IPUMS-I: descr: PERWT

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PERWT

Person weight

Return to Technical Person variables list

PERWT is an 8-digit numeric variable with 2 implied decimal places. See the variable description.


      class Perwt : public Editor {

public:
  Perwt(VarPointer varInfo) : Editor(varInfo) {}
  void edit() {

    int64_t a = getRecoded();
    switch (dataSet) {
    case dataset_id::br1960a:
      a = 50000;
      break;
    case dataset_id::br1970a:
      a = BR1970A_0432() * 10000;
      break;
    case dataset_id::br1980a:
      a = BR1980A_0400() * 10000;
      break;
    case dataset_id::br1991a: {
      long long l = BR1991A_0495();
      long long w = l;
      l = l / 10000;
      if (w % 10000 > 5000)
        l++;
      a = l;
    } break;
    case dataset_id::br2000a: {
      long long l = BR2000A_0556();
      long long w = l;
      l = l / 10000;
      if (w % 10000 > 5000)
        l++;
      a = l;
    } break;
    case dataset_id::ie1901a:
    case dataset_id::ie1911a:
      a = 10000;
      break;
    case dataset_id::pr1970a:
    case dataset_id::cn1982a:
    case dataset_id::cn2000a:
    case dataset_id::hn1961a:
      a = 1000000;
      break;
    case dataset_id::my1980a:
      a = 600000;
      break;
    case dataset_id::ar1970a:
    case dataset_id::co1964a:
    case dataset_id::ca1981a:
    case dataset_id::my1970a:
    case dataset_id::my1991a:
    case dataset_id::my2000a:
      a = 500000;
      break;
    case dataset_id::ht1982a:
      a = 400000;
      break;
    case dataset_id::am2001a:
    case dataset_id::am2011a:
    case dataset_id::ar2001a:
    case dataset_id::ar2010a:
    case dataset_id::at1971a:
    case dataset_id::at1981a:
    case dataset_id::at1991a:
    case dataset_id::at2001a:
    case dataset_id::at2011a:
    case dataset_id::bd1991a:
    case dataset_id::bd2001a:
    case dataset_id::bf1985a:
    case dataset_id::bf1996a:
    case dataset_id::bf2006a:
    case dataset_id::bj1979a:
    case dataset_id::bj1992a:
    case dataset_id::bj2002a:
    case dataset_id::bj2013a:
    case dataset_id::bo1976a:
    case dataset_id::bo1992a:
    case dataset_id::bo2001a:
    case dataset_id::bw1981a:
    case dataset_id::bw1991a:
    case dataset_id::bw2001a:
    case dataset_id::bw2011a:
    case dataset_id::by1999a:
    case dataset_id::by2009a:
    case dataset_id::cl1970a:
    case dataset_id::cl1982a:
    case dataset_id::cl1992a:
    case dataset_id::cl2002a:
    case dataset_id::cl2017a:
    case dataset_id::cm1976a:
    case dataset_id::cm1987a:
    case dataset_id::cm2005a:
    case dataset_id::co1973a:
    case dataset_id::co1993a:
    case dataset_id::cr1973a:
    case dataset_id::cr1984a:
    case dataset_id::cr2000a:
    case dataset_id::cr2011a:
    case dataset_id::cu2002a:
    case dataset_id::cu2012a:
    case dataset_id::do2002a:
    case dataset_id::do2010a:
    case dataset_id::ec1982a:
    case dataset_id::ec1990a:
    case dataset_id::ec2001a:
    case dataset_id::ec2010a:
    case dataset_id::eg2006a:
    case dataset_id::et1984a:
    case dataset_id::fj1966a:
    case dataset_id::fj1976a:
    case dataset_id::fj1986a:
    case dataset_id::fj1996a:
    case dataset_id::fj2007a:
    case dataset_id::fj2014a:
    case dataset_id::gh1984a:
    case dataset_id::gh2000a:
    case dataset_id::gh2010a:
    case dataset_id::gn1983a:
    case dataset_id::gn1996a:
    case dataset_id::gn2014a:
    case dataset_id::gr1971a:
    case dataset_id::gr1981a:
    case dataset_id::gr1991a:
    case dataset_id::gr2001a:
    case dataset_id::gr2011a:
    case dataset_id::gt1994a:
    case dataset_id::gt2002a:
    case dataset_id::hn1974a:
    case dataset_id::hn1988a:
    case dataset_id::hn2001a:
    case dataset_id::ht1971a:
    case dataset_id::ht2003a:
    case dataset_id::id2000a:
    case dataset_id::id2010a:
    case dataset_id::ie1971a:
    case dataset_id::ie1979a:
    case dataset_id::ie1981a:
    case dataset_id::ie1986a:
    case dataset_id::ie1991a:
    case dataset_id::ie1996a:
    case dataset_id::ie2002a:
    case dataset_id::ie2006a:
    case dataset_id::ie2011a:
    case dataset_id::ie2016a:
    case dataset_id::il1972a:
    case dataset_id::il1983a:
    case dataset_id::il1995a:
    case dataset_id::iq1997a:
    case dataset_id::jm1982a:
    case dataset_id::jm1991a:
    case dataset_id::jo2004a:
    case dataset_id::ke2009a:
    case dataset_id::kg1999a:
    case dataset_id::kg2009a:
    case dataset_id::kh1998a:
    case dataset_id::kh2008a:
    case dataset_id::la2005a:
    case dataset_id::lc1980a:
    case dataset_id::lc1991a:
    case dataset_id::lr1974a:
    case dataset_id::lr2008a:
    case dataset_id::ls1996a:
    case dataset_id::ls2006a:
    case dataset_id::ma2014a:
    case dataset_id::ml1987a:
    case dataset_id::ml1998a:
    case dataset_id::ml2009a:
    case dataset_id::mn2000a:
    case dataset_id::mu1990a:
    case dataset_id::mu2000a:
    case dataset_id::mu2011a:
    case dataset_id::mw1987a:
    case dataset_id::mw1998a:
    case dataset_id::mw2008a:
    case dataset_id::mx1990a:
    case dataset_id::mx2005a:
    case dataset_id::mz1997a:
    case dataset_id::mz2007a:
    case dataset_id::ni1971a:
    case dataset_id::ni1995a:
    case dataset_id::ni2005a:
    case dataset_id::pa1970a:
    case dataset_id::pa1980a:
    case dataset_id::pa1990a:
    case dataset_id::pa2000a:
    case dataset_id::pa2010a:
    case dataset_id::pe1993a:
    case dataset_id::pe2007a:
    case dataset_id::pg1980a:
    case dataset_id::pg1990a:
    case dataset_id::pg2000a:
    case dataset_id::pg2011a:
    case dataset_id::ph1995a:
    case dataset_id::pk1998a:
    case dataset_id::pl1978a:
    case dataset_id::pl1988a:
    case dataset_id::pl2002a:
    case dataset_id::pl2011a:
    case dataset_id::py1972a:
    case dataset_id::py1982a:
    case dataset_id::py1992a:
    case dataset_id::ro1977a:
    case dataset_id::ro1992a:
    case dataset_id::ro2002a:
    case dataset_id::ro2011a:
    case dataset_id::rw1991a:
    case dataset_id::rw2002a:
    case dataset_id::rw2012a:
    case dataset_id::si2002a:
    case dataset_id::sl2004a:
    case dataset_id::sl2015a:
    case dataset_id::sn1988a:
    case dataset_id::sn2002a:
    case dataset_id::sr2004a:
    case dataset_id::sr2012a:
    case dataset_id::sv1992a:
    case dataset_id::sv2007a:
    case dataset_id::tg1960a:
    case dataset_id::tt1980a:
    case dataset_id::tt1990a:
    case dataset_id::tt2000a:
    case dataset_id::ua2001a:
    case dataset_id::ug2002a:
    case dataset_id::ug2014a:
    case dataset_id::uy1963a:
    case dataset_id::uy1975a:
    case dataset_id::uy1985a:
    case dataset_id::uy1996a:
    case dataset_id::uy2011a:
    case dataset_id::ve1981a:
    case dataset_id::ve2001a:
    case dataset_id::zm1990a:
    case dataset_id::zm2000a:
    case dataset_id::zm2010a:
      a = 100000;
      break;
    case dataset_id::tt2011a:
      a = 114000;
      break;
    case dataset_id::tt1970a:
      a = 134000;
      break;
    case dataset_id::co1985a:
      a = CO1985A_0428() * 10000;
      break;
    case dataset_id::gt1973a:
      a = 180000;
      break;
    case dataset_id::fr1962a:
    case dataset_id::fr1968a:
    case dataset_id::fr1975a:
    case dataset_id::fr1982a:
    case dataset_id::ke1989a:
    case dataset_id::ke1999a:
    case dataset_id::es2001a:
    case dataset_id::hu1970a:
    case dataset_id::hu1980a:
    case dataset_id::hu1990a:
    case dataset_id::hu2001a:
