This thesis examines empirical and theoretical issues related to the role of uninsurable individual risk and heterogeneity in macroeconomics. The thesis includes four chapters. The first chapter uses data from the Panel Study of Income Dynamics (PSID) to test full risk-sharing among North American households. The second chapter is a short essay where I use simulated data to show how the method applied in the previous chapter can be used to distinguish between partial risk sharing and imperfect credit markets. The third chapter develops a heterogeneous agent dynamic general equilibrium model which jointly models aggregate saving and employment. Finally, the fourth chapter investigates empirically the ability of financial market incompleteness to help explaining the equity premium puzzle. The central motivation throughout this dissertation is the recognition that the interaction between cross-sectional volatility and aggregate volatility is of fundamental importance to understand the way we should model macroeconomic aggregates such as aggregate consumption, asset prices and business cycle fluctuations.<p><p> / Doctorat en Sciences économiques et de gestion / info:eu-repo/semantics/nonPublished

This study argues that governments with sustained GDP growth, open markets, low country risk, high levels and low standard deviation of government performance, and few or no occurrences of war, will see larger levels of foreign direct investment (FDI) over time. Scholarship on the determinants of FDI variously argues the influence of GDP growth, the openness of a country's economy, a government's level of political capacity, the level of country risk, and the negative effects of inter-, intra- and extrastate conflict. These studies on the various effects on FDI, while providing insightful and substantial statistical results, fail to capture the simultaneous effects of macroeconomic, government performance, country risk, and war variables. The present study attempts to resolve this gap in the literature on FDI by proposing a multi-dimensional model of the combined effects of un-weighted macroeconomic, political, country risk, and war variables on FDI flows over time. The empirical results confirm the expected multi-dimensional nature of FDI flows over time and provide insight into the macroeconomic and political effects on regional and country-level yearly flows of FDI, as well as yielding some unexpected and counter-intuitive results of the role war plays on FDI flows over time.

Along this dissertation I propose to walk the reader through several macroeconomic<p>implications of information asymmetries, with a special focus on financial<p>issues. This exercise is mainly theoretical: I develop stylized models that aim<p>at capturing macroeconomic phenomena such as self-fulfilling liquidity dry-ups,<p>the rise and the fall of securitization markets, and the creation of systemic risk.<p>The dissertation consists of three chapters. The first one proposes an explanation<p>to self-fulfilling liquidity dry-ups. The second chapters proposes a formalization<p>of the concept of market discipline and an application to securitization<p>markets as risk-sharing mechanisms. The third one offers a complementary<p>analysis to the second as the rise of securitization is presented as banker optimal<p>response to strict capital constraints.<p>Two concepts that do not have unique acceptations in economics play a central<p>role in these models: liquidity and market discipline.<p>The liquidity of an asset refers to the ability for his owner to transform it into<p>current consumption goods. Secondary markets for long-term assets play thus<p>an important role with that respect. However, such markets might be illiquid due<p>to adverse selection.<p>In the first chapter, I show that: (1) when agents expect a liquidity dry-up<p>on such markets, they optimally choose to self-insure through the hoarding of<p>non-productive but liquid assets; (2) this hoarding behavior worsens adverse selection and dries up market liquidity; (3) such liquidity dry-ups are Pareto inefficient<p>equilibria; (4) the government can rule them out. Additionally, I show<p>that idiosyncratic liquidity shocks à la Diamond and Dybvig have stabilizing effects,<p>which is at odds with the banking literature. The main contribution of the<p>chapter is to show that market breakdowns due to adverse selection are highly<p>endogenous to past balance-sheet decisions.<p>I consider that agents are under market discipline when their current behavior<p>is influenced by future market outcomes. A key ingredient for market discipline<p>to be at play is that the market outcome depends on information that is observable<p>but not verifiable (that is, information that cannot be proved in court, and<p>consequently, upon which enforceable contracts cannot be based).<p>In the second chapter, after introducing this novel formalization of market<p>discipline, I ask whether securitization really contributes to better risk-sharing:<p>I compare it with other mechanisms that differ on the timing of risk-transfer. I<p>find that for securitization to be an efficient risk-sharing mechanism, it requires<p>market discipline to be strong and adverse selection not to be severe. This seems<p>to seriously restrict the set of assets that should be securitized for risk-sharing<p>motive.<p>Additionally, I show how ex-ante leverage may mitigate interim adverse selection<p>in securitization markets and therefore enhance ex-post risk-sharing. This<p>is interesting because high leverage is usually associated with “excessive” risktaking.