IPUMS-I: descr: HHWT

Select samples

HHWT

Household weight

Return to Technical Household variables list

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


      class Hhwt : public Editor {

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

    long a = getRecoded();
    switch (dataSet) {
    case dataset_id::br1970a:
      a = BR1970A_0432(1) * 10000;
      break;
    case dataset_id::br1980a:
      a = BR1980A_0029(0) * 10000;
      break;
    case dataset_id::br1991a: {
      long long l = BR1991A_0048(0);
      long long w = l;
      l = l / 10000;
      if (w % 10000 > 5000)
        l++;
      a = l;
    } break;
    case dataset_id::br2000a: {
      long long l = BR2000A_0077(0);
      long long w = l;
      l = l / 10000;
      if (w % 10000 > 5000)
        l++;
      a = l;
    } break;
    case dataset_id::co1985a:
      a = CO1985A_0027(0) * 10000;
      break;
    case dataset_id::ec1974a:
      a = EC1974A_0033() * 140;
      break;
    case dataset_id::mx2000a:
      a = MX2000A_0006(0) * 10000;
      break;
    case dataset_id::ph1990a:
      a = PH1990A_0055(0) * 10000;
      break;
    case dataset_id::ph2000a:
      a = PH2000A_0063(0) * 10000;
      break;
    case dataset_id::ug1991a:
      a = UG1991A_0076(0) * 10000;
      break;
    case dataset_id::ve1990a:
      a = VE1990A_0047(0) * 30000;
      break;
    case dataset_id::za1996a:
      a = ZA1996A_0048(0) * 10;
      break;
    case dataset_id::za2001a:
      a = (long long)(ZA2001A_0043(0) * 0.01);
      break;
    case dataset_id::ie1901a:
    case dataset_id::ie1911a:
      a = 10000;
      break;
    case dataset_id::br1960a:
      a = 50000;
      break;
    case dataset_id::py1962a:
    case dataset_id::pt2011a:
      a = 200000;
      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::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::ve1971a:
    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::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::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::es2001a:
    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::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::cl1960a:
      a = 830000;
      break;
    case dataset_id::es1981a:
      a = ES1981A_0432(1);
      break;
    case dataset_id::us1960a:
      a = US1960A_0006(0) * 10000;
      break;
    case dataset_id::us1970a:
      a = US1970A_0006(0) * 10000;
      break;
    case dataset_id::us1980a:
      a = US1980A_0006(0) * 10000;
      break;
    case dataset_id::us1990a:
      a = US1990A_0006(0) * 10000;
      break;
    case dataset_id::us2000a:
      a = US2000A_0006(0) * 10000;
      break;
    case dataset_id::us2005a:
      a = US2005A_0141(0) * 10000;
      break;
    case dataset_id::us2010a:
      a = US2010A_0020(0) * 10000;
      break;
    case dataset_id::us2015a:
      a = US2015A_0006(0) * 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(1) * 2;
      long long w = l;
      l = l / 100;
      if (w % 100 > 50)
        l++;
      a = l;
    } break;
    case dataset_id::ar1980a:
      a = AR1980A_0052(0) * 20000;
      break;
    case dataset_id::ar1991a:
      a = AR1991A_0048(0) * 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:
      a = MX1995A_0027(0) * 10000;
      break;
    case dataset_id::pa1960a:
      a = 200000;
      break;
    case dataset_id::ca2001a:
      a = (long long)(CA2001A_0525(1) * 0.01);
      break;
    case dataset_id::co2005a:
      a = (long long)(CO2005A_0127(0) * 1.0e-06);
      break;
    case dataset_id::eg1996a:
      a = (long long)(EG1996A_0093(0) * 0.1);
      break;
    case dataset_id::nl1960a:
      a = (long long)(NL1960A_0410(1) * 1.0e-08);
      break;
    case dataset_id::nl1971a:
      a = (long long)(NL1971A_0412(1) * 1.0e-08);
      break;
    case dataset_id::nl2001a:
      a = (long long)(NL2001A_0412(1) * 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_0063(0) * 10;
      break;
    case dataset_id::za2007a: {
      if (ZA2007A_0067(0) == 0)
        a = 0;
    } break;
    case dataset_id::pk1973a:
      a = PK1973A_0026(0) * 10000;
      break;
    case dataset_id::pk1981a:
      a = PK1981A_0409(1) * 38000;
      break;
    case dataset_id::pr1990a:
      a = PR1990A_0042(0) * 10000;
