3
votes
3answers
59 views

Endogeneity & IV = model misspecification?

I'd like to raise a controversial point: if you need instrumental variables, your model is wrong. Basic endogeneity problem and the IV solution Let us suppose the basic framework of endogeneity and ...
3
votes
2answers
48 views

Graphical and Statistical Tests for Robustness of Sharp RD

I'm doing sharp regression discontinuity design with my treatment variable $$ D_i = \begin{cases} 1 \enspace \quad \text{if $x_i \geq \overline{x}$} \\ 0 \quad \text{otherwise} \end{cases} $$ where ...
4
votes
1answer
37 views

Measurment error for two variables

I am interested in estimating the effect of security S on crime C in a given city over time (eight quarters) for twenty cities, so it's panel data. The problem is, instead of actual security spending ...
7
votes
2answers
278 views

Causality in microeconometrics versus granger causality in time-series econometrics

I understand the causality as used in microeconomics (in particular IV or regression discontinuity design) and also the Granger causality as used in time-series econometrics. How do I relate one with ...
5
votes
1answer
112 views

How do instrumental variables address selection bias?

I'm wondering how an instrumental variable addresses selection bias in regression. Here's the example I'm chewing on: In Mostly Harmless Econometrics, the authors discuss and IV regression relating ...
1
vote
0answers
48 views

causal inference with correlated multivariate outcomes

I've been struggling with how to think about the causal estimate of a program on two outcomes, when one of the two outcomes affects the other outcome. It seems sort of like simultaneous equations, ...
2
votes
1answer
67 views

Why is the conditional mean of the reduced form error zero?

For example, we have a simultaneous equation model of supply and demand: Supply: $$s(p)=\alpha_{s}+\beta_{s}p+\epsilon_{s}$$ Demand: $$d(p)=\alpha_{d}-\beta_{d}p+\epsilon_{d}$$ Market clearing ...
1
vote
0answers
230 views

Difference-in-difference in panel data

Under which conditions should we expect the difference-in-difference estimate to be equal to the equivalent panel data model? Strictly speaking, whenever we have a experiment that offers a well ...
3
votes
3answers
231 views

Mathematical definition of causality

Let $Y$ and $X$ be random variables. $E(Y|X)$ is the conditional mean of $Y$ given $X$. We say $Y$ is not causally related to $X$ if $E(Y|X)$ does not depend on $X$, which implies it is equal to ...
2
votes
0answers
46 views

Roy model question

I am referring to G.S. Maddala: Limited Dependent and Qualitative Variables in Econometrics, pages 257-258. I add the relevant screenshots here: My question is, why is ...
1
vote
0answers
478 views

Econometrics: Sargan test

Here are 3 questions about econometrics and R codes. Test the endogeneity of the variable EDUC: ...
1
vote
1answer
276 views

What test is this for endogenous variables?

Can somebody tell me whether the following R code (for econometrics endogenous variables) is for a Hausman test, a Nakamura test, or some other test? ...
5
votes
1answer
77 views

Causal identification and penalized splines

I just got a rejection from an economics journal. Among the reasons cited for rejection were: the benefits of using the semi-parametric method are not clearly brought out compared to ...
2
votes
2answers
206 views

Causality, omitted variable bias

This might be a basic question, but I want to be sure that what I'm doing is right. I have a model that suggests that variable X causes both Y and Z. When I regress Y on X, or Z on X, I get positive ...
4
votes
1answer
121 views

Why arrange variables by causality in bivariate regression?

Suppose we have variables $(X,Y)$ and we have theory tell us that $X$ $\overset{\text{cause}}{\implies} Y$. Perhaps they're time-series variables and it would be common to see something like this: ...
4
votes
3answers
495 views

Fuzzy regression discontinuity design and exclusion restriction

In a fuzzy regression discontinuity design, what does the exclusion restriction look like in terms of a conditional expectation between the instrument in the first stage and the error term in the ...
1
vote
1answer
204 views

How to account for a regressand affecting a regressor?

I forget the terminology, but this happens when you regress, say, $Y$ on a list of variables, and you suspect that $Y$ affects, say, $x_3$ in addition to $x_3$ affecting $Y.$ I forget how this is ...
3
votes
1answer
592 views

Heckman selection model with difference-in-differences specification

Following my question on Tobit with DiD specification I am wondering if it is possible to estimate a heckman sample selection model with a Difference in Differences specification? For example in ...
8
votes
3answers
621 views

Random assignment: why bother?

Random assignment is valuable because it ensures independence of treatment from potential outcomes. That is how it leads to unbiased estimates of the average treatment effect. But other assignment ...
4
votes
3answers
252 views

Formal definition of random assignment

I am looking for a formal definition of random assignment. Let $\mathbf{Z}$ be a vector of treatment assignments in which each element is 0 (unit not assigned to treatment) or 1 (unit assigned to ...
5
votes
1answer
1k views

Can I use Synthetic Control Method for Comparative Case Studies with survey data?

I'd like to assess the impact of an upcoming policy implementation, as measured by changes in questionnaire response to a Likert-scale question. I understand I could use a difference-in-difference ...
3
votes
1answer
579 views

How to test for causation in a static panel data model with small t?

I have a static panel data model with small T (T=5) that makes it impossible for me to use granger causality as it requires a long time span. So my question: Is there any alternative solution to ...