<p>In the third chapter, I consider risk-neutral bankers facing strict capital constraints;<p>their capital is indeed required to cover the worst-case-scenario losses.<p>In such a set-up, I find that: 1) banker optimal autarky response is to diversify<p>lower-tail risk and maximize leverage; 2) securitization helps to free up capital<p>and to increase leverage, but distorts incentives to screen loan applicants properly; 3) market discipline mitigates this problem, but if it is overestimated by<p>the supervisor, it leads to excess leverage, which creates systemic risk. Finally,<p>I consider opaque securitization and I show that the supervisor: 4) faces uncertainty<p>about the trade-off between the size of the economy and the probability<p>and the severity of a systemic crisis; 5) can generally not set capital constraints<p>at the socially efficient level. / Doctorat en Sciences économiques et de gestion / info:eu-repo/semantics/nonPublished

Doctorat en Sciences politiques et sociales / info:eu-repo/semantics/nonPublished

The contribution of this thesis is to build a small macro-econometric model of the Namibian economy, which demonstrates that there is significant statistical support for the hypothesis that there is a contemporaneous relationship between real wage, productivity, unemployment and interest rates in Namibia. This phenomenon has not yet been exploited using macro-econometric modelling, and thus, represents a significant contribution to modelling literature in Namibia. The determination of the sources of unemployment also receives special attention given that high unemployment is a chronic problem in Namibia. All models specified and estimated in the study use the SVAR methodology for the period 1980 to 2013. The study develops a small macro-econometric model using three modular experiments, which include, a basic model, models that separately append demand and exchange rate channels variables to the basic model, and the specification of a small macro-econometric model. The ultimate aim is to find out if monetary policy plays a role in influencing labour market and nominal variables. The hypothesis that the basic real wage, productivity, unemployment rate and interest rate system can be estimated simultaneously is validated. Further, demand and exchange rate channels variables are found to have important additional information, which explains the monetary transmission process, and that shocks to labour market variables affect monetary policy in Namibia. The results also show that the demand channel (import prices and bank credit to the private sector) and the exchange rate channel (nominal exchange rate) variables have important additional information, which affects monetary transmission process in Namibia, which justifies their inclusion in the small macro-econometric model. In addition, shocks to the import price and exchange rate in the macro-econometric model significantly affect labour market variables. However, shocks to bank credit only partially perform as expected, implying that its results need to be considered cautiously. The study further finds that tight monetary policy shocks significantly affect real and nominal variables in Namibia. The results also show that shocks to all variables in the unemployment model significantly affect unemployment, suggesting that the hysteresis assumption is corroborated. This implies that long run aggregate demand is non-neutral in Namibia. / Economics / D. Litt. et Phil. (Economics)

The active use of macroeconomic policies to smooth economic fluctuations and, as a<p>consequence, the stance that policymakers should adopt over the business cycle, remain<p>controversial issues in the economic literature.<p>In the light of the dramatic experience of the early 1930s’ Great Depression, Keynes (1936)<p>argued that the market mechanism could not be relied upon to spontaneously recover from<p>a slump, and advocated counter-cyclical public spending and monetary policy to stimulate<p>demand. Albeit the Keynesian doctrine had largely influenced policymaking during<p>the two decades following World War II, it began to be seriously challenged in several<p>directions since the start of the 1970s. The introduction of rational expectations within<p>macroeconomic models implied that aggregate demand management could not stabilize<p>the economy’s responses to shocks (see in particular Sargent and Wallace (1975)). According<p>to this view, in fact, rational agents foresee the effects of the implemented policies, and<p>wage and price expectations are revised upwards accordingly. Therefore, real wages and<p>money balances remain constant and so does output. Within such a conceptual framework,<p>only unexpected policy interventions would have some short-run effects upon the economy.<p>The "real business cycle (RBC) theory", pioneered by Kydland and Prescott (1982), offered<p>an alternative explanation on the nature of fluctuations in economic activity, viewed<p>as reflecting the efficient responses of optimizing agents to exogenous sources of fluctuations, outside the direct control of policymakers. The normative implication was that<p>there should be no role for economic policy activism: fiscal and monetary policy should be<p>acyclical. The latest generation of New Keynesian dynamic stochastic general equilibrium<p>(DSGE) models builds on rigorous foundations in intertemporal optimizing behavior by<p>consumers and firms inherited from the RBC literature, but incorporates some frictions<p>in the adjustment of nominal and real quantities in response to macroeconomic shocks<p>(see Woodford (2003)). In such a framework, not only policy "surprises" may have an<p>impact on the economic activity, but also the way policymakers "systematically" respond<p>to exogenous sources of fluctuation plays a fundamental role in affecting the economic<p>activity, thereby rekindling interest in the use of counter-cyclical stabilization policies to<p>fine tune the business cycle.