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\begin{document}

\bibliographystyle{APSR}

\begin{center}\begin{LARGE}\textbf{Democracy and Multilateralism: \\Supplementary Appendix}\end{LARGE}\end{center}

\bigskip

\subsection*{Overview of Appendix}

The appendix to ``Democracy and Multilateralism'' includes additional details and results not included in the main manuscript. Specifically, we provide:

\begin{itemize}

\item details about the creation of our punishment and rewards variable,

\item a table that lists all of the issues that are included as important votes along with the distribution of observations across these issues,

\item descriptive statistics for the regressors included in U.S. and recipient utilities, 

\item additional figures that show the how the combination of GDP per capita and trade affect predicted probabilities,

\item the full table of results for the Cold War and post-Cold War periods described in the main text,

\item alternative results for the Cold War and post-Cold War periods that use 1991 as the last year of the Cold War,


\item tables that show the relationship between correct prediction and democracy in the full sample, 

\item results using a 99\% and a 90\% confidence interval threshold for creation of the aid reward and aid punishment variables,

\item results that treat abstentions as disagreement with the US position rather than agreement,

\item results from a random sample of one vote per recipient per year, and,

\item results using a measure of aid punishments and rewards that is only based on aid data from 1980 onwards,

\item evidence that shocks from natural disasters are irrelevant to US aid disbursement and consequently do not influence our coding of aid rewards.


%\item the full set of estimated results for the Cold War and post-Cold War samples, with the main results reported in the paper provided for comparison.

\end{itemize}


\section*{Creation of the Punishment and Reward Variables}

Creation of the aid disbursement variables requires care to ensure that we do not treat aid fluctuations that result
from temporal trends such as inflation or exogenous factors unrelated to particular UN votes as punishments or rewards. For each country $i$, aid at time $t$ is estimated using the following specification
\begin{equation}\label{panel_est}
AID_{i,t}=\beta_{i}+COM_{i,t}\beta_{1}+AID_{i,t-1}\beta_{2}+\epsilon_{i,t}.
\end{equation}

\noindent We focus on the post-1984 period in our main analysis, but we use the full time-series of aid disbursement data from 1966--2001 to predict disbursements, because the information about aid trends contained in the prior years sharpens the predictions of the model. Including more time units also avoids some potential methodological concerns specific to dynamic panel models, which we discuss below. The inclusion of more than one lag has no effect on the fit or predictions of the model, so we include only the first lag. The inclusion of year-fixed effects does not change the results or predictive power of the model, so we exclude them. The estimation results are as follows.

\begin{center}
[Table \ref{predmodel} about here.]
\end{center}

%\begin{table}[!h]
%\begin{center}
%\caption{Results of Predictive Model}\label{predmodel}
%\begin{tabular}{lcc}
%&&\\
%  \hline
%Variable & Estimate & Standard Error\\
%    \hline
%    &&\\
%Constant           &  9.186& 1.407 \\
%&&\\
%$Commitments_{t}$ &  0.387& 0.007 \\
%&&\\
%$Aid_{t-1} $     &  0.332 & 0.010 \\
%&&\\
%  \hline
%\end{tabular}
%\end{center}\vspace{-3mm}
%\vspace{0mm}\hspace{42mm}\footnotesize{R-Squared Within Group: 0.53} \\ %
%\vspace{0mm}\hspace{42mm}\footnotesize{R-Squared Between Group: 0.99} \\ %
%\vspace{0mm}\hspace{42mm}\footnotesize{F-test for Fixed Effects: $P>$0.006} \\ %
%\end{table}

We are not substantively interested in the coefficients in this model, since its purpose is to forecast aid disbursements, but it is reassuring that aid commitments are positively associated with aid disbursements. The strong fit of the model is not unexpected with a lagged dependent variable and fixed effects, but it justifies our claim that observations that fall outside of the confidence interval are unexpected and potentially important. We utilize the model shown in Table \ref{predmodel} to produce predicted aid disbursements with 95\% confidence
intervals for each recipient in each year. The punishment variable takes a value of one if the actual aid
disbursement is below the lower bound of the 95\% confidence
interval, and zero otherwise, and the reward variable takes a value of 1
if the actual disbursement is greater than the upper bound of the
95\% confidence interval, and zero otherwise.

There are a couple of potential methodological concerns about the model depicted in equation \ref{panel_est}, which we briefly address here. First, given the time-series component and the $R^{2}\approx0.99$, one might be concerned that aid disbursements have unit root. We test for a unit root in each panel using the Dickey-Fuller test and combine the tests across (unbalanced) panels using four Fisher-type tests proposed by \citet{choi01}. All test statistics reject the hypothesis that there is a unit root. Given the panel structure of the data, one might be concerned that the inclusion of fixed effects and a lagged dependent variable induce bias, i.e., ``Nickell bias'' \citep{nickell81}. \citet{judsonowen99} provide extensive Monte Carlo evidence which suggests that bias is not an issue for data with at least 30 time periods and 100 cross-sectional units. Given that we have 35 years and 165 potential recipient countries, we are not worried about bias. Furthermore, if we drop our lagged dependent variable, the coefficient on our commitments variable (i.e., $\beta_{1}$) is unaffected. Thus, bias does not appear to be an issue here. Note that the existence of either a unit root or Nickell bias would affect the validity of any inferences drawn from the coefficients presented in Table \ref{predmodel}, which we do not use, but would not affect the validity of our measures of punishments and rewards.

\section*{Descriptive Statistics}

Table \ref{votes_table} depicts the full range of issues that comprised important votes identified by the U.S. State Department between 1985--2001. While the topics of human rights, weapons of mass destruction, and the Israel-Palestine conflict are the most frequent, the table establishes that there is a fairly wide range of additional topics. Table \ref{desc.stats} displays descriptive statistics for the regressors included in the U.S.'s and the recipients' utility functions. 

 
\begin{center}
[Table \ref{votes_table} about here.]
\end{center}


\begin{center}
[Table \ref{desc.stats} about here.]
\end{center}


\section*{Wealth and Trade Figures}

Figures  \ref{graphs2:edge-a}--\ref{graphs2:edge-b} show the effects that GDP per capita and trade have on the probabilities that the U.S. will reward or punish an aid recipient. Figure \ref{graphs2:edge-a} further illustrate our finding that the U.S. is more likely to punish relatively poor recipients, who are more sensitive to aid flows. However, the probability of punishment also decreases as we look at countries with stronger trade relations with the U.S. Thus, the influence that the U.S. has on poorer recipients dissipates with strength of trade ties, as the threat (and pain) of punishments becomes less credible. Figure \ref{graphs2:edge-a} shows a trend consistent with this interpretation, as rewards are also less likely to flow to countries with stronger trade ties with the U.S. Aid rewards are less likely to have great effect in countries that enjoy such strong bilateral trade relationships with the U.S. Wealthier countries are more likely to be rewarded, although the effect is sharpest where the U.S. has minimal trade ties with the recipient. 


