

b. Using the information from year 1, what is the level of per capita output in this economy in year 5?

3. Consider Table 7.1 for the following questions:

Table 7.1: U.S. Employment Status (in thousands)
	Jan 2012	Jan 2013
Civilian population	242,269	244,663
Unemployed	12,748	12,332
Employed	141,608	143,322
Not in Labor Force	87,913	89,008

a. Find the unemployment rate for Jan 2012.

b. Find the employment-population ratio for Jan 2013.

c. How much did the unemployment rate change between Jan 2012 and Jan 2013?

4. Using the "bathtub model" of unemployment, calculate the natural rate of unemployment in 2015 and 2016.

	Separation rate	Finding rate	Labor force
2015	2%	20%	130
2016	2.5%	15%	100

5. In 1979, in the face of rising competition in the fast food hamburger market, McDonald's reduced the price of its cheeseburger to $0.43. If the CPI in 1979 was 37.2 and the CPI in 2005 was 100, what is the price of a 1979 cheeseburger in 2005 dollars?

6. You are the head of the central bank and you want to maintain 2 percent long-run inflation, using the quantity theory of money. If the real GDP growth is 4 percent and velocity is constant, what must the growth rate of money be to the inflation target?