IDEAS home Printed from https://ideas.repec.org/a/lde/journl/y2016i84p33-58.html
   My bibliography  Save this article

Assessing the loss due to working in the informal sector in Venezuela

Author

Listed:
  • Josefa Ramoni

    (Universidad de Santander)

  • Giampaolo Orlandoni

    (Universidad de Santander)

Abstract

In Venezuela, 40% of the workers are employed in the informal sector. This sector is known for being underproductive, meaning that the income received by its workers is less than what they could earn working in formal sector jobs. This paper uses data from the Household Sample Survey (2012-2013) to estimate differencein-differences linear and quantile regression models, controlling for some demographic characteristics, to quantify the loss associated with working in this market, as an indirect way to quantify the size of the informal sector. The parallel trend assumption is satisfied through propensity score matching, exception made for the highest quartile. The results suggest that informal sector workers lose about 34% of their potential income, loss that is larger for women and with an ambiguous behavior across levels of education. The study also indicates that the average difference in wages between the two sectors tends to narrow over time

Suggested Citation

  • Josefa Ramoni & Giampaolo Orlandoni, 2016. "Assessing the loss due to working in the informal sector in Venezuela," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 84, pages 33-58, Enero - J.
    • Handle: RePEc:lde:journl:y:2016:i:84:p:33-58
    DOI: 10.17533/udea.le.n84a02
    as