Figures \ref{graphs2:edge-c}--\ref{graphs2:edge-d} explore the strategic effects of rewards and punishments by
illustrating how the probability of recipient opposition changes as a function of GDP per capita and trade. Figure
\ref{graphs2:edge-c} depicts ``Yes'' votes while \ref{graphs2:edge-d} depicts more controversial ``No'' votes.  Again,
recipient behavior is markedly different on ``No'' votes than on ``Yes'' votes.  In both cases, however, poor countries
and those that have a high volume of trade with the United States are the most likely to oppose the U.S. position.  Poor countries have preferences that are inherently opposed to those of the United States \citep{kimrussett96,voeten00}.  

%The positive coefficient in the third column of Table 4 (4.42) indicates that as countries increase in development, they come to prefer receiving U.S. rewards to voting in opposition, which implies the opposite for poor countries.  As countries become poorer, in fact, the increasing preference for opposing the United States overwhelms the fact that poor countries are more vulnerable to U.S. sanctions.  The positive coefficient (9.87) in the first column indicates that the cost of aid withheld is greatest for poor countries, but they nevertheless oppose U.S. positions more frequently.

\begin{center}
[Figure \ref{graphs2} about here.]
\end{center}

It is a counter-intuitive result that high-volume trading partners are more likely to vote against the United States. The explanation is strategic.  The United States is unlikely to punish or reward its major trading partners, which provides more leeway for these governments to vote against the U.S. position. The substantive significance of this finding depends on the level of economic development, but trade volume has a monotonic effect that increases opposition.

\section*{Cold War and Post-Cold War: 1989 Cutpoint}

In table \ref{cw_results89} we display the full results for the Cold War and post-Cold War subsamples. These are the results that are discussed in the main text and also are the basis of the substantive effects in table 3 in the main text.

\begin{center}
[Table \ref{cw_results89} about here.]
\end{center}


\section*{Cold War and Post-Cold War: 1991 Cutpoint}

In table \ref{subst_cw91} we display a table of substantive effects for the Cold War and post-Cold War subsamples that treats 1991 as the end of the Cold War. The table is identical to table 3 in the main text, to facilitate comparison to the results that treat 1989 as the end of the Cold War. These results demonstrate that our findings are not dependent upon this choice, as the results and the differences between the Cold War and post-Cold War periods are not substantially different if we treat 1991 as the end of the Cold War. We report the 1989 results in the main text as 1989 is a more appropriate cutoff point for the Cold War period, given that the fall of communism in Eastern Europe effectively ended Cold War era East-West competition. Indeed, it makes sense to think that US policy would take this change into account and begin reaching out to former communist countries in a different way after 1989. However, table \ref{subst_cw91} demonstrate that our conclusions are not dependent upon this choice.

\begin{center}
[Table \ref{subst_cw91} about here.]
\end{center}

%Note that we do not show the utilities for which only a constant is estimated in the models, e.g., $U_{R}(\neg Reward)$ in the table that displays the main results in the text. Instead, we move this estimated coefficient into the player's utility for the opposite outcome and flip the sign, e.g., $U_{R}(Reward)$ for the constant included in $U_{R}(\neg Reward)$. This is done to make the table fit on one page. The results in the table are described in the main manuscript. Note that our central findings concerning the role that democracy plays in U.S. strategy are robust across the two periods. %However, the role that the left-right orientation of the executive and a recipient's status as a U.S. ally change in intuitive ways after the end of the Cold War. In general, 


\section*{Predictive Power of Strategic and Non-Strategic Models}

Table \ref{democracy_prediction} summarizes the relationship between prediction and regime type. The table is based on a comparison of the main model presented in the text (in table 1) and the non-strategic alternative. The table contains a cross-tabulation of whether the strategic model produces better predictions than the non-strategic model for a given case and whether the case involves a democratic or non-democratic recipient country. This is an interesting and informative way to examine the data given the importance of democracy to the theoretical discussion and empirical results. The tabulations show that while the strategic model predicts more accurately for both democracies and non-democracies, its advantage in predictive power is much greater for democracies. The bold numbers in the table indicate the raw data, while the numbers in parentheses indicate the ``expected numbers'' under the assumption of independence between democracy and predictive power. Clearly, the strategic model's predictive power is closely related to the democracy/non-democracy distinction, as the Chi-square test statistic is over 750 with one degree of freedom. 

\begin{center}
[Table \ref{democracy_prediction} about here.]
\end{center}

%Table \ref{prediction} summarizes the prediction data for Pakistan described in the paper. As noted in the main text, the strategic model has more predictive power almost 100\% of the time in the years that Pakistan is a democracy, while it has more predictive power 60\% of the time when Pakistan is a non-democracy.
%
%\begin{center}
%[Table \ref{prediction} about here.]
%\end{center}

\section*{Alternative Thresholds for Aid Deviations}

As noted above, we generate our aid punishment and aid rewards variables by (1.) identifying a good predictive model of aid flows and (2.) identifying whether aid flows from the US to a recipient in a given year fall above or below the predicted 95\% confidence intervals. We defend this approach in the main text and think it is an appropriate way to measure significant deviations and to also tie them to voting behavior. The choice of a 95\% threshold is not wholly arbitrary, as it is probably the most common threshold used in the literature and also generates a conservative measure of rewards and punishments. However, we also want to ensure that our results are not too dependent on our choice of threshold, as a 90\% or 99\% threshold may also be deemed reasonable. Thus, we also generated our dependent variables using these two alternative thresholds to identify punishments and rewards. The predicted marginal effects using the 99\% threshold are shown in table \ref{results_99}, while the results using the 90\% threshold are shown in table \ref{results_90}. The results do not differ in any theoretically important ways from the main results presented in the text. Specifically, our key findings about the relationship between democracy, voting behavior, and US aid policy are robust to these alternative thresholds. 

\begin{center}
[Table \ref{results_99} about here.]
\end{center}

\begin{center}
[Table \ref{results_90} about here.]
\end{center}


\section*{Alternative Treatment of Abstentions}

Another potential objection to the results reported in the main text involves our treatment of abstentions. As noted in the text, we treat recipient country abstention from an important vote as agreement, as the US often works hard to obtain abstentions on controversial important votes. While we think this is the substantively correct way to treat abstentions, we are sensitive to the potential criticism that our treatment of abstentions is inappropriate or is too influential in driving our key results. To assess whether this is the case we also create our dependent variables assuming that abstentions indicate disagreement. The results of this robustness check are contained in table \ref{results_abstain}. While some of the secondary results change slightly, our main findings about the behavior of democracies is robust to this change. We alert readers to this robustness check in footnote 17 in the main text.

