How committed are bank lines of credit? Experiences in the subprime mortgage crisis

Using the subprime mortgage crisis as a shock, this paper shows that commercial borrowers served by more distressed banks (as measured by recent bank stock returns or the nonperforming loan ratio) took down fewer funds from precommitted, formal lines of credit. The credit constraints affected mainly smaller, riskier (by internal loan ratings), and shorter-relationship borrowers, and depended also on the lenders' size, liquidity condition, capitalization position, and core deposit funding. The evidence suggests that credit lines provided only contingent and partial insurance during the crisis since bank conditions appeared to influence credit line utilization in the short term. It provides a new explanation as to why credit lines are not perfect substitutes for cash holdings for some (e.g. small) firms. Finally, loan level analyses show that more distressed banks charged higher credit spreads on newly negotiated loans but not on funds disbursed from precommitted, formal credit lines. The author's analyses are based on commercial loan flow data from the confidential Survey of Terms of Business Lending (STBL).Commercial credit ; Global financial crisis

The effect of monetary tightening on local banks

This study shows that during Paul Volcker’s drastic monetary tightening in the early 1980s, local banks operating in only one county reduced loan supply much more sharply than local subsidiaries of multi-county bank holding companies in similar markets, after controlling for bank (and holding company) size, liquidity, capital conditions, and, most important, local credit demand. The study allows cleaner identification by examining 18 U.S. “county-banking states” where a bank’s local lending volume at the county level was observable because no one was allowed to branch across county borders. The local nature of lending allows us to approximate and control for the exogenous component of local loan demand using the prediction that counties with a higher share of manufacturing employment exhibit weaker loan demand during tightening (which is consistent with the interest rate channel and the balance-sheet channel of monetary policy transmission).The study sheds light on the working of the bank lending channel of monetary policy transmission.Monetary policy

Because I'm worth it? CEO pay and corporate governance

Recently, there has been strong public outrage against current pay practices for corporate CEOs. To deal with this issue, the Dodd-Frank Wall Street Reform and Consumer Protection Act signed into law by President Obama on July 21, 2010 will allow shareholders to vote on executive pay packages and federal regulators to oversee executive compensation at financial firms. Are there problems with CEO pay? According to a recent survey, 98 percent of respondents from major financial institutions “believe that compensation structures were a factor underlying the crisis.” In “Because I’m Worth It? CEO Pay and Corporate Governance,” Rocco Huang outlines what we know about how CEOs are paid, how the pay is set, how CEO compensation affects CEOs’ incentives and actions and their firms’ performance, and how government regulations affect CEO pay.Corporate governance ; Executives - Salaries ; Regulation

The dark side of bank wholesale funding

Banks increasingly use short-term wholesale funds to supplement traditional retail deposits. Existing literature mainly points to the "bright side" of wholesale funding: sophisticated financiers can monitor banks, disciplining bad but refinancing good ones. This paper models a "dark side" of wholesale funding. In an environment with a costless but noisy public signal on bank project quality, short-term wholesale financiers have lower incentives to conduct costly monitoring, and instead may withdraw based on negative public signals, triggering inefficient liquidations. Comparative statics suggest that such distortions of incentives are smaller when public signals are less relevant and project liquidation costs are higher, e.g., when banks hold mostly relationship-based small business loans. JEL Classification: G21, G28, G33Financial crises, liquidity risk, regulation, Wholesale Funding

Distance and Trade: Disentangling unfamiliarity effects and transport cost effects

This paper provides evidence supporting Grossman’s (1996) claim that not only transport costs but also unfamiliarity can explain the negative correlation between geographic distances and bilateral trade volumes. A gravity model that controls for as many natural causes of trade as possible reveals that countries high in uncertainty-aversion (based on Hofstede’s survey) export disproportionately less to distant countries (with which they are presumably less familiar). More important, this result is mainly driven by differentiated products, not by products with international organized exchanges or with reference prices. For transport costs alone to explain such a trade pattern, one would have to assume that distance-related ad valorem transport costs are higher when a trade route originates from a high uncertainty-aversion country, which is unlikely. This trade pattern is easy to explain, however, if one accepts that geographic distance is a proxy for unfamiliarity and that exporters in high uncertainty-aversion countries are more sensitive to informational ambiguity. A further result is that high uncertainty- aversion countries trade less and thus grow more slowly in the long run, which suggests that cultural factors are as important as geographic ones in determining trade openness.

Industry Choices and Social Interactions of Entrepreneurs: Identification by Residential Addresses

This paper shows that industry choices of entrepreneurs are determined by their social networks. The separation of residential and business addresses helps us establish the causality, because we can safely argue that residential addresses determine social networks but do not directly affect industry choices. In a large cross-section of London neighborhoods (average area: one squared-mile), we show that new generation of entrepreneurs are more likely to enter industries overrepresented by their residential neighbors. We further show that industry composition of a neighborhood is more persistent when social interactions are more intensive and of higher quality, as proxied by higher ethnic homogeneity, more sociable housing structures, or higher entrepreneurial population density. The effect is also stronger in industries that require more informational interactions, as proxied by greater geographic agglomeration of entrepreneurs. The median home- business distances in our sample is nearly six kilometers, thus the persistence of a neighborhood’s industry specialization is unlikely to be driven by unobservable common product market conditions. We also control for industry specialization at borough level (each borough contains around 20 neighborhoods), to further remove the effects of unobservable factors. Finally, we also use various sub-groups of entrepreneurs to test for a series of alternative hypotheses, and we do not find support for them. We do not find failure rates to be significantly different for entrepreneurs who follow their neighbors’ popular choices. Overall, the results suggest that entry of new entrepreneurs tend to reinforce agglomeration, while exits do not reverse it. These evidences (weakly) lend support to the existence of agglomeration economies.

