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Questions tagged [instrumental-variables]

Instrumental variables (IV) are used for causal inference with observational data in the presence of endogeneity when standard regression methods yield biased and inconsistent estimates.

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How to combine intention-to-treatment randomization with block randomized experimental designs for within-differences in Power Analysis

I want to calculate the power for my experiment. Within multiple blocks of similarities (e.g., same gender, same pre-treatment outcome), respondents get the opportunity to take part in a treatment. As ...
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Interaction of endogenous variable with binary predictors (feols)

I would like to inquire about the correct way to specify interactions of endogenous variable with binary predictors (time and treat) with the feols function. Ideally I would like to specify a 3 way ...
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IV estimation in R: reduced form, standard error and 1st stage

I am analysing a panel dataset of individuals. I have a set of dependent variables, Y, 1 endogenous variable, X and 1 instrument, Z. I also have a set of fixed effects, such as birth year, and birth ...
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If two IV yield distinct F-statistics in the first-stage regression, does it indicate that they are different IV, regardless of the correlation?

Suppose we are in a panel context where we are estimating while controlling for fixed effects. Let's assume that we have two instruments Z1 and Z2 for the X endogenous variable and both instrument are ...
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Can the exclusion restriction in instrumental variable estimation be expressed as $\mathrm{cov}(Z, Y | X) = 0$?

In instrumental variable (IV) estimation of the regression model $Y = \alpha + \beta X + \epsilon$, where $Y$ is the outcome, $X$ is an endogenous independent variable, $\epsilon$ is the error term, ...
Peter Jordanson's user avatar
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Why can we formally test the relevance assumption of instrument variable?

I saw in my old slides about IV, the professor said we cannot test exclusion assumption of IV but we can test relevance assumption of IV. His argument for not able to test exclusion is: $y=\beta_1 ...
Eileen's user avatar
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causal effect and exogeneity in small samples vs in large samples

Under this title two questions are included. In regression of Y on X and controls Z with random error e, In small sample if strictly exogeneity, i.e. E(e|X,Z)=0, is satisfied, does it means the ...
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Does an instrumental variable require independence between the instrument and treatment?

An instrumental variable Z is a legitimate instrument for T (the treatment) if the following hold: Z has a causal effect on Y that is fully mediated by T (i.e. no direct effect from Z to Y, and the ...
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Do first and second stage regressions combined with fixed effects have to follow the same model?

I suspect reverse causality between Y and X1, therefore I'm applying an instrumental variable approach to panel data. My main regression consists of country- and year-fixed effects. Do I have to also ...
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Does multiplying an exogenous variable reduce endogeneity?

Let $X$ be an endogenous variable, $Y$ be a non-negative exogenous variable, and $e$ the error term. Define $\operatorname{cov}(.,.)$ as the covariance. Then, $\operatorname{cov}(X,e) \neq 0$ and $\...
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Instrumental variable with measurement error

I have a question related to measurement error bias and the use of instrumental variables. Assume I have a continuous outcome variable $Y$ which is observed with no error and an endogenous (continuous)...
Panagiotis's user avatar
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Can I instrument multiple (related) variables with a single instrumental variable?

I have a valid instrumental variable, $Z$, for my endogenous variable $DeathRate$. I can decompose the latter into components, e.g.: $$ DeathRate = DeathRate^{GroupA} + DeathRate^{GroupB} $$ Could I ...
Martin Georg Haas's user avatar
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Endogeneity in cross sectional data

As someone new to econometrics, I am currently facing challenges in constructing a theoretically persuasive model to identify causal effects. My interest is whether agricultural labor demand in ...
Sho's user avatar
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Consistency of IV Estimator

I have a quick question about the proof of the consistency of the IV estimator. I following the Davidson and MacKinnon (1st ed.) text where, as one of their assumptions, they state the following ...
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Two-Step GMM and Instrumental Variable

I am trying to run a regression in r using country-level panel data with female labour force participation rate as the independent variable and lnGDP, lnGDP^2, Trade (as % of GDP), Fertility, School ...
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Do I need to include confounding variables in my regression model when I use instrument variables?

Suppose I believe 'Age', 'Gender', 'Ability', and 'Motivation' are confounding variables influencing both the dependent variable and endogenous variables. I use the 'Education Level' for the treatment ...
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Instrumental Variable with Conditional Randomization?

