Dissertations / Theses on the topic 'Capital movements Econometric models'

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

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.

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.

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

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.

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

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

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.

Doctorat en sciences économiques, Orientation économie
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Chapter 2: Investment in Vocational and General Human Capital: A Theoretical Approach

Chapter 3: Urban Migrations and the Labor Market

Chapter 4: Local social capital and geographical mobility

Chapter 5: Social Supervision and Electoral Stability on the Geographical Scale in Belgium
Doctorat en Sciences économiques et de gestion
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The study of the structure and collective modes of financial markets attracts more and more attention. It has been shown that some agent based models are able to reproduce some stylized facts. Despite their partial success, there is still the problem of rules design. In this work, we used a statistical inverse approach to model the structure and co-movements in financial markets. Inverse models restrict the number of assumptions. We found that a pairwise maximum entropy model is consistent with the data and is able to describe the complex structure of financial systems. We considered the existence of a critical state which is linked to how the market processes information, how it responds to exogenous inputs and how its structure changes. The considered data sets did not reveal a persistent critical state but rather oscillations between order and disorder.

In this framework, we also showed that the collective modes are mostly dominated by pairwise co-movements and that univariate models are not good candidates to model crashes. The analysis also suggests a genuine adaptive process since both the maximum variance of the log-likelihood and the accuracy of the predictive scheme vary through time. This approach may provide some clue to crash precursors and may provide highlights on how a shock spreads in a financial network and if it will lead to a crash. The natural continuation of the present work could be the study of such a mechanism.
Doctorat en Sciences économiques et de gestion
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Le changement structurel est un processus nécessaire qui améliore considérablement les conditions de vie dans nos sociétés. Il peut découler par exemple de l'introduction de nouvelles avancées technologiques qui permettent d'augmenter à long terme la productivité agrégée dans nos économies. En retour, la hausse de la productivité a un impact sur notre consommation de tous les jours. Elle nous permet notamment de vivre dans un plus grand confort. Les individus peuvent alors s'épanouir dans leur ensemble. Il est évident que le changement structurel peut prendre d'autres formes que celle du changement technologique, mais il est souvent issu d'une transformation des forces qui influencent les marchés et en général aboutit à long terme à une amélioration du bien-être global.

Mais le changement structurel est aussi un processus douloureux. Il peut durer plusieurs décennies et, durant cette période, nous sommes beaucoup à devoir en supporter les coûts. Comme nous allons l'illustrer dans ce chapitre introductif, le changement structurel a pour conséquence une modification du rapport aux facteurs de production, ce qui alors mène à modifier l'ensemble des prix relatifs qui caractérisent une économie. En particulier, la modification des prix est due à une transformation des demandes relatives de facteurs. Ces derniers se révèlent alors inutiles à l'exécution de certaines tâches ou sont fortement demandés dans d'autres points de l'économie.

Souvent, le changement structurel entraîne alors un processus de réallocation. Des pans entiers de travailleurs doivent par conséquent se réallouer à d'autres tâches. Les lois du marché les incitent ainsi à devoir s'adapter à un nouveau contexte, mais elles le font pour un futur meilleur.

Cette thèse s'intéresse à cette problématique. Elle suppose que tout processus de changement structurel implique un mouvement de réallocation des facteurs de production, notamment des travailleurs puisqu'il s'agit d'une thèse en économie du travail, mais qu'un tel processus engendre souvent des coûts non négligeables. Elle se veut surtout positive, mais la nature des questions qu'elle pose mène naturellement à un débat normatif. Par exemple, elle cherche des réponses aux interrogations suivantes: comment s'ajuste une économie au changement structurel? Quelle est la nature des coûts associés au changement? Ces coûts peuvent-ils en excéder les gains? Le processus de réallocation en vaut-il vraiment la peine? Les gains issus d'un tel processus sont-ils distribués de manière égale?

La thèse est composée de quatre chapitres qui chacun considère l’impact d’un changement structurel particulier.

