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          Inquérito de Base do Sector Agrário (IBSA)
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          Ministerio da Agricultura e Desenvolvimento Rural
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            Ministerio da Agricultura e Desenvolvimento Rural
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            Instituto Nacional de Estatisticas
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      <prodStmt>
        <producer abbr="MADER" affiliation="INE" role="Produtor">
          <![CDATA[Ministerio  da Agricultura e Desenvolvimento Rural]]>
        </producer>
        <producer abbr="INE" affiliation="SEN" role="Produtor">
          Instituto Nacional de Estatisticas
        </producer>
        <copyright>
          IAI-2020
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          Inquérito Agrário Integrado 2020
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          IAI-2020
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          Ministerio da Agricultura e Desenvolvimento Rural
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        <AuthEnty affiliation="SEN">
          Instituto Nacional de Estatisticas
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        <producer abbr="INE" affiliation="SEN" role="Produtor">
          INstituto NAcional de EStatisticas
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        <fundAg abbr="FIDA" role="Financiador">
          Fundo Internacional para o Desenvolvimento de Agricultura
        </fundAg>
        <fundAg abbr="BAD" role="Financiador">
          BAnco Africano para o Desenvolvimento
        </fundAg>
      </prodStmt>
      <distStmt>
        <distrbtr abbr="MADER" affiliation="INE">
          Ministerio da Agricultura e Desenvolvimento Rural
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        <distrbtr abbr="INE" affiliation="SEN">
          Instituto Nacional de Estatisticas
        </distrbtr>
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          <![CDATA[No âmbito do desenvolvimento das Estatísticas Agrárias em Moçambique, enquadrado no Plano Director de Estatísticas Agrárias (PDEA 2012 - 2022), o MADER, como órgão Delegado do INE para produção de Estatísticas Agrárias, tem a obrigação de realizar inquéritos por amostragem probabilística.
Assim sendo, a DPP vai realizar um Inquérito de Base Para o Sector Agrário (IBSA) com objectivo de avaliar o estágio actual do desenvolvimento do sector agrário.
Estes dados serão usados como fonte principal para a avaliação do grau de implementação dos Programas e planos do sector agrário, com destaque para o Plano Quinquenal do Governo (PQG) e o Plano Económico Social (PES) entre outros, bem como os vários compromissos regionais e internacionais assumidos pelo Governo de Moçambique sobre o sector da agricultura, tais como: Declaração de Malabo, os objectivos de Desenvolvimento Sustentável (ODS) e de outros programas do sector agrário. 
Estas operações estatísticas são levadas a cabo em estreita colaboração com o INE, na qualidade de supervisor deste exercício.]]>
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    </citation>
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          Inquerito Agrario 2020
        </keyword>
        <topcClas>
          IAI-2020
        </topcClas>
      </subject>
      <abstract>
        A fonte de dados para a disponibilização da informação requerida são os agregados familiares ou empresas que praticam actividadde agro-pecuária, que pode ser agrícola, pecuária ou a combinação das duas e estão estratificados em pequenas, Médias e Grandes Explorações localizadas em todos os Distritos do país.
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        <collDate date="2020" event="end"/>
        <nation>
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        </nation>
        <geogCover>
          Nacional
        </geogCover>
        <anlyUnit>
          A fonte de dados para a disponibilização da informação requerida são os agregados familiares ou empresas que praticam actividadde agro-pecuária, que pode ser agrícola, pecuária ou a combinação das duas e estão estratificados em pequenas, Médias e Grandes Explorações localizadas em todos os Distritos do país.
        </anlyUnit>
        <universe>
          A população alvo é composta por agregados familiares agrícolas e empresas que possuem explorações agro-pecuárias operando no território nacional.
        </universe>
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          <![CDATA[Para a selecção da amostra foi usado o método de amostragem probabilístico e bi-etápico. A amostra é estratificada por urbano e rural; contudo, para melhorar o desenho da amostra, uma estratificação implícita por zonas agro-ecológicas foi realizada antes da selecçao da amostra das unidades primárias de amostragem em cada estrati explícito. 
A base de amostragem para o inquérito é o MSF (Master Sample Frame for Agricultural Survey) elaborado na base dos dados do Recenseamento Geral de População e Habitação (IV RGPH 2017), Sessão F-Agro-Pecuária.
