Дисертації з теми "Finance Australia Econometric models"

implications of information asymmetries, with a special focus on financial

issues. This exercise is mainly theoretical: I develop stylized models that aim

at capturing macroeconomic phenomena such as self-fulfilling liquidity dry-ups,

the rise and the fall of securitization markets, and the creation of systemic risk.

The dissertation consists of three chapters. The first one proposes an explanation

to self-fulfilling liquidity dry-ups. The second chapters proposes a formalization

of the concept of market discipline and an application to securitization

markets as risk-sharing mechanisms. The third one offers a complementary

analysis to the second as the rise of securitization is presented as banker optimal

response to strict capital constraints.

Two concepts that do not have unique acceptations in economics play a central

role in these models: liquidity and market discipline.

The liquidity of an asset refers to the ability for his owner to transform it into

current consumption goods. Secondary markets for long-term assets play thus

an important role with that respect. However, such markets might be illiquid due

to adverse selection.

In the first chapter, I show that: (1) when agents expect a liquidity dry-up

on such markets, they optimally choose to self-insure through the hoarding of

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

equilibria; (4) the government can rule them out. Additionally, I show

that idiosyncratic liquidity shocks à la Diamond and Dybvig have stabilizing effects,

which is at odds with the banking literature. The main contribution of the

chapter is to show that market breakdowns due to adverse selection are highly

endogenous to past balance-sheet decisions.

I consider that agents are under market discipline when their current behavior

is influenced by future market outcomes. A key ingredient for market discipline

to be at play is that the market outcome depends on information that is observable

but not verifiable (that is, information that cannot be proved in court, and

consequently, upon which enforceable contracts cannot be based).

In the second chapter, after introducing this novel formalization of market

discipline, I ask whether securitization really contributes to better risk-sharing:

I compare it with other mechanisms that differ on the timing of risk-transfer. I

find that for securitization to be an efficient risk-sharing mechanism, it requires

market discipline to be strong and adverse selection not to be severe. This seems

to seriously restrict the set of assets that should be securitized for risk-sharing

motive.

Additionally, I show how ex-ante leverage may mitigate interim adverse selection

in securitization markets and therefore enhance ex-post risk-sharing. This

is interesting because high leverage is usually associated with “excessive” risktaking.

In the third chapter, I consider risk-neutral bankers facing strict capital constraints;

their capital is indeed required to cover the worst-case-scenario losses.

In such a set-up, I find that: 1) banker optimal autarky response is to diversify

lower-tail risk and maximize leverage; 2) securitization helps to free up capital

and to increase leverage, but distorts incentives to screen loan applicants properly; 3) market discipline mitigates this problem, but if it is overestimated by

the supervisor, it leads to excess leverage, which creates systemic risk. Finally,

I consider opaque securitization and I show that the supervisor: 4) faces uncertainty

about the trade-off between the size of the economy and the probability

and the severity of a systemic crisis; 5) can generally not set capital constraints

at the socially efficient level.
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Central Banks behave so cautiously compared to optimal theoretical

benchmarks, (ii) do monetary variables add information about

future Euro Area inflation to a large amount of non monetary

variables and (iii) why national saving and investment are so

correlated in OECD countries in spite of the high degree of

integration of international financial markets.

The process of innovation in the elaboration of economic theory

and statistical analysis of the data witnessed in the last thirty

years has greatly enriched the toolbox available to

macroeconomists. Two aspects of such a process are particularly

noteworthy for addressing the issues in this thesis: the

development of macroeconomic dynamic stochastic general

equilibrium models (see Woodford, 1999b for an historical

perspective) and of techniques that enable to handle large data

sets in a parsimonious and flexible manner (see Reichlin, 2002 for

an historical perspective).

Dynamic stochastic general equilibrium models (DSGE) provide the

appropriate tools to evaluate the macroeconomic consequences of

policy changes. These models, by exploiting modern intertemporal

general equilibrium theory, aggregate the optimal responses of

individual as consumers and firms in order to identify the

aggregate shocks and their propagation mechanisms by the

restrictions imposed by optimizing individual behavior. Such a

modelling strategy, uncovering economic relationships invariant to

a change in policy regimes, provides a framework to analyze the

effects of economic policy that is robust to the Lucas'critique

(see Lucas, 1976). The early attempts of explaining business

cycles by starting from microeconomic behavior suggested that

economic policy should play no role since business cycles

reflected the efficient response of economic agents to exogenous

sources of fluctuations (see the seminal paper by Kydland and Prescott, 1982}

and, more recently, King and Rebelo, 1999). This view was challenged by

several empirical studies showing that the adjustment mechanisms

of variables at the heart of macroeconomic propagation mechanisms

like prices and wages are not well represented by efficient

responses of individual agents in frictionless economies (see, for

example, Kashyap, 1999; Cecchetti, 1986; Bils and Klenow, 2004 and Dhyne et al. 2004). Hence, macroeconomic models currently incorporate

some sources of nominal and real rigidities in the DSGE framework

and allow the study of the optimal policy reactions to inefficient

fluctuations stemming from frictions in macroeconomic propagation

mechanisms.