Le premier chapitre s’intéresse à l’impact de l’ouverture internationale aux échanges sur le niveau de l’emploi. Il s’appuie sur des travaux récents en économie internationale qui ont montré que la libéralisation du commerce mène à l’expansion des firmes les plus productives et à la destruction des entreprises dont la productivité est moins élevée. La raison de cette dichotomie est la présence d’un coût à l’entrée sur le marché des exports qui a été documentée par de nombreuses études. Certaines entreprises se développent suite à la libéralisation car elles ont accès à de nouveaux marchés et d’autres meurent car elles ne peuvent pas faire face aux entreprises les plus productives. Puisque le commerce crée à la fois des emplois et en détruit d’autres, ce chapitre a pour but de déterminer l’effet net de ce processus de réallocation sur le niveau agrégé de l’emploi.

Dans cette perspective, il présente un modèle avec firmes hétérogènes où pour exporter une entreprise doit payer un coût fixe, ce qui implique que seules les entreprises les plus productives peuvent entrer sur le marché international. Le modèle génère le processus de réallocation que l’ouverture au commerce international suppose. En effet, comme les entreprises les plus productives veulent exporter, elles vont donc embaucher plus de travailleurs, mais comme elles sont également capables de fixer des prix moins élevés et que les biens sont substituables, les entreprises les moins productives vont donc faire faillite. L’effet net sur l’emploi est négatif car les exportateurs ont à la marge moins d’incitants à embaucher des travailleurs du au comportement de concurrence monopolistique.

Le chapitre analyse également d’un point de vue empirique l’effet d’une ouverture au commerce au niveau sectoriel sur les flux d’emplois. Les résultats empiriques confirment ceux du modèle, c’est-à-dire qu’une hausse de l’ouverture au commerce génère plus de destructions que de créations d’emplois au niveau d’un secteur.

Le second chapitre considère un modèle similaire à celui du premier chapitre, mais se focalise plutôt sur l’effet du commerce en termes de bien-être. Il montre notamment que l’impact dépend en fait de la courbe de demande de travail agrégée. Si la courbe est croissante, l’effet est positif, alors qu’il est négatif si elle est décroissante.

Le troisième chapitre essaie de comprendre quels sont les déterminants de la mobilité géographique. Le but est notamment d’étudier le niveau du chômage en Europe. En effet, la littérature a souvent affirmé que la faible mobilité géographique du travail est un facteur de chômage lorsque les travailleurs sans emploi préfèrent rester dans leur région d’origine plutôt que d’aller prospecter dans les régions les plus dynamiques. Il semble donc rationnel pour ces individus de créer des liens sociaux locaux si ils anticipent qu’ils ne déménageront pas vers une autre région. De même, une fois le capital social local accumulé, les incitants à la mobilité sont réduits.

Le troisième chapitre illustre donc un modèle caractérisé par diverses complémentarités qui mènent à des équilibres multiples (un équilibre avec beaucoup de capital social local, peu de mobilité et un chômage élevé et un autre avec des caractéristiques opposées). Le modèle montre également que le capital social local est systématiquement négatif pour la mobilité et peut être négatif pour l’emploi, mais d’autres types de capital social peuvent en fait faire augmenter le niveau de l’emploi.

Dans ce troisième chapitre, une illustration empirique qui se base sur plusieurs mesures montre que le capital social est un facteur dominant d’immobilité. C’est aussi un facteur de chômage lorsque le capital social est clairement local, alors que d’autres types de capital social s’avèrent avoir un effet positif sur le taux d’emploi. Cette partie empirique illustre également la causalité inverse où des individus qui vivent dans une région qui ne correspond pas à leur région de naissance accumulent moins de capital social local, ce qui donne de la crédibilité à une théorie d’équilibres multiples.

Finalement, en observant que les individus dans le Sud de l’Europe semblent accumuler plus de capital social local, alors que dans le Nord de l’Europe on tend à investir dans des types plus généraux de capital social, nous suggérons qu’une partie du problème de chômage en Europe peut mieux se comprendre grâce au concept de capital social local.