\begin{center}
[Table \ref{results_abstain} about here.]
\end{center}


\section*{Randomly Sample One Vote per Year}

We are also sensitive to multiple important votes in each year potentially biasing our results. We address problems that the lack of independence among these votes might introduce in our standard errors by bootstrapping the standard errors and sampling by year. The results are very similar if we bootstrap the standard errors and sample by vote. However, this does not address the possibility that a country might vote against the US on a set of votes in a given year, and vote with the US on another set of votes in that year, which could lead to coding punishment of a recipient following disagreement and no action following agreement in the same year. Examination of the data suggests that this is not much of an issue. However, to assess whether it influences results at all, we randomly sample one vote per recipient per year and estimate our model. If multiple votes have no effect, the results for the random sample of votes should not differ from the full sample of votes. The results in table \ref{results_samp} confirm that this is the case. In short, multiple votes do not lead to any bias in the results.

\begin{center}
[Table \ref{results_samp} about here.]
\end{center}


\section*{Natural Disasters and Aid Rewards}

One potential objection to the creation of our aid reward variable is that aid increases that are unexpected given trends might be US reactions to natural disasters in the recipient. We investigate this and find no evidence that natural disasters have any significant effect on aid disbursements. Specifically, we include a measure of the level of damage from natural disasters to the aid prediction model presented in table \ref{predmodel}. The disaster data measures the estimated damage from earthquakes, mudslides, windstorms and hurricanes, volcanoes, and waves and surges. The data is from the Centre for Research on the Epidemiology of Disasters (CRED) and is also utilized in \citet{ramsay11}. We find that natural disasters are never a significant predictor of aid flows, regardless of whether we include the raw measure or include the natural log of damage from natural disasters. Furthermore, the punishment and reward variables are unaffected by inclusion of these variables. Natural disasters do not even have any effect on aid flows in cases where the US has made no aid commitment. This is perhaps not surprising given that our predictive model includes country-fixed effects and also is robust to inclusion of year-fixed effects. All of these results are presented in table \ref{results_d}. 

\begin{center}
[Table \ref{results_d} about here.]
\end{center}

\pagebreak


\bibliography{unvote3}


\pagebreak


\begin{table}[!h]
\begin{center}
\caption{Results of Predictive Model}\label{predmodel}
\begin{tabular}{lcc}
&&\\
  \hline
Variable & Estimate & Standard Error\\
    \hline
    &&\\
Constant           &  9.186& 1.407 \\
&&\\
$Commitments_{t}$ &  0.387& 0.007 \\
&&\\
$Aid_{t-1} $     &  0.332 & 0.010 \\
&&\\
  \hline
\end{tabular}
\end{center}\vspace{-3mm}
\vspace{0mm}\hspace{42mm}\footnotesize{R-Squared Within Group: 0.53} \\ %
\vspace{0mm}\hspace{42mm}\footnotesize{R-Squared Between Group: 0.99} \\ %
\vspace{0mm}\hspace{42mm}\footnotesize{F-test for Fixed Effects: $P>$0.006} \\ %
\end{table}

\pagebreak


\begin{table}[!h]
\begin{center}
\caption{Frequency of Important Vote Topics}\label{votes_table}
\vspace{2mm}
\begin{tabular}{lcc}
\hline
\\
Important Vote Issue & Total Number of Votes & Percentage of Total\\
\\
\hline
\\
Iraq & 12 & 4.4\% \\[1.3ex]
Afghanistan & 6 &  2.2\% \\[1.3ex]
Cuba & 18 & 6.6\% \\[1.3ex]
Kampuchea & 5 & 1.8\% \\[1.3ex]
Former Yugoslavia & 11 & 4.0\% \\[1.3ex]
Weapons of Mass Destruction* & 37 & 13.5\% \\[1.3ex]
Sudan & 6 & 2.2\% \\[1.3ex]
Human Rights**  & 67 & 24.5\% \\[1.3ex]
Iran & 15 & 5.5\% \\[1.3ex]
Nicaragua & 6 & 2.2\% \\[1.3ex]
International Peace \& Security & 12 & 4.4\% \\[1.3ex]
Israel/Palestine & 42 & 15.3\% \\[1.3ex]
Economic Issues & 12 & 4.4\% \\[1.3ex]
Democracy/Governance & 9 & 3.3\% \\[1.3ex]
Other Countries & 8 & 2.9\% \\[1.3ex]
Other Issues & 8  & 2.9\%\\[1.3ex]
\hline
\\
\multicolumn{3}{l}{* 7 votes are cross-listed with specific countries.}\\[.5ex]
\multicolumn{3}{l}{** 54 votes are cross-listed with specific countries.}
\end{tabular}
\end{center}
\end{table}

\pagebreak


\begin{sidewaystable}[!h]
\begin{center}
\caption{Descriptive Statistics for Regressors}\label{desc.stats}
\begin{tabular}{lccccccl}
&&&&&&\\
  \hline
   & Minimum &  Median & Mean &  Maximum & Standard& &Data Source\\
&&&&& Deviation && \\
    \hline
    &&      &    &   & & &\\
 Recipient Polity   &  -10 &  -1& 0.19 & 10 &6.99 && Polity IV \\
      &    &  &&& & & \\
 Allies & 0 & 0 & 0.22 & 1 & 0.41 && Correlates of War \\
      &    &  && &&  &\\
 GDP pc & 281.3 & 3358 & 4793 & 29170 & 4762.37 && Oneal and Russett \\
     &    &  && &&& \\
 Trade  & 0   & 318.40 & 3869 & 259500 & 15051.09 && Oneal and Russett\\
      &    &  & & &&& \\
 Left-Wing Executive &0 & 0 & 0.31&1 & 0.46& & Database of Political  \\
      &    &  & & & &&Institutions\\[1.3ex]
 Right-Wing Executive & 0 & 0 & 0.18 & 1 & 0.39& & Database of Political \\
      &    &  & & & &&Institutions\\[1.3ex]
   \hline
\end{tabular}
\end{center}
\end{sidewaystable}


\begin{center}
\begin{figure}[!h]
\subfigure[Trade, Development, and
Punishment]{\label{graphs2:edge-a}\includegraphics[scale=.5]{/Users/dbcarter/documents/Randy.Project/Results2/trade_gdp_4.pdf}}%
\subfigure[Trade, Development, and
Reward]{\label{graphs2:edge-b}\includegraphics[scale=.5]{/Users/dbcarter/documents/Randy.Project/Results2/trade_gdp_6.pdf}}\\
\subfigure[Development, Trade, and ``Yes''
Votes]{\label{graphs2:edge-c}\includegraphics[scale=.5]{/Users/dbcarter/documents/Randy.Project/Results2/trade_gdp_1_yes_lw.pdf}}%
\subfigure[Development, Trade, and ``No''
Votes]{\label{graphs2:edge-d}\includegraphics[scale=.5]{/Users/dbcarter/documents/Randy.Project/Results2/trade_gdp_1_no_lw.pdf}}
\caption{Trade, Wealth, and Predicted Behavior}\label{graphs2}%
\end{figure}
\end{center}



