[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/ags/aare20/305253.html
   My bibliography  Save this paper

Technology heterogeneity and poverty traps: A latent class approach to technology gap drivers of chronic poverty

Author

Listed:
  • Hill, Daniel
Abstract
We use a latent class production function approach to consider the existence of differences in household income functions to observe whether this is a key determinant to livelihood outcomes between households in rural India. Empirical analysis is valuable in understanding the levels of poverty, observed poverty dynamics, and the mechanisms behind why households have alternative livelihood dynamics. However, survey measures of income and consumption are often prone to large volatility and measurement error. To account for this, many papers adopt a livelihood regression index which describes a relationship between a measured livelihood of a household and the value of the assets owned. The fitted values from this regression can generate predicted livelihoods of households given a set of assets, avoiding the previously discussed volatility. However, previous studies have estimated the livelihood index as an average across the entire sample population, only allowing for homogeneous differences in how livelihoods are generated between households and across time. This assumes all households share the same marginal elasticises from assets. However, this is inconsistent with the livelihood literature where structural differences in livelihoods is often argued to be driven by differences in the levels and contributions assets provide in generating a livelihood. This paper presents a latent grouping strategy that allocates households into the sub-groups that best represents their average observed livelihoods, using the ICRISAT data of agrarian households in rural India. The algorithm estimates the livelihood index given an initial clustering on outcomes, and then reallocates households if the log-likelihood of being represented by another group is higher. The algorithm is repeated until there are no movements between groups in the sample. A latent estimation allows for estimations to not be based on assumptions of homogeneity or subjective a-priori grouping of households. The resulting fitted values of the estimated livelihood indexes is used in a first-order auto-regressive process to consider the existence of possible unstable thresholds in livelihood dynamics. This shows whether subgroups converge to a single livelihood equilibrium or diverge to separate equilibrium contingent on their starting livelihood endowment. A divergence would indicate the existence of a poverty trap where households converge to persistently low livelihood outcomes and do not have the assets or capabilities to overcome structural obstacles. The latent estimation shows there is significant heterogeneity in how households utilise asset holdings to generate a livelihood which cannot be observed through a homogeneous livelihood estimations. The sub-technologies also allow for a discussion on the qualitative differences between technologies and groups, where the results indicates households derive greater livelihoods from diversification in income, insurance against macroeconomic shocks and access to collective technology. The corresponding fitted values from the sub-group livelihoods find conditional convergence of livelihoods but at different levels and rates between the sub-groups. These differences in trajectory functions cannot be observed with homogeneous estimations and emphasises that a latent estimation is crucial in analysing poverty through livelihood trajectories when there is significant household heterogeneity.

