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 20 years.

I conducted a fixed effects regression where the explanatory variable for sanctions is a dummy variable that takes the value 1 in each year in which a sanction is imposed between a given country pair. I include fixed effects for each country pair and each year in the sample.

\begin{equation*} \text{Capital_flows}_{c1, c2, t} = \beta_0 + \beta_1 \text{sanction}_{c1, c2, t} + \eta_{c1, c2} + \varphi_t + \varepsilon_{c1, c2, t} \end{equation*}

(where $\eta_{c1, c2}$ is a set of country-combination specific fixed effects and $\varphi_{t}$ is a set of time-specific fixed effects.)

As I understand, my fixed effects will remove all the time-invariant factors determining capital flows that were previously included in my error term. As such, I am now stuck with the various time-variant factors determining capital flows.

Having done some reading, the main problem with my approach seems to be endogeneity, i.e., my sanctions dummy will be correlated with my error term. I was planning on addressing this issue by carefully adding additional (time-variant) control variables to my model.

However, having spoken to one of my professors, he mentioned that the way to resolve this is through an instrumental variable approach and a Generalised Method of Moments estimator.

I have several questions regarding all this, and would really appreciate any advice:

• Is my idea to address endogeneity through additional (time-variant) control variables wrong?
• What exactly would an instrumental variable approach with a GMM estimator require me to do? As far as I understand, it is often very hard to find adequate instrumental variables.
• From my reading it seems that researchers sometimes use lagged dependent variables as instrumental variables. Would something like this apply to my case?
• Is there another way of getting a consistent estimator?

Thank you!

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 20 years.

I conducted a fixed effects regression where the explanatory variable for sanctions is a dummy variable that takes the value 1 in each year in which a sanction is imposed between a given country pair. I include fixed effects for each country pair and each year in the sample.

\begin{equation*} \text{Capital_flows}_{c_1, c_2, t} = \beta_0 + \beta_1 \text{sanction}_{c_1, c_2, t} + \eta_{c_1, c_2} + \varphi_t + \varepsilon_{c_1, c_2, t} \end{equation*}

(where $\eta_{c_1, c_2}$ is a set of country-combination specific fixed effects and $\varphi_{t}$ is a set of time-specific fixed effects.)

As I understand, my fixed effects will remove all the time-invariant factors determining capital flows that were previously included in my error term. As such, I am now stuck with the various time-variant factors determining capital flows.

Having done some reading, the main problem with my approach seems to be endogeneity, i.e., my sanctions dummy will be correlated with my error term. I was planning on addressing this issue by carefully adding additional (time-variant) control variables to my model.

However, having spoken to one of my professors, he mentioned that the way to resolve this is through an instrumental variable approach and a Generalised Method of Moments estimator.

I have several questions regarding all this, and would really appreciate any advice:

• Is my idea to address endogeneity through additional (time-variant) control variables wrong?
• What exactly would an instrumental variable approach with a GMM estimator require me to do? As far as I understand, it is often very hard to find adequate instrumental variables.
• From my reading it seems that researchers sometimes use lagged dependent variables as instrumental variables. Would something like this apply to my case?
• Is there another way of getting a consistent estimator?