Interpretation of a 2SLS Coefficient - Civil War Determinants I am a bit confused because of the interpretation of a coefficient in my analysis. I am using 2SLS in two different subsamples with economic growth as endogenous variable. It is instrumented by a variable for natural disasters. The outcome variable is a measure of civil conflict onset. The first stage shows that if natural disasters increase, economic growth decreases. The second stage then provides a positive coefficient for one subsample, while it produces a negative coefficient in the other subsample.
Does a positive coefficient in the second stage mean that a decrease in economic growth (as a consequence of increased natural disasters) decreases the risk of conflict onset?
I am confused because I do not know how to interpret the coefficients since the instrument is negatively correlated to the instrumented variable. If natural disasters would increase economic growth, then the interpretation would be easier since the direction is the same.
Below, you find my LaTeX Output Table. I hope this will help. The coefficients I am interested in are on the one hand -0.0312 and     0.0210 on the other hand.
I know, there is no F test and no control in the analysis. This analysis is not supposed to be sophisticated, it is basically just a means to understand the interpretation of those coefficients.

\begin{table}[t!]\centering
\begin{threeparttable}
\renewcommand{\arraystretch}{1.2} % Default value: 1
\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}
\begin{tabular}{l*{3}{c}}
\hline\hline
            &amp;\multicolumn{1}{c}{(1)}&amp;\multicolumn{1}{c}{(2)}&amp;\multicolumn{1}{c}{(3)}\\
            &amp;\multicolumn{1}{c}{GDP growth p.c.}&amp;\multicolumn{1}{c}{Onset of Conflict}&amp;\multicolumn{1}{c}{Onset of Conflict}\\
\hline
GDP growth p.c.&amp;                     &amp;    -0.0312\sym{**}&amp;     0.0210\sym{**}        \\
            &amp;                     &amp;     (-2.01)         &amp;      (2.00)         \\
Natural Disasters&amp;      -18.02\sym{***}&amp;     Instrument&amp;              Instrument       \\
            &amp;     (-3.39)         &amp;              &amp;                     \\
\hline
Observations       &amp;        3894         &amp;        3894         &amp;        3894         \\

\end{tabular}
\end{threeparttable}
\end{table}

The code produces following table:
$$
\begin{array}{|l|c|c|c|} 
 \hline
   &amp; \text{(1)} &amp; \text{(2)} &amp; \text{(3)} \\
   &amp; \text{GDP growth p.c.} &amp; \text{Onset of Conflict} &amp; \text{Onset of Conflict} \\ \hline
\text{GDP growth p.c.} &amp; &amp; -0.0312^{**}  &amp; 0.0210^{∗∗} \\ 
 &amp; &amp; (-2.01) &amp; (2.00) \\ 
\text{Natural Disasters} &amp; -18.02^{***} &amp; \text{Instrument} &amp; \text{Instrument}  \\ 
 &amp; (-3.39) &amp; &amp; \\ \hline
 \text{Observations} &amp; 3894 &amp; 3894 &amp; 3894 \\ \hline
\end{array}
$$
You have a model
$$(1)\  y = x \beta + e,$$
where $x$ is endogenous $\mathbb E[xe] \not =0$. This is the structural model in the sense that the parameter you are interested in is $\beta$ interpreted by its appearance in (1). In your case

y is civil conflict onset
x economic growth

suggesting that you are interested in examining how economic growth affects propensity for civil conflict. So positive $\beta$ means economic growth increase propensity for civil conflict.
Using 2SLS you get an IV-estimate of $\beta$ which we can denote $\hat \beta_{IV}$. When $\hat \beta_{IV}$ is positive it suggests that $\beta$ is positive and hence  economic growth increase propensity for civil conflict.
Interpretation is independent of $Cov(z,x)$ where $z$ is the instrument. Which in this case is

z is natural disaster.

For instrumental regression instruments must be relevant which in the simple univariate case reduces to $Cov(z,x) \not = 0$, but the sign is irrelevant (you can try to use $w := -z$ as instrument then $Cov(z,x) &lt; 0 \Leftrightarrow Cov(w,x) &gt; 0$ but the 2SLS estimate $\hat \beta_{IV}$ will be the same).