Suggested Citation

  • Hill, Daniel, 2020. "Technology heterogeneity and poverty traps: A latent class approach to technology gap drivers of chronic poverty," 2020 Conference (64th), February 12-14, 2020, Perth, Western Australia 305253, Australian Agricultural and Resource Economics Society.
    • Handle: RePEc:ags:aare20:305253
    DOI: 10.22004/ag.econ.305253
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/305253/files/257Technologyheterogeneityandpovertytraps.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.305253?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Harold Alderman & Jere Behrman & Hans-Peter Kohler & John A. Maluccio & Susan Watkins, 2001. "Attrition in Longitudinal Household Survey Data," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 5(4), pages 79-124.
    2. Chaudhuri, Shubham & Ravallion, Martin, 1994. "How well do static indicators identify the chronically poor?," Journal of Public Economics, Elsevier, vol. 53(3), pages 367-394, March.
    3. World Bank Group, 2016. "Poverty and Shared Prosperity 2016," World Bank Publications - Books, The World Bank Group, number 25078.
    4. Carter, Michael R. & May, Julian, 2001. "One Kind of Freedom: Poverty Dynamics in Post-apartheid South Africa," World Development, Elsevier, vol. 29(12), pages 1987-2006, December.
    5. Giesbert, Lena & Schindler, Kati, 2012. "Assets, Shocks, and Poverty Traps in Rural Mozambique," World Development, Elsevier, vol. 40(8), pages 1594-1609.
    6. Deon Filmer & Kinnon Scott, 2012. "Assessing Asset Indices," Demography, Springer;Population Association of America (PAA), vol. 49(1), pages 359-392, February.
    7. Luis Orea & Subal C. Kumbhakar, 2004. "Efficiency measurement using a latent class stochastic frontier model," Empirical Economics, Springer, vol. 29(1), pages 169-183, January.
    8. Lin, Boqiang & Du, Kerui, 2013. "Technology gap and China's regional energy efficiency: A parametric metafrontier approach," Energy Economics, Elsevier, vol. 40(C), pages 529-536.
    9. Sungil Kwak & Stephen C. Smith, 2013. "Regional Agricultural Endowments and Shifts of Poverty Trap Equilibria: Evidence from Ethiopian Panel Data," Journal of Development Studies, Taylor & Francis Journals, vol. 49(7), pages 955-975, July.
    10. Ambrus, Attila & Field, Erica, 2008. "Early Marriage, Age of Menarche, and Female Schooling Attainment in Bangladesh," Scholarly Articles 3200264, Harvard University Department of Economics.
    11. Carter, Michael R. & Lybbert, Travis J., 2012. "Consumption versus asset smoothing: testing the implications of poverty trap theory in Burkina Faso," Journal of Development Economics, Elsevier, vol. 99(2), pages 255-264.
    12. Naschold, Felix, 2012. "“The Poor Stay Poor”: Household Asset Poverty Traps in Rural Semi-Arid India," World Development, Elsevier, vol. 40(10), pages 2033-2043.
    13. Laure Latruffe & Boris E. Bravo-Ureta & Alain Carpentier & Yann Desjeux & Víctor H. Moreira, 2017. "Subsidies and Technical Efficiency in Agriculture: Evidence from European Dairy Farms," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 99(3), pages 783-799.
    14. Wang, Qunwei & Zhao, Zengyao & Zhou, Peng & Zhou, Dequn, 2013. "Energy efficiency and production technology heterogeneity in China: A meta-frontier DEA approach," Economic Modelling, Elsevier, vol. 35(C), pages 283-289.
    15. Christopher B. Barrett & Michael R. Carter, 2013. "The Economics of Poverty Traps and Persistent Poverty: Empirical and Policy Implications," Journal of Development Studies, Taylor & Francis Journals, vol. 49(7), pages 976-990, July.
    16. Víctor Moreira & Boris Bravo-Ureta, 2010. "Technical efficiency and metatechnology ratios for dairy farms in three southern cone countries: a stochastic meta-frontier model," Journal of Productivity Analysis, Springer, vol. 33(1), pages 33-45, February.
    17. Mosse, David, 2018. "Caste and development: Contemporary perspectives on a structure of discrimination and advantage," World Development, Elsevier, vol. 110(C), pages 422-436.
    18. Moser, Caroline O. N., 1998. "The asset vulnerability framework: Reassessing urban poverty reduction strategies," World Development, Elsevier, vol. 26(1), pages 1-19, January.
    19. Erica Field & Attila Ambrus, 2008. "Early Marriage, Age of Menarche, and Female Schooling Attainment in Bangladesh," Journal of Political Economy, University of Chicago Press, vol. 116(5), pages 881-930, October.
    20. Laure Latruffe & Boris E. Bravo-Ureta & Alain Carpentier & Yann Desjeux & Víctor H. Moreira, 2017. "Subsidies and Technical Efficiency in Agriculture: Evidence from European Dairy Farms," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 99(3), pages 783-799.
    21. Felix Naschold, 2013. "Welfare Dynamics in Pakistan and Ethiopia -- Does the Estimation Method Matter?," Journal of Development Studies, Taylor & Francis Journals, vol. 49(7), pages 936-954, July.
    22. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    23. Angus Deaton & Salman Zaidi, 2002. "Guidelines for Constructing Consumption Aggregates for Welfare Analysis," World Bank Publications, The World Bank, number 14101, April.
    24. K. P. C. Rao, 2008. "Changes in dry land agriculture in the semi-arid tropics of India, 1975-2004," The European Journal of Development Research, Taylor and Francis Journals, vol. 20(4), pages 562-578.