    case dataset_id::pt1981a:
    case dataset_id::pt1991a:
    case dataset_id::pt2001a:
    case dataset_id::fr1999a:
    case dataset_id::pr1980a:
    case dataset_id::ch1970a:
    case dataset_id::ch1980a:
    case dataset_id::ch1990a:
    case dataset_id::ch2000a:
    case dataset_id::it2001a:
    case dataset_id::ma1982a:
    case dataset_id::ma1994a:
    case dataset_id::ma2004a:
    case dataset_id::tr1985a:
    case dataset_id::tr1990a:
    case dataset_id::tr2000a:
    case dataset_id::bd2011a:
    case dataset_id::de1970a:
    case dataset_id::de1987a:
    case dataset_id::py1962a:
    case dataset_id::pt2011a:
    case dataset_id::hu2011a:
    case dataset_id::it2011a:
    case dataset_id::zw2012a:
    case dataset_id::gt1964a:
    case dataset_id::gt1981a:
    case dataset_id::ru2002a:
    case dataset_id::ru2010a:
    case dataset_id::fi2010a:
      a = 200000;
      break;
    case dataset_id::fr1990a:
      a = 240000;
      break;
    case dataset_id::mx1960a:
      a = 670000;
      break;
    case dataset_id::mx1970a:
    case dataset_id::ca1971a:
    case dataset_id::cn1990a:
    case dataset_id::uk1991a:
    case dataset_id::tg1970a:
      a = 1000000;
      break;
    case dataset_id::mx2000a:
      a = MX2000A_0006() * 10000;
      break;
    case dataset_id::cl1960a:
      a = 830000;
      break;
    case dataset_id::ec1974a:
      a = EC1974A_0426() * 140;
      break;
    case dataset_id::ph1990a:
      a = PH1990A_0438() * 10000;
      break;
    case dataset_id::ph2000a:
      a = PH2000A_0426() * 10000;
      break;
    case dataset_id::ug1991a:
      a = UG1991A_0428() * 10000;
      break;
    case dataset_id::ve1971a:
      a = VE1971A_0439() * 20000;
      break;
    case dataset_id::ve1990a:
      a = VE1990A_0433() * 30000;
      break;
    case dataset_id::za1996a:
      a = ZA1996A_0448() * 10;
      break;
    case dataset_id::za2001a:
      a = (long long)(ZA2001A_0484() * 0.01 + 0.55);
      break;
    case dataset_id::za2007a:
      a = (long long)(ZA2007A_0573() * 0.01 + 0.55);
      break;
    case dataset_id::vn1989a: {
      if (VN1989A_0402() == 1)
        a = VN1989A_0009(0);
      if (VN1989A_0402() == 2)
        a = VN1989A_0010(0);
    } break;
    case dataset_id::us1960a:
      a = US1960A_0406() * 10000;
      break;
    case dataset_id::us1970a:
      a = US1970A_0405() * 10000;
      break;
    case dataset_id::us1980a:
      a = US1980A_0405() * 10000;
      break;
    case dataset_id::us1990a:
      a = US1990A_0405() * 10000;
      break;
    case dataset_id::us2000a:
      a = US2000A_0405() * 10000;
      break;
    case dataset_id::us2005a:
      a = US2005A_0642() * 10000;
      break;
    case dataset_id::us2010a:
      a = US2010A_0402() * 10000;
      break;
    case dataset_id::us2015a:
      a = US2015A_0401() * 10000;
      break;
    case dataset_id::cr1963a:
      a = 170000;
      break;
    case dataset_id::ec1962a:
      a = 330000;
      break;
    case dataset_id::ps1997a: {
      long long l = PS1997A_0428() * 2;
      long long w = l;
      l = l / 100;
      if (w % 100 > 50)
        l++;
      a = l;
    } break;
    case dataset_id::ar1980a:
      a = AR1980A_0426() * 20000;
      break;
    case dataset_id::ar1991a:
      a = AR1991A_0433() * 10000;
      break;
    case dataset_id::de1971a:
    case dataset_id::de1981a:
      a = 40000;
      break;
    case dataset_id::ca1991a:
    case dataset_id::uk2001a:
      a = 333333;
      break;
    case dataset_id::mx1995a: {
      if (MX1995A_0019(0) == 7)
        a = MX1995A_0027(0) * 10000;
      if (MX1995A_0019(0) != 7)
        a = MX1995A_0400() * 10000;
    } break;
    case dataset_id::pa1960a:
      a = 200000;
      break;
    case dataset_id::ca2001a:
      a = (long long)(CA2001A_0525() * 0.01);
      break;
    case dataset_id::co2005a:
      a = (long long)(CO2005A_0538() * 1.0e-06);
      break;
    case dataset_id::eg1996a:
      a = (long long)(EG1996A_0440() * 0.1);
      break;
    case dataset_id::nl1960a:
      a = (long long)(NL1960A_0410() * 1.0e-08);
      break;
    case dataset_id::nl1971a:
      a = (long long)(NL1971A_0412() * 1.0e-08);
      break;
    case dataset_id::nl2001a:
      a = (long long)(NL2001A_0412() * 0.01);
      break;
    case dataset_id::in1983a:
      a = IN1983A_0069(0) * 10000;
      break;
    case dataset_id::in1987a:
      a = IN1987A_0077(0) * 10000;
      break;
    case dataset_id::in1993a:
      a = IN1993A_0090(0) * 100;
      break;
    case dataset_id::in1999a:
      a = (long long)(IN1999A_0034(0) / 8 * 100);
      break;
    case dataset_id::in2004a: {
      if (IN2004A_0051(0) == IN2004A_0052(0))
        a = IN2004A_0053(0);
      if (IN2004A_0051(0) != IN2004A_0052(0))
        a = IN2004A_0053(0) / 2;
      a = a * 100;
    } break;
    case dataset_id::in2009a: {
      if (IN2009A_0052(0) == IN2009A_0053(0))
        a = IN2009A_0054(0);
      if (IN2009A_0052(0) != IN2009A_0053(0))
        a = IN2009A_0054(0) / 2;
      a = a * 100;
    } break;
    case dataset_id::mn1989a:
      a = MN1989A_0421() * 10;
      break;
    case dataset_id::pk1973a:
      a = PK1973A_0428() * 10000;
      break;
    case dataset_id::pk1981a:
      a = PK1981A_0409() * 38000;
      break;
    case dataset_id::pr1990a:
      a = PR1990A_0402() * 10000;
      break;
    case dataset_id::pr2000a:
      a = PR2000A_0402() * 10000;
      break;
    case dataset_id::pr2005a:
      a = PR2005A_0402() * 10000;
      break;
    case dataset_id::tz1988a:
      a = (long long)(TZ1988A_0426() * 2.0e-07);
      break;
    case dataset_id::tz2002a:
      a = TZ2002A_0441() * 10;
      break;
    case dataset_id::th1970a:
      a = (long long)(TH1970A_0446() * 0.0001);
      break;
    case dataset_id::th1990a:
      a = TH1990A_0435() * 100;
      break;
    case dataset_id::fr2006a:
      a = (long long)(FR2006A_0427() * 1.0e-08);
      break;
    case dataset_id::fr2011a:
      a = (long long)(FR2011A_0426() * 1.0e-10);
      break;
    case dataset_id::ir2006a:
      a = (long long)(IR2006A_0451() * 5.0e-09);
      break;
    case dataset_id::jm2001a:
      a = JM2001A_0523() * 100;
      break;
    case dataset_id::ps2007a:
      a = (long long)(PS2007A_0430() * 2.0e-07);
      break;
    case dataset_id::vn2009a:
      a = (long long)(VN2009A_0441() * 1.0e-08);
      break;
    case dataset_id::sd2008a:
      a = SD2008A_0555();
      break;
    case dataset_id::id1971a:
      a = ID1971A_0418() * 10000;
      break;
    case dataset_id::id1976a:
      a = ID1976A_0498() * 10000;
      break;
    case dataset_id::id1980a:
      a = ID1980A_0454() * 10000;
      break;
    case dataset_id::id1985a:
      a = ID1985A_0452() * 10000;
      break;
    case dataset_id::id1990a:
      a = ID1990A_0463() * 10000;
      break;
    case dataset_id::id1995a:
      a = ID1995A_0056(0) * 10000;
      break;
    case dataset_id::id2005a:
      a = ID2005A_0502() * 10000;
      break;
    case dataset_id::mx2010a:
      a = MX2010A_0481() * 10000;
      break;
    case dataset_id::uy2006a:
      a = UY2006A_0613() * 10000;
      break;
    case dataset_id::ke1979a:
      a = (long long)(KE1979A_0422() * 0.1);
      break;
    case dataset_id::br2010a:
      a = (long long)(BR2010A_0027(0) * 1.00e-06);
      break;
    case dataset_id::ke1969a:
      a = KE1969A_0429() * 100;
      break;
    case dataset_id::do1981a:
      a = DO1981A_0021(0) * 10000;
      break;
