Working papers results

I review the burgeoning literature on applications of Markov regime switching models in empirical finance. In particular, distinct attention is devoted to the ability of Markov Switching models to fit the data, filter unknown regimes and states on the basis of the data, to allow a powerful tool to test hypothesesformulated in the light of financial theories, and to their forecasting performance with reference to both point and density predictions. The review covers papers concerning a multiplicity of sub-fields in financial economics, ranging from empirical analyses of stock returns, the term structure of default-free interest rates, the dynamics of exchange rates, as well as the joint process of stock and bond returns.

It is often suggested that through a judicious choice of predictors that track business cycles and market sentiment, simple Vector Autoregressive (VAR) models could produce optimal strategic portfolio allocations that hedge against the bull and bear dynamics typical of financial markets. However, a distinct literature exists that shows that nonlinear econometric frameworks, such as Markov switching (MS), are also natural tools to compute optimal portfolios in the presence of stochastic good and bad market states. In this paper we examine whether simple VARs can produce portfolio rules similar to those obtained under MS, by studying the effects of expanding both the order of the VAR and the number/selection of predictor variables included. In a typical stock-bond strategic asset allocation problem, we compute the out-of-sample certainty equivalent returns for a wide range of VARs and compare these measures of performance with those typical of nonlinear models for a long-horizon investor with constant relative risk aversion. We conclude that most VARs cannot produce portfolio rules, hedging demands, or (netof transaction costs) out-of-sample performances that approximate those obtained from equally simple nonlinear frameworks. We also compute the improvement in realized performance that may be achieved adopting more complex MS models and report this may be substantial in the case of regime switching ARCH.

We provide a bridge between Bewley preferences [2] and Uncertainty averse preferences [4]. In doing this, we generalize the findings of Gilboa, Maccheroni, Marinacci, and Schmeidler [11]. To exemplify this new framework, we then study a class of preferences that we call Constrained Multiplier preferences and that was first proposed by Wang [19].

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This article documents and examines the integration of grain markets in Europe across the early modern/late modern divide and across distances and regions. It relies on principal component analysis to identify market structures. The analysis finds that a European market emerged only in the nineteenth century, but the process had earlier roots. In early modern times a fall in trading costs was followed by an increase in market efficiency. Gradually expanding processes of integration unfolded in the long-run. Early modern regional integration was widespread but uneven, with North-Western Europe reaching high levels of integration at a particularly early stage. Low-land European markets tended to be larger and better integrated than in land-locked Europe, especially within large, centralised states. In the nineteenth century, national markets grew in old states, but continental and domestic dynamics had become strictly linked.

We exploit the quasi-random assignment of borrowers to loan officers using data from a large Albanian lender to show that own-gender preferences affect both credit supply and demand. Borrowers matched to officers of the opposite sex are less likely to return for a second loan. The effect is larger when officers have little prior exposure to borrowers of the other gender and when they have more discretion to act on their gender beliefs, as proxied by financial market competition and branch size. We examine one channel of influence, loan conditionality. Borrowers assigned to opposite-sex officers pay higher interest rates and receive lower loan amounts, but do not experience higher arrears. Our results imply that own-gender preferences in the credit market can have substantial negative welfare effects.

We find that Epstein (2010)'s Ellsberg-style thought experiments pose, contrary to his claims, no paradox or difficulty for the smooth ambiguity model of decision making under uncertainty developed by Klibanoff, Marinacci and Mukerji (2005). Not only are the thought experiments naturally handled by the smooth ambiguity model, but our reanalysis shows that they highlight some of its strengths compared to models such as the maxmin expected utility model (Gilboa and Schmeidler (1989)). In particular, these examples pose no challenge to the model's foundations, interpretation of the model as affording a separation of ambiguity and ambiguity attitude or the potential for calibrating ambiguity attitude in the model.

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During a fiscal stimulus, does it matter, for the size of the government spending multiplier, which category of agents bears the brunt of the current and/or future adjustment in taxes? In an economy with heterogeneous agents and imperfect financial markets, the answer depends on whether or not New Keynesian features, such are price rigidity, are present. If prices are flexible, the tax-financing rule is either neutral or quasi-neutral. If prices are sticky, who bears the brunt of the adjustment, whether financially constrained borrowers as opposed to unconstrained savers, does matter. The differential effect on the multiplier, however, depends crucially on (i) the degree of persistence of the fiscal expansion, and (ii) on whether the expansion is balanced-budget as opposed to debt-financed.

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With perfect credit markets, any (lump-sum) tax redistribution is neutral. We study the eects of a tax redistribution in an economy with heterogenous agents and borrowing constraints. Under flexible prices, a tax redistribution that favors 'the poor' (i.e., the credit constrained) is neutral, or, possibly, even mildly contractionary. When nominal prices are sticky, that result is overturned: a tax redistribution from the savers to the constrained borrowers is expansionary on output. Key to the non-neutrality result is the agents' heterogenous sensitivity to movements in the credit premium.

The aim of this paper is to show how the richer frequency and variety of fiscal policy shocks available in an international sample can be analyzed recognizing the heterogeneity that exists across different countries. The main conclusion of our empirical analysis is that the question "what is the fiscal policy multiplier" is an ill-posed one. There is no unconditional fiscal policy multiplier. The effect of fiscal policy on output is different depending on the different debt dynamics, the different degree of openness and the different fiscal reaction functions in different countries. There are many fiscal multipliers and an average fiscal multiplier is of very little use to describe the effect of exogenous shifts in fiscal policy on output.

In this paper we propose a model to forecast future mortality that includes information on the limits to life and on progress in medicine. We apply the model to forecasting future mortality and survival rates for the males population in England andWales. Our proposal ex- tends the benchmark stochastic mortality model along two dimensions. First, we try and deal explicitly with tail risk in the cross-sectional estimation. by including information about the 'limit to life' in the sample used to construct factors for the cross-sectional dimension of mortality rates. Second, we propose to substitute the usual stochastic trend model adopted for the time series of risk factors with a predictive framework based on available evidence on medical progress and causes of death. The model projects very little variability for limits to life over the next ten years and predicts that in 2020 the probability that an individual age 65 will survive until 85 is 20% with an upper bound of 23% and a lower bound of 17%.