\documentclass[11pt,twoside]{article}\makeatletter

\IfFileExists{xcolor.sty}%
  {\RequirePackage{xcolor}}%
  {\RequirePackage{color}}
\usepackage{colortbl}
\usepackage{wrapfig}
\usepackage{ifxetex}
\ifxetex
  \usepackage{fontspec}
  \usepackage{xunicode}
  \catcode`⃥=\active \def⃥{\textbackslash}
  \catcode`❴=\active \def❴{\{}
  \catcode`❵=\active \def❵{\}}
  \def\textJapanese{\fontspec{Noto Sans CJK JP}}
  \def\textChinese{\fontspec{Noto Sans CJK SC}}
  \def\textKorean{\fontspec{Noto Sans CJK KR}}
  \setmonofont{DejaVu Sans Mono}
  
\else
  \IfFileExists{utf8x.def}%
   {\usepackage[utf8x]{inputenc}
      \PrerenderUnicode{–}
    }%
   {\usepackage[utf8]{inputenc}}
  \usepackage[english]{babel}
  \usepackage[T1]{fontenc}
  \usepackage{float}
  \usepackage[]{ucs}
  \uc@dclc{8421}{default}{\textbackslash }
  \uc@dclc{10100}{default}{\{}
  \uc@dclc{10101}{default}{\}}
  \uc@dclc{8491}{default}{\AA{}}
  \uc@dclc{8239}{default}{\,}
  \uc@dclc{20154}{default}{ }
  \uc@dclc{10148}{default}{>}
  \def\textschwa{\rotatebox{-90}{e}}
  \def\textJapanese{}
  \def\textChinese{}
  \IfFileExists{tipa.sty}{\usepackage{tipa}}{}
\fi
\def\exampleFont{\ttfamily\small}
\DeclareTextSymbol{\textpi}{OML}{25}
\usepackage{relsize}
\RequirePackage{array}
\def\@testpach{\@chclass
 \ifnum \@lastchclass=6 \@ne \@chnum \@ne \else
  \ifnum \@lastchclass=7 5 \else
   \ifnum \@lastchclass=8 \tw@ \else
    \ifnum \@lastchclass=9 \thr@@
   \else \z@
   \ifnum \@lastchclass = 10 \else
   \edef\@nextchar{\expandafter\string\@nextchar}%
   \@chnum
   \if \@nextchar c\z@ \else
    \if \@nextchar l\@ne \else
     \if \@nextchar r\tw@ \else
   \z@ \@chclass
   \if\@nextchar |\@ne \else
    \if \@nextchar !6 \else
     \if \@nextchar @7 \else
      \if \@nextchar (8 \else
       \if \@nextchar )9 \else
  10
  \@chnum
  \if \@nextchar m\thr@@\else
   \if \@nextchar p4 \else
    \if \@nextchar b5 \else
   \z@ \@chclass \z@ \@preamerr \z@ \fi \fi \fi \fi
   \fi \fi  \fi  \fi  \fi  \fi  \fi \fi \fi \fi \fi \fi}
\gdef\arraybackslash{\let\\=\@arraycr}
\def\@textsubscript#1{{\m@th\ensuremath{_{\mbox{\fontsize\sf@size\z@#1}}}}}
\def\Panel#1#2#3#4{\multicolumn{#3}{){\columncolor{#2}}#4}{#1}}
\def\abbr{}
\def\corr{}
\def\expan{}
\def\gap{}
\def\orig{}
\def\reg{}
\def\ref{}
\def\sic{}
\def\persName{}\def\name{}
\def\placeName{}
\def\orgName{}
\def\textcal#1{{\fontspec{Lucida Calligraphy}#1}}
\def\textgothic#1{{\fontspec{Lucida Blackletter}#1}}
\def\textlarge#1{{\large #1}}
\def\textoverbar#1{\ensuremath{\overline{#1}}}
\def\textquoted#1{‘#1’}
\def\textsmall#1{{\small #1}}
\def\textsubscript#1{\@textsubscript{\selectfont#1}}
\def\textxi{\ensuremath{\xi}}
\def\titlem{\itshape}
\newenvironment{biblfree}{}{\ifvmode\par\fi }
\newenvironment{bibl}{}{}
\newenvironment{byline}{\vskip6pt\itshape\fontsize{16pt}{18pt}\selectfont}{\par }
\newenvironment{citbibl}{}{\ifvmode\par\fi }
\newenvironment{docAuthor}{\ifvmode\vskip4pt\fontsize{16pt}{18pt}\selectfont\fi\itshape}{\ifvmode\par\fi }
\newenvironment{docDate}{}{\ifvmode\par\fi }
\newenvironment{docImprint}{\vskip 6pt}{\ifvmode\par\fi }
\newenvironment{docTitle}{\vskip6pt\bfseries\fontsize{22pt}{25pt}\selectfont}{\par }
\newenvironment{msHead}{\vskip 6pt}{\par}
\newenvironment{msItem}{\vskip 6pt}{\par}
\newenvironment{rubric}{}{}
\newenvironment{titlePart}{}{\par }

\newcolumntype{L}[1]{){\raggedright\arraybackslash}p{#1}}
\newcolumntype{C}[1]{){\centering\arraybackslash}p{#1}}
\newcolumntype{R}[1]{){\raggedleft\arraybackslash}p{#1}}
\newcolumntype{P}[1]{){\arraybackslash}p{#1}}
\newcolumntype{B}[1]{){\arraybackslash}b{#1}}
\newcolumntype{M}[1]{){\arraybackslash}m{#1}}
\definecolor{label}{gray}{0.75}
\def\unusedattribute#1{\sout{\textcolor{label}{#1}}}
\DeclareRobustCommand*{\xref}{\hyper@normalise\xref@}
\def\xref@#1#2{\hyper@linkurl{#2}{#1}}
\begingroup
\catcode`\_=\active
\gdef_#1{\ensuremath{\sb{\mathrm{#1}}}}
\endgroup
\mathcode`\_=\string"8000
\catcode`\_=12\relax

\usepackage[a4paper,twoside,lmargin=1in,rmargin=1in,tmargin=1in,bmargin=1in,marginparwidth=0.75in]{geometry}
\usepackage{framed}

\definecolor{shadecolor}{gray}{0.95}
\usepackage{longtable}
\usepackage[normalem]{ulem}
\usepackage{fancyvrb}
\usepackage{fancyhdr}
\usepackage{graphicx}
\usepackage{marginnote}

\renewcommand{\@cite}[1]{#1}


\renewcommand*{\marginfont}{\itshape\footnotesize}

\def\Gin@extensions{.pdf,.png,.jpg,.mps,.tif}

  \pagestyle{fancy}

\usepackage[pdftitle={Food and Cash Crop Productivities and Poverty Reduction in Ghana},
 pdfauthor={}]{hyperref}
\hyperbaseurl{}

	 \paperwidth210mm
	 \paperheight297mm
              
\def\@pnumwidth{1.55em}
\def\@tocrmarg {2.55em}
\def\@dotsep{4.5}
\setcounter{tocdepth}{3}
\clubpenalty=8000
\emergencystretch 3em
\hbadness=4000
\hyphenpenalty=400
\pretolerance=750
\tolerance=2000
\vbadness=4000
\widowpenalty=10000

\renewcommand\section{\@startsection {section}{1}{\z@}%
     {-1.75ex \@plus -0.5ex \@minus -.2ex}%
     {0.5ex \@plus .2ex}%
     {\reset@font\Large\bfseries}}
\renewcommand\subsection{\@startsection{subsection}{2}{\z@}%
     {-1.75ex\@plus -0.5ex \@minus- .2ex}%
     {0.5ex \@plus .2ex}%
     {\reset@font\Large}}
\renewcommand\subsubsection{\@startsection{subsubsection}{3}{\z@}%
     {-1.5ex\@plus -0.35ex \@minus -.2ex}%
     {0.5ex \@plus .2ex}%
     {\reset@font\large}}
\renewcommand\paragraph{\@startsection{paragraph}{4}{\z@}%
     {-1ex \@plus-0.35ex \@minus -0.2ex}%
     {0.5ex \@plus .2ex}%
     {\reset@font\normalsize}}
\renewcommand\subparagraph{\@startsection{subparagraph}{5}{\parindent}%
     {1.5ex \@plus1ex \@minus .2ex}%
     {-1em}%
     {\reset@font\normalsize\bfseries}}