<p>Yet, despite impressive advances in the economic theory and econometric techniques, there are no definitive answers on the systematic stance policymakers should follow, and on the<p>effects of macroeconomic policies upon the economy. Against this background, the present thesis attempts to inspect the interrelations between macroeconomic policies and the economic activity from novel angles. Three contributions<p>are proposed. <p><p>In the first Chapter, I show that relying on the information actually available to policymakers when budgetary decisions are taken is of fundamental importance for the assessment of the cyclical stance of governments. In the second, I explore whether the effectiveness of fiscal shocks in spurring the economic activity has declined since the beginning of the 1970s. In the third, the impact of systematic monetary policies over U.S. industrial sectors is investigated. In the existing literature, empirical assessments of the historical stance of policymakers over the economic cycle have been mainly drawn from the estimation of "reduced-form" policy reaction functions (see in particular Taylor (1993) and Galì and Perotti (2003)). Such rules typically relate a policy instrument (a reference short-term interest rate or an indicator of discretionary fiscal policy) to a set of explanatory variables (notably inflation, the output gap and the debt-GDP ratio, as long as fiscal policy is concerned). Although these policy rules can be seen as simple approximations of what derived from an explicit optimization problem solved by social planners (see Kollmann (2007)), they received considerable attention since they proved to track the behavior of central banks and fiscal<p>policymakers relatively well. Typically, revised data, i.e. observations available to the<p>econometrician when the study is carried out, are used in the estimation of such policy<p>reaction functions. However, data available in "real-time" to policymakers may end up<p>to be remarkably different from what it is observed ex-post. Orphanides (2001), in an<p>innovative and thought-provoking paper on the U.S. monetary policy, challenged the way<p>policy evaluation was conducted that far by showing that unrealistic assumptions about<p>the timeliness of data availability may yield misleading descriptions of historical policy.<p>In the spirit of Orphanides (2001), in the first Chapter of this thesis I reconsider how<p>the intentional cyclical stance of fiscal authorities should be assessed. Importantly, in<p>the framework of fiscal policy rules, not only variables such as potential output and the<p>output gap are subject to measurement errors, but also the main discretionary "operating<p>instrument" in the hands of governments: the structural budget balance, i.e. the headline<p>government balance net of the effects due to automatic stabilizers. In fact, the actual<p>realization of planned fiscal measures may depend on several factors (such as the growth<p>rate of GDP, the implementation lags that often follow the adoption of many policy<p>measures, and others more) outside the direct and full control of fiscal authorities. Hence,<p>there might be sizeable differences between discretionary fiscal measures as planned in the<p>past and what it is observed ex-post. To be noted, this does not apply to monetary policy<p>since central bankers can control their operating interest rates with great accuracy.<p>When the historical behavior of fiscal authorities is analyzed from a real-time perspective, it emerges that the intentional stance has been counter-cyclical, especially during expansions, in the main OECD countries throughout the last thirteen years. This is at<p>odds with findings based on revised data, generally pointing to pro-cyclicality (see for example Gavin and Perotti (1997)). It is shown that empirical correlations among revision<p>errors and other second-order moments allow to predict the size and the sign of the bias<p>incurred in estimating the intentional stance of the policy when revised data are (mistakenly)<p>used. It addition, formal tests, based on a refinement of Hansen (1999), do not reject<p>the hypothesis that the intentional reaction of fiscal policy to the cycle is characterized by<p>two regimes: one counter-cyclical, when output is above its potential level, and the other<p>acyclical, in the opposite case. On the contrary, the use of revised data does not allow to identify any threshold effect.<p><p>The second and third Chapters of this thesis are devoted to the exploration of the impact<p>of fiscal and monetary policies upon the economy.<p>Over the last years, two approaches have been mainly followed by practitioners for the<p>estimation of the effects of macroeconomic policies on the real activity. On the one hand,<p>calibrated and estimated DSGE models allow to trace out the economy’s responses to<p>policy disturbances within an analytical framework derived from solid microeconomic<p>foundations. On the other, vector autoregressive (VAR) models continue to be largely<p>used since they have proved to fit macro data particularly well, albeit they cannot fully<p>serve to inspect structural interrelations among economic variables.