You are hired to forecast the unemployment rate in a geographical area that is peripheral to a large metropolitan area in the United States. The area in question is called the Inland Empire (San Bernardino County and Riverside County)and is situated east of Greater Los Angeles (Los Angeles County and Orange County). While the area has a large population (it is the 14^th largest metropolitan statistical area in the United States), its economic activity relies heavily on that of the larger area it is attached to. For example, it is estimated that approximately 20% of its workforce commutes into the Greater Los Angeles area for work and few workers commute the other way. Furthermore, its logistics industry is heavily dependent on economic activity in the Greater Los Angeles Area. As a result, you view the unemployment rate of the Greater Los Angeles Area (ur^GLA)to be exogenous in determining the unemployment rate in the Inland Empire (ur^IE). You estimate the following distributed lag model, where numbers in parenthesis are HAC standard errors:

a. What is the impact effect of a one percentage point increase (say from 0.06 to 0.07)of the unemployment rate in the Greater Los Angeles area?
b. What is the long-run cumulative dynamic multiplier?
c. Why do you think the variables above appear in changes rather than in levels?

Question

You are hired to forecast the unemployment rate in a geographical area that is peripheral to a large metropolitan area in the United States. The area in question is called the Inland Empire (San Bernardino County and Riverside County)and is situated east of Greater Los Angeles (Los Angeles County and Orange County). While the area has a large population (it is the 14^th largest metropolitan statistical area in the United States), its economic activity relies heavily on that of the larger area it is attached to. For example, it is estimated that approximately 20% of its workforce commutes into the Greater Los Angeles area for work and few workers commute the other way. Furthermore, its logistics industry is heavily dependent on economic activity in the Greater Los Angeles Area. As a result, you view the unemployment rate of the Greater Los Angeles Area (ur^GLA)to be exogenous in determining the unemployment rate in the Inland Empire (ur^IE). You estimate the following distributed lag model, where numbers in parenthesis are HAC standard errors:

a. What is the impact effect of a one percentage point increase (say from 0.06 to 0.07)of the unemployment rate in the Greater Los Angeles area?
b. What is the long-run cumulative dynamic multiplier?
c. Why do you think the variables above appear in changes rather than in levels?

Quizplus · Accepted Answer

The Answer of You are hired to forecast the unemployment rate in a geographical area that is peripheral to a large metropolitan area in the United States. The area in question is called the Inland Empire (San Bernardino County and Riverside County)and is situated east of Greater Los Angeles (Los Angeles County and Orange County). While the area has a large population (it is the 14^th largest metropolitan statistical area in the United States), its economic activity relies heavily on that of the larger area it is attached to. For example, it is estimated that approximately 20% of its workforce commutes into the Greater Los Angeles area for work and few workers commute the other way. Furthermore, its logistics industry is heavily dependent on economic activity in the Greater Los Angeles Area. As a result, you view the unemployment rate of the Greater Los Angeles Area (ur^GLA)to be exogenous in determining the unemployment rate in the Inland Empire (ur^IE). You estimate the following distributed lag model, where numbers in parenthesis are HAC standard errors: a. What is the impact effect of a one percentage point increase (say from 0.06 to 0.07)of the unemployment rate in the Greater Los Angeles area? b. What is the long-run cumulative dynamic multiplier? c. Why do you think the variables above appear in changes rather than in levels?

You Are Hired to Forecast the Unemployment Rate in a Geographical