    case dataset_id::do1960a:
      a = DO1960A_0026(0) * 100;
      break;
    case dataset_id::do1970a:
      a = DO1970A_0427() * 10000;
      break;
    case dataset_id::ng2006a:
      a = NG2006A_0512() * 100;
      break;
    case dataset_id::ng2007a:
      a = NG2007A_0471() * 100;
      break;
    case dataset_id::ng2008a:
      a = NG2008A_0479();
      break;
    case dataset_id::ng2009a:
      a = NG2009A_0507() * 100;
      break;
    case dataset_id::ng2010a:
      a = NG2010A_0529() * 10000;
      break;
    case dataset_id::et1994a:
      a = ET1994A_0043(0) * 10000;
      break;
    case dataset_id::et2007a:
      a = (long long)(ET2007A_0431() * 0.1);
      break;
    case dataset_id::py2002a:
      a = PY2002A_0459();
      break;
    case dataset_id::pr2010a:
      a = PR2010A_0724() * 100;
      break;
    case dataset_id::za2011a:
      a = (long long)(ZA2011A_0485() * 1.0e-05);
      break;
    case dataset_id::es2011a:
      a = (long long)(ES2011A_0025(0) * 1.0e-06);
      break;
    case dataset_id::ir2011a:
      a = IR2011A_0457();
      break;
    case dataset_id::mx2015a:
      a = MX2015A_0030(0) * 10000;
      break;
    case dataset_id::ca2011a:
      a = (long long)(CA2011A_0442() * 1.0e-09);
      break;
    case dataset_id::tz2012a:
      a = TZ2012A_0468() * .0275;
      break;
    case dataset_id::eg1986a:
      a = (long long)(EG1986A_0071(0) * 1.0e-05);
      break;
    case dataset_id::nl2011a:
      a = (long long)(NL2011A_0412() * 1.0e-06);
      break;
    case dataset_id::ph2010a:
      a = (long long)(PH2010A_0440() * 2.0e-05);
      break;
    case dataset_id::kh2004a:
      a = (long long)(KH2004A_0027(0) * 1.00e-06);
      break;
    case dataset_id::kh2013a:
      a = (long long)(KH2013A_0454() * 0.1);
      break;
    case dataset_id::np2001a:
      a = NP2001A_0050(0);
      break;
    case dataset_id::np2011a:
      a = 81000;
      break;
    case dataset_id::tg2010a:
      a = TG2010A_0103(0) * 10;
      break;
    case dataset_id::es2005h:
    case dataset_id::es2005i:
    case dataset_id::es2005j:
    case dataset_id::es2005k:
    case dataset_id::es2006h:
    case dataset_id::es2006i:
    case dataset_id::es2006j:
    case dataset_id::es2006k:
    case dataset_id::es2007h:
    case dataset_id::es2007i:
    case dataset_id::es2007j:
    case dataset_id::es2007k:
    case dataset_id::es2008h:
    case dataset_id::es2008i:
    case dataset_id::es2008j:
    case dataset_id::es2008k:
    case dataset_id::es2009h:
    case dataset_id::es2009i:
    case dataset_id::es2009j:
    case dataset_id::es2009k:
    case dataset_id::es2010h:
    case dataset_id::es2010i:
    case dataset_id::es2010j:
    case dataset_id::es2010k:
    case dataset_id::es2011h:
    case dataset_id::es2011i:
    case dataset_id::es2011j:
    case dataset_id::es2011k:
    case dataset_id::es2012h:
    case dataset_id::es2012i:
    case dataset_id::es2012j:
    case dataset_id::es2012k:
    case dataset_id::es2013h:
    case dataset_id::es2013i:
    case dataset_id::es2013j:
    case dataset_id::es2013k:
    case dataset_id::es2014h:
    case dataset_id::es2014i:
    case dataset_id::es2014j:
    case dataset_id::es2014k:
    case dataset_id::es2015h:
    case dataset_id::es2015i:
    case dataset_id::es2015j:
    case dataset_id::es2015k:
    case dataset_id::es2016h:
    case dataset_id::es2016i:
    case dataset_id::es2016j:
    case dataset_id::es2016k:
    case dataset_id::es2017h:
    case dataset_id::es2017i:
    case dataset_id::es2017j:
    case dataset_id::es2017k:
    case dataset_id::es2018h:
    case dataset_id::es2018i:
    case dataset_id::es2018j:
    case dataset_id::es2018k:
    case dataset_id::es2019h:
    case dataset_id::es2019i:
    case dataset_id::es2019j:
    case dataset_id::es2019k:
    case dataset_id::es2020h:
    case dataset_id::es2020i:
    case dataset_id::es2020j:
    case dataset_id::es2020k: {
      long factorw = valueFromFirstAvailable(
          {ES2005H_0488_ref, ES2005I_0488_ref, ES2005J_0488_ref,
           ES2005K_0488_ref, ES2006H_0488_ref, ES2006I_0488_ref,
           ES2006J_0488_ref, ES2006K_0488_ref, ES2007H_0488_ref,
           ES2007I_0488_ref, ES2007J_0488_ref, ES2007K_0488_ref,
           ES2008H_0488_ref, ES2008I_0488_ref, ES2008J_0488_ref,
           ES2008K_0488_ref, ES2009H_0488_ref, ES2009I_0488_ref,
           ES2009J_0488_ref, ES2009K_0488_ref, ES2010H_0488_ref,
           ES2010I_0488_ref, ES2010J_0488_ref, ES2010K_0488_ref,
           ES2011H_0488_ref, ES2011I_0488_ref, ES2011J_0488_ref,
           ES2011K_0488_ref, ES2012H_0488_ref, ES2012I_0488_ref,
           ES2012J_0488_ref, ES2012K_0488_ref, ES2013H_0488_ref,
           ES2013I_0488_ref, ES2013J_0488_ref, ES2013K_0488_ref,
           ES2014H_0488_ref, ES2014I_0488_ref, ES2014J_0488_ref,
           ES2014K_0488_ref, ES2015H_0488_ref, ES2015I_0488_ref,
           ES2015J_0488_ref, ES2015K_0488_ref, ES2016H_0488_ref,
           ES2016I_0488_ref, ES2016J_0488_ref, ES2016K_0488_ref,
           ES2017H_0488_ref, ES2017I_0488_ref, ES2017J_0488_ref,
           ES2017K_0488_ref, ES2018H_0488_ref, ES2018I_0488_ref,
           ES2018J_0488_ref, ES2018K_0488_ref, ES2019H_0488_ref,
           ES2019I_0488_ref, ES2019J_0488_ref, ES2019K_0488_ref,
           ES2020H_0488_ref, ES2020I_0488_ref, ES2020J_0488_ref,
           ES2020K_0488_ref});
      { a = factorw * 100; }
    } break;
    case dataset_id::it2011h:
    case dataset_id::it2012h:
    case dataset_id::it2013h: {
      long factorw = valueFromFirstAvailable(
          {IT2011H_0739_ref, IT2012H_0739_ref, IT2013H_0739_ref});
      { a = factorw * 1000; }
    } break;
    case dataset_id::it2014h:
    case dataset_id::it2015h:
    case dataset_id::it2016h:
    case dataset_id::it2017h:
    case dataset_id::it2018h:
    case dataset_id::it2019h:
    case dataset_id::it2020h: {
      long factorw = valueFromFirstAvailable(
          {IT2014H_0766_ref, IT2015H_0766_ref, IT2016H_0766_ref,
           IT2017H_0766_ref, IT2018H_0766_ref, IT2019H_0766_ref,
           IT2020H_0766_ref});
      { a = factorw * 1000; }
    } break;
    case dataset_id::bo2012a:
      a = (long long)(BO2012A_0070(0) * 0.00001);
      break;
    case dataset_id::il2008a:
      a = (long long)(IL2008A_0470() * 10);
      break;
    case dataset_id::mm2014a:
      a = (long long)(MM2014A_0441());
      break;
    case dataset_id::ps2017a:
      a = (long long)(PS2017A_0433() * 0.00000002);
      break;
    case dataset_id::sn2013a:
      a = (long long)(SN2013A_0097(0) * 0.0001);
      break;
    case dataset_id::za2016a:
      a = (long long)(ZA2016A_0490() * 0.00001);
      break;
    case dataset_id::eg1848a:
      a = (long long)(EG1848A_0445() * 0.1);
      break;
    case dataset_id::eg1868a:
      a = (long long)(EG1868A_0445() * 0.1);
      break;
    case dataset_id::sk1991a:
      a = (long long)(SK1991A_0415() * 0.00001);
      break;
    case dataset_id::sk2001a:
      a = (long long)(SK2001A_0417() * 0.00001);
      break;
    case dataset_id::sk2011a:
      a = (long long)(SK2011A_0417() * 0.00001);
      break;
    case dataset_id::mx2005h:
    case dataset_id::mx2005i:
    case dataset_id::mx2005j:
    case dataset_id::mx2005k:
    case dataset_id::mx2006h:
    case dataset_id::mx2006i:
    case dataset_id::mx2006j:
    case dataset_id::mx2006k:
    case dataset_id::mx2007h:
    case dataset_id::mx2007i:
    case dataset_id::mx2007j:
    case dataset_id::mx2007k:
