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Household income dynamics in rural China (Inglês)

Theoretical work has shown that nonlinear dynamics in household incomes can yield poverty traps and distribution-dependent growth. If this is true, the potential implications for policy are dramatic: effective social protection from transient poverty would be an investment with lasting benefits, and pro-poor redistribution would promote aggregate economic growth. The authors test for nonlinearity in the dynamics of household incomes and expenditures using panel data for 6,000 households over six years in rural southwest China. While they find evidence of nonlinearity in the income and expenditure dynamics, there is no sign of a dynamic poverty trap. The authors argue that existing private and social arrangements in this setting protect vulnerable households from the risk of destitution. However, their findings imply that the speed of recovery from an income shock is appreciably slower for the poor than for others. They also find that current inequality reduces future growth in mean incomes, though the "growth cost" of inequality appears to be small. The maximum contribution of inequality is estimated to be 4-7 percent of mean income and 2 percent of mean consumption.

Detalhes

  • Autor

    Jalan, Jyotsna Ravallion, Martin

  • Data do documento

    2001/11/30

  • TIpo de documento

    Documento de trabalho sobre pesquisa de políticas

  • No. do relatório

    WPS2706

  • Nº do volume

    1

  • Total Volume(s)

    1

  • País

    China,

  • Região

    Leste Asiático e Pacífico,

  • Data de divulgação

    2010/07/01

  • Nome do documento

    Household income dynamics in rural China

  • Palavras-chave

    speed of recovery;transient shock;effect of inequality on growth;household income;dynamic model;current income;panel data;dynamic panel data model;poverty trap;moment condition;multiple equilibria;income risk;liquid wealth;Transient Poverty;speed of adjustment;geographic poverty trap;inequality and growth;credit market failure;income and expenditure;income dynamic;instrumental variable;income shock;asymptotic covariance matrix;fluctuations in consumption;foreign bank entry;informal insurance arrangement;estimation of equation;independent measurement error;return to education;expenditure per capita;method of moments;rate of growth;safety net policy;safety net intervention;inequality will;effects of income;rise and fall;change in income;growth and development;exposure to risk;determinants of growth;panel data set;process of adjustment;rural living standard;level of consumption;consistent standard error;degrees of freedom;vulnerable household;sample household;adjustment process;business cycle;dynamic poverty;initial distribution;dynamic process;uninsured risk;household expenditure;wealth effect;constant term;income decline;stable equilibrium;nutritional requirement;covariate risk;econometric model;lagged value;efficiency wage;consumption insurance;concave function;serial dependence;long-term effect;parameter vector;aggregate shock;empirical work;income variable;lagged dependent;transfer payment;model specification;labor earning;standard deviation;negative shock;Social Protection;estimation method;behavioral response;

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