Against this background, the first chapter of this thesis sets up

a DSGE model in order to analyze optimal monetary policy in an

economy with sectorial heterogeneity in the frequency of price

adjustments. Price setters are divided in two groups: those

subject to Calvo type nominal rigidities and those able to change

their prices at each period. Sectorial heterogeneity in price

setting behavior is a relevant feature in real economies (see, for

example, Bils and Klenow, 2004 for the US and Dhyne, 2004 for the Euro

Area). Hence, neglecting it would lead to an understatement of the

heterogeneity in the transmission mechanisms of economy wide

shocks. In this framework, Aoki (2001) shows that a Central

Bank maximizing social welfare should stabilize only inflation in

the sector where prices are sticky (hereafter, core inflation).

Since complete stabilization is the only true objective of the

policymaker in Aoki (2001) and, hence, is not only desirable

but also implementable, the equilibrium real interest rate in the

economy is equal to the natural interest rate irrespective of the

degree of heterogeneity that is assumed. This would lead to

conclude that stabilizing core inflation rather than overall

inflation does not imply any observable difference in the

aggressiveness of the policy behavior. While maintaining the

assumption of sectorial heterogeneity in the frequency of price

adjustments, this chapter adds non negligible transaction

frictions to the model economy in Aoki (2001). As a

consequence, the social welfare maximizing monetary policymaker

faces a trade-off among the stabilization of core inflation,

economy wide output gap and the nominal interest rate. This

feature reflects the trade-offs between conflicting objectives

faced by actual policymakers. The chapter shows that the existence

of this trade-off makes the aggressiveness of the monetary policy

reaction dependent on the degree of sectorial heterogeneity in the

economy. In particular, in presence of sectorial heterogeneity in

price adjustments, Central Banks are much more likely to behave

less aggressively than in an economy where all firms face nominal

rigidities. Hence, the chapter concludes that the excessive

caution in the conduct of monetary policy shown by actual Central

Banks (see, for example, Rudebusch and Svennsson, 1999 and Sack, 2000) might not

represent a sub-optimal behavior but, on the contrary, might be

the optimal monetary policy response in presence of a relevant

sectorial dispersion in the frequency of price adjustments.

DSGE models are proving useful also in empirical applications and

recently efforts have been made to incorporate large amounts of

information in their framework (see Boivin and Giannoni, 2006). However, the

typical DSGE model still relies on a handful of variables. Partly,

this reflects the fact that, increasing the number of variables,

the specification of a plausible set of theoretical restrictions

identifying aggregate shocks and their propagation mechanisms

becomes cumbersome. On the other hand, several questions in

macroeconomics require the study of a large amount of variables.

Among others, two examples related to the second and third chapter

of this thesis can help to understand why. First, policymakers

analyze a large quantity of information to assess the current and

future stance of their economies and, because of model

uncertainty, do not rely on a single modelling framework.

Consequently, macroeconomic policy can be better understood if the

econometrician relies on large set of variables without imposing

too much a priori structure on the relationships governing their

evolution (see, for example, Giannone et al. 2004 and Bernanke et al. 2005).

Moreover, the process of integration of good and financial markets

implies that the source of aggregate shocks is increasingly global

requiring, in turn, the study of their propagation through cross

country links (see, among others, Forni and Reichlin, 2001 and Kose et al. 2003). A

priori, country specific behavior cannot be ruled out and many of

the homogeneity assumptions that are typically embodied in open

macroeconomic models for keeping them tractable are rejected by

the data. Summing up, in order to deal with such issues, we need

modelling frameworks able to treat a large amount of variables in

a flexible manner, i.e. without pre-committing on too many

a-priori restrictions more likely to be rejected by the data. The

large extent of comovement among wide cross sections of economic

variables suggests the existence of few common sources of

fluctuations (Forni et al. 2000 and Stock and Watson, 2002) around which

individual variables may display specific features: a shock to the

world price of oil, for example, hits oil exporters and importers

with different sign and intensity or global technological advances

can affect some countries before others (Giannone and Reichlin, 2004). Factor

models mainly rely on the identification assumption that the

dynamics of each variable can be decomposed into two orthogonal

components - common and idiosyncratic - and provide a parsimonious

tool allowing the analysis of the aggregate shocks and their

propagation mechanisms in a large cross section of variables. In

fact, while the idiosyncratic components are poorly

cross-sectionally correlated, driven by shocks specific of a

variable or a group of variables or measurement error, the common

components capture the bulk of cross-sectional correlation, and

are driven by few shocks that affect, through variable specific

factor loadings, all items in a panel of economic time series.

Focusing on the latter components allows useful insights on the

identity and propagation mechanisms of aggregate shocks underlying

a large amount of variables. The second and third chapter of this

thesis exploit this idea.

The second chapter deals with the issue whether monetary variables

help to forecast inflation in the Euro Area harmonized index of

consumer prices (HICP). Policymakers form their views on the

economic outlook by drawing on large amounts of potentially

relevant information. Indeed, the monetary policy strategy of the

European Central Bank acknowledges that many variables and models

can be informative about future Euro Area inflation. A peculiarity

of such strategy is that it assigns to monetary information the

role of providing insights for the medium - long term evolution of

prices while a wide range of alternative non monetary variables

and models are employed in order to form a view on the short term

and to cross-check the inference based on monetary information.

