Panel discussion monetary policy modeling: where are we and where should we be going?

Monetary policy ; Inflation (Finance) ; Econometric models

Panel discussion

"The Importance of Being Predictable" by John B. Taylor -- "Monetary Policy Under Uncertainty" by Ben S. Bernanke -- "The Importance of Being Predictable" by William PooleMonetary policy

Real-time prediction with U.K. monetary aggregates in the presence of model uncertainty

A popular account for the demise of the U.K.’s monetary targeting regime in the 1980s blames the fluctuating predictive relationships between broad money and inflation and real output growth. Yet ex post policy analysis based on heavily revised data suggests no fluctuations in the predictive content of money. In this paper, we investigate the predictive relationships for inflation and output growth using both real-time and heavily revised data. We consider a large set of recursively estimated vector autoregressive (VAR) and vector error correction models (VECM). These models differ in terms of lag length and the number of cointegrating relationships. We use Bayesian model averaging (BMA) to demonstrate that real-time monetary policymakers faced considerable model uncertainty. The in-sample predictive content of money fluctuated during the 1980s as a result of data revisions in the presence of model uncertainty. This feature is only apparent with real-time data as heavily revised data obscure these fluctuations. Out-of-sample predictive evaluations rarely suggest that money matters for either inflation or real output. We conclude that both data revisions and model uncertainty contributed to the demise of the U.K.’s monetary targeting regime

When Micro Prudence Increases Macro Risk: The Destabilizing Effects of Financial Innovation, Leverage, and Diversification

By exploiting basic common practice accounting and risk-management rules, we propose a simple analytical dynamical model to investigate the effects of microprudential changes on macroprudential outcomes. Specifically, we study the consequence of the introduction of a financial innovation that allows reducing the cost of portfolio diversification in a financial system populated by financial institutions having capital requirements in the form of Value at Risk (VaR) constraint and following standard mark-to-market and risk-management rules. We provide a full analytical quantification of the multivariate feedback effects between investment prices and bank behavior induced by portfolio rebalancing in presence of asset illiquidity and show how changes in the constraints of the bank portfolio optimization endogenously drive the dynamics of the balance sheet aggregate of financial institutions and, thereby, the availability of bank liquidity to the economic system and systemic risk. The model shows that when financial innovation reduces the cost of diversification below a given threshold, the strength (because of higher leverage) and coordination (because of similarity of bank portfolios) of feedback effects increase, triggering a transition from a stationary dynamics of price returns to a nonstationary one characterized by steep growths (bubbles) and plunges (bursts) of market prices

Small versus big-data factor extraction in Dynamic Factor Models: An empirical assessment

In the context of Dynamic Factor Models (DFM), we compare point and interval estimates of the underlying unobserved factors extracted using small and big-data procedures. Our paper differs from previous works in the related literature in several ways. First, we focus on factor extraction rather than on prediction of a given variable in the system. Second, the comparisons are carried out by implementing the procedures considered to the same data. Third, we are interested not only on point estimates but also on confidence intervals for the factors. Based on a simulated system and the macroeconomic data set popularized by Stock and Watson (2012), we show that, for a given procedure, factor estimates based on different cross-sectional dimensions are highly correlated. On the other hand, given the cross-sectional dimension, the Maximum Likelihood Kalman filter and smoother (KFS) factor estimates are highly correlated with those obtained using hybrid Principal Components (PC) and KFS procedures. The PC estimates are somehow less correlated. Finally, the PC intervals based on asymptotic approximations are unrealistically tiny.Financial support from the Spanish Government projects ECO2012-32854 and ECO2012-32401 is acknowledged by the first and second authors respectivel

Investments in recessions

We argue that the strategy literature has been virtually silent on the issue of recessions, and that this constitutes a regrettable sin of omission. A key route to rectify this omission is to focus on how recessions affect investment behavior, and thereby firms stocks of assets and capabilities which ultimately will affect competitive outcomes. In the present paper we aim to contribute by analyzing how two key aspects of recessions, demand reductions and reductions in credit availability, affect three different types of investments: physical capital, R&D and innovation and human- and organizational capital. We point out that recessions not only affect the level of investment, but also the composition of investments. Some of these effects are quite counterintuitive. For example, investments in R&D are more sensitive to credit constraints than physical capital is. Investments in human capital grow as demand falls, and both R&D and human capital investments show important nonlinearities with respect to changes in demand

Can Europe recover without credit?

Data from 135 countries covering five decades suggests that creditless recoveries, in which the stock of real credit does not return to the pre-crisis level for three years after the GDP trough, are not rare and are characterised by remarkable real GDP growth rates: 4.7 percent per year in middle-income countries and 3.2 percent per year in high-income countries. However, the implications of these historical episodes for the current European situation are limited, for two main reasons. First, creditless recoveries are much less common in highincome countries, than in low-income countries which are financially undeveloped. European economies heavily depend on bank loans and research suggests that loan supply played a major role in the recent weak credit performance of Europe. There are reasons to believe that, despite various efforts, normal lending has not yet been restored. Limited loan supply could be disruptive for the European economic recovery and there has been only a minor substitution of bank loans with debt securities. Second, creditless recoveries were associated with significant real exchange rate depreciation, which has hardly occurred so far in most of Europe. This stylised fact suggests that it might be difficult to re-establish economic growth in the absence of sizeable real exchange rate depreciation, if credit growth does not return

Friedman's Money Supply Rule vs. Optimal Interest Rate Policy

Using New Keynesian models, we compare Friedman's k-percent money supply rule to optimal interest rate setting, with respect to determinacy, stability under learning and optimality.We first review the recent literature.Open-loop interest rate rules are subject to indeterminacy and instability problems, but a properly chosen expectations-based rule yields determinacy and stability under learning, and implements optimal policy.We then show that Friedman's rule also can generate equilibria that are determinate and stable under learning.However, in computing the mean quadratic welfare loss, we find that for calibrated models Friedman's rule performs poorly compared to the optimal interest rate rule

Strategies used as spectroscopy of financial markets reveal new stylized facts

We propose a new set of stylized facts quantifying the structure of financial markets. The key idea is to study the combined structure of both investment strategies and prices in order to open a qualitatively new level of understanding of financial and economic markets. We study the detailed order flow on the Shenzhen Stock Exchange of China for the whole year of 2003. This enormous dataset allows us to compare (i) a closed national market (A-shares) with an international market (B-shares), (ii) individuals and institutions and (iii) real investors to random strategies with respect to timing that share otherwise all other characteristics. We find that more trading results in smaller net return due to trading frictions. We unveiled quantitative power laws with non-trivial exponents, that quantify the deterioration of performance with frequency and with holding period of the strategies used by investors. Random strategies are found to perform much better than real ones, both for winners and losers. Surprising large arbitrage opportunities exist, especially when using zero-intelligence strategies. This is a diagnostic of possible inefficiencies of these financial markets.Comment: 13 pages including 5 figures and 1 tabl

Sources of pro-cyclicality in east Asian financial systems

Procyclicality is a normal feature of economic systems, but financial sector weaknesses can exacerbate it sufficiently to pose a threat to macroeconomic and financial stability. These include shortcomings in bank risk management and governance, in supervision and in terms of dependence on volatile sources of funds. The paper tests econometrically for the importance of such features leading to pro-cyclicality in the financial systems of 11 East Asian countries. This analysis makes it possible to identify specific policy measures for East Asian countries that could limit the extent to which financial systems exacerbate pro-cyclicality