Combining tabularx and longtable
Here is a MWE using the xltabular package.
\documentclass{article}
\usepackage{geometry}
\usepackage{tabularx}
\usepackage{xltabular}
\usepackage{longtable}
\usepackage{apacite}
\begin{document}
\begin{xltabular}{\textwidth}{l>{\hsize=0.75\hsize}X>{\hsize=1.125\hsize}X>{\hsize=1.125\hsize}X}
\caption{Summary of Multipliers from the Literature}\label{Lit Summary table}\\
\hline\hline
\textbf{Study} & \textbf{Geographical Location and Level} & \textbf{Identification} & \textbf{Multiplier Result} \\ \hline \hline
\endhead
\citeA{nakamura2014fiscal} & US State Level & Instrumented on the fact that when national spending on the military rises by 1 percentage point of GDP in the US, different states, depending on their exposure to military spending, experience different levels of military build-up & 1.5 growing to 2.0 at zero lower bound \\ \hline
\citeA{ramey2011identifying} & US Federal Level & Looked at the military build-up during significant wars throughout the 20\textsuperscript{th} century in the US & 0.6-1.2 \\ \hline \citeA{Barro} & US Federal Level & Spending multipliers are identified primarily from variations in defense spending, especially changes associated with buildups and aftermaths of wars. & 0.4-0.5 contemporaneously, 0.6-0.7 2 years later and if multiplier is permanent then this adds 0.1-0.2 to the multiplier \\ \hline \citeA{auerbach} & US Federal Level & Extended SVAR approach & 0-0.5 in Expansion and 1.0-1.5 in Recession \\ \hline \citeA{fazzari2015state} & US State Level & Bayesian model comparison and generalized impulse response analysis to test for nonlinearities in the responses of output to government spending & 0.8 for states with low slack and 1.6 for states with high slack \\ \hline \citeA{Ramey2018} & US Federal Level & Analysed quarterly US data over a 120 year period using the local projection method developed by \citeA{Jorda} & 0.3-1.5 depending on the methodology and robustness check they used. \\ \hline \citeA{shoag2010impact} & US State Level & Instrumented on the windfall gains that US states receive from investing public pension funds & Baseline multiplier over 2, rising to over 3 in times of economic slack \\ \hline \citeA{suarez2016estimating} & US County Level & Instrumented on Federal transfers to local counties due to changes in population forecasts between Census and Non-census years & 1.7-2 rising in counties experiencing economic slack \\ \hline \citeA{michaillat2014theory} & US Federal Level & Simple search-and-matching model to highlight the key economic forces of the multiplier & The multiplier doubles when unemployment rises from 5\% to 8\% \\ \hline \citeA{clemens2012} & US State Level & Instrumented on the variation in the strictness states' balanced budget requirements to determine the level as a means of measuring the level of spending cuts during a recession & 0.4 however it may be higher if states receive windfall funding \\ \hline \citeA{Ilzetzki} & 44 countries around the world \footnote{20 high-income and 44 low income} & SVAR approach on a novel dataset & High income countries tend to have a statistically significant positive fiscal multiplier while the opposite is true of developing countries and Investment in infrastructure could lead to a higher multiplier \\ \hline \citeA{acconcia2014mafia} & Italy Local Level & Looked at a situation when local governments were dismissed and public funding was severely reduced in Italy is response to being infiltrated by the mafia. & 1.5 on impact, growing to 1.9 when dynamic effects are included. \\ \hline \citeA{fishback2015multiplier} & US State Level & Panel of annual Federal expenditure in each State during the 1930s & 0.96 when Federal transfer payments are excluded falling to 0.83 when they are included \\
\end{xltabular}
\end{document}
I would also recommend to use booktabs for the horizontal rules (not included in the MWE)
\documentclass[a4paper]{article}
\usepackage{geometry}
\usepackage{xltabular}
\def\citeA#1{}% For demo here
\begin{document}
\begin{xltabular}{\linewidth}{lp{3cm}XX}
\caption{Summary of Multipliers from the Literature}\label{Lit Summary table}\\ \hline\hline
\textbf{Study} & \textbf{Geographical Location and Level} & \textbf{Identification} &
\textbf{Multiplier Result} \\ \hline \hline
\endfirsthead
\hline\hline
\textbf{Study} & \textbf{Geographical Location and Level} & \textbf{Identification} &
\textbf{Multiplier Result} \\ \hline \hline
\endhead
\hline
\endfoot
\citeA{nakamura2014fiscal} & US State Level & Instrumented on the fact that when national spending on
the military rises by 1 percentage point of GDP in the US, different states, depending on their
exposure to military spending, experience different levels of military build-up & 1.5 growing to 2.0
at zero lower bound \\ \hline
\citeA{ramey2011identifying} & US Federal Level & Looked at the military build-up during significant
wars throughout the 20\textsuperscript{th} century in the US & 0.6-1.2 \\ \hline \citeA{Barro} & US
Federal Level & Spending multipliers are identified primarily from variations in defense spending,
especially changes associated with buildups and aftermaths of wars. & 0.4-0.5 contemporaneously,
0.6-0.7 2 years later and if multiplier is permanent then this adds 0.1-0.2 to the multiplier \\
\hline \citeA{auerbach} & US Federal Level & Extended SVAR approach & 0-0.5 in Expansion and 1.0-1.5
in Recession \\ \hline \citeA{fazzari2015state} & US State Level & Bayesian model comparison and
generalized impulse response analysis to test for nonlinearities in the responses of output to
government spending & 0.8 for states with low slack and 1.6 for states with high slack \\ \hline
\citeA{Ramey2018} & US Federal Level & Analysed quarterly US data over a 120 year period using the
local projection method developed by \citeA{Jorda} & 0.3-1.5 depending on the methodology and
robustness check they used. \\ \hline \citeA{shoag2010impact} & US State Level & Instrumented on the
windfall gains that US states receive from investing public pension funds & Baseline multiplier over
2, rising to over 3 in times of economic slack \\ \hline \citeA{suarez2016estimating} & US County
Level & Instrumented on Federal transfers to local counties due to changes in population forecasts
between Census and Non-census years & 1.7-2 rising in counties experiencing economic slack \\ \hline
\citeA{michaillat2014theory} & US Federal Level & Simple search-and-matching model to highlight the
key economic forces of the multiplier & The multiplier doubles when unemployment rises from 5\% to
8\% \\ \hline \citeA{clemens2012} & US State Level & Instrumented on the variation in the strictness
states' balanced budget requirements to determine the level as a means of measuring the level of
spending cuts during a recession & 0.4 however it may be higher if states receive windfall funding \\
\hline \citeA{Ilzetzki} & 44 countries around the world \footnote{20 high-income and 44 low income} &
SVAR approach on a novel dataset & High income countries tend to have a statistically significant
positive fiscal multiplier while the opposite is true of developing countries and Investment in
infrastructure could lead to a higher multiplier \\ \hline \citeA{acconcia2014mafia} & Italy Local
Level & Looked at a situation when local governments were dismissed and public funding was severely
reduced in Italy is response to being infiltrated by the mafia. & 1.5 on impact, growing to 1.9
when dynamic effects are included. \\ \hline \citeA{fishback2015multiplier} & US State Level & Panel
of annual Federal expenditure in each State during the 1930s & 0.96 when Federal transfer payments
are excluded falling to 0.83 when they are included \\
\end{xltabular}
\end{document}