      break;
    case dataset_id::pr2000a:
      a = PR2000A_0021(0) * 10000;
      break;
    case dataset_id::pr2005a:
      a = PR2005A_0021(0) * 10000;
      break;
    case dataset_id::tz1988a:
      a = (long long)(TZ1988A_0426(1) * 2.0e-07);
      break;
    case dataset_id::tz2002a:
      a = TZ2002A_0051(0) * 10;
      break;
    case dataset_id::th1970a:
      a = (long long)(TH1970A_0446(1) * 0.0001);
      break;
    case dataset_id::th1990a:
      a = TH1990A_0086(0) * 100;
      break;
    case dataset_id::fr2006a:
      a = (long long)(FR2006A_0427(1) * 1.0e-08);
      break;
    case dataset_id::fr2011a:
      a = (long long)(FR2011A_0426(1) * 1.0e-10);
      break;
    case dataset_id::ir2006a:
      a = (long long)(IR2006A_0094() * 5.0e-09);
      break;
    case dataset_id::jm2001a:
      a = JM2001A_0523(1) * 100;
      break;
    case dataset_id::ps2007a:
      a = (long long)(PS2007A_0430(1) * 2.0e-07);
      break;
    case dataset_id::vn2009a:
      a = (long long)(VN2009A_0055() * 1.0e-08);
      break;
    case dataset_id::sd2008a:
      a = SD2008A_0188(0);
      break;
    case dataset_id::id1971a:
      a = ID1971A_0047(0) * 10000;
      break;
    case dataset_id::id1976a:
      a = ID1976A_0066(0) * 10000;
      break;
    case dataset_id::id1980a:
      a = ID1980A_0064(0) * 10000;
      break;
    case dataset_id::id1985a:
      a = ID1985A_0050(0) * 10000;
      break;
    case dataset_id::id1990a:
      a = ID1990A_0055(0) * 10000;
      break;
    case dataset_id::id1995a:
      a = ID1995A_0056(0) * 10000;
      break;
    case dataset_id::id2005a:
      a = ID2005A_0502(1) * 10000;
      break;
    case dataset_id::mx2010a:
      a = MX2010A_0069(0) * 10000;
      break;
    case dataset_id::uy2006a:
      a = UY2006A_0185(0) * 10000;
      break;
    case dataset_id::et1994a:
      a = ET1994A_0043(0) * 10000;
      break;
    case dataset_id::mz1997a:
      a = MZ1997A_0050(0) * 10000;
      break;
    case dataset_id::py2002a:
      a = PY2002A_0083(0) * 10000;
      break;
    case dataset_id::br2010a:
      a = (long long)(BR2010A_0027(0) * 1.00e-06);
      break;
    case dataset_id::ke1979a:
      a = (long long)(KE1979A_0422(1) * 0.1);
      break;
    case dataset_id::ke1969a:
      a = KE1969A_0429(1) * 100;
      break;
    case dataset_id::do1981a:
      a = DO1981A_0021(0) * 10000;
      break;
    case dataset_id::do1970a:
      a = DO1970A_0427(1) * 10000;
      break;
    case dataset_id::do1960a:
      a = DO1960A_0026(0) * 100;
      break;
    case dataset_id::ng2006a:
      a = NG2006A_0066(0) * 100;
      break;
    case dataset_id::ng2007a:
      a = NG2007A_0046(0) * 100;
      break;
    case dataset_id::ng2008a:
      a = NG2008A_0059(0);
      break;
    case dataset_id::ng2009a:
      a = NG2009A_0507(1) * 100;
      break;
    case dataset_id::ng2010a:
      a = NG2010A_0529(1) * 10000;
      break;
    case dataset_id::pr2010a:
      a = PR2010A_0210(0) * 100;
      break;
    case dataset_id::et2007a:
      a = (long long)(ET2007A_0067() * 0.1);
      break;
    case dataset_id::za2011a:
      a = (long long)(ZA2011A_0076() * 1.0e-05);
      break;
    case dataset_id::es2011a:
      a = (long long)(ES2011A_0025() * 1.0e-06);
      break;
    case dataset_id::mx2015a:
      a = MX2015A_0030(0) * 10000;
      break;
    case dataset_id::ir2011a:
      a = IR2011A_0457(1);
      break;
    case dataset_id::ca2011a:
      a = (long long)(CA2011A_0442(1) * 1.0e-09);
      break;
    case dataset_id::tz2012a:
      a = TZ2012A_0095() * 27.5;
      break;
    case dataset_id::eg1986a:
      a = (long long)(EG1986A_0071() * 1.0e-05);
      break;
    case dataset_id::nl2011a:
      a = (long long)(NL2011A_0412(1) * 1.0e-06);
      break;
    case dataset_id::ph2010a:
      a = (long long)(PH2010A_0074() * 2.0e-05);
      break;
    case dataset_id::kh2004a:
      a = (long long)(KH2004A_0027() * 1.00e-06);
      break;
    case dataset_id::kh2013a:
      a = (long long)(KH2013A_0032() * 0.1);
      break;
    case dataset_id::np2001a:
      a = NP2001A_0050();
      break;
    case dataset_id::np2011a:
      a = 81000;
      break;
    case dataset_id::tg2010a:
      a = TG2010A_0103() * 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: {