\begin{sidewaystable*}[!h]
\begin{scriptsize}
\begin{center}
\caption{Cold War and Post Cold War Effects: 1989 Cutpoint}\label{cw_results89}
\begin{tabular}{lcccccccccccccccccc}
  \hline\hline
  & & & & &&& & && &&&\\
&\multicolumn{3}{c}{\normalsize{$U_{R}(Punish)$}} &&\multicolumn{3}{c}{\normalsize{$U_{R}(Reward)$}}&&\multicolumn{3}{c}{\normalsize{$U_{U.S.}(Punish)$}} &&\multicolumn{3}{c}{\normalsize{$U_{U.S.}(Reward)$}}\\
  & & & & &&& & & &&&&\\
Variable   &   Cold War& Post- & Pooled &&   Cold War& Post- & Pooled & &  Cold War& Post- & Pooled &&   Cold War& Post- & Pooled \\				                                                    					 
& &  Cold War&&& &  Cold War&&& & Cold War&& & & Cold War&\\
    \hline\hline
        & & & & & && &&& & && \\
Recipient Polity & -0.82 & \textbf{-3.19} &\textbf{-3.50} &  &  \textbf{-2.00} & \textbf{-4.86} & \textbf{-0.63} && \textbf{0.05} & \textbf{0.09} &\textbf{0.05} &  &  \textbf{0.19} & \textbf{0.08} & \textbf{0.10} \\
& \tiny{(1.67)}&  \tiny{(0.32)}  &\tiny{(0.35)}&  &\tiny{(0.27)} & \tiny{(1.04)} &  \tiny{(0.15)} && \tiny{(0.02)}&  \tiny{0.01}  &\tiny{(0.01)}&  &\tiny{(0.02)} & \tiny{(0.01)} &  \tiny{(0.02)} \\[1ex]
Allies& 2.67 &  \textbf{-14.78}  & 0.04 && -1.45 & -4.15 & \textbf{-9.91} && \textbf{-1.19} &  \textbf{0.34}  & 0.19 && \textbf{-0.90} & 0.25 & 0.07\\                                                                                   				
&\tiny{(10.15)} & \tiny{(3.58)}  &\tiny{(3.69)} & & \tiny{(2.71)}& \tiny{(5.96)} &  \tiny{(1.51)} &&\tiny{(0.41)} & \tiny{(0.15)}  &\tiny{(0.13)} & & \tiny{(0.31)}& \tiny{(0.16)} &  \tiny{(0.35)}\\[1ex]
Recipient GDP&\textbf{-1.14}  & \textbf{13.71}  & \textbf{8.31} &&   \textbf{0.47} & \textbf{3.98} & \textbf{-0.34} & & \textbf{0.04}  & \textbf{-0.14}  & -0.09 &&   0.02 & 0.03 & 0.02 \\                                          		
&\tiny{(0.31)} & \tiny{(1.01)}& \tiny{(1.12)} & & \tiny{(0.21)} & \tiny{(0.76)} &  \tiny{(0.14)}& &\tiny{(0.02)} & \tiny{(0.02)}& \tiny{(0.16)} & & \tiny{(0.03)} & \tiny{(0.02)} &  \tiny{(0.03)}  \\[1ex]
Trade& -3.43 & \textbf{7.98} & \textbf{3.05}& & 91.10 & \textbf{11.67} & \textbf{1.73} && 0.33 & -0.06 & \textbf{-0.05}& & -0.13 & -0.08 & -0.08 \\
&\tiny{(48.27)}  & \tiny{(3.18)} & \tiny{(1.13)} & & \tiny{(57.65)}&  \tiny{(6.04)} &  \tiny{(0.55)} &&\tiny{(0.20)}  & \tiny{(0.06)} & \tiny{(0.02)} & & \tiny{(0.45)}&  \tiny{(0.07)} &  \tiny{(0.06)} \\[1ex]
Left-Wing Executive& \textbf{-45.55} & \textbf{-11.34} & 1.08 &  & 3.91 & \textbf{14.53} & 2.65 && \textbf{0.81} & \textbf{-0.51} & -0.07 &  & -0.54 & \textbf{-0.62} & \textbf{-0.54} \\
&\tiny{(3.59)} & \tiny{(2.89)} & \tiny{(3.88)} & & \tiny{(3.84)} &  \tiny{(3.49)} &  \tiny{(2.47)}& &\tiny{(0.21)} & \tiny{(0.14)} & \tiny{(0.11)} & & \tiny{(0.33)} &  \tiny{(0.17)} &  \tiny{(0.21)} \\[1ex]
Right-Wing Executive & \textbf{378.80} & 7.94 & \textbf{38.46} & &  \textbf{-6.46} & \textbf{66.24} & \textbf{10.40} && \textbf{-1.65} & \textbf{-0.56} & \textbf{-0.71} & &  \textbf{-0.85} & \textbf{-0.48} & -0.43  \\
&\tiny{(53.10)} & \tiny{(9.97)}& \tiny{(5.88)} & & \tiny{(3.06)} &  \tiny{(9.33)} &  \tiny{(4.19)} &&\tiny{(0.75)} & \tiny{(0.18)}& \tiny{(0.15)} & & \tiny{(0.37)} &  \tiny{(0.17)} &  \tiny{(0.29)} \\[1ex]
U.S. Votes No & \textbf{-1.67} & \textbf{-97.54}  &\textbf{-1.50}&  & \textbf{-3.25} & \textbf{-7.81} & -0.56 && \textbf{-0.11} & \textbf{-0.06}  &\textbf{-0.08}&  & \textbf{0.10} & \textbf{0.02} & \textbf{0.02}\\
& \tiny{(0.51)} & \tiny{(22.06)}  &\tiny{(0.46)} &&  \tiny{(0.45)} & \tiny{(1.24)} &  \tiny{(0.51)} && \tiny{(0.04)} & \tiny{(0.03)}  &\tiny{(0.03)} &&  \tiny{(0.03)} & \tiny{(0.01)} &  \tiny{(0.01)}\\
Constant & \textbf{76.81} & \textbf{98.06}  &\textbf{62.63}&  & \textbf{-1.50} & \textbf{-2.98} & \textbf{-5.79}& &\textbf{-2.29} & \textbf{-1.94}  &\textbf{-1.91}&  & \textbf{-2.27} & \textbf{-2.91} & \textbf{-2.85} \\
& \tiny{(23.44)} & \tiny{(23.22)}  &\tiny{(8.42)} &&  \tiny{(0.36)} & \tiny{(0.66)} &  \tiny{(0.69)} && \tiny{(0.49)} & \tiny{(0.32)}  &\tiny{(0.40)} &&  \tiny{(0.26)} & \tiny{(0.13)} &  \tiny{(0.21)}\\[1ex]
  \hline
     & & & & & &&& &&& & &&\\
N =   & 3822 & 10515 &14337 & & 3822 & 10515 &14337&& 3822 & 10515 &14337 & & 3822 & 10515 &14337\\
     & & & & & &&& & &&& &&\\                                                                                                                                                                               
\hline \hline																								                          \end{tabular}
\end{center}
\vspace{-2mm}\hspace{3mm}{Bootstrapped Standard Errors in Parentheses}\\ %
\vspace{-2mm}\hspace{3mm}{Bold Indicates Significance at the .05 Level} \\ %
\end{scriptsize}
\end{sidewaystable*}


