Nominal versus indexed debt: A quantitative horse race

The main arguments in favor and against nominal and indexed debts are the incentive to default through inflation versus hedging against unforeseen shocks. We model and calibrate these arguments to assess their quantitative importance. We use a dynamic equilibrium model with tax distortion, government outlays uncertainty, and contingent-debt service. Our framework also recognizes that contingent debt can be associated with incentive problems and lack of commitment. Thus, the benefits of unexpected inflation are tempered by higher interest rates. We obtain that costs from inflation more than offset the benefits from reducing tax distortions. We further discuss sustainability of nominal debt in developing (volatile) countries.     

Back to square one: Identification issues in DSGE models

We investigate identification issues in DSGE models and their consequences for parameter estimation and model evaluation when the objective function measures the distance between estimated and model-based impulse responses. Observational equivalence, partial and weak identification problems are widespread and typically produced by an ill-behaved mapping between the structural parameters and the coefficients of the solution. Different objective functions affect identification and small samples interact with parameters identification. Diagnostics to detect identification deficiencies are provided and applied to a widely used model.     

Have changes in the financial structure affected bank profitability? Evidence for Austria

We examine the impact of changes in the financial structure of the Austrian banking sector over the past 15 years, such as disintermediation, internationalization and privatization, on the profitability of banks. Several proxies based on bank balance sheet data at the micro-level as well as macroeconomic variables are used to capture these changes. The case of Austria is particularly interesting because the opening up of the Austrian banking sector due to EU accession and the strong engagement of Austrian banks in Eastern Europe coincided with the global trend toward deregulation of banking activities. Our estimation results, which are based on dynamic panel regression methods, indicate that disintermediation (a lower percentage of loans over total assets) and higher market concentration in the banking sector had a positive effect on bank profitability, while changes in the ownership structure (privatization and increased foreign ownership) as well as more foreign lending by Austrian banks did not have a clear-cut or significant impact on bank profits.     

Ben Fine (2001) Social Capital versus Social Theory: Political Economy and Social Science at the Turn of the Millennium

Book reviewed in this article:
Ben Fine, Social Capital versus Social Theory: Political Economy and Social Science at the Turn of the Millennium     

MONETARY POLICY WITH A WIDER INFORMATION SET: A BAYESIAN MODEL AVERAGING APPROACH

Monetary policy has been usually analyzed in the context of small macroeconomic models where central banks are allowed to exploit a limited amount of information. Under these frameworks, researchers typically derive the optimality of aggressive monetary rules, contrasting with the observed policy conservatism and interest rate smoothing. This paper allows the central bank to exploit a wider information set, while taking into account the associated model uncertainty, by employing Bayesian model averaging with Markov chain model composition. In this enriched environment, we derive the optimality of smoother and more cautious policy rates, together with clear gains in macroeconomic efficiency.     

Forecasting distress in cooperative banks: The role of asset quality

This paper analyzes the drivers of financial distress that were experienced by small Italian cooperative banks during the latest deep recession, focusing mainly on the importance of bank capital as a predictor of bankruptcy for Italian nonprofit banks. The analysis aims to build an early-warning model that is suitable for this type of bank.The results reveal non-monotonic effects of bank capital on the probability of failure. In contrast to distress models for for-profit banks, non-performing loans, profitability, liquidity, and management quality have a negligible predictive value. The findings also show that unreserved impaired loans have an important impact on the probability of bank distress. Moreover, the loan–loss ratio provision on substandard loans constitutes a suitable antibody against bank distress. Overall, the results are robust in terms of both the methodology (i.e., frequentist and Bayesian approaches) and the sample used (i.e., cooperative banks in Italy and euro-area countries).     

Estimating and Forecasting the Yield Curve Using A Markov Switching Dynamic Nelson and Siegel Model

We estimate versions of the Nelson–Siegel model of the yield curve of US government bonds using a Markov switching latent variable model that allows for discrete changes in the stochastic process followed by the interest rates. Our modeling approach is motivated by evidence suggesting the existence of breaks in the behavior of the US yield curve that depend, for example, on whether the economy is in a recession or a boom, or on the stance of monetary policy. Our model is parsimonious, relatively easy to estimate and flexible enough to match the changing shapes of the yield curve over time. We also derive the discrete time non‐arbitrage restrictions for the Markov switching model. We compare the forecasting performance of these models with that of the standard dynamic Nelson and Siegel model and an extension that allows the decay rate parameter to be time varying. We show that some parametrizations of our model with regime shifts outperform the single‐regime Nelson and Siegel model and other standard empirical models of the yield curve. Copyright © 2014 John Wiley & Sons, Ltd.     

Balancing the additional costs of purchasing and the vendor set dimension to reduce public procurement costs

The paper addresses the reduction of the total cost of purchasing in public procurement, focusing on tenders called for in the European Union and awarded by the Lowest Price (LP) criterion. Taking into account the main characteristic features of governmental purchasing (competition, prescribed procedures, and transparency) and building upon the related contributions in the literature, we present a probabilistic approach for evaluating and limiting the total cost of purchasing in public tenders awarded according to the LP criterion. The presented framework includes the evaluation of the so-called additional costs of purchasing (ACP), a part of the transaction cost that is typically considered in the related literature from a private organization perspective only. The approach can be applied to a generic transaction in any public tender issued according to the European legislation with the LP criterion. Considering the real case study of the public tender for maintenance works on a municipal sport facility in Bari (Italy), we take into account the costs of both transaction counterparts, i.e., the ACP regarding the contracting authority and those related to the firms involved in the tender. Applying the model to the case study, we underline the relevance of ACP for public tenders and show that, by inviting a suitable number of bidders to participate in the call, it is possible to save money both for the contracting authority and the involved competitors.