|The I Theory of Money||1.31 MB|
A theory of money needs a proper place for financial intermediaries. Intermediaries create money by taking deposits from savers and investing them in productive projects. The money multiplier depends on the size of intermediary balance sheets, and their ability to take risks. In downturns, as lending contracts and the money multiplier shrinks, the value of money rises. This leads to a Fisher deflation that hurts borrowers and amplifies shocks. An accommodative monetary policy in downturns, focused on the assets held by constrained agents, can mitigate these destabilizing adverse feedback effects. We devote particular attention to interest rate cuts, and study the potential for such policies to create moral hazard.
Whether trustworthy record-keeping is better arranged through distributed ledger technology (DLT) or via a centralized intermediary depends on users' ability to detect and respond to misconduct. Blockchains/DLT also rely on miners' competition as miners' free entry rules out any dynamic incentivization via franchise value, the core mechanism the traditional centralized intermediary arrangement relies on. A blockchain is cheaper when intermediary's franchise value is not fragile, e.g. for a too-big-to-fail institution. While blockchains can keep track of transfer of ownership, proper enforcement of possession rights is still needed, except in the case of (fiat) cryptocurrencies.
The recent Great Recession led to a transformational rethinking of Monetary Economics. While prior to the Great Recession the key frictions were price stickiness and wage rigidities, the great recession highlighted the importance of financial frictions. Similarly, financial regulation shifted course. Whereas prior to the crisis the focus was on micro-prudential regulation, measuring the soundness and risks of individual banks in isolation, current thinking stresses the importance of macro-prudential regulation with its focus on spillover risks. Several new systemic risk measures were proposed. The course would also cover interaction between monetary policy and macro-prudential policy as well as spillover analysis and the implications for the international financial architecture. Given this fundamental rethinking and Princeton’s leading role in developing the new conceptual framework, this course would (i) expose students to these new research trends and also (ii) contrasts it with the established New Keynesian framework.
In terms of economic methodology, the course would teach students new advanced tools, including formal modeling, economic dynamical systems in continuous time, strategic interactions, asymmetric information, and modern welfare analysis. The empirical component would range from model estimation, calibration to reduced form analysis. There is strong interest from many Ph.D. students, and expect that advanced undergraduate and possibly for Master students will also take this course.
We examine the relation among measures of credit expansion, measures of financial market stress, and standard macroeconomic aggregates. We use a form of structural VAR with monthly data on 10 variables. The model explains observed variation as driven by 10 mutually independent structural disturbances. We identify the shocks from variation across time in their relative variability. One of them emerges as representing monetary policy. We find two distinct financial stress shocks, suggesting that attempts to create a one-dimensional index of financial stress may be misguided. While our results are consistent with the finding by others of a negative reduced form relation between credit expansion and future output growth at certain frequencies, we find the output decline to be explained by the monetary policy response to the inflation that accompanies the credit expansion. In pseudo-out-of-sample forecasting tests, neither bond spreads, interbank spreads, nor credit aggregates had much predictive value far in advance of the 2008-9 downturn, though spreads (but not credit aggregates) were helpful in recognizing the downturn once it had begun.
China's economic model involves active government intervention in financial markets. It relaxes/tightens market regulations and even directs asset trading with the objective to maintain market stability. We develop a theoretical framework that anchors government intervention on a mission to prevent market breakdown and the explosion of volatility caused by the reluctance of short-term investors to trade against noise traders when the risk of trading against them is sufficiently large. In the presence of realistic information frictions about unobservable asset fundamentals, our framework shows that the government can alter market dynamics by making noise in its intervention program an additional factor driving asset prices, and can divert investor attention toward acquiring information about this noise rather than fundamentals. Through this latter channel, the widely-adopted objective of government intervention to reduce asset price volatility may exacerbate, rather than improve, the information efficiency of asset prices.
China’s gradualistic approach allowed the government to learn how the economy reacts to small policy changes, and to adjust its reforms before implementing them in full. With fully developed financial markets, however, private actors’ may front-run future policy changes making it impossible for the implement policies gradually. With financial markets the government faces a time-inconsistency problem. The government would like to commit to a gradualistic approach, but after it observes the economy’s quick reaction, it has no incentive to implement its policies in small steps.