The response of real wages to unanticipated money growth

This paper investigates the response of real wages to unanticipated money growth in the light of equilibrium theories of the business cycle. These theories, in their main different versions, do not deliver a common and unambiguous hypothesis on this issue. While some models implu a countercyclical real wage response during monetary cycles, others yield the opposite result of a procyclical real wage. Econometric analysis of annual and quarterly U.S. data, reported in the paper, indicates that there is a weak negative real wage response to an unanticipated increase in money growth.     

Soft versus hard targets for exchange rate intervention

Exchange rate intervention by monetary authorities should defend a band not for the spot exchange rate, but for a moving average of its recent values. This target zone is soft, in that it allows greater short-run flexibility, but also rigorous: it still precludes any sustained easing of monetary policy. In comparison with conventional hard target zones for the spot exchange rate, we find considerable advantages for the rule we propose. In particular, without compromising long-run discipline, it increases resilience against speculative attacks, especially when shocks to exchange rate fundamentals are transitory.     

Sudden Stops,Time Inconsistency,and the Duration of Sovereign Debt

We study the sovereign debt duration chosen by the government in the context of a standard model of sovereign default. The government balances off increasing the duration of its debt to mitigate rollover risk and lowering duration to mitigate the debt dilution problem. We present two main results. First, when the government decides the debt duration on a sequential basis, sudden stop risk increases the average duration by 1 year. Second, we illustrate the time inconsistency problem in the choice of sovereign debt duration: governments would like to commit to a duration that is 1.7 years shorter than the one they choose when decisions are made sequentially.     

Relative forecasting performance of volatility models: Monte Carlo evidence

Abstract

A Monte Carlo (MC) experiment is conducted to study the forecasting performance of a variety of volatility models under alternative data-generating processes (DGPs). The models included in the MC study are the (Fractionally Integrated) Generalized Autoregressive Conditional Heteroskedasticity models ((FI)GARCH), the Stochastic Volatility model (SV), the Long Memory Stochastic Volatility model (LMSV) and the Markov-switching Multifractal model (MSM). The MC study enables us to compare the relative forecasting performance of the models accounting for different characterizations of the latent volatility process: specifications that incorporate short/long memory, autoregressive components, stochastic shocks, Markov-switching and multifractality. Forecasts are evaluated by means of mean squared errors (MSE), mean absolute errors (MAE) and value-at-risk (VaR) diagnostics. Furthermore, complementarities between models are explored via forecast combinations. The results show that (i) the MSM model best forecasts volatility under any other alternative characterization of the latent volatility process and (ii) forecast combinations provide systematic improvements upon most single misspecified models, but are typically inferior to the MSM model even if the latter is applied to data governed by other processes.     

Are there asymmetries in the response of bank interest rates to monetary shocks?

This article examines the velocity and asymmetry of the response of bank interest rates to monetary policy shocks. Using an asymmetric vector error correction model, it analyses the pass-through of changes in money market rates to retail bank interest rates in Italy in the period 1985–2002. The main results of the article are: (1) the speed of adjustment of bank interest rates to monetary policy changes increased significantly after the introduction of the 1993 Consolidated Law on Banking; (2) interest rate adjustment in response to positive and negative shocks is asymmetric in the short run, but not in the long run; (3) banks adjust their loan (deposit) rate faster during periods of monetary tightening (easing); (4) this asymmetry almost vanished since the 1990s.     

Scoring environmental credentials: a review of UK conference and meetings venues using the GREENER VENUE framework

This paper investigates frameworks to conceptualise, monitor and compare corporate social responsibility (CSR) performance at individual conference venues, and provides a new comparative framework that organises and communicates information detailing business performance on 10 environmental policy initiatives (EPIs) (expressed by the acronym “GREENER”) using a CSR scale (expressed by the acronym “VENUE”). This GREENER VENUE framework reduces the gap in the CSR literature by accentuating discretionary practices, and by exhibiting conceptual and psychometric properties enabling the framework's application to broad and diverse contexts. Its use is grounded in theory: the framework is practical, simple to implement, easily understandable and highly relatable. Applying the GREENER VENUE framework to data collected via a self-administered internet questionnaire of 191 UK conference and meeting venues reveals that the biggest groups of such venues are classified as “Eager” on a rising scale from Eternal denial (11%), through Unmotivated (16%), to Nonchalant (30%) and so to Eager (36%), and finally, the top group, Venerated (7%). The paper also investigates the relative influence of all 10 EPI variables of the GREENER measure – considered simultaneously – towards enhancing firms’ behaviour on an inventory of 18 well-known environmental best practices (EBPIs).     

Model risk adjusted hedge ratios

Most option pricing models assume all parameters except volatility are fixed; yet they almost invariably change on re‐calibration. This article explains how to capture the model risk that arises when parameters that are assumed constant have calibrated values that change over time and how to use this model risk to adjust the price hedge ratios of the model. Empirical results demonstrate an improvement in hedging performance after the model risk adjustment. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 29:1021–1049, 2009     

Learning non-rational expectations equilibria

A hyperinflation model is analyzed under bounded rationality learning. Agents believe in a misspecified model which is correctly specified at theRational Expectations Equilibrium of the model and they adjust their beliefs by means of theLeast Mean Squares algorithm. Convergence of the bounded rationality learning activity to anon-Rational Expectations Equilibrium point is obtained for any set of parameters of the model.

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Sommario In questo lavoro gli autori analizzano il modello di iperinflazioneà la Cagan sotto l'ipotesi di razionalità limitata. Gli agenti non formano le loro aspettative coerentemente con la struttura completa del modello economico, essi si basano su un modello lineare non correttamente specificato che risulta essere corretto soltanto in corrispondenza dell'equilibrio con aspettative razionali. Si ipotizza che i soggetti aggiornino le loro aspettative tramite un algoritmo di apprendimento. Nel caso specifico, l'algoritmo adottato è ilLeast Mean Squares. Il principale risultato del lavoro è che l'apprendimento con razionalità limitata da parte dei soggetti economici può convergere ad un punto che non è un equilibrio con aspettative razionali. Il risultato è particolarmente interessante poiché la maggior parte degli studi noti in questa letteratura, nonostante non assicurino la convergenza ad un equilibrio con aspettative razionali, assicurano la non convergenza ad un equilibrio che non sia di aspecttative razionali. La convergenza ad un equilibrio non di aspettative razionali è dovuta ad una non corretta specificazione del modello secondo cui i soggetti formano le loro aspettative. In particolare, la convergenza ad un equilibrio non di aspettative razionali si verifica allorché i soggetti non tengono conto nel loro apprendimento di una variabile rilevante che essi classificano come rumore bianco.

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Authors would like to thank an anonymous referee and all of those who gave comments and suggestions at theSociety of Economic Dynamics and Control Conference (SEDC) '94 (Los Angeles, CA-USA);International Conference on Artificial Neural Networks (ICANN) '94 (Salerno, Italy);World Conference on Neural Networks (WCNN) '94 (San Diego, CA-USA);AMASES '94 Conference (Modena, Italy). The usual disclaimers apply.