<p>Yet, the typical DSGE and VAR models are designed to handle a limited number of variables<p>and are not suitable to address economic questions potentially involving a large<p>amount of information. In a DSGE framework, in fact, identifying aggregate shocks and<p>their propagation mechanism under a plausible set of theoretical restrictions becomes a<p>thorny issue when many variables are considered. As for VARs, estimation problems may<p>arise when models are specified in a large number of indicators (although latest contributions suggest that large-scale Bayesian VARs perform surprisingly well in forecasting.<p>See in particular Banbura, Giannone and Reichlin (2007)). As a consequence, the growing<p>popularity of factor models as effective econometric tools allowing to summarize in<p>a parsimonious and flexible manner large amounts of information may be explained not<p>only by their usefulness in deriving business cycle indicators and forecasting (see for example<p>Reichlin (2002) and D’Agostino and Giannone (2006)), but also, due to recent<p>developments, by their ability in evaluating the response of economic systems to identified<p>structural shocks (see Giannone, Reichlin and Sala (2002) and Forni, Giannone, Lippi<p>and Reichlin (2007)). Parallelly, some attempts have been made to combine the rigor of<p>DSGE models and the tractability of VAR ones, with the advantages of factor analysis<p>(see Boivin and Giannoni (2006) and Bernanke, Boivin and Eliasz (2005)).<p><p>The second Chapter of this thesis, based on a joint work with Agnès Bénassy-Quéré, presents an original study combining factor and VAR analysis in an encompassing framework,<p>to investigate how "unexpected" and "unsystematic" variations in taxes and government<p>spending feed through the economy in the home country and abroad. The domestic<p>impact of fiscal shocks in Germany, the U.K. and the U.S. and cross-border fiscal spillovers<p>from Germany to seven European economies is analyzed. In addition, the time evolution of domestic and cross-border tax and spending multipliers is explored. In fact, the way fiscal policy impacts on domestic and foreign economies<p>depends on several factors, possibly changing over time. In particular, the presence of excess<p>capacity, accommodating monetary policy, distortionary taxation and liquidity constrained<p>consumers, plays a prominent role in affecting how fiscal policies stimulate the<p>economic activity in the home country. The impact on foreign output crucially depends<p>on the importance of trade links, on real exchange rates and, in a monetary union, on<p>the sensitiveness of foreign economies to the common interest rate. It is well documented<p>that the last thirty years have witnessed frequent changes in the economic environment.<p>For instance, in most OECD countries, the monetary policy stance became less accommodating<p>in the 1980s compared to the 1970s, and more accommodating again in the<p>late 1990s and early 2000s. Moreover, financial markets have been heavily deregulated.<p>Hence, fiscal policy might have lost (or gained) power as a stimulating tool in the hands<p>of policymakers. Importantly, the issue of cross-border transmission of fiscal policy decisions is of the utmost relevance in the framework of the European Monetary Union and this explains why the debate on fiscal policy coordination has received so much attention since the adoption<p>of the single currency (see Ahearne, Sapir and Véron (2006) and European Commission<p>(2006)). It is found that over the period 1971 to 2004 tax shocks have generally been more effective in spurring domestic output than government spending shocks. Interestingly, the inclusion of common factors representing global economic phenomena yields to smaller multipliers<p>reconciling, at least for the U.K. the evidence from large-scale macroeconomic models,<p>generally finding feeble multipliers (see e.g. European Commission’s QUEST model), with<p>the one from a prototypical structural VAR pointing to stronger effects of fiscal policy.<p>When the estimation is performed recursively over samples of seventeen years of data, it<p>emerges that GDP multipliers have dropped drastically from early 1990s on, especially<p>in Germany (tax shocks) and in the U.S. (both tax and government spending shocks).<p>Moreover, the conduct of fiscal policy seems to have become less erratic, as documented<p>by a lower variance of fiscal shocks over time, and this might contribute to explain why<p>business cycles have shown less volatility in the countries under examination.<p>Expansionary fiscal policies in Germany do not generally have beggar-thy-neighbor effects<p>on other European countries. In particular, our results suggest that tax multipliers have<p>been positive but vanishing for neighboring countries (France, Italy, the Netherlands, Belgium and Austria), weak and mostly not significant for more remote ones (the U.K.<p>and Spain). Cross-border government spending multipliers are found to be monotonically<p>weak for all the subsamples considered.