I am doing a study with an IV design. In my setting, the IV is only conditionally random within a year and within a cohort. In this case, do I simply include year and cohort as controls in the IV ...
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Instrumental variable for panel data

I am trying to quantify the effect of financial sanctions on cross-border capital flows. I have built a dyadic dataset of sanctions and capital flows by country pair and year. My sample period spans ...
Loki5714's user avatar
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2 answers
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Instrumental variable as a control variable

I understand that instrumental variable is used to address endogeneity bias since there could be correlation between the variable of interest and the error term. Suppose now we want to see the ...
hiu's user avatar
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Using multiple instruments to construct bounds

Suppose I have three candidate instruments $Z_1, Z_2, Z_3$ for the same endogenous variable $T$. I have no clear preference for which one the exclusion restriction is actually valid. Can I combine the ...
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Testing Exogeneity of regressors

Good evening, I have a problem with solving this exercise: I could calculate the F-Statistics with the weak instrument test on my own. But I don't know how to test for exogeneity with two endogenous ...
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Using instrumental variable in a difference-in-differences setup using feols

I have the following regression model: $$y_{ist} = \beta_0 + \beta_1 Post_{ist} + \beta2 Post_{ist} \times Distance_{i} + \theta_i + \alpha_t + \gamma_{st} + \epsilon_{ist} $$ Where, $y_{ist}$ is the ...
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3 answers
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Weak instrument but 2nd stage significant

My IV's 1st stage F-stat is 4.7 (considered weak by the rule of thumb). The 2nd-stage regression coefficient is significant. I wonder what is the best way to interpret such observations.
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Which approach (probably similar to 2SLS) should I use in order to estimate effects of fitted and residual components? Thinking about CF but not sure

I assume that the growth of variable $Y$ depends on variable $X$, and that the variable $X$ depends on variable $Z$. I would like to estimate the effect of $X$ on the growth of $Y$, but to ...
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Bias vs consistency in instrumental variable estimation

So in Mostly Harmless Econometrics, page 154, they analyse the bias of instrumental variables: They consider the case of one endogenous variable $x$, multiple instruments $Z$, and $\eta$ is the ...
clog14's user avatar
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Excluding second-stage covariates from first stage

I have a question about the inclusion/exclusion of certain covariates in a 2SLS model. My concern is that my instrumental variable, Z, influences Y through two pathways: X1 and X2. If I am ...
Carl's user avatar
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Partial derivative of interaction term with endogenous variable

I am trying to estimate the price elasticity based on a 2sls regression. The price in logarithmic form is treated as an endogenous variable. The price appears in an interaction term with income $\...
octopus161's user avatar
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Reverse Causality on a "exogenous" instrument Z

Suppose we want to do an instrumental variable regression. We have an endogenous variable X, exogenous instrument Z, dependent variable Y and an error term U. In order for the approach to be valid, we ...
Marlon Brando's user avatar
1 vote
1 answer
166 views

warning: variance matrix is nonsymmetric or highly singular [closed]

I get the above warning when running a 2SLS regression in Stata with robust standard errors. Specifically, I get this for the first stage, where in addition the first stage has no F-statistic, p-value,...
john_hawthorne's user avatar
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Temporal Order of Control Variables in 2SLS

I am analyzing pooled cross-sectional data with the instrumental variable being educational policy, the independent variable as high school graduation, and the dependent variable as subjective class ...
Nobody Nobody's user avatar
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Estimating Complier Average Causal Effect (CACE) in a Field Experiment with One-Sided Noncompliance

I am working on a referee report for a field experiment focused on the employment process. The experiment investigates if including a video in job applications can reduce employment disadvantages for ...
john_hawthorne's user avatar
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Time order problem of control variables in IV regression

Y is the dependent variable, X is the independent variable, and C is a control variable. However, since X is endogenous, I plan to use an instrumental variable Z for X. From what I understand, if I ...
Nobody Nobody's user avatar
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2sls with interaction terms

I am running 2sls. Dependent variable - y Independent variable - x Instrumental variables - z1, z2, z3, z4 Interaction terms - xz1, xz2, xz3, xz4 Control variables Thus, the first stage of 2sls: x ...
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Relevance & Exogeneity of IV