\def\l@section#1#2{\addpenalty{\@secpenalty} \addvspace{1.0em plus 1pt}
 \@tempdima 1.5em \begingroup
 \parindent \z@ \rightskip \@pnumwidth 
 \parfillskip -\@pnumwidth 
 \bfseries \leavevmode #1\hfil \hbox to\@pnumwidth{\hss #2}\par
 \endgroup}
\def\l@subsection{\@dottedtocline{2}{1.5em}{2.3em}}
\def\l@subsubsection{\@dottedtocline{3}{3.8em}{3.2em}}
\def\l@paragraph{\@dottedtocline{4}{7.0em}{4.1em}}
\def\l@subparagraph{\@dottedtocline{5}{10em}{5em}}
\@ifundefined{c@section}{\newcounter{section}}{}
\@ifundefined{c@chapter}{\newcounter{chapter}}{}
\newif\if@mainmatter 
\@mainmattertrue
\def\chaptername{Chapter}
\def\frontmatter{%
  \pagenumbering{roman}
  \def\thechapter{\@roman\c@chapter}
  \def\theHchapter{\roman{chapter}}
  \def\thesection{\@roman\c@section}
  \def\theHsection{\roman{section}}
  \def\@chapapp{}%
}
\def\mainmatter{%
  \cleardoublepage
  \def\thechapter{\@arabic\c@chapter}
  \setcounter{chapter}{0}
  \setcounter{section}{0}
  \pagenumbering{arabic}
  \setcounter{secnumdepth}{6}
  \def\@chapapp{\chaptername}%
  \def\theHchapter{\arabic{chapter}}
  \def\thesection{\@arabic\c@section}
  \def\theHsection{\arabic{section}}
}
\def\backmatter{%
  \cleardoublepage
  \setcounter{chapter}{0}
  \setcounter{section}{0}
  \setcounter{secnumdepth}{2}
  \def\@chapapp{\appendixname}%
  \def\thechapter{\@Alph\c@chapter}
  \def\theHchapter{\Alph{chapter}}
  \appendix
}
\newenvironment{bibitemlist}[1]{%
   \list{\@biblabel{\@arabic\c@enumiv}}%
       {\settowidth\labelwidth{\@biblabel{#1}}%
        \leftmargin\labelwidth
        \advance\leftmargin\labelsep
        \@openbib@code
        \usecounter{enumiv}%
        \let\p@enumiv\@empty
        \renewcommand\theenumiv{\@arabic\c@enumiv}%
	}%
  \sloppy
  \clubpenalty4000
  \@clubpenalty \clubpenalty
  \widowpenalty4000%
  \sfcode`\.\@m}%
  {\def\@noitemerr
    {\@latex@warning{Empty `bibitemlist' environment}}%
    \endlist}

\def\tableofcontents{\section*{\contentsname}\@starttoc{toc}}
\parskip0pt
\parindent1em
\def\Panel#1#2#3#4{\multicolumn{#3}{){\columncolor{#2}}#4}{#1}}
\newenvironment{reflist}{%
  \begin{raggedright}\begin{list}{}
  {%
   \setlength{\topsep}{0pt}%
   \setlength{\rightmargin}{0.25in}%
   \setlength{\itemsep}{0pt}%
   \setlength{\itemindent}{0pt}%
   \setlength{\parskip}{0pt}%
   \setlength{\parsep}{2pt}%
   \def\makelabel##1{\itshape ##1}}%
  }
  {\end{list}\end{raggedright}}
\newenvironment{sansreflist}{%
  \begin{raggedright}\begin{list}{}
  {%
   \setlength{\topsep}{0pt}%
   \setlength{\rightmargin}{0.25in}%
   \setlength{\itemindent}{0pt}%
   \setlength{\parskip}{0pt}%
   \setlength{\itemsep}{0pt}%
   \setlength{\parsep}{2pt}%
   \def\makelabel##1{\upshape ##1}}%
  }
  {\end{list}\end{raggedright}}
\newenvironment{specHead}[2]%
 {\vspace{20pt}\hrule\vspace{10pt}%
  \phantomsection\label{#1}\markright{#2}%

  \pdfbookmark[2]{#2}{#1}%
  \hspace{-0.75in}{\bfseries\fontsize{16pt}{18pt}\selectfont#2}%
  }{}
      \def\TheFullDate{1970-01-01 (revised: 01 January 1970)}
\def\TheID{\makeatother }
\def\TheDate{1970-01-01}
\title{Food and Cash Crop Productivities and Poverty Reduction in Ghana}
\author{}\makeatletter 
\makeatletter
\newcommand*{\cleartoleftpage}{%
  \clearpage
    \if@twoside
    \ifodd\c@page
      \hbox{}\newpage
      \if@twocolumn
        \hbox{}\newpage
      \fi
    \fi
  \fi
}
\makeatother
\makeatletter
\thispagestyle{empty}
\markright{\@title}\markboth{\@title}{\@author}
\renewcommand\small{\@setfontsize\small{9pt}{11pt}\abovedisplayskip 8.5\p@ plus3\p@ minus4\p@
\belowdisplayskip \abovedisplayskip
\abovedisplayshortskip \z@ plus2\p@
\belowdisplayshortskip 4\p@ plus2\p@ minus2\p@
\def\@listi{\leftmargin\leftmargini
               \topsep 2\p@ plus1\p@ minus1\p@
               \parsep 2\p@ plus\p@ minus\p@
               \itemsep 1pt}
}
\makeatother
\fvset{frame=single,numberblanklines=false,xleftmargin=5mm,xrightmargin=5mm}
\fancyhf{} 
\setlength{\headheight}{14pt}
\fancyhead[LE]{\bfseries\leftmark} 
\fancyhead[RO]{\bfseries\rightmark} 
\fancyfoot[RO]{}
\fancyfoot[CO]{\thepage}
\fancyfoot[LO]{\TheID}
\fancyfoot[LE]{}
\fancyfoot[CE]{\thepage}
\fancyfoot[RE]{\TheID}
\hypersetup{citebordercolor=0.75 0.75 0.75,linkbordercolor=0.75 0.75 0.75,urlbordercolor=0.75 0.75 0.75,bookmarksnumbered=true}
\fancypagestyle{plain}{\fancyhead{}\renewcommand{\headrulewidth}{0pt}}

\date{}
\usepackage{authblk}

\providecommand{\keywords}[1]
{
\footnotesize
  \textbf{\textit{Index terms---}} #1
}

\usepackage{graphicx,xcolor}
\definecolor{GJBlue}{HTML}{273B81}
\definecolor{GJLightBlue}{HTML}{0A9DD9}
\definecolor{GJMediumGrey}{HTML}{6D6E70}
\definecolor{GJLightGrey}{HTML}{929497} 

\renewenvironment{abstract}{%
   \setlength{\parindent}{0pt}\raggedright
   \textcolor{GJMediumGrey}{\rule{\textwidth}{2pt}}
   \vskip16pt
   \textcolor{GJBlue}{\large\bfseries\abstractname\space}
}{%   
   \vskip8pt
   \textcolor{GJMediumGrey}{\rule{\textwidth}{2pt}}
   \vskip16pt
}

\usepackage[absolute,overlay]{textpos}

\makeatother 
      \usepackage{lineno}
      \linenumbers
      
\begin{document}

             \author[1]{Boahen Atta  Oppong}

             \author[2]{Edward Ebo  Onumah}

             \author[3]{Ramatu Mahama  Al-Hassan}

             \author[4]{Akwasi  Mensah-Bonsu}

             \affil[1]{  University of Ghana}

\renewcommand\Authands{ and }

\date{\small \em Received: 1 January 1970 Accepted: 1 January 1970 Published: 1 January 1970}

\maketitle


\begin{abstract}
        


Food and cash crop productivities growth provide food and improve smallholder farmers? income to reduce poverty. Crop farmers poverty rate is disaggregated into food and cash crop type but beyond 2006 the poverty rate is not disaggregated which is addressed by this study. Food and cash crops have different growth paths and unequal pathways towards poverty. The paper estimates the poverty rates among food and cash crop farmers and examines their productivities effect on poverty.

\end{abstract}


\keywords{crop productivity, poverty, wellbeing.}

\begin{textblock*}{18cm}(1cm,1cm) % {block width} (coords) 
\textcolor{GJBlue}{\LARGE Global Journals \LaTeX\ JournalKaleidoscope\texttrademark}
\end{textblock*}

\begin{textblock*}{18cm}(1.4cm,1.5cm) % {block width} (coords) 
\textcolor{GJBlue}{\footnotesize \\ Artificial Intelligence formulated this projection for compatibility purposes from the original article published at Global Journals. However, this technology is currently in beta. \emph{Therefore, kindly ignore odd layouts, missed formulae, text, tables, or figures.}}
\end{textblock*}