Enfin, le quatrième chapitre s’intéresse à l’effet de la croissance économique sur la qualité des emplois. En particulier, il analyse le fait qu’un individu puisse avoir un emploi qui corresponde ou non à ses qualifications, ce qui, dans le contexte de ce chapitre, détermine s’il s’agit de bons ou mauvais emplois.

Ce chapitre se base sur deux mécanismes qui ont été largement abordés par la littérature. Le premier est le concept de « destruction créatrice » qui dit que la croissance détruit de nouveaux emplois car elle les rend obsolètes. Le second est le processus de « capitalisation » qui nous dit que la croissance va créer de nombreux emplois car les entreprises anticipent des profits plus élevés dans le futur.

Alors que des études récentes, suggèrent que la destruction créatrice ne permet pas d’expliquer le lien entre croissance et chômage, ce chapitre montre qu’un tel concept permet de mieux comprendre la relation entre croissance et qualité des emplois.

Avec des données issues du panel européen, nous illustrons que la corrélation entre croissance et qualité des emplois est positive. Nous présentons une série de trois modèles qui diffèrent de la manière suivante :(i) le fait de pouvoir chercher un emploi ou non alors qu’on en a déjà un, (ii) le fait pour une entreprise de pouvoir acquérir des équipements modernes. Les résultats suggèrent que pour expliquer l’effet de la croissance sur la qualité des emplois, la meilleure stratégie est une combinaison entre les effets dits de destruction créatrice et de capitalisation. Alors que le premier effet influence le taux de destruction des mauvais emplois, le second a un impact sur la mobilité du travail des mauvais vers les bons emplois.

Doctorat en Sciences économiques et de gestion
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This thesis aims at analysing some aspects of Venture Capital (VC) and high-tech entrepreneurship. The focus is both at the macroeconomic level, comparing venture capital from an international point of view and Technology-Based Small Firms (TBSF) at company and founder’s level in Belgium. The approach is mainly empirical.

This work is divided into two parts. The first part focuses on venture capital. First of all, we test the impact of VC on productivity. We then identify the determinants of VC and we test their impact on the relative level of VC for a panel of countries.

The second part concerns the technology-based small firms in Belgium. The objective is twofold. It first aims at creating a database on Belgian TBSF to better understand the importance of entrepreneurship. In order to do this, a national survey was developed and the statistical results were analysed. Secondly, it provides an analysis of the role of universities in the employment performance of TBSF.

A broad summary of each chapter is presented below.

PART 1: VENTURE CAPITAL

The Economic Impact of Venture Capital

The objective of this chapter is to perform an evaluation of the macroeconomic impact of venture capital. The main assumption is that VC can be considered as being similar in several respects to business R&D performed by large firms. We test whether VC contributes to economic growth through two main channels. The first one is innovation, characterized by the introduction of new products, processes or services on the market. The second one is the development of an absorptive capacity. These hypotheses are tested quantitatively with a production function model for a panel data set of 16 OECD countries from 1990 to 2001. The results show that the accumulation of VC is a significant factor contributing directly to Multi-Factor Productivity (MFP) growth. The social rate of return to VC is significantly higher than the social rate of return to business or public R&D. VC has also an indirect impact on MFP in the sense that it improves the output elasticity of R&D. An increased VC intensity makes it easier to absorb the knowledge generated by universities and firms, and therefore improves aggregate economic performance.

Technological Opportunity, Entrepreneurial Environment and Venture Capital Development

The objective of this chapter is to identify the main determinants of venture capital. We develop a theoretical model where three main types of factors affect the demand and supply of VC: macroeconomic conditions, technological opportunity, and the entrepreneurial environment. The model is evaluated with a panel dataset of 16 OECD countries over the period 1990-2000. The estimates show that VC intensity is pro-cyclical - it reacts positively and significantly to GDP growth. Interest rates affect the VC intensity mainly because the entrepreneurs create a demand for this type of funding. Indicators of technological opportunity such as the stock of knowledge and the number of triadic patents affect positively and significantly the relative level of VC. Labour market rigidities reduce the impact of the GDP growth rate and of the stock of knowledge, whereas a minimum level of entrepreneurship is required in order to have a positive effect of the available stock of knowledge on VC intensity.