      if (countPeople() > 0) {
        RecordPointer firstPerson = people().front();

        long factorw = valueFromFirstAvailable(
            firstPerson, {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: {

      if (countPeople() > 0) {
        RecordPointer firstPerson = people().front();

        long factorw = valueFromFirstAvailable(
            firstPerson,
            {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: {

      if (countPeople() > 0) {
        RecordPointer firstPerson = people().front();

        long factorw = valueFromFirstAvailable(
            firstPerson, {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(1) * 10);
      break;
    case dataset_id::mm2014a:
      a = (long long)(MM2014A_0054(0));
      break;
    case dataset_id::ps2017a:
      a = (long long)(PS2017A_0026(0) * 0.00000002);
      break;
    case dataset_id::sn2013a:
      a = (long long)(SN2013A_0097(0) * 0.0001);
      break;
    case dataset_id::za2016a:
      a = (long long)(ZA2016A_0158(0) * 0.00001);
      break;
    case dataset_id::eg1848a:
      a = (long long)(EG1848A_0445(1) * 0.1);
      break;
    case dataset_id::eg1868a:
      a = (long long)(EG1868A_0445(1) * 0.1);
      break;
    case dataset_id::sk1991a:
      a = (long long)(SK1991A_0415(1) * 0.00001);
      break;
    case dataset_id::sk2001a:
      a = (long long)(SK2001A_0417(1) * 0.00001);
      break;
    case dataset_id::sk2011a:
      a = (long long)(SK2011A_0417(1) * 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: {
      if (countPeople() > 0) {
        RecordPointer person_rec = people().front();
        auto source_data = getSourceData(person_rec);
        a = applyTransTable(source_data);
      } else
        a = 0;

      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);
    }
    if (GQ(0) == 29)
      a = 0;

    setData(a);
  }
};

Description

HHWT indicates the number of households in the population represented by the household in the sample.

For the samples that are truly weighted (see the comparability discussion), HHWT must be used to yield accurate household-level statistics.

NOTE: HHWT 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
Ecuador
Egypt
El Salvador
Ethiopia
Fiji
Finland
France
Germany
Ghana
Greece
Guatemala
Guinea
Hungary

Indonesia
Iran
Ireland
Israel
Italy
Jamaica
Jordan
Kenya
Kyrgyzstan
Laos
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
United Kingdom
United States
Uruguay
Venezuela
Vietnam

Comparability — General

HHWT is available for all samples, but only some samples have weights that differ among households (i.e., many datasets 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
Ecuador 1974
Egypt 1986, 1996
Ethiopia 1994, 2007
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
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 HHWT may not yield a precise count of the actual population to the extent that the theoretical sampling fraction was imperfect.