\begin{textblock*}{10cm}(1.05cm,3cm)
{{\textit{CrossRef DOI of original article:}} \underline{}}
\end{textblock*}\let\tabcellsep& 	 	 		 
\section[{INTRODUCTION}]{INTRODUCTION}\par
he economy of Ghana consists of three main subsectors of agriculture, services and manufacturing which provide employment opportunities. The average shares of GDP by agriculture, service and industry were 26\%, 52\% and 22\% between 2006 and 2016 (GSS 2017) and 18.5\%, 47.2\%, and 34.2\% in 2019 (GSS 2022). Poverty reduction requires significant income growth from economic growth; however, inclusive growth is the main channel for poverty reduction \hyperref[b19]{(Fosu, 2016)}. About 47\% of total agricultural land area is cultivated mostly by smallholder rain-fed farming, using rudimentary technologies whilst 3.5\% is irrigated. Small holder farming accounts for 80\% of total agricultural production in Ghana. Food crops are "crops that are intended entirely or primarily for home consumption whereas cash crops are defined as crops that are intended entirely or primarily for market \hyperref[b22]{(Govereh \& Jayne 2003)}. Food crops include cereals (e.g., maize and rice), roots and tubers (e.g., yam and cassava) and legumes (e.g., cowpea and groundnuts). Fruits (e.g., avocado and mango) and vegetables (e.g., tomatoes and peppers) and industrial cash crops (e.g., cocoa, rubber, kola, coffee, and oil-palm) are important crops for export revenue \hyperref[b37]{(MOFA 2016)}.\par
Productivity is defined as output per unit input which is used to indicate the performance of crop production \hyperref[b9]{(Coelli et al., 2005)}. Agricultural output grows by improved weather conditions, conventional inputs, and enabled by rural infrastructure, institutional factors and policy frameworks \hyperref[b51]{(Thirtle et al., 2003;}\hyperref[b43]{Reimers \& Klasen 2013)}. According to the World \hyperref[b53]{Bank (2000)}, "poverty is pronounced deprivation in wellbeing" where well-being can be measured by an individual's possession of income, health, nutrition, education, assets, housing, and certain rights, such as freedom of speech. It is also a lack of opportunities, powerlessness, and vulnerability. Poverty rate in Sub-Saharan Africa was high at about 40\% and moderate at 18\% in South Asia in 2015 \hyperref[b44]{(Roser \& Ortiz-Ospina, 2018}; Fosu 2016). Non-income poverty measures of enrolment rates in senior-secondary schools and tertiary education and the quality of learning in both basic and post-basic education are low in poor countries \hyperref[b38]{(Molini \& Paci, 2015)}. By the national poverty line of Ghana, the poverty rate in 1991 of 53\% decreased to 21\% in 2012 but increased to 23.4\% in 2016/17 \hyperref[b25]{(GSS, 2018)}. Similarly, in Uganda poverty reduced from 25\% in 2009 to 21\% in 2013 and geographical disparities characterised this poverty reduction \hyperref[b47]{(Ssewanyana, \& Kasirye, 2014)}. Poverty rates by employment type showed that poverty among farmers reduced from 45\% in 2005 to 39.2\% in 2013; the rural population in the agricultural employment sector have the highest poverty incidence. Nationally, the Gini coefficient of 41.9\% in 2005 increased slightly to 42.3\% in 2013  {\ref (GSS, 2014)}.\par
Poverty is mainly caused by inadequate income or resources for an optimum consumption of commodities and services which consequently show symptoms of malnourishment and lack of assets \hyperref[b46]{(Sen, 1999;}\hyperref[b48]{Stern \& Rogers, 2005}; Tebaldi and Mohan 2010). The agricultural sector of Ghana, which is led by smallholder farmers is burdened with low productivity due to low technology adoption and poor soils, weak infrastructure, low market access, high transaction costs and climatic shocks (ACDI/VOCA 2012). Improved agricultural productivity through innovative technologies that support sustainable development is an important channel that aids in poverty reduction and increased food and nutrition security (Al-Hassan and Diao 2007). Improving agricultural productivity is related to Sustainable Development Goal 8 to promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all poverty and hunger reduction.\par
Christiaensen et al. (  {\ref 2011}) found employment of poor people in agriculture and the linkage of agriculture with other sectors of the economy leads to poverty reduction. Agricultural productivity pathways to poverty reduction are through the effect of income from higher output; lower food prices and multiplier effects on rural economic growth \hyperref[b23]{(Grewal et al., 2012;} {\ref Bresciani \& Valdes, 2007)}. A related study found significant negative relationships between household's intensity of cash crop production and food security due to increasing food prices and competing activities for land use. The adverse relationship between cash crop production and household food security observed calls for caution; results suggest that positive relationships cannot be assumed, and that further empirical evidence is needed to better understand these tradeoffs \hyperref[b3]{(Anderman, et al. 2014}). Food and cash crops have different production systems and synergistic effects or trade offs on farm households' livelihoods \hyperref[b22]{(Govereh and Jayne 2003)}. Crop farmers' poverty rate has not been disaggregated into food and cash crop types and their role on poverty reduction have not been assessed. This study therefore assesses the effect of food and cash crop productivities on poverty. The next section presents the methodology of the study, which entails the data and method of analysis, followed by the results and discussion and lastly conclusion. 
\section[{II.}]{II.} 
\section[{METHODOLOGY a) Conceptual Framework}]{METHODOLOGY a) Conceptual Framework}\par
The conceptual framework adapted for this study shows four pathways out of poverty, namely raising agricultural labor productivity, labor reallocation to rural non-farm activities, migration to reallocate labour to urban activities, and transfer of rural tax reduction or income transfers, price support and input subsidies \hyperref[b45]{(Schneider \& Gugerty 2011)}. Food crops provide food and income while cash crops provide income for farm households towards poverty reduction (Fiqure 1). Food and cash crops have varied growth paths and unequal pathways for poverty reduction \hyperref[b15]{(Diao \& Dorosh, 2007)}. The sub-sectors are distinct by agro ecological conditions, policy, markets and special role towards alleviating poverty. Food crops pathway for poverty reduction is broad-based mainly through supply of food for household consumption and sale of surplus food through domestic and regional market (Al-Hassan \& Poulton 2009; Khan and Verma, 2018; \hyperref[b16]{Diao \& Hazell, 2004)}. Cash crops are high value crops and provide mainly income in well-structured domestic and export markets \hyperref[b16]{(Diao \& Hazell, 2004;} {\ref Hill \& Viner, 2014)}.  
\section[{Theoretical Framework}]{Theoretical Framework}\par
The household economic model provides the theoretical basis of this analysis. The indirect utility function of a rural household is given by ?? = ?????, ?? ?? ? is labour income to purchase commodities and services for optimum satisfaction and pj is price of crop j \hyperref[b42]{(Ravallion, 1996;}\hyperref[b36]{Minten \& Barrett 2008)}. The study assumes the labour income, y is decomposed into farm and non-farm labour income as defined in equation \hyperref[b0]{(1)}.?? = ??[?? ?? ð??"ð??"ð??"ð??"(??, ?? ð??"ð??" ) + ??(?? ?? )/??]\textbf{(1)}\par
where, A is productivity of the underlying technology, ð??"ð??"ð??"ð??"???, ?? ð??"ð??" /??? is the production function ?? represents farm size, ?? ð??"ð??" is farm labour supply ?? ?? is non-farm labour supply, w is the wage rate for unskilled labour and E is the given agroecological conditions.\par
Labour income y specified in equation ( \hyperref[formula_0]{1}) is totally differentiated to give equation ( \hyperref[formula_1]{2}):???? = ???? ???? ?? ???? ?? * ð??"ð??"(??) + ???? ???? ?????? ?? * ð??"ð??"(??) ? ?? ???? ???? ð??"ð??" ??(?? ?? ) + (?? ?? ) ???? ???? ????\textbf{(2)}\par
Equation 2 is simplified as:???? ??ð??"ð??" = ?? ?? ?? ??ð??"ð??" * ?? ?? + ?? ?? . ???? ?? ??ð??"ð??" ? ?? ???? ?? ??ð??"ð??" + ???? ??ð??"ð??" * (?? ?? )\textbf{(3)}\par
???? ?? ??ð??"ð??" is given by ?? ?? ?? ,ð??"ð??" . 
\section[{?? ??}]{?? ??} 
\section[{ð??"ð??"}]{ð??"ð??"}\par
where ? ???? is the price elasticity with respect to productivity. \par
Higher crop productivity growth would increase crop output greater than the decline in crop prices to increase crop income and thereby reduce poverty (Nicholas \& Snyder, 2008; Minten \& Barrett 2008). 
\section[{a) Estimation of Poverty Rate}]{a) Estimation of Poverty Rate}\par