<p>Overall these findings suggest that fiscal "surprises", in the form of unexpected reductions in taxation and expansions in government consumption and investment, have become progressively less successful in stimulating the economic activity at the domestic level, indicating that, in the framework of the European Monetary Union, policymakers can only marginally rely on this discretionary instrument as a substitute for national monetary policies. <p><p>The objective of the third chapter is to inspect the role of monetary policy in the U.S. business cycle. In particular, the effects of "systematic" monetary policies upon several industrial sectors is investigated. The focus is on the systematic, or endogenous, component of monetary policy (i.e. the one which is related to the economic activity in a stable and predictable way), for three main reasons. First, endogenous monetary policies are likely to have sizeable real effects, if agents’ expectations are not perfectly rational and if there are some nominal and real frictions in a market. Second, as widely documented, the variability of the monetary instrument and of the main macro variables is only marginally explained by monetary "shocks", defined as unexpected and exogenous variations in monetary conditions. Third, monetary shocks can be simply interpreted as measurement errors (see Christiano, Eichenbaum<p>and Evans (1998)). Hence, the systematic component of monetary policy is likely to have played a fundamental role in affecting business cycle fluctuations. The strategy to isolate the impact of systematic policies relies on a counterfactual experiment, within a (calibrated or estimated) macroeconomic model. As a first step, a macroeconomic shock to which monetary policy is likely to respond should be selected,<p>and its effects upon the economy simulated. Then, the impact of such shock should be<p>evaluated under a “policy-inactive” scenario, assuming that the central bank does not respond<p>to it. Finally, by comparing the responses of the variables of interest under these<p>two scenarios, some evidence on the sensitivity of the economic system to the endogenous<p>component of the policy can be drawn (see Bernanke, Gertler and Watson (1997)).<p>Such kind of exercise is first proposed within a stylized DSGE model, where the analytical<p>solution of the model can be derived. However, as argued, large-scale multi-sector DSGE<p>models can be solved only numerically, thus implying that the proposed experiment cannot<p>be carried out. Moreover, the estimation of DSGE models becomes a thorny issue when many variables are incorporated (see Canova and Sala (2007)). For these arguments, a less “structural”, but more tractable, approach is followed, where a minimal amount of<p>identifying restrictions is imposed. In particular, a factor model econometric approach<p>is adopted (see in particular Giannone, Reichlin and Sala (2002) and Forni, Giannone,<p>Lippi and Reichlin (2007)). In this framework, I develop a technique to perform the counterfactual experiment needed to assess the impact of systematic monetary policies.<p>It is found that 2 and 3-digit SIC U.S. industries are characterized by very heterogeneous degrees of sensitivity to the endogenous component of the policy. Notably, the industries showing the strongest sensitivities are the ones producing durable goods and metallic<p>materials. Non-durable good producers, food, textile and lumber producing industries are<p>the least affected. In addition, it is highlighted that industrial sectors adjusting prices relatively infrequently are the most "vulnerable" ones. In fact, firms in this group are likely to increase quantities, rather than prices, following a shock positively hitting the economy. Finally, it emerges that sectors characterized by a higher recourse to external sources to finance investments, and sectors investing relatively more in new plants and machineries, are the most affected by endogenous monetary actions. / Doctorat en sciences économiques, Orientation économie / info:eu-repo/semantics/nonPublished

Over the last years, the growing availability of large datasets and the improvements in the computational speed of computers have further fostered the research in the fields of both macroeconomic modeling and forecasting analysis. A primary focus of these research areas is to improve the models performance by exploiting the informational content of several time series. Increasing the dimension of macro models is indeed crucial for a detailed structural understanding of the economic environment, as well as for an accurate forecasting analysis. As consequence, a new generation of large-scale macro models, based on the micro-foundations of a fully specified dynamic stochastic general equilibrium set-up, has became one of the most flourishing research areas of interest both in central banks and academia. At the same time, there has been a revival of forecasting methods dealing with many predictors, such as the factor models. The central idea of factor models is to exploit co-movements among variables through a parsimonious econometric structure. Few underlying common shocks or factors explain most of the co-variations among variables. The unexplained component of series movements is on the other hand due to pure idiosyncratic dynamics. The generality of their framework allows factor models to be suitable for describing a broad variety of models in a macroeconomic and a financial context. The revival of factor models, over the recent years, comes from important developments achieved by Stock and Watson (2002) and Forni, Hallin, Lippi and Reichlin (2000). These authors find the conditions under which some data averages become collinear to the space spanned by the factors when, the cross section dimension, becomes large. Moreover, their factor specifications allow the idiosyncratic dynamics to be mildly cross-correlated (an effect referred to as the 'approximate factor structure' by Chamberlain and Rothschild, 1983), a situation empirically verified in many applications. These findings have