    case dataset_id::mx2008h:
    case dataset_id::mx2008i:
    case dataset_id::mx2008j:
    case dataset_id::mx2008k:
    case dataset_id::mx2009h:
    case dataset_id::mx2009i:
    case dataset_id::mx2009j:
    case dataset_id::mx2009k:
    case dataset_id::mx2010h:
    case dataset_id::mx2010i:
    case dataset_id::mx2010j:
    case dataset_id::mx2010k:
    case dataset_id::mx2011h:
    case dataset_id::mx2011i:
    case dataset_id::mx2011j:
    case dataset_id::mx2011k:
    case dataset_id::mx2012h:
    case dataset_id::mx2012i:
    case dataset_id::mx2012j:
    case dataset_id::mx2012k:
    case dataset_id::mx2013h:
    case dataset_id::mx2013i:
    case dataset_id::mx2013j:
    case dataset_id::mx2013k:
    case dataset_id::mx2014h:
    case dataset_id::mx2014i:
    case dataset_id::mx2014j:
    case dataset_id::mx2014k:
    case dataset_id::mx2015h:
    case dataset_id::mx2015i:
    case dataset_id::mx2015j:
    case dataset_id::mx2015k:
    case dataset_id::mx2016h:
    case dataset_id::mx2016i:
    case dataset_id::mx2016j:
    case dataset_id::mx2016k:
    case dataset_id::mx2017h:
    case dataset_id::mx2017i:
    case dataset_id::mx2017j:
    case dataset_id::mx2017k:
    case dataset_id::mx2018h:
    case dataset_id::mx2018i:
    case dataset_id::mx2018j:
    case dataset_id::mx2018k:
    case dataset_id::mx2019h:
    case dataset_id::mx2019i:
    case dataset_id::mx2019j:
    case dataset_id::mx2019k:
    case dataset_id::mx2020h:
    case dataset_id::mx2020j: {
      long factmx = valueFromFirstAvailable(
          {MX2005H_0040_ref, MX2005I_0040_ref, MX2005J_0040_ref,
           MX2005K_0040_ref, MX2006H_0040_ref, MX2006I_0040_ref,
           MX2006J_0040_ref, MX2006K_0040_ref, MX2007H_0040_ref,
           MX2007I_0040_ref, MX2007J_0040_ref, MX2007K_0040_ref,
           MX2008H_0040_ref, MX2008I_0040_ref, MX2008J_0040_ref,
           MX2008K_0040_ref, MX2009H_0040_ref, MX2009I_0040_ref,
           MX2009J_0040_ref, MX2009K_0040_ref, MX2010H_0040_ref,
           MX2010I_0040_ref, MX2010J_0040_ref, MX2010K_0040_ref,
           MX2011H_0040_ref, MX2011I_0040_ref, MX2011J_0040_ref,
           MX2011K_0040_ref, MX2012H_0040_ref, MX2012I_0040_ref,
           MX2012J_0040_ref, MX2012K_0040_ref, MX2013H_0040_ref,
           MX2013I_0040_ref, MX2013J_0040_ref, MX2013K_0040_ref,
           MX2014H_0040_ref, MX2014I_0040_ref, MX2014J_0040_ref,
           MX2014K_0040_ref, MX2015H_0040_ref, MX2015I_0040_ref,
           MX2015J_0040_ref, MX2015K_0040_ref, MX2016H_0040_ref,
           MX2016I_0040_ref, MX2016J_0040_ref, MX2016K_0040_ref,
           MX2017H_0040_ref, MX2017I_0040_ref, MX2017J_0040_ref,
           MX2017K_0040_ref, MX2018H_0040_ref, MX2018I_0040_ref,
           MX2018J_0040_ref, MX2018K_0040_ref, MX2019H_0040_ref,
           MX2019I_0040_ref, MX2019J_0040_ref, MX2019K_0040_ref,
           MX2020H_0040_ref, MX2020J_0043_ref});
      { a = factmx * 10000; }
    } break;
    case dataset_id::ca1852a:
      a = a * 100;
      break;
    case dataset_id::ca1871a:
      a = (int)((CA1871A_0012(0) / 100.0) + 0.5);
      a = a * 100;
      break;
    case dataset_id::ca1881a:
      a = a * 100;
      break;
    case dataset_id::ca1891a:
      a = a * 100;
      break;
    case dataset_id::ca1901a:
      a = a * 100;
      break;
    case dataset_id::ca1911a:
      a = a * 100;
      break;
    case dataset_id::de1819a:
      a = a * 100;
      break;
    case dataset_id::dk1787a:
      a = a * 100;
      break;
    case dataset_id::dk1801a:
      a = a * 100;
      break;
    case dataset_id::is1703a:
      a = a * 100;
      break;
    case dataset_id::is1729a:
      a = a * 100;
      break;
    case dataset_id::is1801a:
      a = a * 100;
      break;
    case dataset_id::is1901a:
      a = a * 100;
      break;
    case dataset_id::is1910a:
      a = a * 100;
      break;
    case dataset_id::no1801a:
      a = a * 100;
      break;
    case dataset_id::no1865a:
      a = a * 100;
      break;
    case dataset_id::no1875a:
      a = a * 100;
      break;
    case dataset_id::no1900a:
      a = a * 100;
      break;
    case dataset_id::no1910a:
      a = a * 100;
      break;
    case dataset_id::se1880a:
      a = a * 100;
      break;
    case dataset_id::se1890a:
      a = a * 100;
      break;
    case dataset_id::se1900a:
      a = a * 100;
      break;
    case dataset_id::se1910a:
      a = a * 100;
      break;
    case dataset_id::uk1851a:
      a = a * 100;
      break;
    case dataset_id::uk1851b:
      a = a * 100;
      break;
    case dataset_id::uk1851c:
      a = a * 100;
      break;
    case dataset_id::uk1861a:
      a = a * 100;
      break;
    case dataset_id::uk1861b:
      a = a * 100;
      break;
    case dataset_id::uk1871b:
      a = a * 100;
      break;
    case dataset_id::uk1881a:
      a = a * 100;
      break;
    case dataset_id::uk1881b:
      a = a * 100;
      break;
    case dataset_id::uk1891a:
      a = a * 100;
      break;
    case dataset_id::uk1891b:
      a = a * 100;
      break;
    case dataset_id::uk1901a:
      a = a * 100;
      break;
    case dataset_id::uk1901b:
      a = a * 100;
      break;
    case dataset_id::uk1911a:
      a = a * 100;
      break;
    case dataset_id::us1850a:
      a = a * 100;
      break;
    case dataset_id::us1850b:
      a = a * 100;
      break;
    case dataset_id::us1860a:
      a = a * 100;
      break;
    case dataset_id::us1870a:
      a = a * 100;
      break;
    case dataset_id::us1880a:
      a = a * 100;
      break;
    case dataset_id::us1880b:
      a = a * 100;
      break;
    case dataset_id::us1900a:
      a = a * 100;
      break;
    case dataset_id::us1910a:
      a = a * 100;
      break;
    }
    if (!(dataSet == dataset_id::ca1852a || dataSet == dataset_id::ca1871a ||
          dataSet == dataset_id::ca1881a || dataSet == dataset_id::ca1891a ||
          dataSet == dataset_id::ca1901a || dataSet == dataset_id::ca1911a ||
          dataSet == dataset_id::de1819a || dataSet == dataset_id::dk1787a ||
          dataSet == dataset_id::dk1801a || dataSet == dataset_id::is1703a ||
          dataSet == dataset_id::is1729a || dataSet == dataset_id::is1801a ||
          dataSet == dataset_id::is1901a || dataSet == dataset_id::is1910a ||
          dataSet == dataset_id::no1801a || dataSet == dataset_id::no1865a ||
          dataSet == dataset_id::no1875a || dataSet == dataset_id::no1900a ||
          dataSet == dataset_id::no1910a || dataSet == dataset_id::se1880a ||
          dataSet == dataset_id::se1890a || dataSet == dataset_id::se1900a ||
          dataSet == dataset_id::se1910a || dataSet == dataset_id::uk1851a ||
          dataSet == dataset_id::uk1851b || dataSet == dataset_id::uk1851c ||
          dataSet == dataset_id::uk1861a || dataSet == dataset_id::uk1861b ||
          dataSet == dataset_id::uk1871b || dataSet == dataset_id::uk1881a ||
          dataSet == dataset_id::uk1881b || dataSet == dataset_id::uk1891a ||
          dataSet == dataset_id::uk1891b || dataSet == dataset_id::uk1901a ||
          dataSet == dataset_id::uk1901b || dataSet == dataset_id::uk1911a ||
          dataSet == dataset_id::us1850a || dataSet == dataset_id::us1850b ||
          dataSet == dataset_id::us1860a || dataSet == dataset_id::us1870a ||
          dataSet == dataset_id::us1880a || dataSet == dataset_id::us1880b ||
          dataSet == dataset_id::us1900a || dataSet == dataset_id::us1910a)) {
      a = (long long)(a * 0.01 + 0.55);
    }