The Foster-Greer-Thorbecke (1984) (FGT) poverty index is used to estimate the poverty headcount ratio, poverty gap and poverty severity among crop farmers. The measure uses consumption expenditure which is more reliable to obtain from households and more stable than income of farmers. The FGT measures are given as: The food and cash crops productivities are measured as output value per hectare of land and is estimated by the instruments of cost of chemical and intermediate inputs in equation \hyperref[b7]{(8)}. Crop productivity is expected to be endogenous due to possible correlation with the error term, which is corrected by the instruments found to be related to the crop productivity but unrelated to the error term. Poverty measures , poverty headcount ratio, Poit Poverty gap, P1it and Poverty severity, P2it are regressed on the estimated crop productivity (?? 1, ,), household size (?? 2 ,), distance to water source(?? 3 ,), years of education (?? 4 ,), days of ill-health (?? 5 ,), livestock and remittance income (?? 6 ,), in equation \hyperref[b8]{(9)}\hyperref[b9]{(10)}\hyperref[b10]{(11)}.  \hyperref[b14]{Deaton (1985)} suggests creating cohorts, based on some pre-determined characteristics that are time invariant, can substitute for panel data. and have cohort means that generate consistent and efficient estimates (Guillerm 2017).?? 0 = ?? ?? ? Poverty headcount ratio (5) ?? 1 = 1 ?? ? [(?? ? ??) ?? ? ] 1 ?? ??=1 ? Poverty gap (6) ?? 2 = 1 ?? ? [(?? ? ??) ?? ? ] 2 ?? ??=1 ? Poverty severity\textbf{(7}Stage 1: ?????? ?? 1???? = ?? 0 +?? 1 ???????? 1???? + ?? 2 ???????? 2???? (8) Stage 2: ? ?? 0???? 1??? 0???? ? = ?? 0 + ?? 1 ?????? 1???? + ? ?? ?? ?????? 6 ?? =2 ?? ?????? + ?? ???? (9) ???? 1 = ?? 0 + ?? 1 ?????? 1???? + ? ?? ?? ???????? ?????? 6 ?? =2 + ?? ???? (10) ???? 2 = ?? 0 + ?? 1 ?????? 1???? + ? ?? ?? ???????? ?????? 6 ?? =2 + ?? ????\par
IV. 
\section[{Results and Discussion}]{Results and Discussion} 
\section[{a) Summary Statistics of model explanatory variables}]{a) Summary Statistics of model explanatory variables}\par
Crop income per hectare of land increased and consumption expenditure on food and non-food items is lower among poor farmers than non-poor farmers which increased to reduce poverty between 2005 and 2013. Crop productivity (kg/ha) reduced for non-poor farmers and increased for poor farmers between 2005 and 2013. Table \hyperref[tab_2]{II} shows that years of education of household head fell by 14\% for non-poor farmers and 8\% by poor farmers. Years of education is important to use the inputs to obtain optimum output. The study further reveals remittance income increased highly by 260\% for non-poor farmers and by 205\% for poor farmers to support household income for consumption, which is relevant in contributing towards poverty reduction. Additional income from livestock sales increased by 220\% for non-poor farmers but reduced by 52\% for poor farmer, which can have a dampening effect on consumption expenditure to increase poverty. Household size is higher among poor farmers than nonpoor farmers and increased slightly between 2005 and 2013. Distance to water source has reduced significantly between 2005 and 2013 and does not differ significantly between the poor and non-poor. Days of ill health is high and does not differ between the poor and non-poor.\par
Volume XXII Issue VI Version I 50 ( )  \hyperref[tab_3]{III}). Cash crop output increased lower than food crop, farm size reduced slightly, and the productivities output/income per hectare increased higher than food crops to reduce poverty between 2005 and 2013. Cash crop output value increased by 330\% more than food crop output value which increased by 190\% towards poverty reduction between 2005 and 2013. Cash crop yield growth is supported by the well organised value chains which offer technical assistance on production and readily available markets for outputs and inputs \hyperref[b16]{(Diao \& Hazell 2004)}.  
\section[{d) Source of Income}]{d) Source of Income}\par
The study shows major source of income for poor farmers is agriculture and major source of income for non-poor farmers is wage and non-farm income sources towards poverty reduction. Poor farmers spent more income on food than on non-food items in the consumption bundle. Non-food expenditures include those expenditures on health, education, transportation, clothing, recreation, remittances among others. Total expenditure for poor farmers increased by 14\%: food expenditure increased by 30\% and non-food expenditure increased by 14\% between 2005 and 2013 (Table \hyperref[tab_5]{V}). The Ghana Statistical Service requires ?1314.4 minimum food and nonfood expenditure per year to become non-poor (GSS 2014).  \hyperref[tab_6]{VI}). Cash crop sub-sector reduces poverty through significant output value growth by participating in export market for relatively low number of farmers than the food crop sub-sector which engages more farmers \hyperref[b6]{(Broeck et. al, 2017)}. A 1\% growth in food crop productivity reduces the probability of being poor in terms of the elasticity of poverty headcount ratio, poverty gap, and poverty severity by -0.19\%, -0.41\%, -and -0.81\% which are negative but inelastic. The effects are however lower Volume XXII Issue VI Version I 52 ( ) than that due to cash crop productivity (Table \hyperref[tab_7]{VII}). The conduit of food crop productivity towards poverty reduction is mainly by the provision of food and crop income from the productivity growth. Food crop diversity increases by 10\% to provide food and income to decrease the probability of a household being in poverty by 18\% in Ethiopia (Michler \& Josephson 2017; Iheke \& Nwaru 2013). In addition to crop productivity, growth in years of education, livestock income and remittances are important for poverty reduction. However, livestock income does not affect poverty gap and severity. Remittance receipts by households contribute to stabilizing consumption in developing countries \hyperref[b39]{(Mondal \& Khanam 2016)}. Education develops the numeracy and literacy skills to increase income and manage consumption effectively and efficiently (Coppola \& Laurea 2016; Leshoro \& Leshoro 2013; Nowak \& Kijek 2016). The poverty elasticity estimates for household size are all positive suggesting that larger households are more likely to be poor. The response is also elastic for poverty headcount ratio which increases poverty highly to affect wellbeing of farmers. Household size can erode the benefits of crop productivity growth towards poverty reduction due to the larger effect it exerts on poverty \hyperref[b50]{(Teka et al., 2019)}. Increase in days of ill health reduces probability of being poor by poverty headcount ratio, poverty gap and poverty severity by -0.09\%, -0.06\% and -0.11\%. Days sick can positively influence consumption for speedy recovery towards poverty reduction but higher days sick will reduce consumption to increase poverty. \hyperref[b7]{Cho et al. (2016)} found household head's physical, and mental disabilities were associated with higher likelihood of being food insecure. An increase of distance to water source elicits an increase poverty headcount ratio but does not affect poverty gap and poverty severity. Longer distance to fetch water increases poverty incidence because of longer time spent to fetch water to retard household productivity.  The study finds cash crop productivity increases by 1\% reduces poverty headcount ratio, poverty gap, poverty severity, by -0.28\%, -0.44\%, -0.88\% respectively. Poverty elasticity in response to productivity growth in cash crop production, is negative for all poverty indicators (Table \hyperref[tab_9]{IX}). The elasticity values are higher than those estimated for food crop productivity growth in Table  {\ref (VII)}. Cash crops mainly provide income to support household consumption bundles. Cocoa productivity growth increased income to support household consumption expenditure growth towards poverty reduction in Ghana (Danso-Abbeam, \& Baiyegunhi, 2018). Cash crops revenue increase per capita expenditure towards poverty reduction in Vietnam \hyperref[b12]{(Cuong, 2009)}. The effect of an increase in household size on poverty is positive and significant for all poverty indicators. Balagtasa et al. (2014) found an additional family member in rural Bangladesh slightly increased the probability of falling into poverty. A related study revealed an increase in variance of household dependence ratio decreases variance in consumption expenditure by 0.14 standard deviation which negatively affects consumption to increase poverty \hyperref[b18]{(Dzanku, 2015b)}. Table \hyperref[tab_9]{IX} shows a reduction in all poverty indicators with respect to an increase in years of education. Additional years of education promote household management of resources to positively influence consumption. Thirtle \& Piesse (2007), found education increases productivity in farm and non-farm sector. Educated farmers search for new information and use new technologies efficiently to increase productivity towards poverty reduction.\par