    25. Agnes R. Quisumbing & Bob Baulch, 2013. "Assets and Poverty Traps in Rural Bangladesh," Journal of Development Studies, Taylor & Francis Journals, vol. 49(7), pages 898-916, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Janz, Teresa & Augsburg, Britta & Gassmann, Franziska & Nimeh, Zina, 2023. "Leaving no one behind: Urban poverty traps in Sub-Saharan Africa," World Development, Elsevier, vol. 172(C).
    2. Dylan Fitz & Shyam Gouri Suresh, 2021. "Poverty traps across levels of aggregation," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(4), pages 909-953, October.
    3. Arunachalam, Raj & Shenoy, Ajay, 2017. "Poverty traps, convergence, and the dynamics of household income," Journal of Development Economics, Elsevier, vol. 126(C), pages 215-230.
    4. Giesbert, Lena & Schindler, Kati, 2012. "Assets, Shocks, and Poverty Traps in Rural Mozambique," World Development, Elsevier, vol. 40(8), pages 1594-1609.
    5. Bapu Vaitla & Jennifer Denno Cissé & Joanna Upton & Girmay Tesfay & Nigussie Abadi & Daniel Maxwell, 2020. "How the choice of food security indicators affects the assessment of resilience—an example from northern Ethiopia," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 12(1), pages 137-150, February.
    6. Wanglin Ma & Kathryn Bicknell & Alan Renwick, 2019. "Feed use intensification and technical efficiency of dairy farms in New Zealand," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 63(1), pages 20-38, January.
    7. Katharina Lehmann-Uschner & Kati Krähnert, 2018. "When Shocks Become Persistent: Household-Level Asset Growth in the Aftermath of an Extreme Weather Event," Discussion Papers of DIW Berlin 1759, DIW Berlin, German Institute for Economic Research.
    8. Haider, Hamza, "undated". "Asset Management & Coping Strategies in Burkina Faso," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 259956, Agricultural and Applied Economics Association.
    9. K Hervé Dakpo & Laure Latruffe & Yann Desjeux & Philippe Jeanneaux, 2021. "Latent Class Modelling for a Robust Assessment of Productivity: Application to French Grazing Livestock Farms," Journal of Agricultural Economics, Wiley Blackwell, vol. 72(3), pages 760-781, September.
    10. Hang, Yuan, 2017. "Is There a Poverty Trap of multiple Dynamic Equilibria? The Analysis on Data of Rural Fixed Observation Point from 2004 to 2012," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 257264, Agricultural and Applied Economics Association.
    11. K Hervé Dakpo & Laure Latruffe & Yann Desjeux & Philippe Jeanneaux, 2022. "Modeling heterogeneous technologies in the presence of sample selection: The case of dairy farms and the adoption of agri‐environmental schemes in France," Agricultural Economics, International Association of Agricultural Economists, vol. 53(3), pages 422-438, May.
    12. Lin, Boqiang & Du, Kerui, 2014. "Measuring energy efficiency under heterogeneous technologies using a latent class stochastic frontier approach: An application to Chinese energy economy," Energy, Elsevier, vol. 76(C), pages 884-890.
    13. Samuel Mburu & Micha Kaiser & Alfonso Sousa-Poza, 2023. "Livestock Asset Dynamics Amongst Pastoralists in Northern Kenya," Journal of African Economies, Centre for the Study of African Economies, vol. 32(5), pages 572-597.
    14. You, Jing, 2014. "Risk, under-investment in agricultural assets and dynamic asset poverty in rural China," China Economic Review, Elsevier, vol. 29(C), pages 27-45.
    15. Laure Latruffe & Andreas Niedermayr & Yann Desjeux & K Herve Dakpo & Kassoum Ayouba & Lena Schaller & Jochen Kantelhardt & Yan Jin & Kevin Kilcline & Mary Ryan & Cathal O’Donoghue, 2023. "Identifying and assessing intensive and extensive technologies in European dairy farming," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 50(4), pages 1482-1519.
    16. Christopher B. Barrett & Michael R. Carter & Jean-Paul Chavas, 2017. "Introduction to "The Economics of Poverty Traps"," NBER Chapters, in: The Economics of Poverty Traps, pages 1-20, National Bureau of Economic Research, Inc.
    17. Raushan Bokusheva & Lukáš Čechura & Subal C. Kumbhakar, 2023. "Estimating persistent and transient technical efficiency and their determinants in the presence of heterogeneity and endogeneity," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(2), pages 450-472, June.
    18. Subal C. Kumbhakar & Christopher F. Parmeter & Valentin Zelenyuk, 2022. "Stochastic Frontier Analysis: Foundations and Advances I," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 8, pages 331-370, Springer.
    19. Du, Minzhe & Wang, Bing & Zhang, Ning, 2018. "National research funding and energy efficiency: Evidence from the National Science Foundation of China," Energy Policy, Elsevier, vol. 120(C), pages 335-346.
    20. Muntaha Rakib & Julia Anna Matz, 2016. "The Impact of Shocks on Gender-differentiated Asset Dynamics in Bangladesh," Journal of Development Studies, Taylor & Francis Journals, vol. 52(3), pages 377-395, March.

    More about this item

    Keywords

    Community/Rural/Urban Development;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:aare20:305253. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aaresea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.