However, both the academic literature and the practice of the

leading Central Banks other than the ECB do not assign such a

special role to monetary variables (see Gali et al. 2004 and

references therein). Hence, the debate whether money really

provides relevant information for the inflation outlook in the

Euro Area is still open. Specifically, this chapter addresses the

issue whether money provides useful information about future

inflation beyond what contained in a large amount of non monetary

variables. It shows that a few aggregates of the data explain a

large amount of the fluctuations in a large cross section of Euro

Area variables. This allows to postulate a factor structure for

the large panel of variables at hand and to aggregate it in few

synthetic indexes that still retain the salient features of the

large cross section. The database is split in two big blocks of

variables: non monetary (baseline) and monetary variables. Results

show that baseline variables provide a satisfactory predictive

performance improving on the best univariate benchmarks in the

period 1997 - 2005 at all horizons between 6 and 36 months.

Remarkably, monetary variables provide a sensible improvement on

the performance of baseline variables at horizons above two years.

However, the analysis of the evolution of the forecast errors

reveals that most of the gains obtained relative to univariate

benchmarks of non forecastability with baseline and monetary

variables are realized in the first part of the prediction sample

up to the end of 2002, which casts doubts on the current

forecastability of inflation in the Euro Area.

The third chapter is based on a joint work with Domenico Giannone

and gives empirical foundation to the general equilibrium

explanation of the Feldstein - Horioka puzzle. Feldstein and Horioka (1980) found

that domestic saving and investment in OECD countries strongly

comove, contrary to the idea that high capital mobility should

allow countries to seek the highest returns in global financial

markets and, hence, imply a correlation among national saving and

investment closer to zero than one. Moreover, capital mobility has

strongly increased since the publication of Feldstein - Horioka's

seminal paper while the association between saving and investment

does not seem to comparably decrease. Through general equilibrium

mechanisms, the presence of global shocks might rationalize the

correlation between saving and investment. In fact, global shocks,

affecting all countries, tend to create imbalance on global

capital markets causing offsetting movements in the global

interest rate and can generate the observed correlation across

national saving and investment rates. However, previous empirical

studies (see Ventura, 2003) that have controlled for the effects

of global shocks in the context of saving-investment regressions

failed to give empirical foundation to this explanation. We show

that previous studies have neglected the fact that global shocks

may propagate heterogeneously across countries, failing to

properly isolate components of saving and investment that are

affected by non pervasive shocks. We propose a novel factor

augmented panel regression methodology that allows to isolate

idiosyncratic sources of fluctuations under the assumption of

heterogenous transmission mechanisms of global shocks. Remarkably,

by applying our methodology, the association between domestic

saving and investment decreases considerably over time,

consistently with the observed increase in international capital

mobility. In particular, in the last 25 years the correlation

between saving and investment disappears.

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The first chapter introduces a quantile- and simulation-based estimation method, which we call the Method of Simulated Quantiles, or simply MSQ. Since it is based on quantiles, it is a moment-free approach. And since it is based on simulations, we do not need closed form expressions of any function that represents the probability law of the process. Thus, it is useful in case the probability density functions has no closed form or/and moments do not exist. It is based on a vector of functions of quantiles. The principle consists in matching functions of theoretical quantiles, which depend on the parameters of the assumed probability law, with those of empirical quantiles, which depend on the data. Since the theoretical functions of quantiles may not have a closed form expression, we rely on simulations.

The second chapter deals with the estimation of the parameters of elliptical distributions by means of a multivariate extension of MSQ. In this chapter we propose inference for vast dimensional elliptical distributions. Estimation is based on quantiles, which always exist regardless of the thickness of the tails, and testing is based on the geometry of the elliptical family. The multivariate extension of MSQ faces the difficulty of constructing a function of quantiles that is informative about the covariation parameters. We show that the interquartile range of a projection of pairwise random variables onto the 45 degree line is very informative about the covariation.

The third chapter consists in constructing a multivariate tail index estimator. In the univariate case, the most popular estimator for the tail exponent is the Hill estimator introduced by Bruce Hill in 1975. The aim of this chapter is to propose an estimator of the tail index in a multivariate context; more precisely, in the case of regularly varying elliptical distributions. Since, for univariate random variables, our estimator boils down to the Hill estimator, we name it after Bruce Hill. Our estimator is based on the distance between an elliptical probability contour and the exceedance observations.

Finally, the fourth chapter investigates the asymptotic behaviour of the marginal sample quantiles for p-dimensional stationary processes and we obtain the asymptotic normality of the empirical quantile vector. We assume that the processes are S-mixing, a recently introduced and widely applicable notion of dependence. A remarkable property of S-mixing is the fact that it doesn't require any higher order moment assumptions to be verified. Since we are interested in quantiles and processes that are probably heavy-tailed, this is of particular interest.

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