The study further reveals positive poverty elasticity with respect to increase in distance to water sources because of the constraints introduced on consumption due to longer time and effort to access water, and loss of productive hours. Access to livestock income growth by 1\% reduces probability of poverty headcount ratio by 0.12\% due to use of additional income to increase consumption. \hyperref[b31]{Katagame et al. (2017)} found that pigs contribute toward household income to reduce poverty among farmers' in Mimika. Remittance income is associated with poverty reduction through its effect on food consumption expenditure. A 1\% increase in remittance income negatively reduces food insecurity in rural Mali by 0.11\% to provide adequate and nutritious diet for households \hyperref[b20]{(Generoso 2015)}.  
\section[{Conclusions}]{Conclusions}\par
Food and cash crop productivities increase to provide food and income to reduce poverty. Crop farmers poverty rate is disaggregated into food and cash crops which have different growth paths and unequal pathways toward poverty reduction and their role on poverty reduction is assessed differently in this study. Food crops such as maize, rice, millet, cassava, etc mainly supply household food staples and cash crops such as cocoa, rubber, oil palm, cotton, etc. provide income towards poverty reduction. The study finds poor farmers mainly depend on agriculture and food and cash crops productivities grow to provide food and income to increase consumption expenditures mainly on food among poor farmers to reduce poverty. Non-poor farmers spend higher on food and non-food items which include health, education, transportation, clothing, and remittances, etc to reduce poverty. Food crop farmers have higher poverty rates than cash crop farmers and food and cash crops have considerable importance towards poverty reduction between 2005 and 2013. Food and cash crop productivities growth reduce poverty moderately which is inelastic and efforts made to support farmers with resources and skills to increase productivity of food and cash crops will count towards poverty reduction. The farmers should benefit from improved crop varieties, production methods, due to low use of recommended agronomic practices, capacity building, and market access towards productivity growth to provide food and income to reduce poverty.\par
Volume XXII Issue VI Version I 56 ( )\begin{figure}[htbp]
\noindent\textbf{1}\includegraphics[]{image-2.png}
\caption{\label{fig_0}Figure 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-3.png}
\caption{\label{fig_1}}\end{figure}
  \begin{figure}[htbp]
\noindent\textbf{I} \par 
\begin{longtable}{P{0.16822916666666665\textwidth}P{0.36006944444444444\textwidth}P{0.2818576388888889\textwidth}P{0.03984375\textwidth}}
Variables\tabcellsep Definition\tabcellsep Measurement\tabcellsep Apriori sign\\
?? 0????\tabcellsep Poverty headcount ratio\tabcellsep Dummy 1=poor 0=non-poor\tabcellsep \\
?? 1????\tabcellsep Poverty gap\tabcellsep Consumption expenditure\tabcellsep \\
?? 2????\tabcellsep Poverty severity\tabcellsep Consumption expenditure\tabcellsep \\
?? 1\tabcellsep Crop productivity\tabcellsep Output Value? /Ha\tabcellsep -\\
?? 2\tabcellsep Household size\tabcellsep Household members\tabcellsep -/+\\
?? 3\tabcellsep Years of education\tabcellsep Years of education\tabcellsep -\\
?? 4\tabcellsep Distance to water source\tabcellsep Distance Km\tabcellsep -/+\\
?? 5\tabcellsep Days of ill-health\tabcellsep Number of days of inactivity\tabcellsep -/+\\
?? 6\tabcellsep Remittance income\tabcellsep Cedis\tabcellsep +\\
?? 7\tabcellsep Livestock income\tabcellsep Cedis\tabcellsep +\\
?? 1\tabcellsep Cost of chemical inputs (IV)\tabcellsep Cedis\tabcellsep +\\
?? 2\tabcellsep Cost of intermediate inputs (IV)\tabcellsep Cedis\tabcellsep +\\
\multicolumn{2}{l}{Source: Authors Construction, 2018}\tabcellsep \tabcellsep \\
c) The Data\tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_1}Table I :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{II} \par 
\begin{longtable}{P{0.4203636363636364\textwidth}P{0.057954545454545446\textwidth}P{0.06490909090909092\textwidth}P{0.085\textwidth}P{0.058727272727272725\textwidth}P{0.068\textwidth}P{0.09504545454545454\textwidth}}
\tabcellsep \tabcellsep Mean\tabcellsep Mean\tabcellsep \tabcellsep Mean\tabcellsep Mean Diffe\\
Variable Description\tabcellsep Poor\tabcellsep Non-Poor\tabcellsep Difference\tabcellsep Poor\tabcellsep Non-Poor\tabcellsep rence\\
\tabcellsep 2005\tabcellsep 2005\tabcellsep \tabcellsep 2013\tabcellsep 2013\tabcellsep \\
Consumption per Adult\tabcellsep 727.50\tabcellsep 2502.36\tabcellsep 1774.85***\tabcellsep 832.15\tabcellsep 3083.84\tabcellsep 2251.69***\\
Crop productivity kg/ha\tabcellsep 636.30\tabcellsep 954.30\tabcellsep 318.00**\tabcellsep 720.27\tabcellsep 874.92\tabcellsep 154.65***\\
Revenue cedi/ha\tabcellsep 177.93\tabcellsep 283.76\tabcellsep 105.82***\tabcellsep 682.97\tabcellsep 894.46\tabcellsep 211.49***\\
Price cedi/kg\tabcellsep 1.01\tabcellsep 1.18\tabcellsep .17\tabcellsep 1.36\tabcellsep 1.64\tabcellsep 0.28**\\
Chemical Cost (GHS)\tabcellsep 20.94\tabcellsep 54.66\tabcellsep 33.71***\tabcellsep 172.00\tabcellsep 259.59\tabcellsep 87.59***\\
Seed \& Labour Cost (GHS)\tabcellsep 27.43\tabcellsep 82.98\tabcellsep 55.55***\tabcellsep 73.20\tabcellsep 164.68\tabcellsep 91.47***\\
Intermediate Input Cost\tabcellsep 10.42\tabcellsep 22.93\tabcellsep 12.51***\tabcellsep 77.87\tabcellsep 127.92\tabcellsep 50.05**\\
Household Head Age\tabcellsep 47.54\tabcellsep 47.11\tabcellsep -.43\tabcellsep 49.26\tabcellsep 47.94\tabcellsep -1.32***\\
Years of Education\tabcellsep 7.61\tabcellsep 8.69\tabcellsep 1.07***\tabcellsep 6.97\tabcellsep 8.56\tabcellsep 1.58***\\
Remittances Income\tabcellsep 28.68\tabcellsep 59.69\tabcellsep 31.00***\tabcellsep 87.35\tabcellsep 214.96\tabcellsep 127.61***\\
Livestock Income (GHS)\tabcellsep 48.35\tabcellsep 29.78\tabcellsep -16.24**\tabcellsep 23.39\tabcellsep 95.98\tabcellsep 72.58*\\
Household Size Number\tabcellsep 6.06\tabcellsep 3.68\tabcellsep -2.38***\tabcellsep 6.44\tabcellsep 4.40\tabcellsep -2.04***\\
Distance to water source km\tabcellsep 2.9\tabcellsep 2.3\tabcellsep 0.6\tabcellsep .42\tabcellsep .36\tabcellsep -0.069***\\
Days of ill health\tabcellsep 5.64\tabcellsep 6.49\tabcellsep .84*\tabcellsep 6.31\tabcellsep 6.17\tabcellsep -.13\\
Source: Estimation output\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{3}{l}{b) Food and Cash Crop Sub-Sector Productivity}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{3}{l}{Food crop output increased, farm size reduced}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{3}{l}{slightly and the productivities output/income per hectare}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{3}{l}{of land increased towards poverty reduction between}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
2005 and 2013 (Table\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_2}Table II :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{III} \par 
\begin{longtable}{P{0.3940104166666667\textwidth}P{0.03246527777777778\textwidth}P{0.03246527777777778\textwidth}P{0.02361111111111111\textwidth}P{0.23315972222222223\textwidth}P{0.06345486111111111\textwidth}P{0.005902777777777778\textwidth}P{0.03246527777777778\textwidth}P{0.03246527777777778\textwidth}}
\multicolumn{9}{l}{Agro Ecological Zone Mean Output(kg) Farm size (ha) Output (kg/ha) Productivity (?/ha)}\\
\tabcellsep 2005\tabcellsep 2013\tabcellsep 2005\tabcellsep 2013\tabcellsep 2005\tabcellsep 2013\tabcellsep 2005\tabcellsep 2013\\
Food Crop\tabcellsep 1169.5\tabcellsep 1529.3\tabcellsep 2.61\tabcellsep 2.30\tabcellsep \multicolumn{2}{l}{851.35 949.06}\tabcellsep 245.19\tabcellsep 718.80\\
Cash crops\tabcellsep 740.96\tabcellsep 806.38\tabcellsep 2.60\tabcellsep 2.36\tabcellsep \multicolumn{2}{l}{390.27 450.64}\tabcellsep 264.51\tabcellsep 1147.8\\
All Crops\tabcellsep 1284.0\tabcellsep 1603.6\tabcellsep 3.32\tabcellsep 3.35\tabcellsep \multicolumn{2}{l}{763.81 811.59}\tabcellsep 257.24\tabcellsep 806.82\\
\multicolumn{2}{l}{Source Estimation Results, 2018}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
c) Crop Input Use by Farmers\tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{5}{l}{Fertilizer and hired labour are moderately used in crop}\\
\multicolumn{4}{l}{Crop farmers apply inputs such as fertilizer,}\tabcellsep \multicolumn{5}{l}{production process. Farmers do not commonly use}\\
\multicolumn{4}{l}{seed, labor, equipment, to increase productivity.}\tabcellsep \multicolumn{5}{l}{improved seeds and equipment (Table IV).}\end{longtable} \par
 
