Nikolov, Kalin Ognianov
(2010)
Credit frictions and the macroeconomy.
PhD thesis, London School of Economics and Political Science.
Abstract
The unifying theme in my PhD thesis is the effect that credit market imperfections have on aggregate outcomes. My main interest is in the collateral amplification mechanism and on the welfare effects that economic shocks and policies have on different groups in society. In my first chapter (which is joint with Nobu Kiyotaki and Alex Michaelides), we develop a life-cycle model of a production economy in which land and capital are used to build residential and commercial real estate. We find that, in an economy where the share of land in the value of real estates is large, housing prices react more to an exogenous change in expected productivity or the world interest rate, causing a large redistribution between net buyers and net sellers of houses. Changing financing constraints, however, has limited effects on housing prices. My second and third chapters examine environments with credit constrained entrepreneurs similarly to the original Kiyotaki and Moore (1997) paper. My second chapter asks the question of whether tightening capital requirements may be welfare improving when firms face credit constraints. I find that the answer is 'no'. Although tightening the collateral constraint dampens business cycle fluctuations, the first order cost in terms of reduced access to credit is too great. My third chapter examines the extent to which a borrower's reputation for repayment can serve as intangible collateral, thus explaining the movement of downpayment requirements over the business cycle. The main finding is that, under standard technology shocks, down-payments move in a pro-cyclical fashion. Introducing a pro-cyclical productivity gap between firms as well as counter-cyclical degree of idiosyncratic production risk helps to generate counter-cyclical down-payment requirements.
Actions (login required)
 |
Record administration - authorised staff only |
Download statistics
Download statistics