This thesis addresses three relevant macroeconomic issues: (i) why<p>Central Banks behave so cautiously compared to optimal theoretical<p>benchmarks, (ii) do monetary variables add information about<p>future Euro Area inflation to a large amount of non monetary<p>variables and (iii) why national saving and investment are so<p>correlated in OECD countries in spite of the high degree of<p>integration of international financial markets.<p><p>The process of innovation in the elaboration of economic theory<p>and statistical analysis of the data witnessed in the last thirty<p>years has greatly enriched the toolbox available to<p>macroeconomists. Two aspects of such a process are particularly<p>noteworthy for addressing the issues in this thesis: the<p>development of macroeconomic dynamic stochastic general<p>equilibrium models (see Woodford, 1999b for an historical<p>perspective) and of techniques that enable to handle large data<p>sets in a parsimonious and flexible manner (see Reichlin, 2002 for<p>an historical perspective).<p><p>Dynamic stochastic general equilibrium models (DSGE) provide the<p>appropriate tools to evaluate the macroeconomic consequences of<p>policy changes. These models, by exploiting modern intertemporal<p>general equilibrium theory, aggregate the optimal responses of<p>individual as consumers and firms in order to identify the<p>aggregate shocks and their propagation mechanisms by the<p>restrictions imposed by optimizing individual behavior. Such a<p>modelling strategy, uncovering economic relationships invariant to<p>a change in policy regimes, provides a framework to analyze the<p>effects of economic policy that is robust to the Lucas'critique<p>(see Lucas, 1976). The early attempts of explaining business<p>cycles by starting from microeconomic behavior suggested that<p>economic policy should play no role since business cycles<p>reflected the efficient response of economic agents to exogenous<p>sources of fluctuations (see the seminal paper by Kydland and Prescott, 1982}<p>and, more recently, King and Rebelo, 1999). This view was challenged by<p>several empirical studies showing that the adjustment mechanisms<p>of variables at the heart of macroeconomic propagation mechanisms<p>like prices and wages are not well represented by efficient<p>responses of individual agents in frictionless economies (see, for<p>example, Kashyap, 1999; Cecchetti, 1986; Bils and Klenow, 2004 and Dhyne et al. 2004). Hence, macroeconomic models currently incorporate<p>some sources of nominal and real rigidities in the DSGE framework<p>and allow the study of the optimal policy reactions to inefficient<p>fluctuations stemming from frictions in macroeconomic propagation<p>mechanisms.<p><p>Against this background, the first chapter of this thesis sets up<p>a DSGE model in order to analyze optimal monetary policy in an<p>economy with sectorial heterogeneity in the frequency of price<p>adjustments. Price setters are divided in two groups: those<p>subject to Calvo type nominal rigidities and those able to change<p>their prices at each period. Sectorial heterogeneity in price<p>setting behavior is a relevant feature in real economies (see, for<p>example, Bils and Klenow, 2004 for the US and Dhyne, 2004 for the Euro<p>Area). Hence, neglecting it would lead to an understatement of the<p>heterogeneity in the transmission mechanisms of economy wide<p>shocks. In this framework, Aoki (2001) shows that a Central<p>Bank maximizing social welfare should stabilize only inflation in<p>the sector where prices are sticky (hereafter, core inflation).<p>Since complete stabilization is the only true objective of the<p>policymaker in Aoki (2001) and, hence, is not only desirable<p>but also implementable, the equilibrium real interest rate in the<p>economy is equal to the natural interest rate irrespective of the<p>degree of heterogeneity that is assumed. This would lead to<p>conclude that stabilizing core inflation rather than overall<p>inflation does not imply any observable difference in the<p>aggressiveness of the policy behavior. While maintaining the<p>assumption of sectorial heterogeneity in the frequency of price<p>adjustments, this chapter adds non negligible transaction<p>frictions to the model economy in Aoki (2001). As a<p>consequence, the social welfare maximizing monetary policymaker<p>faces a trade-off among the stabilization of core inflation,<p>economy wide output gap and the nominal interest rate. This<p>feature reflects the trade-offs between conflicting objectives<p>faced by actual policymakers. The chapter shows that the existence<p>of this trade-off makes the aggressiveness of the monetary policy<p>reaction dependent on the degree of sectorial heterogeneity in the<p>economy. In particular, in presence of sectorial heterogeneity in<p>price adjustments, Central Banks are much more likely to behave<p>less aggressively than in an economy where all firms face nominal<p>rigidities. Hence, the chapter concludes that the excessive<p>caution in the conduct of monetary policy shown by actual Central<p>Banks (see, for example, Rudebusch and Svennsson, 1999 and Sack, 2000) might not<p>represent a sub-optimal behavior but, on the contrary, might be<p>the optimal monetary policy response in presence of a relevant<p>sectorial dispersion in the frequency of price adjustments.<p><p>DSGE models are proving useful also in empirical applications and<p>recently efforts have been made to incorporate large amounts of<p>information in their framework (see Boivin and Giannoni, 2006). However, the<p>typical DSGE model still relies on a handful of variables. Partly,<p>this reflects the fact that, increasing the number of variables,<p>the specification of a plausible set of theoretical restrictions<p>identifying aggregate shocks and their propagation mechanisms<p>becomes cumbersome. On the other hand, several questions in<p>macroeconomics require the study of a large amount of variables.<p>Among others, two examples related to the second and third chapter<p>of this thesis can help to understand why. First, policymakers<p>analyze a large quantity of information to assess the current and<p>future stance of their economies and, because of model<p>uncertainty, do not rely on a single modelling framework.<p>Consequently, macroeconomic policy can be better understood if the<p>econometrician relies on large set of variables without imposing<p>too much a priori structure on the relationships governing their<p>evolution (see, for example, Giannone et al. 2004 and Bernanke et al. 2005).