BAILOUTS AND CREDIT CYCLES: FANNIE, FREDDIE, AND THE FARM CREDIT SYSTEM

被引:0
|
作者
Hill, Julie Andersen [1 ]
机构
[1] Univ Houston, Ctr Law, Houston, TX 77004 USA
关键词
MARKET; BEHAVIOR; MODEL;
D O I
暂无
中图分类号
D9 [法律]; DF [法律];
学科分类号
0301 ;
摘要
In September 2008, the United States government seized mortgage giants Fannie Mae and Freddie Mac. Since that time, the government has pumped $111 billion of new capital into these government-sponsored enterprises. Yet the future of these companies post-bailout is far from clear. As policymakers consider the future of Fannie and Freddie, it is useful to remember that this is not the first significant bailout of a government-sponsored enterprise. The government also rescued the Farm Credit System in the 1980s. This Article examines the historical cycles in which Fannie, Freddie, and the Farm Credit System have funded loans: they fund more loans in good economic times but fund fewer loans in poor economic times. In other words, they fund loans pro-cyclically with business and credit cycles. By repeatedly providing bailouts, however, government officials demonstrate that they want these government-sponsored enterprises to fund loans in a countercyclical manner. This Article considers the advantages and disadvantages of three possible ways to induce countercyclical behavior. It concludes that policymakers should impose countercyclical capital requirements and create an insurance system funded with risk-based premiums to insure the companies' bonds. It further concludes that, even with these measures, occasional government bailouts may be necessary to stimulate lending during severe economic downturns.
引用
收藏
页码:1 / 77
页数:77
相关论文
共 50 条
  • [21] Coherence and Entropy of Credit Cycles across the Euro Area Candidate Countries
    Criste, Adina
    Lupu, Iulia
    Lupu, Radu
    ENTROPY, 2021, 23 (09)
  • [22] Bank loan loss accounting treatments, credit cycles and crash risk
    Andreou, Panayiotis C.
    Cooper, Ian
    Louca, Christodoulos
    Philip, Dennis
    BRITISH ACCOUNTING REVIEW, 2017, 49 (05) : 474 - 492
  • [23] Leaning against boom-bust cycles in credit and housing prices
    Lambertini, Luisa
    Mendicino, Caterina
    Punzi, Maria Teresa
    JOURNAL OF ECONOMIC DYNAMICS & CONTROL, 2013, 37 (08) : 1500 - 1522
  • [24] Capacity Credit Evaluation of Wind Farm Considering Impact of Turbine Hub Level
    Nga Nguyen
    Almasabi, Saleh
    Mitra, Joydeep
    2019 51ST NORTH AMERICAN POWER SYMPOSIUM (NAPS), 2019,
  • [25] Multi-market credit rationing: The determinants of and impacts on farm performance in Vietnam
    Nguyen Tuan Anh
    Gan, Christopher
    Dao Le Trang Anh
    ECONOMIC ANALYSIS AND POLICY, 2022, 75 : 159 - 173
  • [26] A heterogeneous agent model of credit-linked index insurance and farm technology adoption
    Farrin, Katie
    Miranda, Mario J.
    JOURNAL OF DEVELOPMENT ECONOMICS, 2015, 116 : 199 - 211
  • [27] Assessing optimal credit growth for an emerging banking system
    Jakubik, Petr
    Moinescu, Bogdan
    ECONOMIC SYSTEMS, 2015, 39 (04) : 577 - 591
  • [28] Machine learning and decision support system on credit scoring
    Teles, Gernmanno
    Rodrigues, Joel J. P. C.
    Saleem, Kashif
    Kozlov, Sergei
    Rabelo, Ricardo A. L.
    NEURAL COMPUTING & APPLICATIONS, 2020, 32 (14) : 9809 - 9826
  • [29] Credit risk and the instability of the financial system: An ensemble approach
    Schmitt, Thilo A.
    Chetalova, Desislava
    Schaefer, Rudi
    Guhr, Thomas
    EPL, 2014, 105 (03)
  • [30] Farm expansion under credit constraint: evidence from commercial rice farmers in Guangxi, China
    Chen, Xinjian
    Zeng, Di
    Zhang, Hui
    Kang, Chen
    INTERNATIONAL FOOD AND AGRIBUSINESS MANAGEMENT REVIEW, 2020, 23 (02): : 203 - 215