Credit Constraints, Firms' Precautionary Investment, and the Business Cycle

This paper studies the macroeconomic implications of firms' precautionary investment behavior in response to the anticipation of future financing constraints. Firms increase their demand for liquid and safe investments in order to alleviate future borrowing constraints and decrease the probability of having to forego future profitable investment opportunities. This results in an increase in the share of short-term projects that produces a temporary increase in output, at the expense of lower long-run investment and future output. I show in a calibrated model that this behavior is at the source of a novel and powerful channel of shock transmission of productivity shocks that produces short-run dampening and long-run propagation. Furthermore, it can account for the observed business cycle patterns of the aggregate and firm-level composition of investment.

Chaotic dynamics in credit constrained emerging economies

This paper analyzes the role of financial development as a source of endogenous instability in small open economies. By assuming that firms face credit constraints, our model displays a complex dynamic behavior for intermediate values of the parameter representing the level of financial development of the economy. The basic implication of our model is that economies experiencing a process of financial development are more unstable than both very underdeveloped and very developed economies. Our instability concept means that small shocks have a persistent effect on the long run behavior of the model and also that economies can exhibit cycles with a very high period or even chaotic dynamic patterns.

Credit markets and the propagation of monetary policy shocks

This paper analyzes the propagation of monetary policy shocks through the creation of credit in an economy. Models of the monetary transmission mechanism typically feature responses which last for a few quarters contrary to what the empirical evidence suggests. To propagate the impact of monetary shocks over time, these models introduce adjustment costs by which agents find it optimal to change their decisions slowly. This paper presents another explanation that does not rely on any sort of adjustment costs or stickiness. In our economy, agents own assets and make occupational choices. Banks intermediate between agents demanding and supplying assets. Our interpretation is based on the way banks create credit and how the monetary authority affects the process of financial intermediation through its monetary policy. As the central bank lowers the interest rate by buying government bonds in exchange for reserves, high productive entrepreneurs are able to borrow more resources from low productivity agents. We show that this movement of capital among agents sets in motion a response of the economy that resembles an expansionary phase of the cycle.

Can competition in the credit market be excessive?

We study how market power affects investment and welfare when banks choose between restricting loan sizes and monitoring, in order to alleviate an underlying moral hazard problem. The impact of market power on aggregate welfare is the result of two countervailing effects. An increase in banks' market power results in: (i) higher lending rates, which worsens the borrower's incentive problem and reduces investment by unmonitored firms, (ii) higher monitoring effort, which reduces the proportion of credit-constrained firms. Whenever the second effect dominates, it is optimal to provide banks with some degree of market power.

The Adoption of agricultural credit cooperativism in Spain (1890-1935) : solidarity from below?

The spread of agrarian credit cooperativism in Spain (1890-1934) was done under a variety of ideological and economic orientations. This article focuses on the construction of a few tools and indicators to explain the characteristics of agricultural credit cooperatives. An analysis of financial operations of rural savings banks is related with socio-political aspects that influenced their development; This analysis helps us to explain the relative success of German credit cooperative models adopted in the context of Spanish agriculture, as happened on European periphery.

Leading indicator properties of US high-yield credit spreads

In this paper we examine the out-of-sample forecast performance of high-yield credit spreads regarding real-time and revised data on employment and industrial production in the US. We evaluate models using both a point forecast and a probability forecast exercise. Our main findings suggest the use of few factors obtained by pooling information from a number of sector-specific high-yield credit spreads. This can be justified by observing that, especially for employment, there is a gain from using a principal components model fitted to high-yield credit spreads compared to the prediction produced by benchmarks, such as an AR, and ARDL models that use either the term spread or the aggregate high-yield spread as exogenous regressor. Moreover, forecasts based on real-time data are generally comparable to forecasts based on revised data. JEL Classification: C22; C53; E32 Keywords: Credit spreads; Principal components; Forecasting; Real-time data.