<p>Moreover, the process of integration of good and financial markets<p>implies that the source of aggregate shocks is increasingly global<p>requiring, in turn, the study of their propagation through cross<p>country links (see, among others, Forni and Reichlin, 2001 and Kose et al. 2003). A<p>priori, country specific behavior cannot be ruled out and many of<p>the homogeneity assumptions that are typically embodied in open<p>macroeconomic models for keeping them tractable are rejected by<p>the data. Summing up, in order to deal with such issues, we need<p>modelling frameworks able to treat a large amount of variables in<p>a flexible manner, i.e. without pre-committing on too many<p>a-priori restrictions more likely to be rejected by the data. The<p>large extent of comovement among wide cross sections of economic<p>variables suggests the existence of few common sources of<p>fluctuations (Forni et al. 2000 and Stock and Watson, 2002) around which<p>individual variables may display specific features: a shock to the<p>world price of oil, for example, hits oil exporters and importers<p>with different sign and intensity or global technological advances<p>can affect some countries before others (Giannone and Reichlin, 2004). Factor<p>models mainly rely on the identification assumption that the<p>dynamics of each variable can be decomposed into two orthogonal<p>components - common and idiosyncratic - and provide a parsimonious<p>tool allowing the analysis of the aggregate shocks and their<p>propagation mechanisms in a large cross section of variables. In<p>fact, while the idiosyncratic components are poorly<p>cross-sectionally correlated, driven by shocks specific of a<p>variable or a group of variables or measurement error, the common<p>components capture the bulk of cross-sectional correlation, and<p>are driven by few shocks that affect, through variable specific<p>factor loadings, all items in a panel of economic time series.<p>Focusing on the latter components allows useful insights on the<p>identity and propagation mechanisms of aggregate shocks underlying<p>a large amount of variables. The second and third chapter of this<p>thesis exploit this idea.<p><p>The second chapter deals with the issue whether monetary variables<p>help to forecast inflation in the Euro Area harmonized index of<p>consumer prices (HICP). Policymakers form their views on the<p>economic outlook by drawing on large amounts of potentially<p>relevant information. Indeed, the monetary policy strategy of the<p>European Central Bank acknowledges that many variables and models<p>can be informative about future Euro Area inflation. A peculiarity<p>of such strategy is that it assigns to monetary information the<p>role of providing insights for the medium - long term evolution of<p>prices while a wide range of alternative non monetary variables<p>and models are employed in order to form a view on the short term<p>and to cross-check the inference based on monetary information.<p>However, both the academic literature and the practice of the<p>leading Central Banks other than the ECB do not assign such a<p>special role to monetary variables (see Gali et al. 2004 and<p>references therein). Hence, the debate whether money really<p>provides relevant information for the inflation outlook in the<p>Euro Area is still open. Specifically, this chapter addresses the<p>issue whether money provides useful information about future<p>inflation beyond what contained in a large amount of non monetary<p>variables. It shows that a few aggregates of the data explain a<p>large amount of the fluctuations in a large cross section of Euro<p>Area variables. This allows to postulate a factor structure for<p>the large panel of variables at hand and to aggregate it in few<p>synthetic indexes that still retain the salient features of the<p>large cross section. The database is split in two big blocks of<p>variables: non monetary (baseline) and monetary variables. Results<p>show that baseline variables provide a satisfactory predictive<p>performance improving on the best univariate benchmarks in the<p>period 1997 - 2005 at all horizons between 6 and 36 months.<p>Remarkably, monetary variables provide a sensible improvement on<p>the performance of baseline variables at horizons above two years.<p>However, the analysis of the evolution of the forecast errors<p>reveals that most of the gains obtained relative to univariate<p>benchmarks of non forecastability with baseline and monetary<p>variables are realized in the first part of the prediction sample<p>up to the end of 2002, which casts doubts on the current<p>forecastability of inflation in the Euro Area.<p><p>The third chapter is based on a joint work with Domenico Giannone<p>and gives empirical foundation to the general equilibrium<p>explanation of the Feldstein - Horioka puzzle. Feldstein and Horioka (1980) found<p>that domestic saving and investment in OECD countries strongly<p>comove, contrary to the idea that high capital mobility should<p>allow countries to seek the highest returns in global financial<p>markets and, hence, imply a correlation among national saving and<p>investment closer to zero than one. Moreover, capital mobility has<p>strongly increased since the publication of Feldstein - Horioka's<p>seminal paper while the association between saving and investment<p>does not seem to comparably decrease. Through general equilibrium<p>mechanisms, the presence of global shocks might rationalize the<p>correlation between saving and investment. In fact, global shocks,<p>affecting all countries, tend to create imbalance on global<p>capital markets causing offsetting movements in the global<p>interest rate and can generate the observed correlation across<p>national saving and investment rates. However, previous empirical<p>studies (see Ventura, 2003) that have controlled for the effects<p>of global shocks in the context of saving-investment regressions<p>failed to give empirical foundation to this explanation. We show<p>that previous studies have neglected the fact that global shocks<p>may propagate heterogeneously across countries, failing to<p>properly isolate components of saving and investment that are<p>affected by non pervasive shocks. We propose a novel factor<p>augmented panel regression methodology that allows to isolate<p>idiosyncratic sources of fluctuations under the assumption of<p>heterogenous transmission mechanisms of global shocks. Remarkably,<p>by applying our methodology, the association between domestic<p>saving and investment decreases considerably over time,<p>consistently with the observed increase in international capital<p>mobility. In particular, in the last 25 years the correlation<p>between saving and investment disappears.<p> / Doctorat en sciences économiques, Orientation économie / info:eu-repo/semantics/nonPublished