    setData(a);
  }
};

Description

PERWT indicates the number of persons in the actual population represented by the person in the sample.

For the samples that are truly weighted (see the comparability discussion), PERWT must be used to yield accurate statistics for the population.

NOTE: PERWT has 2 implied decimal places. That is, the last two digits of the eight-digit variable are decimal digits, but there is no actual decimal in the data.

Comparability — Index

GENERAL
Argentina
Armenia
Austria
Belarus
Bolivia
Botswana
Brazil
Cambodia
Canada
Chile
China
Colombia
Costa Rica
Cuba
Côte d'Ivoire
Dominican Republic
Ecuador
Egypt
El Salvador
Ethiopia
Fiji
Finland
France
Germany
Ghana
Greece
Guatemala
Guinea
Hungary

Indonesia
Iran
Ireland
Israel
Italy
Jamaica
Jordan
Kenya
Kyrgyzstan
Laos
Liberia
Malawi
Malaysia
Mali
Mauritius
Mexico
Mongolia
Morocco
Mozambique
Myanmar
Nepal
Netherlands
Nicaragua
Pakistan
Palestine
Panama
Paraguay
Peru
Philippines
Poland

Portugal
Puerto Rico
Romania
Russia
Rwanda
Saint Lucia
Senegal
Sierra Leone
Slovakia
Slovenia
South Africa
South Sudan
Spain
Sudan
Suriname
Switzerland
Tanzania
Thailand
Togo
Trinidad and Tobago
Turkey
Uganda
Ukraine
United Kingdom
United States
Uruguay
Venezuela
Vietnam
Zambia

Comparability — General

PERWT is available for all samples, but only some samples have weights that differ among persons (i.e., many of the samples are "flat" samples in which the use of weights is optional).

The samples for which weights must be used to generate representative statistics are:

Argentina 1980, 1990
Bolivia 2012
Brazil 1970, 1980, 1991, 2000, 2010
Cambodia 2004, 2013
Canada 2001, 2011
Colombia 1985, 2005
Dominican Republic 1970, 1981
Ecuador 1974
Egypt 1986, 1996
Ethiopia 1994, 2007
France 2006, 2011
India 1983, 1987, 1993, 1999, 2004, 2009
Indonesia 1971, 1976, 1980, 1985, 1990, 1995, 2005
Iran 2006, 2011
Israel 2008
Ivory Coast 1988
Jamaica 2001
Kenya 1969, 1979
Mexico 1995, 2000, 2010, 2015, 2020
Mongolia 1989
Mozambique 1997,
Myanmar 2014
Nepal 2001
Netherlands 1960, 1971, 2001
Nigeria 2006, 2007, 2008, 2009, 2010
Pakistan 1973, 1981
Palestine 1997, 2007, 2017
Panama 1980
Paraguay 2002
Philippines 1990, 2000
Puerto Rico 1990, 2000, 2005, 2010, 2015, 2020
Senegal 2013
Slovak Republic 1991, 2001, 2011
South Africa 1996, 2001, 2007, 2011, 2016
South Sudan 2008
Spain 1981, 1991, 2011
Sudan 2008
Switzerland 2011
Tanzania 1988, 2002, 2012
Thailand 1970, 1980, 1990, 2000
Togo 2010
Uganda 1991
United States 1990, 2000, 2005, 2010, 2015, 2020
Uruguay 2006
Venezuela 1971, 1990
Vietnam 1989, 1999, 2009, 2019

For the other samples, a weight was calculated from the sampling fraction. In those samples PERWT may not yield a precise count of the actual population to the extent that the theoretical sampling fraction was imperfect.