\caption{\label{tab_3}Table III :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{IV} \par 
\begin{longtable}{P{0.24142011834319527\textwidth}P{0.2464497041420118\textwidth}P{0.10059171597633135\textwidth}P{0.08047337278106509\textwidth}P{0.10059171597633135\textwidth}P{0.08047337278106509\textwidth}}
Inputs\tabcellsep \multicolumn{5}{l}{Yes Percentage No Percentage Total ??}\\
Fertilizer\tabcellsep 3346\tabcellsep 40.01\tabcellsep 5016\tabcellsep 59.99\tabcellsep 8362\\
Seed\tabcellsep 1519\tabcellsep 18.17\tabcellsep 6843\tabcellsep 81.83\tabcellsep 8362\\
Labour\tabcellsep 4306\tabcellsep 51.49\tabcellsep 4056\tabcellsep 48.51\tabcellsep 8362\\
\multicolumn{2}{l}{Renting Equipment 1331}\tabcellsep 15.92\tabcellsep 7031\tabcellsep 84.08\tabcellsep 8362\end{longtable} \par
  {\small\itshape [Note: Source: Ghana living standards survey, round 6]} 
\caption{\label{tab_4}Table IV :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{V} \par 
\begin{longtable}{P{0.5352343749999999\textwidth}P{0.02390625\textwidth}P{0.031875\textwidth}P{0.075703125\textwidth}P{0.1009375\textwidth}P{0.033203125\textwidth}P{0.049140625\textwidth}}
\tabcellsep \tabcellsep Mean\tabcellsep \multicolumn{2}{l}{2005/06}\tabcellsep Mean\tabcellsep 2012/13\\
\multicolumn{7}{l}{Expenditure Poor Non-Poor Difference Poor Non-poor Difference}\\
Food\tabcellsep 397.78\tabcellsep 1339.93\tabcellsep \multicolumn{2}{l}{942.14 *** 516.96}\tabcellsep 1767.51\tabcellsep 1250.54***\\
Non-food\tabcellsep 275.13\tabcellsep 972.84\tabcellsep \multicolumn{2}{l}{697.71*** 314.52}\tabcellsep 1323.80\tabcellsep 1009.29***\\
Total\tabcellsep 727.77\tabcellsep 2497.60\tabcellsep \multicolumn{2}{l}{1769.81*** 831.47}\tabcellsep 3091.31\tabcellsep 2259.83***\\
\multicolumn{3}{l}{Source: Authors' estimated output, 2018}\tabcellsep \tabcellsep \tabcellsep \\
f) Poverty Levels by Crop Type\tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{3}{l}{2005 to 24\% in 2013, lower than food crop producers as}\\
\multicolumn{4}{l}{Food crop producers of major food crops such}\tabcellsep \multicolumn{2}{l}{highlighted in (Table}\\
\multicolumn{4}{l}{as maize, rice, millet, cassava, and plantain poverty rate}\tabcellsep \tabcellsep \\
\multicolumn{4}{l}{declined from 59\% in 2005 to 39\% in 2013. Cash crop}\tabcellsep \tabcellsep \\
\multicolumn{4}{l}{producers of major crops such as cocoa, cashew,}\tabcellsep \tabcellsep \\
\multicolumn{4}{l}{rubber, and cotton poverty rate declined from 44\%, in}\tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_5}Table V :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{VI} \par 
\begin{longtable}{P{0.25996563573883164\textwidth}P{0.10807560137457044\textwidth}P{0.02336769759450172\textwidth}P{0.02336769759450172\textwidth}P{0.020446735395189004\textwidth}P{0.026288659793814433\textwidth}P{0.026288659793814433\textwidth}P{0.245360824742268\textwidth}P{0.01168384879725086\textwidth}P{0.04965635738831615\textwidth}P{0.055498281786941585\textwidth}}
Crop Categories\tabcellsep P1\tabcellsep \tabcellsep P2\tabcellsep \tabcellsep P3\tabcellsep \tabcellsep \multicolumn{4}{l}{Consumption (?) Population (number)}\\
\tabcellsep \multicolumn{6}{l}{2005 2013 2005 2013 2005 2013}\tabcellsep 2005\tabcellsep 2013\tabcellsep 2005\tabcellsep 2013\\
Food Crops\tabcellsep 59\tabcellsep 39\tabcellsep 27\tabcellsep 15\tabcellsep 16\tabcellsep 7.4\tabcellsep \multicolumn{2}{l}{1432.14 2172.39}\tabcellsep 2,771\tabcellsep 7,454\\
Cash Crops\tabcellsep 44\tabcellsep 24.4\tabcellsep 16\tabcellsep 7.4\tabcellsep 8.5\tabcellsep 3.2\tabcellsep \multicolumn{2}{l}{1796.82 2638.11}\tabcellsep 736\tabcellsep 2,331\\
All Crops\tabcellsep 57\tabcellsep 37\tabcellsep 25\tabcellsep 14\tabcellsep 14\tabcellsep 6.8\tabcellsep \multicolumn{2}{l}{1486.16 2244.07}\tabcellsep 2,957\tabcellsep 8,352\\
\multicolumn{4}{l}{Source: Authors estimated output, GLSS 5 \& 6}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
  {\small\itshape [Note: g) Effect of Food Crop Productivity on Poverty]} 
\caption{\label{tab_6}Table VI :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{VII} \par 
\begin{longtable}{P{0.21384493670886076\textwidth}P{0.1829113924050633\textwidth}P{0.2286392405063291\textwidth}P{0.22460443037974684\textwidth}}
Variables\tabcellsep Poverty Headcount\tabcellsep Poverty Gap\tabcellsep Poverty Severity\\
Output value\tabcellsep -0.192***\tabcellsep -0.405***\tabcellsep -0.810***\\
\tabcellsep (0.0211)\tabcellsep (0.0419)\tabcellsep (0.0837)\\
Household size\tabcellsep 1.333***\tabcellsep 0.317***\tabcellsep 0.634***\\
\tabcellsep (0.0464)\tabcellsep (0.0293)\tabcellsep (0.0585)\\
Education years\tabcellsep -0.378***\tabcellsep -0.0980***\tabcellsep -0.196***\\
\tabcellsep (0.0252)\tabcellsep (0.0168)\tabcellsep (0.0336)\\
Dayssick\tabcellsep -0.0949**\tabcellsep -0.0564**\tabcellsep -0.113**\\
\tabcellsep (0.0412)\tabcellsep (0.0263)\tabcellsep (0.0525)\\
Distance water\tabcellsep 0.0803***\tabcellsep 0.0146\tabcellsep 0.0292\\
\tabcellsep (0.0131)\tabcellsep (0.00896)\tabcellsep (0.0179)\\
Livestock income\tabcellsep -0.159***\tabcellsep 0.0120\tabcellsep 0.0240\\
\tabcellsep (0.0104)\tabcellsep (0.00832)\tabcellsep (0.0166)\\
Remittance income\tabcellsep -0.0333***\tabcellsep -0.0181***\tabcellsep -0.0361***\\
\tabcellsep (0.0102)\tabcellsep (0.00667)\tabcellsep (0.0133)\\
Forest\tabcellsep \tabcellsep 0.0889\tabcellsep 0.178\\
\tabcellsep \tabcellsep (0.0826)\tabcellsep (0.165)\\
Savannah\tabcellsep \tabcellsep 0.455***\tabcellsep 0.911***\\
\tabcellsep \tabcellsep (0.0794)\tabcellsep (0.159)\\
Constant\tabcellsep \tabcellsep 0.121\tabcellsep 0.242\\
\tabcellsep \tabcellsep (0.238)\tabcellsep (0.476)\\
\multicolumn{2}{l}{Source: Authors estimated output}\tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_7}Table VII :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{VIII} \par 
\begin{longtable}{P{0.1876126126126126\textwidth}P{0.27950450450450454\textwidth}P{0.06509009009009008\textwidth}P{0.3177927927927928\textwidth}}
h)\tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep \tabcellsep \tabcellsep Year 2022\\
\tabcellsep \tabcellsep \tabcellsep 53\\
\tabcellsep \tabcellsep \tabcellsep Volume XXII Issue VI Version I\\
\tabcellsep \tabcellsep \tabcellsep )\\
\tabcellsep \tabcellsep \tabcellsep E\\
\tabcellsep \tabcellsep \tabcellsep (\\
\tabcellsep \tabcellsep \tabcellsep Global Journal of Human Social Science -\\
\multicolumn{3}{l}{Poverty Measure Statement of Hypothesis Test Statistic}\tabcellsep Decision Rule\\
Headcount Ratio\tabcellsep H0: Random effects model Ha: Fixed effects model\tabcellsep 12.05 (0.09)\tabcellsep Reject Null\\
Poverty Gap\tabcellsep H0: Random effects model Ha: Fixed effects model\tabcellsep 9.02 (0.25)\tabcellsep Do not Reject Null\\
Poverty Severity\tabcellsep H0 : Random effects model Ha : Fixed effects model\tabcellsep 9.02 (0.25)\tabcellsep Do not Reject Null\\
\tabcellsep \tabcellsep \tabcellsep © 2022 Global Journals\end{longtable} \par
 
