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10 two stage least squares and demand estimation

om vi har Y = B0 + B1 college + u
vad är the first stage regression?

om instrument = z = dist

vad estimerar den?

côllêge = ø0 + ø1 dist

it estimates the best linear prediction som skrivs

(college)lin(dist) = côllêge

what does this tell us?

college = (college)lin(dist) + (college - (college)lin(dist) )

the right part of + tells us how far the best linear prediction is from the true value.
and can also be denited as W

how can we rewrite

college = (college)lin(dist) + (college - (college)lin(dist) )

college = ø0 + ø1dist + W

where côv(W,dist) = 0

what would be the second stage regression? and what is the exogeneity assumption?

regressing wage on côllêge

wâge = B0^ + B1^IV • côllêge


E[u|ø0 + ø1dist] = 0

what does the endogeneity problem bero på?

best linear prediction from previous question can be seen as expgenous, so it must be W that makes college an endogenous variable in the structural (original) equation.

what does 2SLS learn from?

it learns from exogenous variation and ignores endogenous variation

titta i häfte och second stage regression

.

what are the assumptions for second stage regression

exogeneity ols. E[u | (x1)lin(z)] = 0 which also means that
cov((x1)lin(z), ũ) = 0


OLS full rank:

var((x1)lin(z)) ≠ 0 och stoppa in bets linear prediction and solve for ø feta

end up with:

ø= cov(x,z) / var(z)

which means that cov(x,z) ≠ 0 which is the intrument relevance assumption

how does the two assumptions work to make sure that our second stage regression estimates the true causal effect?

relevance assumption is for the forst stage. it ensures that there is a behavioural change that generates variation that is both exogen and endogen.
the exogeneity assumption makes sure that the variation is only exogen.

which assumtion is testable anf not?

relevance is testable. we can set
H0: ø1 = 0 and test its significance in explaining the variable of interest. if we reject, the intrument relevance assumption holds.


exogen. assum. is not testable. we have to use expnomic arguemnt for why the instument cant predict u.

when do we have equilibrium?

when all agents are correctly accounting for all consequenses of their actions

how does endogeneity problem appear?

when the ols exogeneity assumptions fail because of economic equilibrium conditions

what is another name for population?

markets

explain:
Q(p) = B0 - B1•p + u

Q quantity demanded
p hypothetical price

B1 how demand react to price changes

u is the denand shocks

where is demand elasticity

if we put logs on output variable and regressor can we call B1 for demand elasticity

another name for hypothetical price and why

counterfactual price and the equation from previous question allows us to evaluate demand for prices that are nor factual (market) price.

what is RCT

random controlled trial

if we assaigb randomized price to each market, then p should be uninfomative about the demand shock, hence


E[u| p] = 0 which makes sure that we can use ols to estimate B1

however, RCT is impossible to implement since we cannot change prices like that.

we have to use market price P* that is determined in a given market and therefore is ENDOGENOUS to the market.

what is the new demand funtion, expgeneity adsumption and how do we get eqilibrium?

Q(P*) = B0 + B1•P* + u

E[u| P*] = 0


Q(P*) demand = Q(P*) supply

does our new E[u| P*] = 0 hold? why, why not? how can we see that?

it does not hold due to P* depending on the demand curve. we can see that by looking at an equilibrium graph. P* will change if there is a denand shock because of the demand curve shift.
= by looking at P* we can learn something about u. etc a higher price may indicate that there is a positive denand shock incressing the price


om vi sätter demand = supply och löser för P*. vi ser att P* beror på u.

sen sötter in funtionen för P* i Q* funtionen för att få Q*

is there any correlation between u snd P*?

yes since the exogeneity assumption does not hold. there is positive correlation since increased u also means increased P*

what can we say about a regression of Q* on P*?

it wont give the desired causal effect of price

varför uppstår the problem of endogeneity på markander?

demand shocks distinguish different markets

all markets are not the same, persistent heterogeneity between markets.


product differentiation, the orice cannot be the same everywhere due to different products


there may be monopoly power, imperfect competetion


consumers and producers make dynamic decision and do not act simultaneously as we have in our model

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