5]]>
        </sampProc>
        <collMode>
          <![CDATA[A recolha de dados é efectuada através de inquéritos aos agregados familiares e empresas que praticam actividade agro-pecuaria usando o tablet como meio de recolha e de forma presencial. Ou seja, utilizar-se-á a metodologia CAPI (Computer-Assisted Personal Interviewing), permitindo que os dados sejam enviados directamente para um servidor, o que facilita o acesso imediato a eles, como também a plataforma pode armazenar uma grande quantidade de informações sem exigir custos de impressão ou registro de dados.
2.3.3 Período de Referência dos Dados
a)	Para a produção agrícola: Campanha agrícola 2019-20;
b)	Para a produção pecuária:
b.1. Efectivos pecuários: Data da entrevista;  
b.2. Vacinação de animais, entradas e saídas de animais e outros aspectos: 
Nos últimos 12 meses e para as Aves, o período de referência são os últimos 3 meses.]]>
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        <weight>
          Para que as estimativas da amostra de um inquérito sejam representativas da população, é necessário multiplicar os dados por um ponderador de amostragem. O ponderador básico para cada exploração agrícola amostral seria igual ao inverso da sua probabilidade de selecção (calculado multiplicando as probabilidades em cada etapa de amostragem). Dado que os ponderadores serão diferentes para cada tipo de exploração (pequeno, médio e grande), o cálculo dos ponderadores é especificado individualmente para cada tipo de exploração agrícola.
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        <catStat type="freq">
          393
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          NÃO
        </catValu>
        <catStat type="freq">
          175
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          SIM
        </catValu>
        <catStat type="freq">
          93
        </catStat>
      </catgry>
      <varFormat type="character" schema="other"/>
    </var>
    <var ID="V16" name="LimiteFron_first_1" files="F1" intrvl="discrete">
      <location width="14"/>
      <labl/>
      <sumStat type="vald">
        675
      </sumStat>
      <sumStat type="invd">
        0
      </sumStat>
      <catgry>
        <catValu>
          NAO
        </catValu>
        <catStat type="freq">
          592
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          NÃO
        </catValu>
        <catStat type="freq">
          1
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          SIM
        </catValu>
        <catStat type="freq">
          82
        </catStat>
      </catgry>
      <varFormat type="character" schema="other"/>
    </var>
    <var ID="V17" name="N_Total_UMn_AE" files="F1" dcml="0" intrvl="discrete">
      <location width="10"/>
      <labl/>
      <valrng>
        <range min="1" max="6"/>
      </valrng>
      <sumStat type="vald">
        675
      </sumStat>
      <sumStat type="invd">
        0
      </sumStat>
      <catgry>
        <catValu>
          1
        </catValu>
        <catStat type="freq">
          521
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          2
        </catValu>
        <catStat type="freq">
          131
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          3
        </catValu>
        <catStat type="freq">
          18
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          4
        </catValu>
        <catStat type="freq">
          4
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          6
        </catValu>
        <catStat type="freq">
          1
        </catStat>
      </catgry>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V18" name="A2_PROVINCIA" files="F1" dcml="0" intrvl="discrete">
      <location width="10"/>
      <labl>
        Província Censo 2017
      </labl>
      <valrng>
        <range min="1" max="11"/>
      </valrng>
      <sumStat type="vald">
        675
      </sumStat>
      <sumStat type="invd">
        0
      </sumStat>
      <catgry>
        <catValu>
          1
        </catValu>
        <labl>
          Niassa
        </labl>
        <catStat type="freq">
          43
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          2
        </catValu>
        <labl>
          Cabo Delgado
        </labl>
        <catStat type="freq">
          70
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          3
        </catValu>
        <labl>
          Nampula
        </labl>
        <catStat type="freq">
          117
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          4
        </catValu>
        <labl>
          Zambézia
        </labl>
        <catStat type="freq">
          112
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          5
        </catValu>
        <labl>
          Tete
        </labl>
        <catStat type="freq">
          74
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          6
        </catValu>
        <labl>
