Technology Heterogeneity and Poverty Traps: A Latent Class Approach to Technology Gap Drivers of Chronic Poverty.

The analysis of household wealth dynamic remains an important methodology in the identification of poverty traps. To overcome measurement issues in survey data, livelihoods-based approaches of the dynamics of poverty are typically examined using panel regressions of a livelihoods regression on house...

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Publicado en:Journal of Development Studies Vol. 59; no. 2; pp. 224 - 242
Autores principales: Hill, Daniel, McWhinnie, Stephanie F., Kumar, Shalander, Gregg, Daniel
Formato: Artículo
Publicado: Taylor & Francis Ltd Feb2023
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Feb2023
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      pub: Taylor & Francis Ltd
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        10.1080/00220388.2022.2128775
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        atl: Technology Heterogeneity and Poverty Traps: A Latent Class Approach to Technology Gap Drivers of Chronic Poverty.
      aug:
        au:
          Hill, Daniel
          McWhinnie, Stephanie F.
          Kumar, Shalander
          Gregg, Daniel
        affil:
          School of Business, University of New England, Armidale, Australia
          School of Economics and Public Policy, University of Adelaide, Adelaide, Australia
          Enabling Systems Transformation, International Crops Research Institute for the Semi-Arid Tropics, Hyderabad, India
          Heuris Pty Ltd, Adelaide, Australia
      su:
        India
        Heterogeneity
        Poverty
        Socioeconomic factors
        Households
        Digital divide
      sug:
        subj:
          Heterogeneity
          Poverty
          Socioeconomic factors
          Households
          India
          Private Households
          Digital divide
      keyword:
        asset indices
        latent class model
        Livelihood dynamics
        poverty traps
        asset indices
        latent class model
        Livelihood dynamics
        poverty traps
      ab: The analysis of household wealth dynamic remains an important methodology in the identification of poverty traps. To overcome measurement issues in survey data, livelihoods-based approaches of the dynamics of poverty are typically examined using panel regressions of a livelihoods regression on household assets and other socio-economic factors over time. In this paper, we characterise the livelihoods regression as a 'livelihoods technology', and use a latent class-technology approach to account for heterogeneity in how households generate a livelihood. We use a detailed dataset from rural India covering 213 households across 2001–2014, and control for selection issues through a Heckman Selection model. Our results are the first in the wealth dynamics literature to show that substantial heterogeneity exists in the technologies with which households generate their livelihoods. Importantly, we show that accounting for heterogeneity in household livelihoods 'technologies' more readily identifies different equilibria in wealth levels and provides previously foregone information on who is poor and why they remain poor.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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