PART 2: TECHNOLOGY-BASED SMALL FIRMS

Survey in Belgium

The first purpose of this chapter is to present the existing literature on the performance of companies. In order to get a quantitative insight into the entrepreneurial growth process, an original survey of TBSF in Belgium was launched in 2002. The second purpose is to describe the methodology of our national TBSF survey. This survey has two main merits. The first one lies in the quality of the information. Indeed, most of national and international surveys have been developed at firm-level. There exist only a few surveys at founder-level. In the TBSF database, information both at firm and at entrepreneur-level will be found.

The second merit is about the subject covered. TBSF survey tackles the financing of firms (availability of public funds, role of venture capitalists, availability of business angels,…), the framework conditions (e.g. the quality and availability of infrastructures and communication channels, the level of academic and public research, the patenting process,…) and, finally, the socio-cultural factors associated with the entrepreneurs and their environment (e.g. level of education, their parents’education, gender,…).

Statistical Evidence

The main characteristics of companies in our sample are that employment and profits net of taxation do not follow the same trend. Indeed, employment may decrease while results after taxes may stay constant. Only a few companies enjoy a growth in both employment and results after taxes between 1998 and 2003.

On the financing front, our findings suggest that internal finance in the form of personal funds, as well as the funds of family and friends are the primary source of capital to start-up a high-tech company in Belgium. Entrepreneurs rely on their own personal savings in 84 percent of the cases. Commercial bank loans are the secondary source of finance. This part of external financing (debt-finance) exceeds the combined angel funds and venture capital funds (equity-finance).

On the entrepreneur front, the preliminary results show that 80 percent of entrepreneurs in this study have a university degree while 42 percent hold postgraduate degrees (i.e. master’s, and doctorate). In term of research activities, 88 percent of the entrepreneurs holding a Ph.D. or a post-doctorate collaborate with Belgian higher education institutes. Moreover, more than 90 percent of these entrepreneurs are working in a university spin-off.

The Contribution of Universities to Employment Growth

The objective of this chapter is to test whether universities play a role amongst the determinants of employment growth in Belgian TBSF. The empirical model is based on our original survey of 87 Belgian TBSF. The results suggest that both academic spin-offs and TBSF created on the basis of an idea originating from business R&D activities are associated with an above than average growth in employees. As most ‘high-tech’ entrepreneurs are at least graduated from universities, there is no significant impact of the level of education. Nevertheless, these results must be taken with caution, as they are highly sensitive to the presence of outliers. Young high-tech firms are by definition highly volatile, and might be therefore difficult to understand.

CONCLUSION

In this last chapter, recommendations for policy-makers are drawn from the results of the thesis. The possible interventions of governments are classified according to whether they influence the demand or the supply of entrepreneurship and/or VC. We present some possible actions such as direct intervention in the VC funds, interventions of public sector through labour market rigidities, pension system, patent and research policy, level of entrepreneurial activities, bankruptcy legislation, entrepreneurial education, development of university spin-offs, and creation of a national database of TBSF.

Doctorat en Sciences économiques et de gestion
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This thesis studies comovement in financial markets under three dimensions. First, I consider comovement in equity liquidity. The liquidity of an asset is the ease with which that asset can be bought or sold. Liquidity can be measured in various ways and the first chapter concludes that market movements of two different liquidity measures have the same origin. Second, I study the impact correlation comovement on the price of stocks. The correlations between stock returns and the market return evolve through time and are correlated themselves. The effect of this correlation comovement on asset prices is however ambiguous and there is not enough evidence to depict a clear image. Finally, I develop a model to investigate contagion dynamics in the secondary market for European sovereign bonds over the past two years. More particularly, I study whether changes in the bond price of one specific country have an impact the next day on the average bond price in Europe. The study concludes of that bonds of France, Ireland, Portugal, Spain and Italy have been most contagious, whereas the much more volatile Greek bonds have had little impact on the other European countries.
Doctorat en Sciences économiques et de gestion
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