relevant implications. The most important being that the use of a large number of series is no longer representative of a dimensional constraint. On the other hand, it does help to identify the factor space. This new generation of factor models has been applied in several areas of macroeconomics and finance as well as for policy evaluation. It is consequently very likely to become a milestone in the literature of forecasting methods using many predictors. This thesis contributes to the empirical literature on factor models by proposing four original applications. <p><p>In the first chapter of this thesis, the generalized dynamic factor model of Forni et. al (2002) is employed to explore the predictive content of the asset returns in forecasting Consumer Price Index (CPI) inflation and the growth rate of Industrial Production (IP). The connection between stock markets and economic growth is well known. In the fundamental valuation of equity, the stock price is equal to the discounted future streams of expected dividends. Since the future dividends are related to future growth, a revision of prices, and hence returns, should signal movements in the future growth path. Though other important transmission channels, such as the Tobin's q theory (Tobin, 1969), the wealth effect as well as capital market imperfections, have been widely studied in this literature. I show that an aggregate index, such as the S&P500, could be misleading if used as a proxy for the informative content of the stock market as a whole. Despite the widespread wisdom of considering such index as a leading variable, only part of the assets included in the composition of the index has a leading behaviour with respect to the variables of interest. Its forecasting performance might be poor, leading to sceptical conclusions about the effectiveness of asset prices in forecasting macroeconomic variables. The main idea of the first essay is therefore to analyze the lead-lag structure of the assets composing the S&P500. The classification in leading, lagging and coincident variables is achieved by means of the cross correlation function cleaned of idiosyncratic noise and short run fluctuations. I assume that asset returns follow a factor structure. That is, they are the sum of two parts: a common part driven by few shocks common to all the assets and an idiosyncratic part, which is rather asset specific. The correlation<p>function, computed on the common part of the series, is not affected by the assets' specific dynamics and should provide information only on the series driven by the same common factors. Once the leading series are identified, they are grouped within the economic sector they belong to. The predictive content that such aggregates have in forecasting IP growth and CPI inflation is then explored and compared with the forecasting power of the S&P500 composite index. The forecasting exercise is addressed in the following way: first, in an autoregressive (AR) model I choose the truncation lag that minimizes the Mean Square Forecast Error (MSFE) in 11 years out of sample simulations for 1, 6 and 12 steps ahead, both for the IP growth rate and the CPI inflation. Second, the S&P500 is added as an explanatory variable to the previous AR specification. I repeat the simulation exercise and find that there are very small improvements of the MSFE statistics. Third, averages of stock return leading series, in the respective sector, are added as additional explanatory variables in the benchmark regression. Remarkable improvements are achieved with respect to the benchmark specification especially for one year horizon forecast. Significant improvements are also achieved for the shorter forecast horizons, when the leading series of the technology and energy sectors are used. <p><p>The second chapter of this thesis disentangles the sources of aggregate risk and measures the extent of co-movements in five European stock markets. Based on the static factor model of Stock and Watson (2002), it proposes a new method for measuring the impact of international, national and industry-specific shocks. The process of European economic and monetary integration with the advent of the EMU has been a central issue for investors and policy makers. During these years, the number of studies on the integration and linkages among European stock markets has increased enormously. Given their forward looking nature, stock prices are considered a key variable to use for establishing the developments in the economic and financial markets. Therefore, measuring the extent of co-movements between European stock markets has became, especially over the last years, one of the main concerns both for policy makers, who want to best shape their policy responses, and for investors who need to adapt their hedging strategies to the new political and economic environment. An optimal portfolio allocation strategy is based on a timely identification of the factors affecting asset returns. So far, literature dating back to Solnik (1974) identifies national factors as the main contributors to the co-variations among stock returns, with the industry factors playing a marginal role. The increasing financial and economic integration over the past years, fostered by the decline of trade barriers and a greater policy coordination, should have strongly reduced the importance of national factors and increased the importance of global determinants, such as industry determinants. However, somehow puzzling, recent studies demonstrated that countries sources are still very important and generally more