Macroéconomie | EPFL Graph Search

thumb|Modélisation des relations macroéconomiques entre agrégats dans une économie. La macroéconomie est une discipline de l'économie qui étudie le système économique au niveau agrégé à travers les relations entre les grands agrégats économiques que sont le revenu, l'investissement, la consommation. La macroéconomie constitue l'outil essentiel d'analyse des politiques économiques des États ou des organisations internationales. Il s'agit d'expliquer les mécanismes par lesquels sont produites les richesses à travers le cycle de la production, de la consommation, et de la répartition des revenus au niveau national ou international. Définition La macroéconomie est une branche de la science économique. Elle se consacre à l'étude des grandes variables économiques nationales ou internationales, et aux relations entre ces variables. Elle repose sur une approche globale, quoiqu'elle puisse se fonder sur des comportements microéconomiques. Parce qu'elle fonctionne par la comparaiso

The triangular value of patents

Albina Khairullina

This thesis addresses the question of a patent value from three different angles. It comprises three papers on the patent valuation methods. The patent valuation issues are well-known to the world of research and practice. However, the debates over what the patent contributes to the business and the economy overall remain open. The main contribution of my dissertation is that I present novel ways of addressing the value of patents from both micro- and macroeconomic perspectives. I bridge the theoretical modeling with real-world estimations, which sheds light on the legitimacy of certain hypothetical assumptions in patent valuation. In the first paper, I develop a factor model to value patents in a corporate patent portfolio. According to the results, the patent value is determined by five factors, such as forward and backward citations, family size, the number of oppositions received, and the number of claims. I contribute to the literature by introducing an interaction of a quantitative measure of a patent value with its qualitative assessment derived from a survey of patent managers. The results show that model estimates are weakly consistent with an expert opinion on the value of patents. In the second paper, we collaborate with a large multinational company and analyze internal and highly confidential data on product sales, revenues, and other corporate performance measures by tracing each patent down to its product market. To establish causality, we design a randomized controlled trial together with the management of the company, in which some randomly chosen patents are dropped from the portfolio, while others are kept for the duration of the study. To our knowledge, this is the first study that conducts a randomized controlled trial to measure the real market effect of patent protection. In the third paper, we study whether the regulator expands production possibilities of the economy by assigning a standard-essential status to patents. As we show, the innovatorsâ risk of losing the standard-setting game ex-ante attenuates the anticipation of a larger market share. Secondly, since the discovery of new technologies is typically slower than the discounting rate for the monopoly profits, standards with a positive contribution to productivity tend to be growth-reducing. Our results have significant policy implications. Regulators impose Fair, Reasonable, And Non-Discriminatory (FRAND) pricing on standard-essential technologies to compensate for the larger market-share the innovators get. We demonstrate how FRAND regulation of mark-ups has an unambiguously negative effect on growth and long-term growth-destroying consequences.

