Econ Exam 1 Flashcards
Economic Assumptions of Perfectly Competitive Market
1) firms are price takers (large #, sell identical products, full info on both sides, low transaction costs, firms can freely enter/exit market)
2) cannot sell above market price
3) perfect mobility of production factors
4) no externalities
Production Function
q= f (L, K), usually K is fixed in the short run, lariable labor
Marginal Product of Labor
MPL= dq/dL = d [f (K,L)]/ dL “additional output produced by an additional unit of labor”
Average Product of Labor
APL = q/L “ratio of output to unit of labor”
Relationship between APL and MPL
APL max. when APL= MPL, both rise at first, but when MPL crosses over APL, they both fall, a firm will only operate if MPL is positive
Law of Diminishing Marginal Returns
holding all other inputs + tech constant an increase in input will lead to diminishing increase in output
Long Run
K and L variable
Isoquant
curve of efficient combinations of inputs for fixed amount of q (cardinal not just ordinal)
Properties of Isoquant
- farther from origin= greater level of output
- cannot cross
- downward slope
- thin
Reinstatement Effect
technology requires new kinds of labor but labor still has comparative advantage (e.g. cyber security jobs)
Perfect Substitutability Isoquants
Isoquants that are straight line (demand direction)
Fixed Proportions Isoquants
Right angle isoquants (e.g. Leontief, workers and lawnmowers
Marginal Rate of Technical Substitution (MRTS)
“how many unites of K the firm can replace with extra unit of L”, MRTS= change in K/ change in L
MRTS= dK/dL = -MPL/MPK
instantaneous slope of isoquant line
Basically the MRS but the two goods are L and K
Why does MRTS diminish along convex isoquant?
the more L a firm employs the fewer K would be needed to replace, if firm employs very little L, you would need a lot of K to replace one unit of L
What measures the curve of the isoquant?
Elasticity of Substitution (K and L)
d(K/L)/dMRTS [MRTS/(K/L)]
Types of Elasticity of Substitution (K and L)
omega = 1/1-price
Linear: omega = infinity
Leontief: omega approaches 0
Cobb Douglass: omega = 1
Constant Returns to Scale
x% increase in input yields x% increase in output
Test: f(2L + 2K) = 2 f(L, K)
Increasing Returns to Scale
increase input yields greater increase in output
Test: f(2L + 2K) greater than 2 f(L, K)
Usually happens with specialization
Decreasing Returns to Scale
increase input yields less increase in output
Test: f(2L + 2K) less than 2 f(L,K)
Usually happens when organizing/coordinating production is difficult