IDEAS home Printed from https://ideas.repec.org/p/lvl/pmmacr/2017-24.html
   My bibliography  Save this paper

A top-down behaviour (TDB) microsimulation toolkit for distributive analysis

Author

Listed:
  • Luca Tiberti
  • John Cockburn
  • Martín Cicowiez

Abstract

CGE models are often combined with microsimulation (MS) models to perform distributive impact analysis for fiscal or structural policies, or external shocks. This paper describes a user-friendly Stata-based toolkit to perform microsimulations combined with CGE models in a top down fashion. The toolkit is organized in various modules. It first estimates income generation by type of work and skill of workers. Then it estimates households’ specific price deflators based on individual utility. The changes estimated by a CGE model (or from other sources) in the employment (by skill and sector), in the wage payroll (by skill), in the revenues from self-employment activities (by skill) as well as in the commodities prices are fed into the MS model in a consistent way. Once the new vector of real consumption or revenue is estimated, it performs a series of distributive analysis, such as the computation of standard poverty and inequality indices, their decomposition by income factor, robustness analysis and growth incidence curves, and compare the baseline with the simulation results. This makes it possible to run standard poverty and distributive analyses, and to see whether a given shock or policy has had some impact on household welfare and who are the most affected households. Based on such information, social protection policies can be accurately designed in order to minimize the, e.g., negative effects of a given shock in a cost-effective manner. An illustrative analysis is run on data from Uganda.

Suggested Citation

  • Luca Tiberti & John Cockburn & Martín Cicowiez, 2017. "A top-down behaviour (TDB) microsimulation toolkit for distributive analysis," Working Papers PMMA 2017-24, PEP-PMMA.
  • Handle: RePEc:lvl:pmmacr:2017-24
    as

    Download full text from publisher

    File URL: https://portal.pep-net.org/document/download/31308
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. François Bourguignon & Maurizio Bussolo & Luiz A. Pereira da Silva, 2008. "The Impact of Macroeconomic Policies on Poverty and Income Distribution : Macro-Micro Evaluation Techniques and Tools," World Bank Publications, The World Bank, number 6586, July.
    2. G. A. Meagher & Nisha Agrawal, 1986. "Taxation Reform and Income Distribution in Australia," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 19(3), pages 33-56, September.
    3. Anne‐Sophie Robilliard & Sherman Robinson, 2003. "Reconciling Household Surveys and National Accounts Data Using a Cross Entropy Estimation Method," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 49(3), pages 395-406, September.
    4. François Bourguignon & Martin Fournier & Marc Gurgand, 2004. "Selection Bias Corrections Based on the Multinomial Logit Model: Monte-Carlo Comparisons," DELTA Working Papers 2004-20, DELTA (Ecole normale supérieure).
    5. François Bourguignon & Maurizio Bussolo & Luis Pereira, 2008. "The Impact of Macroeconomic Policies on Poverty and Income Distribution," PSE-Ecole d'économie de Paris (Postprint) halshs-00754864, HAL.
    6. Anthony Shorrocks, 2013. "Decomposition procedures for distributional analysis: a unified framework based on the Shapley value," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 11(1), pages 99-126, March.
    7. Ravallion, Martin & Chen, Shaohua, 2003. "Measuring pro-poor growth," Economics Letters, Elsevier, vol. 78(1), pages 93-99, January.
    8. Grimm, M., 2005. "Educational policies and poverty reduction in Cote d'Ivoire," Journal of Policy Modeling, Elsevier, vol. 27(2), pages 231-247, March.
    9. Azevedo, Joao Pedro & Inchauste, Gabriela & Olivieri, Sergio & Saavedra, Jaime & Winkler, Hernan, 2013. "Is labor income responsible for poverty reduction ? a decomposition approach," Policy Research Working Paper Series 6414, The World Bank.
    10. François Bourguignon & Martin Fournier & Marc Gurgand, 2007. "Selection Bias Corrections Based On The Multinomial Logit Model: Monte Carlo Comparisons," Journal of Economic Surveys, Wiley Blackwell, vol. 21(1), pages 174-205, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Luca Tiberti & Martin Cicowiez & John Cockburn, 2018. "A Top-Down with Behaviour (TDB) Microsimulation Toolkit for Distributive Analysis," International Journal of Microsimulation, International Microsimulation Association, vol. 11(2), pages 191-213.