NOTE: The 1991 Argentina sample has an alternate weight variable that must be used to create accurate statistics for some variables. See the Argentina comparability discussion.

NOTE: Egypt 1986 is a recovered sample with missing geographic areas. Weights were constructed based on village and district population totals. Detailed notes about missing areas can be found in the geographic variables for Egypt.

NOTE: Ethiopia samples of 1984 and 2007 have special weight issues. In 1984, parts of the country are missing; weights do not correct for the missing geographic areas. The 2007 Ethiopia sample includes records from both the long and short forms, but only long form records are weighted (short form records are weighted zero). See the Ethiopia comparability section.

Some samples use fractional weights (to two decimal places), while most use only whole numbers (the first 6 digits of PERWT).

NOTE: Some samples from early years are missing geographic areas. These samples include Brazil 1960, Ethiopia 1984, Haiti 1982, Indonesia 1995, Indonesia 2005, Iraq 1997, Malaysia 1970 and 1980, Pakistan 1973, and Romania 1977.

NOTE: Mexico 1995, 2000, 2010, and Mongolia 1989 have clustered sample designs.

Comparability — Argentina [top]

The 1980 and 1991 samples are weighted; the 1970 and 2001 samples are flat.

Several important variables in 1991 require the use of an alternative weight: the unharmonized variable AR1991A_0434. That alternative weight -- not PERWT -- must be used to generate accurate statistics for industry, occupation, previous residence and birthplace. Those variables have missing responses for roughly half the population, and AR1991A_0434 corrects for this.

Comparability — Armenia [top]

The samples are flat: every record represents 10 persons in the population.

Comparability — Austria [top]

The samples are flat: every record represents 10 persons in the population.

Comparability — Belarus [top]

The samples are flat: every record represents ten persons in the population.

Comparability — Bolivia [top]

The 1976-2001 samples are flat: every record represents 10 persons in the population. The 2012 sample has differential weights by department (first geography level).

Comparability — Botswana [top]

The samples are flat: every record represents ten persons in the population.

Comparability — Brazil [top]

In 1960, the weight variable was missing from the microdata. The IPUMS weights are therefore theoretical weights based on the census design: 25 percent of households were to receive the long-form questionnaire from which the microdata sample is derived. All persons receive an equal weight corresponding to the overall sample density for the country in 1960.

In all other years, the weight varies among individuals and within households.

Comparability — Cambodia [top]

The Cambodia 1998, 2008, and 2019 samples are flat: every record represents 10 persons in the population. In 2004 and 2013, the weight varies across households.

Comparability — Canada [top]

The 2001 and 2011 samples are weighted; the others are flat. The 2001 and 2009 samples use fractional weights.

Comparability — Chile [top]

All samples are flat: every record represents 100 (in 1960) or 10 (in 1970-2017) persons in the population.

Comparability — China [top]

The samples are flat: every record represents 100 persons in the population.

Comparability — Colombia [top]

The 1985 and 2005 samples are weighted; the others are flat. The 2005 sample uses fractional weights.

Comparability — Costa Rica [top]

All samples are flat: every record represents an equal number of persons in the population (16.7 or 10, depending on the year).

Comparability — Cuba [top]

The 2002 and 2012 samples are flat: every record represents 10 persons in the population.

Comparability — Côte d'Ivoire [top]

The 1988 sample is weighted; weights are based on the probability of selection by department (first level of administrative geography). The 1998 sample is flat: every record represents 100 persons in the population.

Comparability — Dominican Republic [top]

Samples for 1960, 2002, and 2010 are flat: every record represents an equal number of persons in the population. Samples for 1970 and 1982 are differentially weighted.

Comparability — Ecuador [top]

The 1974 sample uses fractional weights. The other samples are flat: every person represents an equal number of persons in the population.

Comparability — Egypt [top]

The 1986 sample is weighted and uses fractions. This is a partially recovered data file; many geographic areas of the country are missing in part or in whole. Weights reflect village totals for villages where available. For details about missing geographic areas, see the geography variable documentation for Egypt.

The 1996 sample is weighted and uses fractions; the 2006 sample is flat.

Comparability — El Salvador [top]

The samples are flat: every record represents 10 persons in the population.

Comparability — Ethiopia [top]

The 1984 sample from Ethiopia is not representative of the country-level population. The file is a 1 in 10 sample of enumerated households. However, due to famine and conflict, parts of the country are missing from the sample. Detailed documentation about the nature of the undercount and affected geographic areas is available in a report.

Regions were sampled at different rates in 1994. Use of weights is especially important since Somali and Affar regions were sampled at lower densities.

The sample from 2007 includes records from both the long and short forms. When combined, the total set of records constitutes a flat 10% sample, but few variables are available. The weight applies to long form respondents only (short form respondents have a weight of zero). Use of the weight is essential for most analyses and yields point estimates that correspond closely to published reports for all variables.

Comparability — Fiji [top]

The samples are flat: every record represents 10 persons in the population.

Comparability — Finland [top]

The sample is flat: every record represents 20 persons in the population.

Comparability — France [top]

The 1962-1999 samples are flat: every record represents an equal number of persons in the population. The 2006 and 2010 samples are weighted and use fractions.

Comparability — Germany [top]

All samples are flat: every record represents an equal number of persons in the population.

Comparability — Ghana [top]

The samples are flat: every record represents 10 persons in the population.

Comparability — Greece [top]

All samples are flat: every record represents an equal number of persons in the population.

Comparability — Guatemala [top]

The samples are flat and the weights are defined according to the proportion of the population represented: every record represents 10 persons in 1994 and 2002, 18 persons in 1973, and 20 persons in 1964 and 1981.

Comparability — Guinea [top]

All samples are flat: every record represents 10 persons in the population.

Comparability — Hungary [top]

All samples are flat: every record represents an equal number of persons in the population.

Comparability — Indonesia [top]

The samples for 1971-1995 and 2005 are weighted. The 2000 and 2010 samples are flat: every record represents 20 persons in the population.

Comparability — Iran [top]

The samples are weighted and use fractions.

Comparability — Ireland [top]

All samples are flat: each record represents 10 persons in the population.

Comparability — Israel [top]

The 1972, 1983, and 1995 samples are flat: every record represents 10 persons in the population. The 2008 sample is weighted.

Comparability — Italy [top]

The sample is flat: every record represents 20 persons in the population.

Comparability — Jamaica [top]

The 1982 and 1991 samples are flat; the 2001 sample is weighted.

Comparability — Jordan [top]

The sample is flat: every record represents 10 persons in the population.

Comparability — Kenya [top]

The 1969 and 1979 samples are weighted. The later samples are flat: every record represents 10 or 20 persons in the population.

Comparability — Kyrgyzstan [top]

The sample is flat: every record represents 10 persons in the population.

Comparability — Laos [top]

The 1995, 2005, and 2015 samples are flat: every record represents 10 persons in the population.

Comparability — Liberia [top]

Both samples are flat: every record represents the same number of persons in the population.

Comparability — Malawi [top]

The samples are flat: every record represents 10 persons in the population.

Comparability — Malaysia [top]

The samples are flat: every record represents 50 persons in the population.

Comparability — Mali [top]

All samples are flat: every record represents 10 persons in the population.

Comparability — Mauritius [top]

All samples are flat: every record represents 10 persons in the population.

Comparability — Mexico [top]

The 1995, 2000, 2010, 2015, and 2020 samples are weighted; the others are flat. The state of Chiapas lacked person weights in the 1995 sample; we substituted the dwelling weights for that state.

Comparability — Mongolia [top]

The 2000 sample is flat; the 1989 sample is weighted. The 1989 sample design was highly clustered. All provinces are covered, but within provinces entire districts were included in the sample, while other districts were not sampled at all. We have weighted the data at the province level using published data on age structure, but for some applications the data may not be entirely representative of the population.