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.

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

In several samples, at least some very large households were split into individual records. These households may or may not represent group quarters. A household record is written for each of these individuals. Households created as a result of these divisions have household weights set to zero. Relevant records are identified in the group quarters variable (GQ) by code 29 "1-person unit created by splitting large household."

Comparability — Argentina [top]

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

Comparability — Armenia [top]

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

Comparability — Austria [top]

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

Comparability — Belarus [top]

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

Comparability — Bolivia [top]

The 1976-2001 samples are flat: every record represents 10 households 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 households 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 households. In 1970, the household weight is derived from the weight of the first person in the household.

Comparability — Cambodia [top]

The Cambodia 1998, 2008, 2019 samples are flat: every record represents 10 households 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 2011 samples use fractional weights (two decimal places).

Comparability — Chile [top]

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

Comparability — China [top]

The samples are flat: every record represents 100 households 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 households 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 households 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 — Ecuador [top]

The 1974 sample uses fractional weights. The other samples are flat.

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. For details about missing 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 households 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 households in the population.

Comparability — Finland [top]

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

Comparability — France [top]

The 1962-1999 samples are flat: every record represents an equal number of households in the population. The 2006 and 2011 samples are weighted and use fractions.

Comparability — Germany [top]

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

Comparability — Ghana [top]

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

Comparability — Greece [top]

All samples are flat: every record represents an equal number of households 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 households in 1994 and 2002, 18 households in 1973, and 20 households in 1964 and 1981.

Comparability — Guinea [top]

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

Comparability — Hungary [top]

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

Comparability — Iran [top]

The samples are weighted and use fractions.

Comparability — Ireland [top]

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

Comparability — Israel [top]

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

Comparability — Italy [top]

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

Comparability — Kenya [top]

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

Comparability — Kyrgyzstan [top]

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

Comparability — Laos [top]

The 1995, 2005, and 2015 samples are flat: every record represents 10 households in the population. In 2005, the weighted number of collective households are larger than those in published census results.

Comparability — Malawi [top]

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

Comparability — Malaysia [top]

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

Comparability — Mali [top]

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

Comparability — Mauritius [top]

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

Comparability — Mexico [top]

The 1995, 2000, 2010, 2015, and 2020 samples are weighted; the others are flat.

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 households in the population. The 2014 sample is also flat, but every record represents 10 households in the population.

Comparability — Mozambique [top]

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

Comparability — Myanmar [top]

The 2014 sample is weighted.

Comparability — Nepal [top]

The 2011 sample is flat: every record represents 8.1 households 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 household 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 households 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 households in the population depending on the sample. The 2002 sample is differentially weighted.

Comparability — Peru [top]

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

Comparability — Portugal [top]

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

Comparability — Puerto Rico [top]

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

Comparability — Romania [top]

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

Comparability — Russia [top]

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

Comparability — Rwanda [top]

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

Comparability — Saint Lucia [top]

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

Comparability — Senegal [top]

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

Comparability — Sierra Leone [top]

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

Comparability — South Africa [top]

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

In 1996, collective dwellings did not receive a weight. We have applied the nominal average sample weight to these cases: they all get a weight of "10" in the IPUMS.

Comparability — South Sudan [top]

The sample is weighted and uses fractions.

Comparability — Spain [top]

The 1981 and 1991 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 households 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.

Comparability — Togo [top]

The 1960 and 1970 samples are flat: every record represents 10 households in 1960 and 100 households 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 households in the population.

Comparability — Turkey [top]

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

Comparability — Uganda [top]

The 1991 sample is weighted. The 2002 and 2014 samples are flat: every record represents 10 households in the population.

Comparability — United Kingdom [top]

The samples are flat: every record represents an equal number of households 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 samples are flat, with each record representing 10 households 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.

Universe

All households

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 — 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 — 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]

Comparability — Tanzania [top]

Comparability — Thailand [top]