\caption{\label{tab_8}Table VIII :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{IX} \par 
\begin{longtable}{P{0.21145662847790506\textwidth}P{0.23232405891980362\textwidth}P{0.20589198036006548\textwidth}P{0.20032733224222585\textwidth}}
Variables\tabcellsep \multicolumn{3}{l}{Poverty Headcount Ratio Poverty Gap Poverty Severity}\\
Outputvalueha\tabcellsep -0.283***\tabcellsep -0.440***\tabcellsep -0.879***\\
\tabcellsep (0.0382)\tabcellsep (0.136)\tabcellsep (0.272)\\
Household size\tabcellsep 1.473***\tabcellsep 0.527***\tabcellsep 1.053***\\
\tabcellsep (0.105)\tabcellsep (0.0834)\tabcellsep (0.167)\\
Education years\tabcellsep -0.447***\tabcellsep -0.131***\tabcellsep -0.263***\\
\tabcellsep (0.0549)\tabcellsep (0.0446)\tabcellsep (0.0892)\\
Dayssick\tabcellsep -0.0233\tabcellsep -0.0767\tabcellsep -0.153\\
\tabcellsep (0.0842)\tabcellsep (0.0715)\tabcellsep (0.143)\\
Diswater source\tabcellsep 0.120***\tabcellsep 0.0307\tabcellsep 0.0615\\
\tabcellsep (0.0317)\tabcellsep (0.0277)\tabcellsep (0.0554)\\
Livestockincome\tabcellsep -0.119***\tabcellsep 0.00321\tabcellsep 0.00642\\
\tabcellsep (0.0241)\tabcellsep (0.0190)\tabcellsep (0.0381)\\
Remittance\tabcellsep -0.0792***\tabcellsep -0.0678***\tabcellsep -0.136***\\
\tabcellsep (0.0220)\tabcellsep (0.0186)\tabcellsep (0.0371)\\
Forest\tabcellsep \tabcellsep 0.250\tabcellsep 0.501\\
\tabcellsep \tabcellsep (0.247)\tabcellsep (0.495)\\
Savannah\tabcellsep \tabcellsep 0.104\tabcellsep 0.208\\
\tabcellsep \tabcellsep (0.226)\tabcellsep (0.451)\\
Constant\tabcellsep \tabcellsep -0.146\tabcellsep -0.292\\
\tabcellsep \tabcellsep (0.722)\tabcellsep (1.444)\\
\multicolumn{2}{l}{Source: Estimation Result, 2018}\tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_9}Table IX :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{X} \par 
\begin{longtable}{P{0.27255434782608695\textwidth}P{0.3279891304347826\textwidth}P{0.1108695652173913\textwidth}P{0.13858695652173914\textwidth}}
V.\tabcellsep \tabcellsep \tabcellsep \\
54\tabcellsep \tabcellsep \tabcellsep \\
Volume XXII Issue VI Version I\tabcellsep \tabcellsep \tabcellsep \\
)\tabcellsep \tabcellsep \tabcellsep \\
(\tabcellsep \tabcellsep \tabcellsep \\
Poverty Measure\tabcellsep Statement of Hypothesis\tabcellsep Test Statistic\tabcellsep Decision Rule\\
\multicolumn{2}{l}{Headcount Ratio H0: Random effects model}\tabcellsep 18.56 (0.01)\tabcellsep Reject Null\\
\tabcellsep Ha: Fixed effects model\tabcellsep \tabcellsep \\
Poverty Gap\tabcellsep H0: Random effects model\tabcellsep 2.49 (0.92)\tabcellsep Do not Reject Null\\
\tabcellsep Ha: Fixed effects model\tabcellsep \tabcellsep \\
Poverty Severity\tabcellsep H0 : Random effects model\tabcellsep 2.49 (0.92)\tabcellsep Do not Reject Null\\
\tabcellsep Ha : Fixed effects model\tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_10}Table X :}\end{figure}
 		 		\backmatter  			  				\begin{bibitemlist}{1}
\bibitem[Springer]{b29}\label{b29} 	 		\textit{},  		 			Dordrecht Springer 		.  		 	 
\bibitem[Bank ()]{b53}\label{b53} 	 		\textit{},  		 			World Bank 		.  		2000. 2000-2001. Washington, DC: World Bank.  	 	 (World Development Report) 
\bibitem[ GSS ()]{b24}\label{b24} 	 		\textit{},  		 \url{http://www.statsghana.gov.gh/docfiles/GDP/GDP2017}  	 	 		\textit{GSS}  		2017.  	 	 (Ghana Statistical Service Provisional 2016 Annual Gross Domestic Product) 
\bibitem[Schneider and Gugerty ()]{b45}\label{b45} 	 		‘Agricultural productivity and poverty reduction: Linkages and pathways’.  		 			K Schneider 		,  		 			M K Gugerty 		.  	 	 		\textit{Libraries Test Journal}  		2011. 1  (1)  p. .  	 
\bibitem[Minten and Barrett ()]{b36}\label{b36} 	 		‘Agricultural technology, productivity, and poverty in Madagascar’.  		 			B Minten 		,  		 			C B Barrett 		.  	 	 		\textit{World Development}  		2008. 36  (5)  p. .  	 
\bibitem[Al-Hassan and Poulton ()]{b1}\label{b1} 	 		\textit{Agriculture and Social Protection in Ghana Futures Agricultures FAC Working Paper No},  		 			R Al-Hassan 		,  		 			C Poulton 		.  		2009.  	 
\bibitem[Mofa ()]{b37}\label{b37} 	 		\textit{Agriculture in Ghana: Facts and Figures (2016) Ministry of Food and Agriculture Statistics},  		 			Mofa 		.  		2016. 2017.  	 	 (Research and Information Directorate (SRID) 
\bibitem[Coelli et al. ()]{b9}\label{b9} 	 		\textit{An introduction to efficiency and productivity analysis},  		 			T J Coelli 		,  		 			D S P Rao 		,  		 			C J O'donnell 		,  		 			G E Battese 		.  		2005. Springer Science \& Business Media.  	 
\bibitem[Bresciani ()]{b5}\label{b5} 	 		‘Beyond food production: the role of agriculture in poverty reduction’.  		 			F Bresciani 		.  	 	 		\textit{Food \& Agriculture Org. Economic and Social Development Dept}  		\& Valdés, A. (ed.)  		2007. 2007. p. .  	 
\bibitem[Govereh ()]{b22}\label{b22} 	 		‘Cash cropping and food crop productivity: synergies or trade-offs?’.  		 			J Govereh 		,  		 			JayneT S 		.  	 	 		\textit{Agricultural Economics}  		2003. 2003. 28 p. .  	 
\bibitem[Diao and Dorosh ()]{b15}\label{b15} 	 		‘Demand constraints on agricultural growth in East and Southern Africa: A general equilibrium analysis’.  		 			X Diao 		,  		 			P Dorosh 		.  	 	 		\textit{Development Policy Review}  		2007. 25  (3)  p. .  	 
\bibitem[Sen ()]{b46}\label{b46} 	 		\textit{Development As Freedom},  		 			Amartya Sen 		.  		1999. Oxford: Oxford University Press.  	 
\bibitem[Balagtas et al. ()]{b4}\label{b4} 	 		‘Did the commodity price spike increase rural poverty? Evidence from a long-run panel in Bangladesh’.  		 			J V Balagtas 		,  		 			H Bhandari 		,  		 			E R Cabrera 		,  		 			S Mohanty 		,  		 			M Hossain 		.  	 	 		\textit{Agricultural Economics}  		2014. 45  (3)  p. .  	 
\bibitem[Khan and Verma ()]{b33}\label{b33} 	 		‘Diversifying cropping systems with aromatic crops for better productivity and profitability in subtropical north Indian plains’.  		 			K Khan 		,  		 			R K Verma 		.  	 	 		\textit{Industrial Crops and Products}  		2018. 115 p. .  	 
\bibitem[Coppola and Di Laurea ()]{b10}\label{b10} 	 		‘Dynamics of persistent poverty in Italy at the beginning of the crisis’.  		 			L Coppola 		,  		 			D Di Laurea 		.  	 	 		\textit{Genus}  		2016. 72  (1)  p. 3.  	 
\bibitem[Diao and Hazell ()]{b16}\label{b16} 	 		‘Exploring market opportunities for African smallholders’.  		 			X Diao 		,  		 			P Hazell 		.  	 	 		\textit{International Food Policy Research Institute (IFPRI)},  				2004.  	 
\bibitem[Cho et al. (2016)]{b7}\label{b7} 	 		‘Food Insecurity and Types of Disability’.  		 			S Cho 		,  		 			A Ishdorj 		,  		 			C Gregory 		.  	 	 		\textit{2016 Annual Meeting},  				 (San Antonio, Texas)  		2016. February 6-9, 2016.  	 
\bibitem[Ghana Living Standards Survey Rounds 7 Ghana Statistical Service]{b26}\label{b26} 	 		\textit{Ghana Living Standards Survey Rounds 7 Ghana Statistical Service},  				 	 
\bibitem[Acdi/Voca (2012)]{b0}\label{b0} 	 		\textit{Ghana-Agriculture Development and Value Chain Enhancement (ADVANCE) Project},  		 			Acdi/Voca 		.  		 \url{http://www.acdivoca.org/site/ID/ghanaADVANCE}  		2012. retrieved October 1, 2019.  	 
\bibitem[Roser and Ortiz-Ospina ()]{b44}\label{b44} 	 		\textit{Global Extreme Poverty},  		 			M Roser 		,  		 			E Ortiz-Ospina 		.  		 https://ourworldin.  		 \url{https://ourworldindata.org/extreme-poverty}  		2018.  	 	 (Published online at OurWorldInData.org. Retrieved from) 
\bibitem[Broeck et al. ()]{b6}\label{b6} 	 		‘Global value chains, large-scale farming, and poverty: Long-term effects in Senegal’.  		 			Broeck 		,  		 			G Van Den 		,  		 			J Swinnen 		,  		 			M Maertens 		.  	 	 		\textit{Food policy}  		2017. 66 p. .  	 
\bibitem[Stern et al. ()]{b48}\label{b48} 	 		\textit{Growth and empowerment. Making development happen},  		 			N Stern 		,  		 			J J Dethier 		,  		 			F H Rogers 		.  		2005. Cambridge: The Massachusetts Institute of Technology Press.  	 
\bibitem[Fosu ()]{b19}\label{b19} 	 		‘Growth, inequality, and poverty reduction in developing countries: recent global evidence’.  		 			A K Fosu 		.  	 	 		\textit{Research in Economics}  		2016. 71  (2)  p. .  	 