EPFL2020

Financial Stability and the Macroeconomy

Corinne Dubois

The financial crisis of 2007-2009 drew attention to the essential role of banks for the macroeconomy and to the importance of having a resilient financial sector. A vulnerability in the financial sector spills over to the real economy and can drive it into a deep recession. Following the financial crisis, policy makers have issued rules and regulations aimed at strengthening the banks. My dissertation considers some of those measures, namely bank liquidity regulation and deposit insurance, and tries to assess their effectiveness in stabilizing the financial sector and the economy in general. The first chapter (joint with Prof. Luisa Lambertini) develops a model with regulated banks and a hedge fund to analyze the behavior of wholesale funding and the macroeconomic consequences of liquidity regulation. Banks raise deposits and subordinated wholesale funding from the hedge fund. Wholesale funding amplifies shocks: it is curtailed in economic downturns to avoid leveraging up and risk-taking by banks, further depressing credit and economic activity. By making banks safer, liquidity regulation increases wholesale funding and bank loans at the steady state. However, flat liquidity regulation requiring banks to hold a constant fraction of liquid assets can have unintended consequences and increase macroeconomic volatility. Our model further shows that cyclically adjusted regulation stabilizes the response of the economy to shocks. We also provide empirical evidence suggesting that liquidity helps contain the contraction in wholesale funding and loans during times of funding stress. The second chapter explores the macroeconomic and welfare implications of harmonizing or joining deposit insurance in the Eurozone. I develop a two-country model to represent the core and periphery countries in the Eurozone. The model features fragile banks that can be subject to endogenous and costly runs. The two countries are financially integrated through an international interbank market. I introduce deposit insurance and compare different insurance regimes in steady state and along the business cycle. The model emphasizes that financial integration implies co-movement in asset prices and the transmission of shocks across the border. I find that when deposit insurance has lower coverage in the periphery than in the core, financial stability is undermined in both regions due to higher asset price volatility and a higher probability of deposit runs. Hence, either harmonizing or joining deposit insurance leads to substantial welfare benefits for both countries. In the third chapter, I develop a macroeconomic model with multiple equilibria and bank runs to analyze deposit insurance. A bank run is a sunspot equilibrium, and it is caused by a self-fulfilling panic of all depositors. The model features a unique no-run equilibrium when macroeconomic conditions are good, but an unexpected negative shock may open up the possibility of a run equilibrium. A bank run is a rare but costly event that drives the economy in a long and severe recession. I analyze the introduction and build-up of a deposit insurance fund and show that it reduces the cost and probability of bank runs. The dynamic simulation of the model reveals that deposit insurance diminishes macroeconomic and financial instability following a technological shock.

EPFL2018

Les mathématiques financières robustes, le maritime et les FFA

Jérôme Reboulleau

Powerful mathematical tools have been developed for trading in stocks and bonds, but other markets that are equally important for the globalized world have to some extent been neglected. We decided to study the shipping market as an new area of development in mathematical finance. The market in shipping derivatives (FFA and FOSVA) has only been developed after 2000 and now exhibits impressive growth. Financial actors have entered the field, but it is still largely undiscovered by institutional investors. The first part of the work was to identify the characteristics of the market in shipping, i.e. the segmentation and the volatility. Because the shipping business is old-fashioned, even the leading actors on the world stage (ship owners and banks) are using macro-economic models to forecast the rates. If the macro-economic models are logical and make sense, they fail to predict. For example, the factor port congestion has been much cited during the last few years, but it is clearly very difficult to control and is simply an indicator of traffic. From our own experience it appears that most ship owners are in fact market driven and rather bad at anticipating trends. Due to their ability to capture large moves, we chose to consider Lévy processes for the underlying price process. Compared with the macro-economic approach, the main advantage is the uniform and systematic structure this imposed on the models. We get in each case a favorable result for our technology and a gain in forecasting accuracy of around 10% depending on the maturity. The global distribution is more effectively modelled and the tails of the distribution are particularly well represented. This model can be used to forecast the market but also to evaluate the risk, for example, by computing the VaR. An important limitation is the non-robustness in the estimation of the Lévy processes. The use of robust estimators reinforces the information obtained from the observed data. Because maximum likelihood estimation is not easy to compute with complex processes, we only consider some very general robust score functions to manage the technical problems. Two new class of robust estimators are suggested. These are based on the work of F. Hampel ([29]) and P. Huber ([30]) using influence functions. The main idea is to bound the maximum likelihood score function. By doing this a bias is created in the parameters estimation, which can be corrected by using a modification of the following type and as proposed by F. Hampel. The procedure for finding a robust estimating equation is thus decomposed into two consecutive steps : Subtract the bias correction and then Bound the score function. In the case of complex Lévy processes, the bias correction is difficult to compute and generally unknown. We have developed a pragmatic solution by inverting the Hampel's procedure. Bound the score function and then Correct for the bias. The price is a loss of the theoretical properties of our estimators, besides the procedure converges to maximum likelihood estimate. A second solution to for achieving robust estimation is presented. It considers the limiting case when the upper and lower bounds tend to zero and leads to B-robust estimators. Because of the complexity of the Lévy distributions, this leads to identification problems.

EPFL2008