\pagebreak



\begin{table}[!h]
\begin{center}
\caption{Marginal Effects of Regressors on U.S. Punishment Decision: 1991 Cold War Cutoff}\label{subst_cw91}
\begin{tabular}{lcccc}
\hline
&&&&\\
  & \multicolumn{2}{c}{Cold War} & \multicolumn{2}{c}{Post-Cold War} \\
  & \multicolumn{2}{c}{U.S. Punishment Decision} & \multicolumn{2}{c}{U.S. Punishment Decision} \\
&&&&\\
  \hline
   & Pr($Punishment$) & \% Change in Pr & Pr($Punishment$) & \% Change in Pr \\
    \hline
         &    &   & & \\
 Median Values    &  0.026 & NA  &  0.068 & NA \\
      &    &  & & \\
 Polity=7   &  \bf0.068  &  +108\%  & \bf0.101 &  +37\%  \\
   &       &    &  &  \\
 Polity=-9 & \bf0.023 & -12\% & \bf 0.025 & -51\% \\
     &    &   & & \\
 Alliance=1   & 0.014  &  -69\%  &  0.097 &  +8\%  \\
   &       &    &  &  \\
 Left-Wing & \bf0.047 & +119\% & \bf 0.041 & -5\% \\
     &    &   & & \\
 Right-Wing  &   \bf0.006   & -80\% & 0.044 &  -46\% \\
     &    &  & & \\
GDP per capita=1,000\$ & 0.024 & -8\% &\bf 0.094 &  +18\% \\
     &    &   & & \\
 GDP per capita=12,000\$  &  0.033  & +31\%  &\bf 0.020 &  -38\%\\
     &    &  & & \\
%Trade=Low & \textbf{0.031} & \textbf{-3\%} & 0.038 &  +0\% \\
%     &    &   & & \\
% Trade= High  &  \textbf{0.038}  & \textbf{+19\%} & 0.039 &  +3\% \\
%     &    &  & & \\
  \hline
\end{tabular}
\end{center}\hspace{2mm}\footnotesize{Bold Cells Indicate Statistical Significance}\\ %
\vspace{-2mm}\hspace{20mm}\\ %
\end{table}


%\begin{sidewaystable*}[!h]
%\begin{scriptsize}
%\begin{center}
%\caption{Cold War and Post Cold War Effects: 1991 Cutpoint}\label{cw_results91}
%\begin{tabular}{lcccccccccccccccccc}
%  \hline\hline
%  & & & & &&& & && &&&\\
%&\multicolumn{3}{c}{\normalsize{$U_{R}(Punish)$}} &&\multicolumn{3}{c}{\normalsize{$U_{R}(Reward)$}}&&\multicolumn{3}{c}{\normalsize{$U_{U.S.}(Punish)$}} &&\multicolumn{3}{c}{\normalsize{$U_{U.S.}(Reward)$}}\\
%  & & & & &&& & & &&&&\\
%Variable   &   Cold War& Post- & Pooled &&   Cold War& Post- & Pooled & &  Cold War& Post- & Pooled &&   Cold War& Post- & Pooled \\				                                                    					 
%& &  Cold War&&& &  Cold War&&& & Cold War&& & & Cold War&\\
%    \hline\hline
%        & & & & & && &&& & && \\
%Recipient Polity & -0.18 & \textbf{2.85} &\textbf{2.75} &  &  -9.33 & \textbf{-4.41} & \textbf{-5.63} && \textbf{0.06} & \textbf{0.07} &\textbf{0.05} &  &  \textbf{0.16} & \textbf{0.13} & \textbf{0.13} \\
%& \tiny{(2.06)}&  \tiny{(0.63)}  &\tiny{(0.64)}&  &\tiny{(14.12)} & \tiny{(0.97)} &  \tiny{(1.02)} && \tiny{(0.01)}&  \tiny{0.01}  &\tiny{(0.01)}&  &\tiny{(0.02)} & \tiny{(0.01)} &  \tiny{(0.01)} \\[1ex]
%Allies& -6.40 &  \textbf{-33.37}  & \textbf{-30.69} && -11.51 & -2.48 & -2.99 && \textbf{-0.66} &  \textbf{0.51}  & 0.19 && \textbf{-0.61} & -0.13 & -0.17\\                                                                                   				
%&\tiny{(12.83)} & \tiny{(5.91)}  &\tiny{(5.02)} & & \tiny{(28.96)}& \tiny{(5.47)} &  \tiny{(5.79)} &&\tiny{(0.30)} & \tiny{(0.15)}  &\tiny{(0.13)} & & \tiny{(0.28)}& \tiny{(0.17)} &  \tiny{(0.14)}\\[1ex]
%Recipient GDP&\textbf{14.52}  & \textbf{10.26}  & \textbf{9.87} &&   9.64& \textbf{3.69} & \textbf{4.42} & &0.02  & \textbf{-0.19}  & -0.09 &&   \textbf{0.07} & \textbf{0.06} & \textbf{0.06} \\                                          		
%&\tiny{(5.67)} & \tiny{(1.72)}& \tiny{(1.90)} & & \tiny{(8.69)} & \tiny{(0.72)} &  \tiny{(0.79)}& &\tiny{(0.02)} & \tiny{(0.02)}& \tiny{(0.16)} & & \tiny{(0.02)} & \tiny{(0.01)} &  \tiny{(0.01)}  \\[1ex]
%Trade& -50.77 & \textbf{-16.59} & \textbf{-15.86}& & 69.21& \textbf{10.60} & 11.46 && \textbf{0.19} & -0.03 & \textbf{-0.05}& & -0.10 & \textbf{-0.08} & \textbf{-0.11} \\
%&\tiny{(40.62)}  & \tiny{(4.63)} & \tiny{(5.04)} & & \tiny{(42.84)}&  \tiny{(5.27)} &  \tiny{(6.39)} &&\tiny{(0.08)}  & \tiny{(0.02)} & \tiny{(0.02)} & & \tiny{(0.14)}&  \tiny{(0.03)} &  \tiny{(0.03)} \\[1ex]
%Left-Wing Executive& 0.27 & \textbf{-10.16} & \textbf{-9.85} &  & -10.32 & \textbf{13.92} & \textbf{14.76} && \textbf{0.66} & \textbf{-0.57} & \textbf{-0.07} &  & -0.27 & \textbf{-0.60} & \textbf{-0.44} \\
%&\tiny{(18.42)} & \tiny{(2.98)} & \tiny{(3.26)} & & \tiny{(44.05)} &  \tiny{(3.58)} &  \tiny{(4.59)}& &\tiny{(0.20)} & \tiny{(0.15)} & \tiny{(0.11)} & & \tiny{(0.26)} &  \tiny{(0.18)} &  \tiny{(0.15)} \\[1ex]
%Right-Wing Executive & 4.87 & 9.43 & 6.96 & &  \textbf{158.02} & \textbf{60.25} & \textbf{68.74} && \textbf{-1.49} & \textbf{-0.52} & \textbf{-0.71} & &  -0.14 & \textbf{-0.44} & -0.28  \\
%&\tiny{(24.80)} & \tiny{(9.26)}& \tiny{(10.41)} & & \tiny{(34.81)} &  \tiny{(8.31)} &  \tiny{(8.85)} &&\tiny{(0.52)} & \tiny{(0.16)}& \tiny{(0.15)} & & \tiny{(0.30)} &  \tiny{(0.18)} &  \tiny{(0.16)} \\[1ex]
%U.S. Votes No & \textbf{-189.79} & \textbf{-90.94}  &\textbf{-109.71}&  & \textbf{-5.93} & \textbf{-7.48} & \textbf{-6.82} && \textbf{0.18} & \textbf{0.24}  &\textbf{0.22}&  & \textbf{-0.20} & \textbf{-0.15} & \textbf{-0.16}\\
%& \tiny{(23.81)} & \tiny{(19.49)}  &\tiny{(21.39)} &&  \tiny{(1.11)} & \tiny{(1.23)} &  \tiny{(1.25)} && \tiny{(0.04)} & \tiny{(0.04)}  &\tiny{(0.02)} &&  \tiny{(0.02)} & \tiny{(0.01)} &  \tiny{(0.01)}\\
%Constant & \textbf{195.03} & \textbf{91.19}  &\textbf{110.53}&  & \textbf{-0.59} & \textbf{-0.28} & \textbf{-0.32}& &\textbf{-0.51} & \textbf{-0.48}  &\textbf{-0.49}&  & \textbf{-0.27} & \textbf{-0.34} & \textbf{-0.32} \\
%& \tiny{(26.27)} & \tiny{(20.46)}  &\tiny{(22.59)} &&  \tiny{(0.11)} & \tiny{(0.06)} &  \tiny{(0.07)} && \tiny{(0.04)} & \tiny{(0.04)}  &\tiny{(0.02)} &&  \tiny{(0.03)} & \tiny{(0.01)} &  \tiny{(0.01)}\\[1ex]
%  \hline
%     & & & & & &&& &&& & &&\\
%N =   & 4966 & 9371 &14337 & & 4966 & 9371 &14337&& 4966 & 9371 &14337 & & 4966 & 9371 &14337\\
%     & & & & & &&& & &&& &&\\                                                                                                                                                                              \hline \hline																								                             
%\end{tabular}
%\end{center}
%\vspace{-2mm}\hspace{3mm}{Bootstrapped Standard Errors in Parentheses}\\ %
%\vspace{-2mm}\hspace{3mm}{Bold Indicates Significance at the .05 Level} \\ %
%\end{scriptsize}
%\end{sidewaystable*}