Trade, firm selection, and innovation: the competition channel

The availability of rich firm-level data sets has recently led researchers to uncover new evidence on the effects of trade liberalization. First, trade openness forces the least productive firms to exit the market. Secondly, it induces surviving firms to increase their innovation efforts and thirdly, it increases the degree of product market competition. In this paper we propose a model aimed at providing a coherent interpretation of these findings. We introducing firm heterogeneity into an innovation-driven growth model, where incumbent firms operating in oligopolistic industries perform cost-reducing innovations. In this framework, trade liberalization leads to higher product market competition, lower markups and higher quantity produced. These changes in markups and quantities, in turn, promote innovation and productivity growth through a direct competition effect, based on the increase in the size of the market, and a selection effect, produced by the reallocation of resources towards more productive firms. Calibrated to match US aggregate and firm-level statistics, the model predicts that a 10 percent reduction in variable trade costs reduces markups by 1:15 percent, firm surviving probabilities by 1 percent, and induces an increase in productivity growth of about 13 percent. More than 90 percent of the trade-induced growth increase can be attributed to the selection effect.

Haar wavelets-based approach for quantifying credit portfolio losses

This paper proposes a new methodology to compute Value at Risk (VaR) for quantifying losses in credit portfolios. We approximate the cumulative distribution of the loss function by a finite combination of Haar wavelet basis functions and calculate the coefficients of the approximation by inverting its Laplace transform. The Wavelet Approximation (WA) method is specially suitable for non-smooth distributions, often arising in small or concentrated portfolios, when the hypothesis of the Basel II formulas are violated. To test the methodology we consider the Vasicek one-factor portfolio credit loss model as our model framework. WA is an accurate, robust and fast method, allowing to estimate VaR much more quickly than with a Monte Carlo (MC) method at the same level of accuracy and reliability.

Credit risk contributions under the Vasicek one-factor model: a fast wavelet expansion approximation

To measure the contribution of individual transactions inside the total risk of a credit portfolio is a major issue in financial institutions. VaR Contributions (VaRC) and Expected Shortfall Contributions (ESC) have become two popular ways of quantifying the risks. However, the usual Monte Carlo (MC) approach is known to be a very time consuming method for computing these risk contributions. In this paper we consider the Wavelet Approximation (WA) method for Value at Risk (VaR) computation presented in [Mas10] in order to calculate the Expected Shortfall (ES) and the risk contributions under the Vasicek one-factor model framework. We decompose the VaR and the ES as a sum of sensitivities representing the marginal impact on the total portfolio risk. Moreover, we present technical improvements in the Wavelet Approximation (WA) that considerably reduce the computational effort in the approximation while, at the same time, the accuracy increases.

Credit consulting : anàlisi de l'amortització anticipada de crèdits mitjançant el VAD

El projecte que he dut a terme és la implementació d'una pàgina web orientada a aquells usuaris que necessiten assessorament davant d'un crèdit bancari que ja posseeixen o que vulguin realitzar. Aquesta web financera té com a objectiu donar un cop de mà a tota aquella gent que té demanat un crèdit bancari a interès fixe i vol saber en un moment determinat si és convenient o no amortitzar anticipadament tenint en compte variables com: interès del mercat, penalització deguda a l'anticipació, la fiscalitat en el cas de les empreses, anys que queden per acabar de pagar el crèdit, sistema d'amortització financera utilitzat, etc.