    Download full text from publisher

    File URL: http://aprendeenlinea.udea.edu.co/revistas/index.php/lecturasdeeconomia/article/view/25644/21241
    Download Restriction: no
    File URL: https://libkey.io/10.17533/udea.le.n84a02?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
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. DiNardo, John & Fortin, Nicole M & Lemieux, Thomas, 1996. "Labor Market Institutions and the Distribution of Wages, 1973-1992: A Semiparametric Approach," Econometrica, Econometric Society, vol. 64(5), pages 1001-1044, September.
    2. David Card, 1990. "The Impact of the Mariel Boatlift on the Miami Labor Market," ILR Review, Cornell University, ILR School, vol. 43(2), pages 245-257, January.
    3. Becker, Sascha & Hvide, Hans V, 2013. "Do entrepreneurs matter?," CAGE Online Working Paper Series 109, Competitive Advantage in the Global Economy (CAGE).
    4. Card, David & Krueger, Alan B, 1994. "Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania," American Economic Review, American Economic Association, vol. 84(4), pages 772-793, September.
    5. Cimoli, Mario & Primi, Annalisa & Pugno, Maurizio, 2006. "A low-growth model: informality as a structural constraint," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), April.
    6. Francesco Devicienti & Fernando Groisman & Ambra Poggi, 2009. "Informality and poverty: Are these processes dynamically interrelated? Evidence from Argentina," Working Papers 146, ECINEQ, Society for the Study of Economic Inequality.
    7. Anderson, Patricia M. & Meyer, Bruce D., 2000. "The effects of the unemployment insurance payroll tax on wages, employment, claims and denials," Journal of Public Economics, Elsevier, vol. 78(1-2), pages 81-106, October.
    8. Feige, Edgar L., 1990. "Defining and estimating underground and informal economies: The new institutional economics approach," World Development, Elsevier, vol. 18(7), pages 989-1002, July.
    9. A. Smith, Jeffrey & E. Todd, Petra, 2005. "Does matching overcome LaLonde's critique of nonexperimental estimators?," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 305-353.
    10. Roger Koenker & Kevin F. Hallock, 2001. "Quantile Regression," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 143-156, Fall.
    11. Sascha O. Becker & Andrea Ichino, 2002. "Estimation of average treatment effects based on propensity scores," Stata Journal, StataCorp LP, vol. 2(4), pages 358-377, November.
    12. Blunch, Niels-Hugo & Canagarajah, Sudharshan & Raju, Dhushyanth, 2001. "The informal sector revisited : a synthesis across space and time," Social Protection Discussion Papers and Notes 23308, The World Bank.
    13. João Pedro Azevedo, 2005. "An Investigation Of The Labour Market Earnings In Deprived Areas: A Test Of Labour Market Segmentation In The Slums," Anais do XXXIII Encontro Nacional de Economia [Proceedings of the 33rd Brazilian Economics Meeting] 162, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    14. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(2), pages 261-294.
    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. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    2. Tymon Słoczyński, 2015. "The Oaxaca–Blinder Unexplained Component as a Treatment Effects Estimator," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(4), pages 588-604, August.
    3. Victor Lavy & Analia Schlosser, 2005. "Targeted Remedial Education for Underperforming Teenagers: Costs and Benefits," Journal of Labor Economics, University of Chicago Press, vol. 23(4), pages 839-874, October.
    4. Andrea Pufahl & Christoph R. Weiss, 2009. "Evaluating the effects of farm programmes: results from propensity score matching," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 36(1), pages 79-101, March.
    5. Cédric Afsa & Pauline Givord, 2009. "Le rôle des conditions de travail dans les absences pour maladie : le cas des horaires irréguliers," Économie et Prévision, Programme National Persée, vol. 187(1), pages 83-103.
    6. Ramírez-Álvarez, Aurora Alejandra, 2019. "Land titling and its effect on the allocation of public goods: Evidence from Mexico," World Development, Elsevier, vol. 124(C), pages 1-1.
    7. Dettmann, Eva & Becker, Claudia & Schmeißer, Christian, 2010. "Is there a Superior Distance Function for Matching in Small Samples?," IWH Discussion Papers 3/2010, Halle Institute for Economic Research (IWH).
    8. Ashok K. Mishra & Anjani Kumar & Pramod K. Joshi & Alwin D'Souza, 2018. "Cooperatives, contract farming, and farm size: The case of tomato producers in Nepal," Agribusiness, John Wiley & Sons, Ltd., vol. 34(4), pages 865-886, October.
    9. Ichimura, Hidehiko & Todd, Petra E., 2007. "Implementing Nonparametric and Semiparametric Estimators," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 74, Elsevier.
    10. Manuela Deidda & Adriana Di Liberto & Marta Foddi & Giovanni Sulis, 2015. "Employment subsidies, informal economy and women’s transition into work in a depressed area: evidence from a matching approach," IZA Journal of Labor Policy, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 4(1), pages 1-25, December.
    11. Rodrigo Dorantes-Gilardi & Aurora A. Ramírez-Álvarez & Diana Terrazas-Santamaría, 2023. "Is there a differentiated gender effect of collaboration with super-cited authors? Evidence from junior researchers in economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(4), pages 2317-2336, April.
    12. Jasmin Kantarevic & Boris Kralj, 2013. "Link Between Pay For Performance Incentives And Physician Payment Mechanisms: Evidence From The Diabetes Management Incentive In Ontario," Health Economics, John Wiley & Sons, Ltd., vol. 22(12), pages 1417-1439, December.
    13. Aradom Gebrekidan Abbay & Roel Rutten, 2016. "Does spatial proximity to small towns matter for rural livelihoods? A propensity score matching analysis in Ethiopia," Letters in Spatial and Resource Sciences, Springer, vol. 9(3), pages 287-307, October.
    14. Gudibande, Rohan Ravindra & Jacob, Arun, 2020. "Minimum wages for domestic workers: impact evaluation of the Indian experience," World Development, Elsevier, vol. 130(C).
    15. Aydemir, Abdurrahman B. & Kırdar, Murat G., 2017. "Quasi-experimental impact estimates of immigrant labor supply shocks: The role of treatment and comparison group matching and relative skill composition," European Economic Review, Elsevier, vol. 98(C), pages 282-315.
    16. Sergei Guriev & Biagio Speciale & Michele Tuccio, 2019. "How do Regulated and Unregulated Labor Markets Respond to Shocks? Evidence from Immigrants During the Great Recession," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 35(1), pages 37-76.
    17. Tolga Bilgicer & Kamel Jedidi & Donald Lehmann & Scott Neslin, 2015. "The Long-Term Effect of Multichannel Usage on Sales," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 2(1), pages 41-56, March.
    18. Richard Blundell & Monica Costa Dias, 2009. "Alternative Approaches to Evaluation in Empirical Microeconomics," Journal of Human Resources, University of Wisconsin Press, vol. 44(3).
    19. Patrick Christian Feihle & Jochen Lawrenz, 2017. "The Issuance of German SME Bonds and its Impact on Operating Performance," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 18(3), pages 227-259, August.
    20. Ferraro, Paul J. & Miranda, Juan José, 2014. "The performance of non-experimental designs in the evaluation of environmental programs: A design-replication study using a large-scale randomized experiment as a benchmark," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PA), pages 344-365.

    More about this item

    Keywords

    employment in the informal sector; Venezuelan labor market; DID regression models; quantile regression; propensity score matching;
    All these keywords.

    JEL classification:

    • J46 - Labor and Demographic Economics - - Particular Labor Markets - - - Informal Labor Market
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

    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:lde:journl:y:2016:i:84:p:33-58. 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: Carlos Andrés Vasco Correa (email available below). General contact details of provider: https://edirc.repec.org/data/deantco.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.