I got two questions which are somehow closely related: Let's take the famous study of Acemoglu et al. (The Colonial Origins of Comparative Development: An Empirical Investigation) as an example. When ...
Marlon Brando's user avatar
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Test an instrument's correlation with unobservable when it's redundant in structural equation

I'm working on Wooldridge's “Econometric Analysis of Cross Section and Panel Data” and I don't fully get why this test would not work. I'll share my work with screenshots so it's clearer hope that's ...
Facundo Arcusa's user avatar
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F-statistic Two stage least squares (2SLS) regression

In Wooldridge's advanced book, on page 105, the F-statistic for 2SLS regression is introduced. Let me illustrate the computation step by step with the following concrete example: \begin{equation} \...
Maximilian's user avatar
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Does reverse causality from Z to Y violate exclusion restriction in IV?

I am estimating the effect of endogenous X on Y using 2SLS estimator with an instrument variable (Z). X: Safety net program participation (binary), designed to increase household income Y: Household ...
TripleDDD's user avatar
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Can I use the same regressors for Instrumental variables and the outcome variable?

I'm reading a research paper that uses an IV, they regress A, and B, to estimate C, then they use estimated C and actual B to regress on D an outcome variable. This seems to violate the only through ...
Ahhhhhhhhh's user avatar
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Instrument variable analysis using randomized data

I am analyzing the effect of two randomized interventions on 1) first-time and, 2) second-time event attendance. All variables are binary (0 vs. 1). Second attendance was conditional on first ...
llsabang's user avatar
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Number of instruments in GMM (using pgmm in R)

Number of instruments used in GMM model (pgmm function in R) I performed a GMM (Generalized Methods of Moments) analysis in R using the ...
Li4991's user avatar
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Problems with GMM (Generalized Methods of Moments) in R

I am interested in performing an analysis using a GMM model for a panel dataset. I am conducting the analysis in R, using the pgmm package. My code is the following:...
Li4991's user avatar
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0 answers
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How to include random effect to ivreg model in R?

I have an endogenous variable X with instrumental variable Z and want to predict outcome variable Y. For this I have longitudinal data with user_id. Currently my model is: ...
pikachu's user avatar
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Serial correlation and heteroskedasticity in a first-stage regression of a 2SLS

I am about to test a Campbell-Mankiw's based model like: $$\Delta c(t) = \mu + \lambda \Delta y(t) + \theta r(t) + e(t)$$ where $ \Delta y(t) = \ln(y(t)) - \ln(y(t-1)),~ \Delta c(t) = \ln(c(t)) - \ln(...
Fernando's user avatar
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1 answer
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Are missing variables an important factor when considering instrumental variable analysis?

I'm currently reading some papers that deal with the effects of education on health (smoking and obesity). Mostly they use an IV approach (college availability). However in several analysis, only a ...
Hans Brecker's user avatar
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What econometrics method is better for the analysis?

I need some tips and tricks to figure out what would be an appropriate econometric method to find causal relationships between $x₁$ and $Y$ in my model $Y = α + β₁x₁ + β₂x₂ + \dotsm + βᵣxᵣ + ε$ where ...
Roe's user avatar
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1 vote
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Help understanding exact mechanics of IV under heterogenous treatment effects (LATE)

I have been reading Blundell and Costa-Dias (2009) to try and understand the exact mechanics why standard IV breaks when heterogenous treatment effects are involved. On page 62 there is an almost ...
Tele's user avatar
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The magnitude of an two-stages least squares coefficient is always larger than the ordinary least squares coefficient?

I have a hard time wrapping my head around this. I know that in case of measurement errors, the OLS estimate is biased downwards zero. Omitted variables can bias the explanatory variable of interest ...
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IVs: would this rainfall specification cut it?

I need feedback to check whether rainfall is an appropriate instrumental variable. Before you boo me out, hear what I have to say. There are two countries: A and B. A and B are 2000 miles apart. My ...
YouLocalRUser's user avatar
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When analyzing causality from X to Y, is IV regression better than Propensity Matching Score

When we are analyzing the causality from X to Y, especially when literature has used extensively IV regression and PSM as a method. However, as I know PSM is matching method while IV is a regression ...
siri's user avatar
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'Policy implementation' dummy as IV in panel data model: same across individuals?

I am using a control function approach for panel data. I have an endogenous variable in the outcome equation. I take this endogeneity into account by adding the generalised residuals of a selection ...
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