          Manica
        </labl>
        <catStat type="freq">
          46
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          7
        </catValu>
        <labl>
          Sofala
        </labl>
        <catStat type="freq">
          60
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          8
        </catValu>
        <labl>
          Inhambane
        </labl>
        <catStat type="freq">
          51
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          9
        </catValu>
        <labl>
          Gaza
        </labl>
        <catStat type="freq">
          49
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          10
        </catValu>
        <labl>
          Maputo provincia
        </labl>
        <catStat type="freq">
          39
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          11
        </catValu>
        <labl>
          Maputo Cidade
        </labl>
        <catStat type="freq">
          14
        </catStat>
      </catgry>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V19" name="A1_URB_RUR" files="F1" dcml="0" intrvl="discrete">
      <location width="10"/>
      <labl>
        Area de residencia
      </labl>
      <valrng>
        <range min="1" max="2"/>
      </valrng>
      <sumStat type="vald">
        675
      </sumStat>
      <sumStat type="invd">
        0
      </sumStat>
      <catgry>
        <catValu>
          1
        </catValu>
        <labl>
          Urbana
        </labl>
        <catStat type="freq">
          181
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          2
        </catValu>
        <labl>
          Rural
        </labl>
        <catStat type="freq">
          494
        </catStat>
      </catgry>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V20" name="Agroecolog_first_1" files="F1" intrvl="discrete">
      <location width="3"/>
      <labl/>
      <sumStat type="vald">
        675
      </sumStat>
      <sumStat type="invd">
        0
      </sumStat>
      <catgry>
        <catValu>
          NA
        </catValu>
        <catStat type="freq">
          14
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          R1
        </catValu>
        <catStat type="freq">
          35
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          R10
        </catValu>
        <catStat type="freq">
          74
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          R2
        </catValu>
        <catStat type="freq">
          80
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          R3
        </catValu>
        <catStat type="freq">
          26
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          R4
        </catValu>
        <catStat type="freq">
          46
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          R5
        </catValu>
        <catStat type="freq">
          75
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          R6
        </catValu>
        <catStat type="freq">
          57
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          R7
        </catValu>
        <catStat type="freq">
          170
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          R8
        </catValu>
        <catStat type="freq">
          94
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          R9
        </catValu>
        <catStat type="freq">
          4
        </catStat>
      </catgry>
      <varFormat type="character" schema="other"/>
    </var>
    <var ID="V21" name="Total_Cows" files="F1" dcml="0" intrvl="contin">
      <location width="10"/>
      <labl>
        Total numeros de bois na área de enumeração
      </labl>
      <valrng>
        <range min="0" max="31670"/>
      </valrng>
      <sumStat type="vald">
        675
      </sumStat>
      <sumStat type="invd">
        0
      </sumStat>
      <sumStat type="min">
        0
      </sumStat>
      <sumStat type="max">
        31670
      </sumStat>
      <sumStat type="mean">
        887.009
      </sumStat>
      <sumStat type="stdev">
        3890.962
      </sumStat>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V22" name="cattle_stratum" files="F1" dcml="0" intrvl="discrete">
      <location width="10"/>
      <labl>
        cattle_ stratum
      </labl>
      <valrng>
        <range min="0" max="1"/>
      </valrng>
      <sumStat type="vald">
        675
      </sumStat>
      <sumStat type="invd">
        0
      </sumStat>
      <catgry>
        <catValu>
          0
        </catValu>
        <catStat type="freq">
          635
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          1
        </catValu>
        <catStat type="freq">
          40
        </catStat>
      </catgry>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V23" name="Samplesize" files="F1" dcml="0" intrvl="contin">
      <location width="10"/>
      <labl>
        sample size
      </labl>
      <valrng>
        <range min="1" max="46"/>