    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. Luca Tiberti & Martin Cicowiez & John Cockburn, 2018. "A Top-Down with Behaviour (TDB) Microsimulation Toolkit for Distributive Analysis," International Journal of Microsimulation, International Microsimulation Association, vol. 11(2), pages 191-213.
    2. Nabil Annabi & Fatou Cissé & John Cockburn & Bernard Decaluwé, 2005. "Trade Liberalisation, Growth and Poverty in Senegal: a Dynamic Microsimulation CGE Model Analysis," Cahiers de recherche 0512, CIRPEE.
    3. Harald SCHMIDBAUER & Ece DEMIREL, 2010. "Monetary Authorities and Exchange Rate Volatility: Turkey and other Cases," EcoMod2010 259600150, EcoMod.
    4. Dorothée Boccanfuso & Luc Savard & Antonio Estache, 2013. "The Distributional Impact of Developed Countries’ Climate Change Policies on Senegal: A Macro-Micro CGE Application," Sustainability, MDPI, Open Access Journal, vol. 5(6), pages 1-24, June.
    5. Ariu, Andrea & Breinlich, Holger & Corcos, Gregory & Mion, Giordano, 2019. "The interconnections between services and goods trade at the firm-level," Journal of International Economics, Elsevier, vol. 116(C), pages 173-188.
    6. Evan J. Miller-Tait & Sandeep Mohapatra & M. K. (Marty) Luckert & Brent M. Swallow, 2019. "Processing technologies for undervalued grains in rural India: on target to help the poor?," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 11(1), pages 151-166, February.
    7. Kassie, Menale & Fisher, Monica & Muricho, Geoffrey & Diiro, Gracious, 2020. "Women’s empowerment boosts the gains in dietary diversity from agricultural technology adoption in rural Kenya," Food Policy, Elsevier, vol. 95(C).
    8. Momanyi, Denis, 2016. "Analysis of the Marketing Behavior of African Indigenous Leafy Vegetables Among Smallholder Farmers in Nyamira County, Kenya," Research Theses 243443, Collaborative Masters Program in Agricultural and Applied Economics.
    9. Breustedt, Gunnar & Schulz, Norbert & Latacz-Lohmann, Uwe, 2013. "Kalibrierung von Vertragsnaturschutzprogrammen mittels eines zweistufigen Discrete-Choice-Experimentes," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 62(04), pages 1-17, November.
    10. Mathias Kuepié & Christophe J. Nordman, 2016. "Where Does Education Pay Off in Sub-Saharan Africa? Evidence from Two Cities of the Republic of Congo," Oxford Development Studies, Taylor & Francis Journals, vol. 44(1), pages 1-27, January.
    11. Guaracyane Lima Campelo & João Mário Santos De França & Emerson Luís Lemos Marinho, 2016. "Impacts Of Malnutrition On Labor Productivity: Empirical Evidences In Rural Brazil," Anais do XLII Encontro Nacional de Economia [Proceedings of the 42nd Brazilian Economics Meeting] 236, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    12. Aleksandra Anić & Gorana Krstić, 2019. "What Lies Behind The Gender Wage Gap In Serbia?," Economic Annals, Faculty of Economics, University of Belgrade, vol. 64(223), pages 137-170, October –.
    13. Timothy Park & Ashok K. Mishra & Shawn J. Wozniak, 2014. "Do farm operators benefit from direct to consumer marketing strategies?," Agricultural Economics, International Association of Agricultural Economists, vol. 45(2), pages 213-224, March.
    14. Ferreira , Francisco H. G., 2010. "Distributions in motion: economic growth, inequality, and poverty dynamics," Policy Research Working Paper Series 5424, The World Bank.
    15. Wanglin Ma & Awudu Abdulai, 2016. "Linking apple farmers to markets: Determinants and impacts of marketing contracts in China," China Agricultural Economic Review, Emerald Group Publishing, vol. 8(1), pages 2-21, February.
    16. Florent Bresson & Jean-Yves Duclos & Flaviana Palmisano, 2019. "Intertemporal pro-poorness," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 52(1), pages 65-96, January.
    17. Damette, Olivier & Delacote, Philippe & Lo, Gaye Del, 2018. "Households energy consumption and transition toward cleaner energy sources," Energy Policy, Elsevier, vol. 113(C), pages 751-764.
    18. C. Duvivier & S. Li & M.-F. Renard, 2013. "Are workers close to cities paid higher nonagricultural wages in rural China?," Applied Economics, Taylor & Francis Journals, vol. 45(30), pages 4308-4322, October.
    19. Kahn, Matthew E. & Sun, Weizeng & Wu, Jianfeng & Zheng, Siqi, 2021. "Do political connections help or hinder urban economic growth? Evidence from 1,400 industrial parks in China," Journal of Urban Economics, Elsevier, vol. 121(C).
    20. Christophe J. Nordman & François Roubaud, 2009. "Reassessing the Gender Wage Gap in Madagascar: Does Labor Force Attachment Really Matter?," Economic Development and Cultural Change, University of Chicago Press, vol. 57(4), pages 785-808, July.

    More about this item

    Keywords

    CGE-microsimulation model; poverty and distributive analysis; Uganda;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:lvl:pmmacr:2017-24. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/cdvlvca.html .

    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: Manuel Paradis (email available below). General contact details of provider: https://edirc.repec.org/data/cdvlvca.html .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.