Assume the Following Model of the Labor Market:
N^d = $\frac { W } { P }$

question 1

Essay

Assume the following model of the labor market:
N^d = ?₀ + ?₁
$\frac { W } { P }$ + u
N^s = ?₀ + ?₁
$\frac { W } { P }$ + v
N^d = N^s = N
where N is employment, (W/P)is the real wage in the labor market, and u and v are determinants other than the real wage which affect labor demand and labor supply (respectively). Let
E(u)= E(v)= 0; var(u)= $\sigma _ { u } ^ { 2 }$ ; var(v)= $\sigma _ { v } ^ { 2 }$ ; cov(u,v)= 0
Assume that you had collected data on employment and the real wage from a random sample of observations and estimated a regression of employment on the real wage (employment being the regressand and the real wage being the regressor). It is easy but tedious to show that $\left( \hat { \beta } _ { 1 } - \beta _ { 1 } \right) \xrightarrow{p} \left( \gamma _ { 1 } - \beta _ { 1 } \right) \frac { \sigma _ { u } ^ { 2 } } { \sigma _ { u } ^ { 2 } + \sigma _ { v } ^ { 2 } }$ > 0
since the slope of the labor supply function is positive and the slope of the labor demand function is negative. Hence, in general, you will not find the correct answer even in large samples.
a. What is this bias referred to?
b. What would the relationship between the variance of the labor supply/demand shift variable have to be for the bias to disappear?
c. Give an intuitive answer why the bias would disappear in that situation. Draw a graph to illustrate your argument.

Estimate required sample sizes for time studies to achieve desired confidence levels and errors.

Appreciate the importance of accurate element descriptions and their impact on time measurement accuracy.

Understand the application of time study findings in operational efficiency and productivity improvement.

Understand the concept of financial projection including sales, dividends, and external financing needs.

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Definitions:

Goods in Process Inventory

The value of incomplete products in a manufacturing process, representing materials, labor, and overhead costs incurred up to a certain point.