IDEAS home Printed from https://ideas.repec.org/p/edj/ceauch/264.html
   My bibliography  Save this paper

Information Asymmetries and an Endogenous Productivity Reversion Mechanism

Author

Listed:
  • Nicolás Figueroa
  • Oksana Leukhina

Abstract

Several empirical studies suggest that the systematic behavior of lending standards, with laxer (tighter) standards applied during expansions (recessions) are responsible for reverting trends in aggregate productivity. We build a dynamic screening model with informational asymmetries in credit markets that rationalizes the observed dependence of lending standards on economic fundamentals and generates reversion of output and productivity trends via the lending standards channel. When the capital stock, which evolves endogenously, is high, liquidity is high for all types of producers, allowing even the unproductive type to meet the early payments on the loan, and thus making signals about entrepreneurs’ type, inferred from such payments, less informative. The early payment required to accomplish screening out the unproductive types thus rises. Because the early payment hurts productive entrepreneurs by restricting their investments, competition among lenders results in the selection of contracts with no screening. Low productivity entrepreneurs enter production along with productive types, the composition effect setting off a recession. The opposite happens for low enough values of capital. JEL Codes: E32, E44, D24.

Suggested Citation

  • Nicolás Figueroa & Oksana Leukhina, 2009. "Information Asymmetries and an Endogenous Productivity Reversion Mechanism," Documentos de Trabajo 264, Centro de Economía Aplicada, Universidad de Chile.
  • Handle: RePEc:edj:ceauch:264
    as

    Download full text from publisher

    File URL: http://www.cea-uchile.cl/wp-content/uploads/doctrab/ASOCFILE120090818152745.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Lown, Cara & Morgan, Donald P., 2006. "The Credit Cycle and the Business Cycle: New Findings Using the Loan Officer Opinion Survey," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(6), pages 1575-1597, September.
    2. Kiyotaki, Nobuhiro & Moore, John, 1997. "Credit Cycles," Journal of Political Economy, University of Chicago Press, vol. 105(2), pages 211-248, April.
    3. Asea, Patrick K. & Blomberg, Brock, 1998. "Lending cycles," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 89-128.
    4. Carlstrom, Charles T & Fuerst, Timothy S, 1997. "Agency Costs, Net Worth, and Business Fluctuations: A Computable General Equilibrium Analysis," American Economic Review, American Economic Association, vol. 87(5), pages 893-910, December.
    5. Pietro Reichlin & Paolo Siconolfi, 2004. "Optimal debt contracts and moral hazard along the business cycle," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 24(1), pages 75-109, July.
    6. Berger, Allen N. & Udell, Gregory F., 2004. "The institutional memory hypothesis and the procyclicality of bank lending behavior," Journal of Financial Intermediation, Elsevier, vol. 13(4), pages 458-495, October.
    7. Bernanke, Ben & Gertler, Mark, 1989. "Agency Costs, Net Worth, and Business Fluctuations," American Economic Review, American Economic Association, vol. 79(1), pages 14-31, March.
    8. Giovanni Dell'Ariccia & Robert Marquez, 2006. "Lending Booms and Lending Standards," Journal of Finance, American Finance Association, vol. 61(5), pages 2511-2546, October.
    9. Rampini, Adriano A., 2004. "Entrepreneurial activity, risk, and the business cycle," Journal of Monetary Economics, Elsevier, vol. 51(3), pages 555-573, April.
    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. Figueroa, Nicolás & Leukhina, Oksana, 2018. "Cash flows and credit cycles," Journal of Banking & Finance, Elsevier, vol. 87(C), pages 318-332.
    2. Figueroa, Nicolás & Leukhina, Oksana, 2015. "Lending terms and aggregate productivity," Journal of Economic Dynamics and Control, Elsevier, vol. 59(C), pages 1-21.
    3. Giovanni Dell’ariccia & Deniz Igan & Luc Laeven, 2012. "Credit Booms and Lending Standards: Evidence from the Subprime Mortgage Market," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44, pages 367-384, March.
    4. Pigini, Claudia & Presbitero, Andrea F. & Zazzaro, Alberto, 2016. "State dependence in access to credit," Journal of Financial Stability, Elsevier, vol. 27(C), pages 17-34.
    5. Rötheli, Tobias F., 2012. "Boundedly rational banks’ contribution to the credit cycle," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 41(5), pages 730-737.
    6. Ebrahimi Kahou, Mahdi & Lehar, Alfred, 2017. "Macroprudential policy: A review," Journal of Financial Stability, Elsevier, vol. 29(C), pages 92-105.
    7. Waters, George A., 2013. "Quantity rationing of credit and the Phillips curve," Journal of Macroeconomics, Elsevier, vol. 37(C), pages 68-80.
    8. Bordo, Michael D. & Haubrich, Joseph G., 2010. "Credit crises, money and contractions: An historical view," Journal of Monetary Economics, Elsevier, vol. 57(1), pages 1-18, January.
    9. Ravn, Søren Hove, 2016. "Endogenous credit standards and aggregate fluctuations," Journal of Economic Dynamics and Control, Elsevier, vol. 69(C), pages 89-111.
    10. Kuncl, Martin, 2019. "Securitization under asymmetric information over the business cycle," European Economic Review, Elsevier, vol. 111(C), pages 237-256.
    11. Delis, Manthos D. & Kouretas, Georgios P. & Tsoumas, Chris, 2014. "Anxious periods and bank lending," Journal of Banking & Finance, Elsevier, vol. 38(C), pages 1-13.
    12. Gabriel Jiménez & Steven Ongena & José-Luis Peydró & Jesús Saurina, 2017. "Macroprudential Policy, Countercyclical Bank Capital Buffers, and Credit Supply: Evidence from the Spanish Dynamic Provisioning Experiments," Journal of Political Economy, University of Chicago Press, vol. 125(6), pages 2126-2177.
    13. Fernández, Ana I. & González, Francisco & Suárez, Nuria, 2016. "Banking stability, competition, and economic volatility," Journal of Financial Stability, Elsevier, vol. 22(C), pages 101-120.
    14. Aysun, Uluc, 2014. "Bankruptcy resolution capacity and economic fluctuations," Journal of Macroeconomics, Elsevier, vol. 40(C), pages 387-399.
    15. Cristiano Cantore & Mathan Satchi, 2009. "Credit Supply and Output Volatility," Studies in Economics 0904, School of Economics, University of Kent.
    16. Uluc Aysun & Raman Khaddaria, 2012. "Bankruptcy resolution capacity and regional economic fluctuations," Working Papers 2012-01, University of Central Florida, Department of Economics.
    17. Stijn Claessens & M Ayhan Kose, 2018. "Frontiers of macrofinancial linkages," BIS Papers, Bank for International Settlements, number 95.
    18. Ander Perez, 2010. "Credit Constraints, Firms' Precautionary Investment, and the Business Cycle," 2010 Meeting Papers 1004, Society for Economic Dynamics.
    19. Nan‐Kuang Chen & Hung‐Jen Wang, 2007. "The Procyclical Leverage Effect Of Collateral Value On Bank Loans—Evidence From The Transaction Data Of Taiwan," Economic Inquiry, Western Economic Association International, vol. 45(2), pages 395-406, April.
    20. Athanasoglou, Panayiotis P. & Daniilidis, Ioannis & Delis, Manthos D., 2014. "Bank procyclicality and output: Issues and policies," Journal of Economics and Business, Elsevier, vol. 72(C), pages 58-83.

    More about this item

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

    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:edj:ceauch:264. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/ceuclcl.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.