Impaired fast-spiking, suppressed cortical inhibition and increased susceptibility to seizures in mice lacking Kv3.2 K+ channel proteins

Voltage-gated K+ channels of the Kv3 subfamily have unusual electrophysiological properties, including activation at very depolarized voltages (positive to −10 mV) and very fast deactivation rates, suggesting special roles in neuronal excitability. In the brain, Kv3 channels are prominently expressed in select neuronal populations, which include fast-spiking (FS) GABAergic interneurons of the neocortex, hippocampus, and caudate, as well as other high-frequency firing neurons. Although evidence points to a key role in high-frequency firing, a definitive understanding of the function of these channels has been hampered by a lack of selective pharmacological tools. We therefore generated mouse lines in which one of the Kv3 genes, Kv3.2, was disrupted by gene-targeting methods. Whole-cell electrophysiological recording showed that the ability to fire spikes at high frequencies was impaired in immunocytochemically identified FS interneurons of deep cortical layers (5-6) in which Kv3.2 proteins are normally prominent. No such impairment was found for FS neurons of superficial layers (2-4) in which Kv3.2 proteins are normally only weakly expressed. These data directly support the hypothesis that Kv3 channels are necessary for high-frequency firing. Moreover, we found that Kv3.2 −/− mice showed specific alterations in their cortical EEG patterns and an increased susceptibility to epileptic seizures consistent with an impairment of cortical inhibitory mechanisms. This implies that, rather than producing hyperexcitability of the inhibitory interneurons, Kv3.2 channel elimination suppresses their activity. These data suggest that normal cortical operations depend on the ability of inhibitory interneurons to generate high-frequency firing.

K(+) channel expression distinguishes subpopulations of parvalbumin- and somatostatin-containing neocortical interneurons

Kv3.1 and Kv3.2 K+ channel proteins form similar voltage-gated K+ channels with unusual properties, including fast activation at voltages positive to −10 mV and very fast deactivation rates. These properties are thought to facilitate sustained high-frequency firing. Kv3.1 subunits are specifically found in fast-spiking, parvalbumin (PV)-containing cortical interneurons, and recent studies have provided support for a crucial role in the generation of the fast-spiking phenotype. Kv3.2 mRNAs are also found in a small subset of neocortical neurons, although the distribution of these neurons is different. We raised antibodies directed against Kv3.2 proteins and used dual-labeling methods to identify the neocortical neurons expressing Kv3.2 proteins and to determine their subcellular localization. Kv3.2 proteins are prominently expressed in patches in somatic and proximal dendritic membrane as well as in axons and presynaptic terminals of GABAergic interneurons. Kv3.2 subunits are found in all PV-containing neurons in deep cortical layers where they probably form heteromultimeric channels with Kv3.1 subunits. In contrast, in superficial layer PV-positive neurons Kv3.2 immunoreactivity is low, but Kv3.1 is still prominently expressed. Because Kv3.1 and Kv3.2 channels are differentially modulated by protein kinases, these results raise the possibility that the fast-spiking properties of superficial- and deep-layer PV neurons are differentially regulated by neuromodulators. Interestingly, Kv3.2 but not Kv3.1 proteins are also prominent in a subset of seemingly non-fast-spiking, somatostatin- and calbindin-containing interneurons, suggesting that the Kv3.1–Kv3.2 current type can have functions other than facilitating high-frequency firing.

Outage probability analysis for MRC in η-μ fading channels with co-channel interference

Exact closed-form expressions are obtained for the outage probability of maximal ratio combining in η-μ fadingchannels with antenna correlation and co-channel interference. The scenario considered in this work assumes the joint presence of background white Gaussian noise and independent Rayleigh-faded interferers with arbitrary powers. Outage probability results are obtained through an appropriate generalization of the moment-generating function of theη-μ fading distribution, for which new closed-form expressions are provided.

Sequential estimation of time-varying multipath channel for MIMO-OFDM systems

In this paper, we introduce a pilot-aided multipath channel estimator for Multiple-Input Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems. Typical estimation algorithms assume the number of multipath components and delays to be known and constant, while theiramplitudes may vary in time. In this work, we focus on the more realistic assumption that also the number of channel taps is unknown and time-varying. The estimation problem arising from this assumption is solved using Random Set Theory (RST), which is a probability theory of finite sets. Due to the lack of a closed form of the optimal filter, a Rao-Blackwellized Particle Filter (RBPF) implementation of the channel estimator is derived. Simulation results demonstrate the estimator effectiveness.