Comparability — Morocco [top]

The 1982, 1994, and 2004 samples are flat: every record represents 20 persons in the population. The 2014 sample is also flat, but every record represents 10 persons in the population.

Comparability — Mozambique [top]

The 1997 sample is differentially weighted. The 2007 sample is flat: every record represents 10 persons in the population.

Comparability — Myanmar [top]

The 2014 sample is weighted.

Comparability — Nepal [top]

The 2011 sample is flat: every record represents 8.1 persons in the population.

The 2001 sample is differentially weighted. The sample weights were constructed by IPUMS in two steps. First, weights were calculated to match published household counts at the district and municipality levels. The person counts included the Central Bureau of Statistics estimates for Wards that could not be enumerated. Second, the initial weights were adjusted to match the marginal distribution of household size within each district, to account for the underrepresentation of large households in the public-use microdata relative to published figures.

Comparability — Netherlands [top]

The samples are weighted and use fractions.

Comparability — Nicaragua [top]

The samples are flat: every record represents 10 persons in the population.

Comparability — Pakistan [top]

The 1973 and 1981 samples are weighted; the 1998 sample is not. The 1973 weight is a crude inflator based on province and urban-rural status.

Comparability — Palestine [top]

The Palestine samples are weighted and use fractions.

Comparability — Panama [top]

The 1980 sample is weighted; the others are flat.

Comparability — Paraguay [top]

The 1962, 1972, 1982, and 1992 samples are flat: every record represents 10 or 20 persons in the population depending on the sample year. The 2002 sample is differentially weighted and uses fractions.

Comparability — Peru [top]

The 1993, 2007, and 2017 samples are flat: every record represents 10 persons in the population.

Comparability — Philippines [top]

The 1990 and 2000 samples are weighted; the 1995 sample is flat.

Comparability — Poland [top]

The samples are flat: every record represents approximately 10 persons in the population.

Comparability — Portugal [top]

All samples are flat: every record represents 20 persons in the population.

Comparability — Puerto Rico [top]

The 1990-2020 samples are weighted; the earlier samples are flat.

Comparability — Romania [top]

All samples are flat: every record represents 10 persons in the population.

Comparability — Russia [top]

The samples are flat: every record represents 20 persons in the population.

Comparability — Rwanda [top]

The samples are flat: every record represents 10 persons in the population.

Comparability — Saint Lucia [top]

Both samples are flat: every record represents 10 persons in the population.

Comparability — Senegal [top]

The 1988 and 2002 samples are flat: every record represents 10 persons in the population. The 2013 sample is weighted.

Comparability — Sierra Leone [top]

The 2004 and 2015 samples are flat: every record represents 10 persons in the population.

Comparability — Slovakia [top]

The 1991, 2001, and 2011 are weighted and use fractions.

Comparability — Slovenia [top]

The sample is flat: every record represents 10 persons in the population.

Comparability — South Africa [top]

All samples are weighted and use fractions. The 2007 multiple weights; we used the adjusted weight.

Comparability — South Sudan [top]

The sample is weighted and uses fractions.

Comparability — Spain [top]

The 1981, 1991, and 2011 samples use fractional weights. The 2001 sample is flat.

Several provinces in 1981 were sampled at roughly 5 times the density of other provinces, making the use of weights particularly critical in that year. The over-sampled provinces are Alava, Guipuzcoa, Navarra, and Vizcaya.

Comparability — Sudan [top]

The sample is weighted and uses fractions.

Comparability — Suriname [top]

The samples are flat: every record represents 10 persons in the population.

Comparability — Switzerland [top]

The 1970-2000 samples are flat: every record represents 20 persons in the population; the 2011 sample is weighted.

Comparability — Tanzania [top]

All Tanzania samples are weighted and use fractions.

Comparability — Thailand [top]

All samples are weighted, reflecting a stratified sample design for each census.

Comparability — Togo [top]

The 1960 and 1970 samples are flat: every record represents 10 persons in 1960 and 100 persons in 1970. The 1960 sample includes only urban population.

The 2010 sample is differentially weighted, according to rural or urban place of residence.

Comparability — Trinidad and Tobago [top]

The samples are flat: every record represents 10 persons in the population.

Comparability — Turkey [top]

The samples are flat: every record represents 20 persons in the population.

Comparability — Uganda [top]

The 1991 sample is weighted. The 1991 person weight data were flawed; the household weights have been substituted for them instead. The 2002 and 2014 samples are flat: every record represents 10 persons in the population.

Comparability — Ukraine [top]

The samples are flat: every record represents an equal number of persons in the population.

Comparability — United Kingdom [top]

The samples are flat: every record represents an equal number of persons in the population.

Comparability — United States [top]

The 1990-2020 samples are weighted; the earlier samples are flat.

Alternative weights, such as replicate weights or sample line weights, are available in the source variables for the 2010 sample.

Comparability — Uruguay [top]

The 2006 sample is weighted. The 1963-1996 and 2011 samples are flat, with each record representing 10 persons in the population.

Comparability — Venezuela [top]

The 1971 and 1990 samples are weighted; the 1981 and 2001 samples are flat.

Comparability — Vietnam [top]

All samples are weighted.

In 1989, men and women have separate weights. The weights are identical for all persons of that sex within a given enumeration area.

Comparability — Zambia [top]

The samples are flat: every record represents 10 persons in the population.