important of the industry ones. This paper tries to cast some light on these conflicting results. The chapter proposes an econometric estimation strategy more flexible and suitable to disentangle and measure the impact of global and country factors. Results point to a declining influence of national determinants and to an increasing influence of the industries ones. The international influences remains the most important driving forces of excess returns. These findings overturn the results in the literature and have important implications for strategic portfolio allocation policies; they need to be revisited and adapted to the changed financial and economic scenario. <p><p>The third chapter presents a new stylized fact which can be helpful for discriminating among alternative explanations of the U.S. macroeconomic stability. The main finding is that the fall in time series volatility is associated with a sizable decline, of the order of 30% on average, in the predictive accuracy of several widely used forecasting models, included the factor models proposed by Stock and Watson (2002). This pattern is not limited to the measures of inflation but also extends to several indicators of real economic activity and interest rates. The generalized fall in predictive ability after the mid-1980s is particularly pronounced for forecast horizons beyond one quarter. Furthermore, this empirical regularity is not simply specific to a single method, rather it is a common feature of all models including those used by public and private institutions. In particular, the forecasts for output and inflation of the Fed's Green book and the Survey of Professional Forecasters (SPF) are significantly more accurate than a random walk only before 1985. After this date, in contrast, the hypothesis of equal predictive ability between naive random walk forecasts and the predictions of those institutions is not rejected for all horizons, the only exception being the current quarter. The results of this chapter may also be of interest for the empirical literature on asymmetric information. Romer and Romer (2000), for instance, consider a sample ending in the early 1990s and find that the Fed produced more accurate forecasts of inflation and output compared to several commercial providers. The results imply that the informational advantage of the Fed and those private forecasters is in fact limited to the 1970s and the beginning of the 1980s. In contrast, during the last two decades no forecasting model is better than "tossing a coin" beyond the first quarter horizon, thereby implying that on average uninformed economic agents can effectively anticipate future macroeconomics developments. On the other hand, econometric models and economists' judgement are quite helpful for the forecasts over the very short horizon, that is relevant for conjunctural analysis. Moreover, the literature on forecasting methods, recently surveyed by Stock and Watson (2005), has devoted a great deal of attention towards identifying the best model for predicting inflation and output. The majority of studies however are based on full-sample periods. The main findings in the chapter reveal that most of the full sample predictability of U.S. macroeconomic series arises from the years before 1985. Long time series appear<p>to attach a far larger weight on the earlier sub-sample, which is characterized by a larger volatility of inflation and output. Results also suggest that some caution should be used in evaluating the performance of alternative forecasting models on the basis of a pool of different sub-periods as full sample analysis are likely to miss parameter instability. <p><p>The fourth chapter performs a detailed forecast comparison between the static factor model of Stock and Watson (2002) (SW) and the dynamic factor model of Forni et. al. (2005) (FHLR). It is not the first work in performing such an evaluation. Boivin and Ng (2005) focus on a very similar problem, while Stock and Watson (2005) compare the performances of a larger class of predictors. The SW and FHLR methods essentially differ in the computation of the forecast of the common component. In particular, they differ in the estimation of the factor space and in the way projections onto this space are performed. In SW, the factors are estimated by static Principal Components (PC) of the sample covariance matrix and the forecast of the common component is simply the projection of the predicted variable on the factors. FHLR propose efficiency improvements in two directions. First, they estimate the common factors based on Generalized Principal Components (GPC) in which observations are weighted according to their signal to noise ratio. Second, they impose the constraints implied by the dynamic factors structure when the variables of interest are projected on the common factors. Specifically, they take into account the leading and lagging relations across series by means of principal components in the frequency domain. This allows for an efficient aggregation of variables that may be out of phase. Whether these efficiency improvements are helpful to forecast in a finite sample is however an empirical question. Literature has not yet reached a consensus. On the one hand, Stock and Watson (2005) show that both methods perform similarly (although they focus on the weighting of the idiosyncratic and not on the dynamic restrictions), while Boivin and Ng (2005) show that SW's method largely outperforms the FHLR's and, in particular, conjecture that the dynamic restrictions implied by the method are harmful for