\begin{table}[!h] \caption{Correct Prediction and Democracy}\label{democracy_prediction}
\begin{center} \begin{tabular} {c|c|c|c}
 & No  &\;\; Improvement \;\; &\; Row \\
 & \; Improvement \; & in Prediction & \; Sum\\
 \hline
 & & & \\
Non-Democracy & \textbf{4293} & \textbf{4716} & \textbf{9019} \\[1ex]
 & (3510) & (5466) & \\
 & & & \\
 \hline
  & & & \\
Democracy & \textbf{1303} & \textbf{4015} & \textbf{5318} \\[1ex]
 & (2070) & (3223) & \\
  & & & \\
\hline
 & & & \\
Column Sum & \textbf{5596} & \textbf{8714} & \textbf{14337} \\ \end{tabular} \end{center}
\vspace{2mm}\hspace{30mm}
\normalsize{\textbf{$\chi^{2}$=750.01}}\vspace{2in}
%\normalsize{\textbf{$\chi^{2}$=750.01}}\\
\end{table}


\begin{sidewaystable}[!h]
\begin{center}
\caption{Marginal Effects of Regressors on U.S. and Recipient Choices: 99\% Confidence Interval}\label{results_99}
\begin{tabular}{lcccccc}
\hline
&&&&&&\\
  & \multicolumn{4}{c}{U.S. Punishment and Reward Decision} & \multicolumn{2}{c}{Recipient Voting Decision} \\
&&&&&&\\
  \hline
   & Pr($Punish$)  & \% Change in Pr & Pr($Reward$) &  \% Change in Pr & Pr($Vote\;With\; U.S.$) & \% Change in Pr \\
    \hline
    &&      &    &   & & \\
 Median Values    &  0.034 & NA & 0.062 & NA  &  0.094 & NA \\
      &    &  && & & \\
 Polity=-9 & \bf0.022  &-35\%& \bf0.030 &-52\% & \bf0.062 & -34\%\\
      &    &  && & & \\
 Polity=7 &\bf 0.051  &+50\%& \bf0.122 & +97\% & \bf0.088 &  -6\% \\
     &    &  && & & \\
Alliance=1  & 0.034   & +0\%  &  0.067 & +8\% & \bf0.065 &  -31\%  \\
   &    &  &   &    &    \\
 Recipient GDP=1,000   & 0.036   & +6\% &\bf 0.055  & -12\% &  \bf0.070 &  -25\%\\
      &    &  && & & \\
 Recipient GDP=12,000 & 0.027  &-21\%&\bf 0.091 &+47\%  & \bf0.167 &  +78\%\\
      &    &  && & & \\
       Trade=15 million & 0.034  & +0\% & 0.062 &+0\% & \bf0.094 &  -0\%  \\
      &    &  && & & \\
 Trade=10 billion & 0.031  &-6\%& 0.058 & -7\% & \bf0.102 &  +9\%\\
      &    &  && & & \\
 Left-Wing & 0.033  & -3\% & \bf0.034 & -45\% & 0.086 &  -9\% \\
     &    &  && & & \\
 Right-Wing & 0.018  & -47\% &  0.037  & -40\%& \bf0.093 &  -1\% \\
     &    &&&   & & \\
 Yes Vote &  \bf0.072 & +112\% & \bf0.044 & -29\% & \bf0.969  & +931\% \\
     &    & &  & && \\
  \hline
\end{tabular}
\end{center}
\vspace{-2mm}\hspace{2mm}\footnotesize{Bold Cells Indicate Statistical Significance}\\ %
\end{sidewaystable}

