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As they clearly say on pp 2267: Alternative specifications were compared using the specification test by Davidson and MacKinnon and the Wald test of coefficient restrictions. So they two tests Davidson and MacKinnon specification test and Wald test. Wald test is a classic test for coefficient restrictions you can learn can learn more about it in any ...

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In Galı́ & Gertler (1999) the authors state that marginal costs is given by: $$MC_t = \frac{S_t}{\alpha}$$ where $\alpha$ is the labor elasticity (from the Cobb-Douglas prod. function), and $S_t$ is the labor share of income (i.e. what portion of output GDP goes to labor). Next they actually get around estimating $\alpha$ by expressing everything in ...

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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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Here's a paper link where they picked up a $R^2$ of over .99 I don't think this is particularly unusual or strange of a result, either. In estimating costs for firms in public utilities, I recall doing numerous exercises with real data from various utilities. I typically got $R^2$'s in the 0.95's or higher, so I feel they are fairly accurate within sample. ...

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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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