\bibitem[Dzanku ()]{b17}\label{b17} 	 		‘Household welfare effects of agricultural productivity: A multidimensional perspective from Ghana’.  		 			F M Dzanku 		.  	 	 		\textit{The Journal of Development Studies}  		2015a. 51  (9)  p. .  	 
\bibitem[Generoso ()]{b20}\label{b20} 	 		‘How do rainfall variability, food security and remittances interact? The case of rural Mali’.  		 			R Generoso 		.  	 	 		\textit{Ghana Statistical Service (2022) Ghana Statistical Service Ghana Statistical Services. (statsghana.gov.gh)},  				2015. 114 p. .  	 
\bibitem[Leshoro and Leshoro ()]{b34}\label{b34} 	 		‘Impacts of literacy rate and human development indices on agricultural production in South Africa’.  		 			S Leshoro 		,  		 			T L Leshoro 		.  	 	 		\textit{Agricultural Economics/Zemedelska Ekonomika}  		2013.  (11)  p. 59.  	 
\bibitem[Katagame et al. ()]{b31}\label{b31} 	 		\textit{Income Contribution of Pig Livestock toward Poverty Reduction and Factors Influencing Pig Farming in Mimika Papua IOSR Journal of Agriculture and Veterinary Science},  		 			A Katagame 		,  		 			Z Fanani 		,  		 			B Nugroho 		,  		 			A 		.  		 ISSN: 2319-2372.  		2017. 10 p. .  	 
\bibitem[Iheke and Nwaru ()]{b30}\label{b30} 	 		‘Innovation Adoption, Farm Productivity and Poverty Status of Rural Smallholder Farm Households’.  		 			O R Iheke 		,  		 			J C Nwaru 		.  	 	 		\textit{the 4th International Conference of the African Association of Agricultural Economists},  				 (South-East, Nigeria; Hammamet, Tunisia)  		2013.  	 	 (Invited paper presented at) 
\bibitem[Tebaldi and Mohan ()]{b49}\label{b49} 	 		‘Institutions and Poverty’.  		 			E Tebaldi 		,  		 			R Mohan 		.  	 	 		\textit{The Journal of Development Studies}  		2010. 46 p. .  	 
\bibitem[Thirtle and Piesse ()]{b52}\label{b52} 	 		‘Irrigation and Drainage: The journal of the International Commission on Irrigation and Drainage’.  		 			C Thirtle 		,  		 			J Piesse 		.  	 	 		\textit{Asia and Latin America}  		2007. 56  (2-3)  p. .  	 	 (Governance, agricultural productivity and poverty reduction in Africa) 
\bibitem[Ravallion ()]{b42}\label{b42} 	 		‘Issues in Measuring and Modeling Poverty. The World Bank’.  		 			M Ravallion 		.  	 	 		\textit{Policy}  		1996.  	 
\bibitem[Hill and Vigneri ()]{b28}\label{b28} 	 		‘Mainstreaming gender sensitivity in cash crop market supply chains’.  		 			R V Hill 		,  		 			M Vigneri 		.  	 	 		\textit{Gender in agriculture},  				2014. p. .  	 
\bibitem[Cuong ()]{b12}\label{b12} 	 		‘Measuring the impact of cash crops on household expenditure and poverty in rural Vietnam’.  		 			N V Cuong 		.  	 	 		\textit{Asia-Pacific Development Journal}  		2009. 16  (2)  p. .  	 
\bibitem[Nicholson and Snyder ()]{b40}\label{b40} 	 		\textit{Microeconomic theory. Basic Principles and Extensions Tenth Edition},  		 			W Nicholson 		,  		 			C Snyder 		.  		2008. Thomson South-Western, Canada.  	 
\bibitem[Deaton ()]{b14}\label{b14} 	 		‘Panel Data from Time-Series of Cross-Section’.  		 			A Deaton 		.  	 	 		\textit{Journal of Econometrics}  		1985. 30 p. .  	 
\bibitem[Katchova ()]{b32}\label{b32} 	 		\textit{Panel Data Models Econometric Academy},  		 			A Katchova 		.  		 \url{https://sites.google.com/site/econometricsacademy/econometrics-models/panel-data-models}  		2013.  	 
\bibitem[Al-Hassan and Diao ()]{b2}\label{b2} 	 		\textit{Policy Options and Public Investment Implications Regional Disparities in Ghana Development Strategy Governance Division International Food Policy},  		 			R Al-Hassan 		,  		 			M Diao 		,  		 			X 		.  		2007.  	 	 (Research Institute IFPRI Discussion Paper No. 00693) 
\bibitem[Poverty profile in Ghana Ghana Statistical Service ()]{b21}\label{b21} 	 		‘Poverty profile in Ghana’.  	 	 		\textit{Ghana Statistical Service},  				 (Accra)  		2014. 2005-2013.  	 
\bibitem[Molini and Paci ()]{b38}\label{b38} 	 		\textit{Poverty Reduction in Ghana-Progress and Challenges},  		 			V Molini 		,  		 			P Paci 		.  		2015.  	 
\bibitem[Gss ()]{b25}\label{b25} 	 		\textit{Poverty Trends in Ghana},  		 			Gss 		.  		2018. 2005-2017.  	 
\bibitem[Guillerm ()]{b27}\label{b27} 	 		‘Pseudo-panel methods and an example of application to Household Wealth data’.  		 			M Guillerm 		.  		 \xref{http://dx.doi.org/10.24187/ecostat.2017.491d.1908}{10.24187/ecostat.2017.491d.1908}.  	 	 		\textit{Economie et Statistique/Economics and Statistics},  				2017. p. .  	 
\bibitem[Reimers and Klasen ()]{b43}\label{b43} 	 		‘Revisiting the role of education for agricultural productivity’.  		 			M Reimers 		,  		 			S Klasen 		.  	 	 		\textit{American Journal of Agricultural Economics}  		2013. 95  (1)  p. .  	 
\bibitem[Crown et al. ()]{b11}\label{b11} 	 		‘Some cautions on the use of instrumental variables estimators in outcomes research: how bias in instrumental variables estimators is affected by instrument strength, instrument contamination, and sample size’.  		 			W H Crown 		,  		 			H J Henk 		,  		 			D J Vanness 		.  	 	 		\textit{Value in Health}  		2011. 14  (8)  p. .  	 
\bibitem[Teka et al. ()]{b50}\label{b50} 	 		‘Status and determinants of poverty and income inequality in pastoral and agro-pastoral communities: Household-based evidence from Afar Regional State’.  		 			A M Teka 		,  		 			G T Woldu 		,  		 			Z Fre 		.  	 	 		\textit{Ethiopia. World Development Perspectives}  		2019. p. 100123.  	 
\bibitem[Anderman et al. ()]{b3}\label{b3} 	 		‘Synergies and tradeoffs between cash crop production and food security: a case study in rural Ghana’.  		 			T L Anderman 		,  		 			R Remans 		,  		 			S A Wood 		.  		 \xref{http://dx.doi.org/10.1007/s12571-014-0360-6}{10.1007/s12571-014-0360-6}.  		 \url{https://doi.org/10.1007/s12571-014-0360-6}  	 	 		\textit{Food Sec}  		2014. 6 p. .  	 
\bibitem[Christiaensen et al. ()]{b8}\label{b8} 	 		‘The (evolving) role of agriculture in poverty reduction-An empirical perspective’.  		 			L Christiaensen 		,  		 			L Demery 		,  		 			J Kuhl 		.  	 	 		\textit{Journal of development economics}  		2011. 96  (2)  p. .  	 
\bibitem[Grewal et al. ()]{b23}\label{b23} 	 		‘The contribution of agricultural growth to reduction’.  		 			B Grewal 		,  		 			H Grunfeld 		,  		 			P Sheehan 		.  	 	 		\textit{Australian Centre for International Agricultural Research}  		2012. ACIAR.  	 
\bibitem[Nowak and Kijek ()]{b41}\label{b41} 	 		‘The effect of human capital on labour productivity of farms in Poland’.  		 			A Nowak 		,  		 			T Kijek 		.  	 	 		\textit{Studies in Agricultural Economics}  		2016. 118  (1)  p. .  	 
\bibitem[Thirtle et al. ()]{b51}\label{b51} 	 		‘The impact of research led agricultural productivity growth on poverty reduction in Africa, and Latin America’.  		 			C Thirtle 		,  		 			L Lin 		,  		 			J Piesse 		.  	 	 		\textit{World Development}  		2003. 31  (12)  p. .  	 
\bibitem[Mondal and Khanam ()]{b39}\label{b39} 	 		\textit{The impacts of international migrants' remittances on household consumption volatility in developing countries},  		 			R K Mondal 		,  		 			R Khanam 		.  		2016.  	 
\bibitem[Michler and Josephson ()]{b35}\label{b35} 	 		‘To specialize or diversify: agricultural diversity and poverty dynamics in Ethiopia’.  		 			J D Michler 		,  		 			A L Josephson 		.  	 	 		\textit{World Development}  		2017. 89 p. .  	 
\bibitem[Dzanku et al. ()]{b18}\label{b18} 	 		‘Transient rural livelihoods and poverty in Ghana’.  		 			F M Dzanku 		,  		 			J Foster 		,  		 			J Greer 		,  		 			E Thorbecke 		.  	 	 		\textit{Econometrica: journal of the econometric society}  		2015b. 1984. 40 p. .  	 	 (Journal of Rural Studies) 
\bibitem[Ssewanyana and Kasirye ()]{b47}\label{b47} 	 		‘Uganda's Progress Towards Poverty Reduction during the last Decade’.  		 			S Ssewanyana 		,  		 			I Kasirye 		.  	 	 		\textit{Is the Gap Between Leading and Lagging Areas Widening or Narrowing},  				2014. 2002/3-2012/13.  	 
\bibitem[Danso-Abbeam and Baiyegunhi ()]{b13}\label{b13} 	 		‘Welfare impact of pesticides management practices among smallholder cocoa farmers in Ghana’.  		 			G Danso-Abbeam 		,  		 			L J Baiyegunhi 		.  	 	 		\textit{Technology in Society}  		2018. 54 p. .  	 
\end{bibitemlist}
 			 		 	 
\end{document}