Universe

All persons

Availability

Argentina: 1970, 1980, 1991, 2001, 2010
Armenia: 2001, 2011
Austria: 1971, 1981, 1991, 2001, 2011
Bangladesh: 1991, 2001, 2011
Belarus: 1999, 2009
Benin: 1979, 1992, 2002, 2013
Bolivia: 1976, 1992, 2001, 2012
Botswana: 1981, 1991, 2001, 2011
Brazil: 1960, 1970, 1980, 1991, 2000, 2010
Burkina Faso: 1985, 1996, 2006
Cambodia: 1998, 2004, 2008, 2013, 2019
Cameroon: 1976, 1987, 2005
Canada: 1852, 1871, 1881, 1891, 1901, 1911, 1971, 1981, 1991, 2001, 2011
Chile: 1960, 1970, 1982, 1992, 2002, 2017
China: 1982, 1990, 2000
Colombia: 1964, 1973, 1985, 1993, 2005
Costa Rica: 1963, 1973, 1984, 2000, 2011
Cuba: 2002, 2012
Côte d'Ivoire: 1988, 1998
Denmark: 1787, 1801, 1845, 1880, 1885
Dominican Republic: 1960, 1970, 1981, 2002, 2010
Ecuador: 1962, 1974, 1982, 1990, 2001, 2010
Egypt: 1848, 1868, 1986, 1996, 2006
El Salvador: 1992, 2007
Ethiopia: 1984, 1994, 2007
Fiji: 1966, 1976, 1986, 1996, 2007, 2014
Finland: 2010
France: 1962, 1968, 1975, 1982, 1990, 1999, 2006, 2011
Germany: 1819, 1970, 1971, 1981, 1987
Ghana: 1984, 2000, 2010
Greece: 1971, 1981, 1991, 2001, 2011
Guatemala: 1964, 1973, 1981, 1994, 2002
Guinea: 1983, 1996, 2014
Haiti: 1971, 1982, 2003
Honduras: 1961, 1974, 1988, 2001
Hungary: 1970, 1980, 1990, 2001, 2011
Iceland: 1703, 1729, 1801, 1901, 1910
India: 1983, 1987, 1993, 1999, 2004, 2009
Indonesia: 1971, 1976, 1980, 1985, 1990, 1995, 2000, 2005, 2010
Iran: 2006, 2011
Iraq: 1997
Ireland: 1901, 1911, 1971, 1979, 1981, 1986, 1991, 1996, 2002, 2006, 2011, 2016
Israel: 1972, 1983, 1995, 2008
Italy: 2001, 2011, 2011Q1, 2012Q1, 2013Q1, 2014Q1, 2015Q1, 2016Q1, 2017Q1, 2018Q1, 2019Q1, 2020Q1
Jamaica: 1982, 1991, 2001
Jordan: 2004
Kenya: 1969, 1979, 1989, 1999, 2009
Kyrgyzstan: 1999, 2009
Laos: 1995, 2005, 2015
Lesotho: 1996, 2006
Liberia: 1974, 2008
Malawi: 1987, 1998, 2008
Malaysia: 1970, 1980, 1991, 2000
Mali: 1987, 1998, 2009
Mauritius: 1990, 2000, 2011
Mexico: 1960, 1970, 1990, 1995, 2000, 2005, 2005Q1, 2005Q2, 2005Q3, 2005Q4, 2006Q1, 2006Q2, 2006Q3, 2006Q4, 2007Q1, 2007Q2, 2007Q3, 2007Q4, 2008Q1, 2008Q2, 2008Q3, 2008Q4, 2009Q1, 2009Q2, 2009Q3, 2009Q4, 2010, 2010Q1, 2010Q2, 2010Q3, 2010Q4, 2011Q1, 2011Q2, 2011Q3, 2011Q4, 2012Q1, 2012Q2, 2012Q3, 2012Q4, 2013Q1, 2013Q2, 2013Q3, 2013Q4, 2014Q1, 2014Q2, 2014Q3, 2014Q4, 2015, 2015Q1, 2015Q2, 2015Q3, 2015Q4, 2016Q1, 2016Q2, 2016Q3, 2016Q4, 2017Q1, 2017Q2, 2017Q3, 2017Q4, 2018Q1, 2018Q2, 2018Q3, 2018Q4, 2019Q1, 2019Q2, 2019Q3, 2019Q4, 2020, 2020Q1, 2020Q3
Mongolia: 1989, 2000
Morocco: 1982, 1994, 2004, 2014
Mozambique: 1997, 2007
Myanmar: 2014
Nepal: 2001, 2011
Netherlands: 1960, 1971, 2001, 2011
Nicaragua: 1971, 1995, 2005
Nigeria: 2006, 2007, 2008, 2009, 2010
Norway: 1801, 1865, 1875, 1900, 1910
Pakistan: 1973, 1981, 1998
Palestine: 1997, 2007, 2017
Panama: 1960, 1970, 1980, 1990, 2000, 2010
Papua New Guinea: 1980, 1990, 2000
Paraguay: 1962, 1972, 1982, 1992, 2002
Peru: 1993, 2007, 2017
Philippines: 1990, 1995, 2000, 2010
Poland: 1978, 1988, 2002, 2011
Portugal: 1981, 1991, 2001, 2011
Puerto Rico: 1970, 1980, 1990, 2000, 2005, 2010, 2015, 2020
Romania: 1977, 1992, 2002, 2011
Russia: 2002, 2010
Rwanda: 1991, 2002, 2012
Saint Lucia: 1980, 1991
Senegal: 1988, 2002, 2013
Sierra Leone: 2004, 2015
Slovakia: 1991, 2001, 2011
Slovenia: 2002
South Africa: 1996, 2001, 2007, 2011, 2016
South Sudan: 2008
Spain: 1981, 1991, 2001, 2005Q1, 2005Q2, 2005Q3, 2005Q4, 2006Q1, 2006Q2, 2006Q3, 2006Q4, 2007Q1, 2007Q2, 2007Q3, 2007Q4, 2008Q1, 2008Q2, 2008Q3, 2008Q4, 2009Q1, 2009Q2, 2009Q3, 2009Q4, 2010Q1, 2010Q2, 2010Q3, 2010Q4, 2011, 2011Q1, 2011Q2, 2011Q3, 2011Q4, 2012Q1, 2012Q2, 2012Q3, 2012Q4, 2013Q1, 2013Q2, 2013Q3, 2013Q4, 2014Q1, 2014Q2, 2014Q3, 2014Q4, 2015Q1, 2015Q2, 2015Q3, 2015Q4, 2016Q1, 2016Q2, 2016Q3, 2016Q4, 2017Q1, 2017Q2, 2017Q3, 2017Q4, 2018Q1, 2018Q2, 2018Q3, 2018Q4, 2019Q1, 2019Q2, 2019Q3, 2019Q4, 2020Q1, 2020Q2, 2020Q3, 2020Q4
Sudan: 2008
Suriname: 2004, 2012
Sweden: 1880, 1890, 1900, 1910
Switzerland: 1970, 1980, 1990, 2000, 2011
Tanzania: 1988, 2002, 2012
Thailand: 1970, 1980, 1990, 2000
Togo: 1960, 1970, 2010
Trinidad and Tobago: 1970, 1980, 1990, 2000, 2011
Turkey: 1985, 1990, 2000
Uganda: 1991, 2002, 2014
Ukraine: 2001
United Kingdom: 1851a, 1851b, 1851c, 1861a, 1861b, 1871b, 1881a, 1881b, 1891a, 1891b, 1901a, 1901b, 1911, 1961, 1971, 1991, 2001
United States: 1850a, 1850b, 1860, 1870, 1880a, 1880b, 1900, 1910, 1960, 1970, 1980, 1990, 2000, 2005, 2010, 2015, 2020
Uruguay: 1963, 1975, 1985, 1996, 2006, 2011
Venezuela: 1971, 1981, 1990, 2001
Vietnam: 1989, 1999, 2009, 2019
Zambia: 1990, 2000, 2010
Zimbabwe: 2012

Data Cart

Your data extract

Description

Comparability — Index

Comparability — General

Comparability — Argentina [top]

Comparability — Armenia [top]

Comparability — Austria [top]

Comparability — Belarus [top]

Comparability — Bolivia [top]

Comparability — Botswana [top]

Comparability — Brazil [top]

Comparability — Cambodia [top]

Comparability — Canada [top]

Comparability — Chile [top]

Comparability — China [top]

Comparability — Colombia [top]

Comparability — Costa Rica [top]

Comparability — Cuba [top]

Comparability — Côte d'Ivoire [top]

Comparability — Dominican Republic [top]

Comparability — Ecuador [top]

Comparability — Egypt [top]

Comparability — El Salvador [top]

Comparability — Ethiopia [top]

Comparability — Fiji [top]

Comparability — Finland [top]

Comparability — France [top]

Comparability — Germany [top]

Comparability — Ghana [top]

Comparability — Greece [top]

Comparability — Guatemala [top]

Comparability — Guinea [top]

Comparability — Hungary [top]

Comparability — Indonesia [top]

Comparability — Iran [top]

Comparability — Ireland [top]

Comparability — Israel [top]

Comparability — Italy [top]

Comparability — Jamaica [top]

Comparability — Jordan [top]

Comparability — Kenya [top]

Comparability — Kyrgyzstan [top]

Comparability — Laos [top]

Comparability — Liberia [top]

Comparability — Malawi [top]

Comparability — Malaysia [top]

Comparability — Mali [top]

Comparability — Mauritius [top]

Comparability — Mexico [top]

Comparability — Mongolia [top]

Comparability — Morocco [top]

Comparability — Mozambique [top]

Comparability — Myanmar [top]

Comparability — Nepal [top]

Comparability — Netherlands [top]

Comparability — Nicaragua [top]

Comparability — Pakistan [top]

Comparability — Palestine [top]

Comparability — Panama [top]

Comparability — Paraguay [top]

Comparability — Peru [top]

Comparability — Philippines [top]

Comparability — Poland [top]

Comparability — Portugal [top]

Comparability — Puerto Rico [top]

Comparability — Romania [top]

Comparability — Russia [top]

Comparability — Rwanda [top]

Comparability — Saint Lucia [top]

Comparability — Senegal [top]

Comparability — Sierra Leone [top]

Comparability — Slovakia [top]

Comparability — Slovenia [top]

Comparability — South Africa [top]

Comparability — South Sudan [top]

Comparability — Spain [top]

Comparability — Sudan [top]

Comparability — Suriname [top]

Comparability — Switzerland [top]