\begin{sidewaystable}[!h]
\begin{center}
\caption{Marginal Effects of Regressors on U.S. and Recipient Choices: 90\% Confidence Interval}\label{results_90}
\begin{tabular}{lcccccc}
\hline
&&&&&&\\
  & \multicolumn{4}{c}{U.S. Punishment and Reward Decision} & \multicolumn{2}{c}{Recipient Voting Decision} \\
&&&&&&\\
  \hline
   & Pr($Punish$)  & \% Change in Pr & Pr($Reward$) &  \% Change in Pr & Pr($Vote\;With\; U.S.$) & \% Change in Pr \\
    \hline
    &&      &    &   & & \\
 Median Values    &  0.050 & NA & 0.075 & NA  &  0.126 & NA \\
      &    &  && & & \\
 Polity=-9 &\bf 0.030  &-40\%& \bf0.039 &-48\% & \bf0.065 & -48\%\\
      &    &  && & & \\
 Polity=7 & \bf0.083  &+66\%& \bf0.140 & +87\% & \bf0.108 &  -14\% \\
     &    &  && & & \\
Alliance=1  &  0.059  & +18\% & 0.081 & +8\% & \bf0.092 &  -27\%  \\
   &    &  &   &    &    \\
 Recipient GDP=1,000   & \bf0.059   & +18\% & \bf0.081  & +8\% &  \bf0.082 &  -35\%\\
      &    &  && & & \\
 Recipient GDP=12,000 & \bf0.028  &-44\%& \bf0.084 &+12\%  & \bf0.206 &  +63\%\\
      &    &  && & & \\
       Trade=15 million & 0.050  & +0\% & 0.075 &+0\% & \bf0.126 &  +0\%  \\
      &    &  && & & \\
 Trade=10 billion & 0.047  &-6\%& 0.071 & -5\% & \bf0.119 &  -6\%\\
      &    &  && & & \\
 Left-Wing & 0.055  & +10\% & \bf0.047 & -37\% & \bf0.133 &  +5\% \\
     &    &  && & & \\
 Right-Wing & 0.035  & -30\% &  0.053  & -29\% &\bf 0.101 &  -20\% \\
     &    &&&   & & \\
 Yes Vote &  \bf0.104 & +108\% & \bf0.064 & -19\% & \bf0.985  & +682\% \\
     &    & &  & && \\
  \hline
\end{tabular}
\end{center}
\vspace{-2mm}\hspace{2mm}\footnotesize{Bold Cells Indicate Statistical Significance}\\ %
\end{sidewaystable}


\begin{sidewaystable}[!h]
\begin{center}
\caption{Marginal Effects of Regressors on U.S. and Recipient Choices: Abstentions as Disagreement}\label{results_abstain}
\begin{tabular}{lcccccc}
\hline
&&&&&&\\
  & \multicolumn{4}{c}{U.S. Punishment and Reward Decision} & \multicolumn{2}{c}{Recipient Voting Decision} \\
&&&&&&\\
  \hline
   & Pr($Punish$)  & \% Change in Pr & Pr($Reward$) &  \% Change in Pr & Pr($Vote\;With\; U.S.$) & \% Change in Pr \\
    \hline
    &&      &    &   & & \\
 Median Values    &  0.047 & NA & 0.082 & NA  &  0.011 & NA \\
      &    &  && & & \\
 Polity=-9 & \bf0.028  &-40\%& \bf0.049 &-40\% & \bf0.003 & -73\%\\
      &    &  && & & \\
 Polity=9 & \bf0.077  &+64\%& \bf0.134 & +63\% & \bf0.011 &  -0\% \\
     &    &  && & & \\
Alliance=1  &  0.054  & +15\%  & 0.113 & +38\% & \bf0.002 &  -82\%  \\
   &    &  &   &    &    \\
 Recipient GDP=1,000   &\bf 0.051   & +8\% & \bf0.074  & -10\% &  \bf0.007 &  -36\%\\
      &    &  && & & \\
 Recipient GDP=12,000 & \bf0.033  &-30\% &\bf 0.118 &+44\%  & \bf0.012 &  +9\%\\
      &    &  && & & \\
       Trade=15 million & \bf0.047  & +0\% & \bf0.082 &+0\% & \bf0.011 &  +0\%  \\
      &    &  && & & \\
 Trade=10 billion & \bf0.043  &-9\%& \bf0.081 & -1\% & \bf0.010 &  -9\%\\
      &    &  && & & \\
 Left-Wing & 0.047  & -0\% & 0.085 & +4\% & 0.012 &  +9\% \\
     &    &  && & & \\
 Right-Wing & \bf0.025  & -82\% &  0.056  & -32\% & \bf0.006 &  -45\% \\
     &    &&&   & & \\
 Yes Vote &  \bf0.063 & +34\% & \bf0.032 & -61\% & \bf0.719  & +6436\% \\
     &    & &  & && \\
  \hline
\end{tabular}
\end{center}
\vspace{-2mm}\hspace{2mm}\footnotesize{Bold Cells Indicate Statistical Significance}\\ %
\end{sidewaystable}


\begin{sidewaystable}[!h]
\begin{center}
\caption{Marginal Effects of Regressors on U.S. and Recipient Choices: One Vote per Country-Year Sample}\label{results_samp}
\begin{tabular}{lcccccc}
\hline
&&&&&&\\
  & \multicolumn{4}{c}{U.S. Punishment and Reward Decision} & \multicolumn{2}{c}{Recipient Voting Decision} \\
&&&&&&\\
  \hline
   & Pr($Punish$)  & \% Change in Pr & Pr($Reward$) &  \% Change in Pr & Pr($Vote\;With\; U.S.$) & \% Change in Pr \\
    \hline
    &&      &    &   & & \\
 Median Values    &  0.041 & NA & 0.095 & NA  &  0.088 & NA \\
      &    &  && & & \\
 Polity=-9 & \bf0.022  &-46\%& \bf0.039 &-52\% & \bf0.060 & -32\%\\
      &    &  && & & \\
 Polity=9 & \bf0.076  &+85\%& \bf0.211 & +140\% & \bf 0.073 &  -17\% \\
     &    &  && & & \\
Alliance=1  &  0.035  & -15\%  & 0.052 & -45\% & \bf0.165 &  +88\%  \\
   &    &  &   &    &    \\
 Recipient GDP=1,000   & 0.041   & +0\% & 0.089  & -6\% &  \bf0.075 &  -15\%\\
      &    &  && & & \\
 Recipient GDP=12,000 &0.039  &-5\%& 0.117 &+24\%  & \bf0.157 &  +78\%\\
      &    &  && & & \\
       Trade=15 million & 0.041  & +0\% & 0.095 &+0\% & 0.088 &  +0\%  \\
      &    &  && & & \\
 Trade=10 billion & 0.039  &-5\%& 0.088 & -7\% & 0.087 &  -2\%\\
      &    &  && & & \\
 Left-Wing & 0.060  & +46\% & 0.064 & -33\% &\bf 0.095 &  +8\% \\
     &    &  && & & \\
 Right-Wing & \bf0.016  & -61\% &  0.077  & -19\%& \bf0.073 &  -17\% \\
     &    &&&   & & \\
 Yes Vote &  0.022 & -46\% & \bf0.039 & -59\% & \bf0.981  & +1197\% \\
     &    & &  & && \\
  \hline
\end{tabular}
\end{center}
\vspace{-2mm}\hspace{2mm}\footnotesize{Bold Cells Indicate Statistical Significance}\\ 
\vspace{-2mm}\hspace{2mm}\footnotesize{Number of Observations 1897}\\ %
\end{sidewaystable}


