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\begin{document}

% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% MAIN ANALYSIS
% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\section*{Does Patient Demand Contribute to the Overuse of Prescription Drugs? (Lopez Sautmann, Schaner)}
\section*{Main Figures and Tables}
\begin{landscape}

% THEORY EXAMPLE
\begin{figure}[ht]
	\caption{Patient Preferences and Doctor Voucher-Sharing Strategies}
	\vspace{1.4cm}
		\label{fig:demand}
		\begin{minipage}{1\linewidth}
			\includegraphics[width=17cm, trim={.75in 4.75in 3.5in 2in}]{{"\fig/1_DocPat-graphs-theory-figure-2020-08-28"}.pdf}
\footnotesize
\vspace{6cm} \newline
\emph{Notes:} Diagonal lines graph patient utility net of costs. Shaded bars with $P$ and $0$ subscripts indicate patient preferences when the price of simple malaria treatment is $P$, and $0$ respectively. $N$ denotes ``no antimalarial purchase'', $L1$ denotes ``simple malaria treatment, unwilling to purchase severe malaria treatment'', $L2$ denotes ``simple malaria treatment, willing to purchase severe malaria treatment'', and $H$ denotes ``severe malaria treatment''. The bottom shaded bars in panels B and C show the outcome when the doctor adopts the strategy specified in the panel title. 	
\end{minipage}
\end{figure}


% RANDOMIZATION DESIGN
\begin{figure}[ht]
	\caption{Within-CSCOM Randomization Design}
		\label{RandDesign}
		\begin{minipage}{.93\linewidth}
			\includegraphics[width=21cm, trim={.75in 1in 1.5in 1in}]{{"\fig/2_DocPat-InterventionScheduleDiagram"}.pdf}
\footnotesize
\emph{Notes:} Before the interventions launched, clinic staff received trainings on RDTs on November 2, 3, and 4 2016. The interventions listed above ran between November 14-December 30 2016 in three two-week blocks, with 20 CSCOMs active in each two-week block. 
\end{minipage}
\end{figure}


% TREATMENT OUTCOMES BY PREDICTED MALARIA RISK IN CONTROL GROUP-NEW
\begin{figure}[ht]
	\caption{Treatment Outcomes by Predicted Malaria Risk in Control Group}
		\label{outcomeXpredpos_control_new}
		\begin{minipage}{.93\linewidth}
			\includegraphics[width=22cm]{{"\fig/3_outcomeXpredpos_control"}.pdf}
\footnotesize
\emph{Notes:} Results from local linear regressions. Regressions are run on the full sample, but graphs omit results for top and bottom 2.5 percent of malaria risk distribution to avoid influence of outliers. Vertical dashed lines indicate 25th, 50th, and 75th percentiles of predicted malaria risk respectively.
\end{minipage}
\end{figure}

% HET TMT EFFECTS BY MALARIA RISK -- NON PARAMETRIC-NEW
\begin{figure}[ht]
	\caption{Treatment Outcomes by Predicted Malaria Risk and Voucher Group}
		\label{tmtXpredpos_new}
		\begin{minipage}{.93\linewidth}
			\includegraphics[width=21cm]{{"\fig/4_tmtXpredpos"}.pdf}
\footnotesize
\emph{Notes:} Results from local linear regressions. Dotted lines give 90 percent confidence intervals. The standard errors used to calculate confidence intervals are bootstrapped by re-sampling clinics and recalculating predicted malaria risk on each of 1,000 bootstrap replications. Regressions are run on the full sample, but graphs omit results for top and bottom 2.5 percent of malaria risk distribution to avoid influence of outliers. Vertical dashed lines indicate 25th, 50th, and 75th percentiles of predicted malaria risk respectively.
\end{minipage}
\end{figure}

% TREATMENT OUTCOMES AND VOUCHER USE BY PREDICTED MALARIA RISK-NEW
\begin{figure}[ht]
	\caption{Use of Vouchers for Simple and Severe Malaria by Treatment Arm}
		\label{voucher_tmt}
		\begin{minipage}{.93\linewidth}
			\includegraphics[width=21cm]{{"\fig/5_voucher_tmt"}.pdf}
\footnotesize
\emph{Notes:} Each panel graphs the share of patients receiving the specified treatment by voucher condition. \end{minipage}
\end{figure}
\end{landscape}

%%%%%%%%%%% TABLES %%%%%%%%%%%
\begin{landscape}
\input{"\tab/1_control_group.tex"}
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%\input{_TabFig/theory_table_new.tex}
\input{"\tab/2_balance.tex"} 

\input{"\tab/3_mal_tmt_overall_new_lso.tex"}

\input{"\tab/4_mal_tmt_het_new_lso.tex"}

\begin{landscape}

\input{"\tab/5_expected_match_decomp_lso.tex"}

\end{landscape}

\end{document}

