Capital (economics) | EPFL Graph Search

In economics, capital goods or capital are "those durable produced goods that are in turn used as productive inputs for further production" of goods and services. At the macroeconomic level, "the nation's capital stock includes buildings, equipment, software, and inventories during a given year." A typical example is the machinery used in factories. Capital can be increased by the use of the factors of production, which however excludes certain durable goods like homes and personal automobiles that are not used in the production of saleable goods and services. Adam Smith defined capital as "that part of man's stock which he expects to afford him revenue". In economic models, capital is an input in the production function. The total physical capital at any given moment in time is referred to as the capital stock (not to be confused with the capital stock of a business entity). Capital goods, real capital, or capital assets are already-produced, durable goods or any non-financial

Essays in Financial Economics

Julien Arsène Blatt

I started my PhD studies in August 2014 with a strong desire to push my own limits without knowing precisely the areas I wanted to cover in detail. To me, it was clear that I was interested by many different fields, however, I was particularly concerned with behavioural finance and with the fact that simple actions could be followed by strong market reactions. It is in this context that my supervisor, Prof. Semyon Malamud, advised me to derive/measure the consequences of the large acceptance of the RiskMetrics variance model on the price of financial assets. Indeed, this method has the advantage of providing a simple formula to estimate the volatility of any financial asset, but above all, has been used significantly by practitioners in the financial industry. The question then arises, ``Is there a link between this method and the price of financial assets?'' In order to answer this question, I have designed a simple portfolio optimization model in which agents update volatility estimates with the RiskMetrics formula. Thanks to this simple idea my first project was born and I quickly realized that I could design an elegant model. With this framework I have been able to establish the existence of a risk factor of which the economic literature was unaware. Moreover, the empirical strategy allows me to estimate the relative risk aversion coefficient independently from established procedures. Importantly, my estimates are in line with the ones obtained with these (standard) approaches. Meanwhile, I was also interested in a topic that covers a large part of all trades and is known as ``over-the-counter markets''. These markets are characterized by their high level of decentralization. Indeed, every transaction is settled directly between a buyer and a seller. In these markets, the only way to secure a trade is to find another agent that is willing to take the counter-party. I became very interested in a series of books and articles that were modeling financial assets traded under these conditions. Hence, I have started to work in this field by solving different models. I was particularly interested in understanding how the price of assets traded with this constraint would react under stressful situations, that is, when agents had to liquidate their investments. After a trial and error process, I found that my model generated puzzling results. Indeed, this model made predictions that were against traditional wisdom. Above all, that model predicted that a large level of capital mobility could impair welfare. Hence, I had eventually found the link between all the fields I wanted to cover in my thesis, where I debate the optimal allocation of capital under different types of frictions. While my first article treats the case of a centralized market with an agent who forecasts volatility using a particular method, the second article concerns how capital flows across markets when agents are subject to searching frictions. My third article is based on the second and discusses the interaction between innovation and the competition between firms supplying the same products. This article focuses on how capital is used by firms to innovate and how firms grow.

EPFL2019

Capital goods, measured TFP and growth: The case of Spain

Luis Franjo Garcia

The effect of investing in equipment and/or structures on TFP and long run growth is investigated here. We argue that economies can grow in spite of stagnant TFP if the investment rate is inefficiently high. We study the case of Spain where real GDP per worker grew at 2.74 percent annually and TFP was stagnant during 1996-2007. We show that low Spanish TFP is due to low ISTC and an inefficiently high investment in residential structures. We quantify the effect of the housing boom of the 2000s, the total cost of subsidies to residential structures in terms of TFP and income growth. (C) 2016 Elsevier B.V. All rights reserved.

Elsevier Science Bv2016

Essays in Financial Economics

Julien Arsène Blatt

EPFL2019