      </valrng>
      <sumStat type="vald">
        675
      </sumStat>
      <sumStat type="invd">
        0
      </sumStat>
      <sumStat type="min">
        1
      </sumStat>
      <sumStat type="max">
        46
      </sumStat>
      <sumStat type="mean">
        19.714
      </sumStat>
      <sumStat type="stdev">
        12.975
      </sumStat>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V24" name="InclusionProbability_1_" files="F1" dcml="0" intrvl="contin">
      <location width="10"/>
      <labl>
        Inclusion (Selection) Probability for Stage 1
      </labl>
      <valrng>
        <range UNITS="REAL" min="0.000700915761679934" max="1"/>
      </valrng>
      <sumStat type="vald">
        675
      </sumStat>
      <sumStat type="invd">
        0
      </sumStat>
      <sumStat type="min">
        0.000701
      </sumStat>
      <sumStat type="max">
        1
      </sumStat>
      <sumStat type="mean">
        0.0204
      </sumStat>
      <sumStat type="stdev">
        0.056
      </sumStat>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V25" name="SampleWeightCumulative_1_" files="F1" dcml="0" intrvl="contin">
      <location width="10"/>
      <labl>
        Cumulative Sampling Weight for Stage 1
      </labl>
      <valrng>
        <range UNITS="REAL" min="1" max="1426.7049689441"/>
      </valrng>
      <sumStat type="vald">
        675
      </sumStat>
      <sumStat type="invd">
        0
      </sumStat>
      <sumStat type="min">
        1
      </sumStat>
      <sumStat type="max">
        1426.705
      </sumStat>
      <sumStat type="mean">
        99.35
      </sumStat>
      <sumStat type="stdev">
        78.153
      </sumStat>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V26" name="PopulationSize_1_" files="F1" dcml="0" intrvl="contin">
      <location width="10"/>
      <labl>
        Population Size for Stage 1
      </labl>
      <valrng>
        <range min="1" max="5129"/>
      </valrng>
      <sumStat type="vald">
        675
      </sumStat>
      <sumStat type="invd">
        0
      </sumStat>
      <sumStat type="min">
        1
      </sumStat>
      <sumStat type="max">
        5129
      </sumStat>
      <sumStat type="mean">
        2024.453
      </sumStat>
      <sumStat type="stdev">
        1459.834
      </sumStat>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V27" name="SampleSize_1_" files="F1" dcml="0" intrvl="contin">
      <location width="10"/>
      <labl>
        Sample Size for Stage 1
      </labl>
      <valrng>
        <range min="1" max="46"/>
      </valrng>
      <sumStat type="vald">
        675
      </sumStat>
      <sumStat type="invd">
        0
      </sumStat>
      <sumStat type="min">
        1
      </sumStat>
      <sumStat type="max">
        46
      </sumStat>
      <sumStat type="mean">
        19.714
      </sumStat>
      <sumStat type="stdev">
        12.975
      </sumStat>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V28" name="SamplingRate_1_" files="F1" dcml="0" intrvl="contin">
      <location width="10"/>
      <labl>
        Sampling Rate for Stage 1
      </labl>
      <valrng>
        <range UNITS="REAL" min="0.00575685743311886" max="1"/>
      </valrng>
      <sumStat type="vald">
        675
      </sumStat>
      <sumStat type="invd">
        0
      </sumStat>
      <sumStat type="min">
        0.00576
      </sumStat>
      <sumStat type="max">
        1
      </sumStat>
      <sumStat type="mean">
        0.0182
      </sumStat>
      <sumStat type="stdev">
        0.0529
      </sumStat>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V29" name="SampleWeight_1_" files="F1" dcml="0" intrvl="contin">
      <location width="10"/>
      <labl>
        Sampling Weight for Stage 1
      </labl>
      <valrng>
        <range UNITS="REAL" min="1" max="1426.7049689441"/>
      </valrng>
      <sumStat type="vald">
        675
      </sumStat>
      <sumStat type="invd">
        0
      </sumStat>
      <sumStat type="min">
        1
      </sumStat>
      <sumStat type="max">
        1426.705
      </sumStat>
      <sumStat type="mean">
        99.35
      </sumStat>
      <sumStat type="stdev">
        78.153
      </sumStat>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V30" name="SampleWeight_Final_" files="F1" dcml="0" intrvl="contin">
      <location width="10"/>
      <labl>
        Final Sampling Weight
      </labl>
      <valrng>
        <range UNITS="REAL" min="1" max="1426.7049689441"/>
      </valrng>
      <sumStat type="vald">
        675
      </sumStat>
      <sumStat type="invd">
        0
      </sumStat>
      <sumStat type="min">
        1
      </sumStat>
      <sumStat type="max">
        1426.705
      </sumStat>
      <sumStat type="mean">
        99.35
      </sumStat>
      <sumStat type="stdev">
        78.153
      </sumStat>
      <varFormat type="numeric" schema="other"/>
    </var>
  </dataDscr>
</codeBook>