the forecast accuracy of the model. This chapter tries to shed some new light on these conflicting results. It<p>focuses on the Industrial Production index (IP) and the Consumer Price Index (CPI) and bases the evaluation on a simulated out-of sample forecasting exercise. The data set, borrowed from Stock and Watson (2002), consists of 146 monthly observations for the US economy. The data spans from 1959 to 1999. In order to isolate and evaluate specific characteristics of the methods, a procedure, where the<p>two non-parametric approaches are nested in a common framework, is designed. In addition, for both versions of the factor model forecasts, the chapter studies the contribution of the idiosyncratic component to the forecast. Other non-core aspects of the model are also investigated: robustness with respect to the choice of the number of factors and variable transformations. Finally, the chapter performs a sub-sample performances of the factor based forecasts. The purpose of this exercise is to design an experiment for assessing the contribution of the core characteristics of different models to the forecasting performance and discussing auxiliary issues. Hopefully this may also serve as a guide for practitioners in the field. As in Stock and Watson (2005), results show that efficiency improvements due to the weighting of the idiosyncratic components do not lead to significant more accurate forecasts, but, in contrast to Boivin and Ng (2005), it is shown that the dynamic restrictions imposed by the procedure of Forni et al. (2005) are not harmful for predictability. The main conclusion is that the two methods have a similar performance and produce highly collinear forecasts. <p> / Doctorat en sciences économiques, Orientation économie / info:eu-repo/semantics/nonPublished

The aim of the thesis is to further explore the relationship between economic integration and firm mobility and investment, both from an empirical and a theoretical perspective, with the objective of drawing conclusions on how government policy can be used to strengthen the positive impact of integration on investment, which is crucial in moving and maintaining countries at the forefront of the technology frontier and accelerating economic growth in a world of rapid technical change and high mobility of ideas, goods, services, capital and labor.<p>The first chapter aims to bring together the literature on economic integration, firm mobility and investment. It contains two sections: one dedicated to the literature on FDI and the second covering the literature on firm entry and exit, economic performance and economic and business regulation.<p>In the second chapter I examine the relationship between the Single Market and FDI both in an intra-EU context and from outside the EU. The empirical results show that the impact of the Single Market on FDI differs substantially from one country to another. This finding may be due to the functioning of institutions.<p>The third chapter studies the relationship between the level of external trade protection put into place by a Regional Integration Agreement(RIA)and the option of a firm from outside the RIA block to serve the RIA market through FDI rather than exports. I find that the level of external trade protection put in place by the RIA depends on the RIA country's capacity to benefit from FDI spillovers, the magnitude of set-up costs of building a plant in the RIA and on the amount of external trade protection erected by the country from outside the reigonal block with respect to the RIA.<p>The fourth chapter studies how the firm entry and exit process is affected by product market reforms and regulations and impact macroeconomic performance. The results show that an increase in deregulation will lead to a rise in firm entry and exit. This in turn will especially affect macroeconomic performance as measured by output growth and labor productivity growth. The analysis done at the sector level shows that results can differ substantially across industries, which implies that deregulation policies should be conducted at the sector level, rather than at the global macroeconomic level. / Doctorat en sciences économiques, Orientation économie / info:eu-repo/semantics/nonPublished

This thesis consists in a collection of research works dealing with various aspects of International Economics. More precisely, we focus on three main themes: (i) the existence of a world business cycle and the implications thereof, (ii) the likelihood of asymmetric shocks in the Euro Zone resulting from fluctuations in the euro exchange rate because of differences in sector specialization patterns and some consequences of such shocks, and (iii) the relationship between trade openness and growth influence of the sector specialization structure on that relationship.<p><p>Regarding the approach pursued to tackle these problems, we have chosen to strictly remain within the boundaries of empirical (macro)economics - that is, applied econometrics. Though we systematically provide theoretical models to back up our empirical approach, our only real concern is to look at the stories the data can (or cannot) tell us. As to the econometric methodology, we will restrict ourselves to the use of panel data analysis. The large spectrum of techniques available within the panel framework allows us to utilize, for each of the problems at hand, the most suitable approach (or what we think it is). / Doctorat en sciences économiques, Orientation économie / info:eu-repo/semantics/nonPublished

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