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yes, the term that you showed for the ALDR non-stochastic steady state: $$\frac{ \beta_1 + \beta_2 }{1- \rho_1 -\rho_2}$$ is long-run multiplier or sometimes also called long run equilibrium coefficient (see Verbeek 2008 Guide to Modern Econometrics 4th ed. pp 340). As far as I can understand there is not much difference between the two concepts in the ...


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The description is bit vague on how many organizations we are talking but you could still do differences-in-differences (DiD) for all treatment-control-pairs that adopted it at the same time separately and then running meta-analysis on the results. As far as I understand based on Angrist & Pischke (2009) Mostly Harmless Econometrics ch.5, DiD solves ...


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...the controls in my IV model are correlated with my instrument? The controls should be in your model precisely because they are correlated with your instrument. In the exogeneity condition $cov(z, \epsilon) = 0$ for the instrument, $\epsilon$ is the error term after controlling for other variables. This condition may not hold without controls. Consider ...


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This would not make instrument necessarily invalid. For some 2SLS instrument model of form: $$y_i = \beta_0 + \beta_1 \hat{x_i} + \beta_2 k_i +\epsilon_i$$ $$x_i = \pi_0 + \pi_1 z_i + \pi_2 k_i +e_i $$ where $y$ is dependent variable, $x_i$ is the endogenous regressor, $k$ some controls and $z$ instrument the main conditions for instrument validity are: $z$...


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It's not clear what you mean by "invertibility of the mean equation". Invertibility, in the Box-Jenkins context, is a property of ARMA processes. A characterization of invertibility is that an ARMA process is invertible if and only if the MA polynomial has no roots inside the unit disk in the complex plane. Empirically speaking, invertibility means ...


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One answer is to try to find variation in the non-pecuniary price of the free good. Here is a famous example from estimating demand for public parks: In 1949, Harold Hotelling wrote a letter to the National Park Service, outlining a method where the park visitor’s round trip distance could be used to proxy the recreation trip price, so that consumer’s ...


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When estimating something like substitution, I once ran into an issue that though there were price fluctuations, they were very small, it was likely I would observe noise rather than actual substitution at this level. A colleague recommended looking for natural experiments. In our case this meant looking for instances when one of the suppliers closed for ...


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If yes, then how does this square with the general point that causality/exclusion cannot generally be established with statistical tests... It seems to me that "[exogeneity of IV] cannot generally be established with statistical tests" does not imply that it cannot be tested in specific cases. In this (very specific) context, the exogeneity claim ...


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Depends on what the dummies are and what is the specification of the model you are using. When you multiply two dummies you are creating what is called an interaction term. Generally speaking you can include interaction terms in panel data. In fact the widely used differences-in-differences (DiD) estimator relies on it. A DiD can be specified as (see Mostly ...


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Yes, it is acceptable. Consider a Mincer wage equation. Let's define a dummy variable Female taking on the value one for females and the value zero for males and a dummy variable Married to equal one if a person is married and zero if otherwise. Then, you can estimate a model that allows for wage differences among four groups: married men, married women, ...


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There are legitimate reasons for wanting to send out more to one group than the other - for example, if you need a sample size of at least 100 to have sufficient power to use certain tests, and you wanted to be able to do some in-group comparisons, you might oversample one or the other. Example: You have 1000 jobs available to sample. You want to test the ...


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No, this should not be a major issue. We will very carefully take into account the different sample sizes. Allow me to continue your example: Assume "Resume A" is the the treatment resume and "Resume B" is the control resume, where the treatment has a less advantaged ethnic name (Jamal, Beyonce) and the control resume contains a ...


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They generally measure the probability of getting an interview, not the number of interviews, so that that the number of applications is normalized out. For example, consider Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination (AER 2004 with ~5000 citations). We study race in the labor market by ...


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