\begin{sidewaystable}[!h]
\begin{center}
\caption{Marginal Effects of Regressors on U.S. and Recipient Choices: Post-1975 Aid Data}\label{post80_aid}
\begin{tabular}{lcccccc}
\hline
&&&&&&\\
  & \multicolumn{4}{c}{U.S. Punishment and Reward Decision} & \multicolumn{2}{c}{Recipient Voting Decision} \\
&&&&&&\\
  \hline
   & Pr($Punish$)  & \% Change in Pr & Pr($Reward$) &  \% Change in Pr & Pr($Vote\;With\; U.S.$) & \% Change in Pr \\
    \hline
    &&      &    &   & & \\
 Median Values    &  0.039 & NA & 0.049 & NA  &  0.080 & NA \\
      &    &  && & & \\
 Polity=-9 & \bf0.026  &-33\%& \bf0.023 &-53\% & \bf0.067 & -43\%\\
      &    &  && & & \\
 Polity=9 & \bf0.059  &+52\%& \bf0.100 & +104\% & \bf0.078 &  -46\% \\
     &    &  && & & \\
Alliance=1  &   0.048 & +23\% & 0.076 & +55\% & \bf0.035 &  -56\%  \\
   &    &  &   &    &    \\
 Recipient GDP=1,000   & 0.040   & +3\% & 0.047  & -4\% &  \bf0.063 &  -21\%\\
      &    &  && & & \\
 Recipient GDP=12,000 & 0.024  &-38\%& 0.055 &+12\%  & \bf0.148 &  +85\%\\
      &    &  && & & \\
       Trade=15 million & \bf0.039  & -0\% & 0.049 &+0\% & \bf0.079 &  -1\%  \\
      &    &  && & & \\
 Trade=10 billion & \bf0.032  &-18\%& 0.043 & -12\% & \bf0.093 &  +16\%\\
      &    &  && & & \\
 Left-Wing & 0.037  & -5\% & \bf0.029 & -41\% & \bf0.072 &  -10\% \\
     &    &  && & & \\
 Right-Wing & 0.025  & -36\% &  \bf0.022  & -55\% & \bf0.071 &  -11\% \\
     &    &&&   & & \\
 Yes Vote &  \bf0.024 & -38\% & 0.043 & -19\% & \bf0.958  & +1098\% \\
     &    & &  & && \\
  \hline
\end{tabular}
\end{center}
\vspace{-2mm}\hspace{2mm}\footnotesize{Bold Cells Indicate Statistical Significance}\\ %
\end{sidewaystable}



\begin{sidewaystable}[H]
\begin{small}
\caption{Natural Disasters and Aid Shocks}\label{results_d}
\vspace{-.1in}
\begin{center}
\begin{tabular}{lccccccccccc}

    \hline
    \\
    &  All     & All   & Zero  & Zero   &  All     & All   & Zero  & Zero \\
    &  Cases    &  Cases  & Commitments & Commitments &  Cases    &  Cases  & Commitments & Commitments \\
    \\
\hline \\[-12pt]
\\
Commitments$_{t}$ &  0.39**  &  0.38** &   &  & 0.39** &  0.39** & &   \\
 &  \footnotesize{(0.05)}& \footnotesize{(0.05)}&   &   &  \footnotesize{(0.05)} &\footnotesize{(0.05)} & & \\[.45ex]
Aid$_{t-1}$ &  0.33** & 0.33** & 0.18** & 0.18** & 0.33** & 0.33** & 0.18** & 0.18**\\
 &\footnotesize{(0.01)} & \footnotesize{(0.01)} & \footnotesize{(0.01)} & \footnotesize{(0.01)} &\footnotesize{(0.01)}  & \footnotesize{(0.01)} & \footnotesize{(0.01)} & \footnotesize{(0.01)} \\[.45ex]
Disaster Damage Estimate &  -0.40 & -1.01 & -0.04 & -1.91 &  &  \\
 &\footnotesize{(0.70)} & \footnotesize{(0.75)} & \footnotesize{(0.04)} & \footnotesize{(1.96)} &  &  \\[.45ex]
Log of Disaster Damage Estimate &   &  &  &  & -0.40 & -1.01 & -0.04& -1.91 \\
 & &  &  &  &\footnotesize{(0.70)}  & \footnotesize{(0.75)} & \footnotesize{(0.04)} & \footnotesize{(1.96)} \\[.45ex]
 Constant &  9.20** &   -0.41 &  3.28** & -1.11 & 9.20**  & -0.41 & 3.28** & -1.11  \\
 & \footnotesize{(2.04)} &\footnotesize{(4.85)}& \footnotesize{(0.03)}& \footnotesize{(3.40)} & \footnotesize{(2.04)} & \footnotesize{(4.85)} & \footnotesize{(0.03)} & \footnotesize{(3.40)}  \\[.45ex]
 \\
Year Fixed Effects &No &  Yes &   No & Yes & No & Yes & No & Yes \\[.45ex]
\\
Country Fixed Effects &Yes & Yes & Yes &Yes & Yes &Yes & Yes &Yes \\[1ex]
\hline
\\
N = &  4869  & 4869 & 1357 & 1357 & 4869 & 4869  & 1357 & 1357  \\[.45ex]
\\
\hline
\begin{footnotesize}Standard errors clustered\end{footnotesize}\\ \begin{footnotesize}by recipient in parentheses \end{footnotesize} \\ ** $p<.05$ ; * $p<.10$    \\
\end{tabular}
\end{center}
\end{small}
\end{sidewaystable}




\end{document} 