Erk5 is a mediator to TGFβ1-induced loss of phenotype and function in human podocytes.

Background: Podocytes are highly specialized cells integral to the normal functioning kidney, however, in diabetic nephropathy injury occurs leading to a compromised phenotype and podocyte dysfunction which critically produces podocyte loss with subsequent renal impairment. TGFβ1 holds a major role in the development of diabetic nephropathy. Erk5 is an atypical mitogen-activated protein (MAP) kinase involved in pathways modulating cell survival, proliferation, differentiation, and motility. Accordingly, the role of Erk5 in mediating TGFβ1-induced podocyte damage was investigated. Methods: Conditionally immortalized human podocytes were stimulated with TGFβ1 (2.5 ng/ml); inhibition of Erk5 activation was conducted with the chemical inhibitor BIX02188 (10 μM) directed to the upstream Mek5; inhibition of Alk5 was performed with SB431542 (10 μM); Ras signaling was inhibited with farnesylthiosalicylic acid (10 μM). Intracellular signaling proteins were investigated by western blotting; phenotype was explored by immunofluorescence; proliferation was assessed with a MTS assay; motility was examined with a scratch assay; barrier function was studied using electric cell-substrate impedance sensing; apoptosis was studied with annexin V-FITC flow cytometry. Results: Podocytes expressed Erk5 which was phosphorylated by TGFβ1 via Mek5, whilst not involving Ras. TGFβ1 altered podocyte phenotype by decreasing P-cadherin staining and increasing α-SMA, as well as reducing podocyte barrier function; both were prevented by inhibiting Erk5 phosphorylation with BIX02188. TGFβ1-induced podocyte proliferation was prevented by BIX02188, whereas the induced apoptosis was not. Podocyte motility was reduced by BIX02188 alone and further diminished with TGFβ1 co-incubation. Conclusion: These results describe for the first time the expression of Erk5 in podocytes and identify it as a potential target for the treatment of diabetic renal disease

Kernel Spectral Clustering and applications

In this chapter we review the main literature related to kernel spectral clustering (KSC), an approach to clustering cast within a kernel-based optimization setting. KSC represents a least-squares support vector machine based formulation of spectral clustering described by a weighted kernel PCA objective. Just as in the classifier case, the binary clustering model is expressed by a hyperplane in a high dimensional space induced by a kernel. In addition, the multi-way clustering can be obtained by combining a set of binary decision functions via an Error Correcting Output Codes (ECOC) encoding scheme. Because of its model-based nature, the KSC method encompasses three main steps: training, validation, testing. In the validation stage model selection is performed to obtain tuning parameters, like the number of clusters present in the data. This is a major advantage compared to classical spectral clustering where the determination of the clustering parameters is unclear and relies on heuristics. Once a KSC model is trained on a small subset of the entire data, it is able to generalize well to unseen test points. Beyond the basic formulation, sparse KSC algorithms based on the Incomplete Cholesky Decomposition (ICD) and $L_0$, $L_1, L_0 + L_1$, Group Lasso regularization are reviewed. In that respect, we show how it is possible to handle large scale data. Also, two possible ways to perform hierarchical clustering and a soft clustering method are presented. Finally, real-world applications such as image segmentation, power load time-series clustering, document clustering and big data learning are considered.Comment: chapter contribution to the book "Unsupervised Learning Algorithms

Proteomic Analysis of Chloroplast-to-Chromoplast Transition in Tomato Reveals Metabolic Shifts Coupled with Disrupted Thylakoid Biogenesis Machinery and Elevated Energy-Production Components

A comparative proteomic approach was performed to identify differentially expressed proteins in plastids at three stages of tomato(Solanum lycopersicum) fruit ripening (mature-green, breaker, red). Stringent curation and processing of the data from three independent replicates identified 1,932 proteins among which 1,529 were quantified by spectral counting. The quantification procedures have been subsequently validated by immunoblot analysis of six proteins representative of distinct metabolic or regulatory pathways. Among the main features of the chloroplast-to-chromoplast transition revealed by the study, chromoplastogenesis appears to be associated with major metabolic shifts: (1) strong decrease in abundance of proteins of light reactions (photosynthesis, Calvin cycle, photorespiration)and carbohydrate metabolism (starch synthesis/degradation), mostly between breaker and red stages and (2) increase in terpenoid biosynthesis (including carotenoids) and stress-response proteins (ascorbate-glutathione cycle, abiotic stress, redox, heat shock). These metabolic shifts are preceded by the accumulation of plastid-encoded acetyl Coenzyme A carboxylase D proteins accounting for the generation of a storage matrix that will accumulate carotenoids. Of particular note is the high abundance of proteins involved in providing energy and in metabolites import. Structural differentiation of the chromoplast is characterized by a sharp and continuous decrease of thylakoid proteins whereas envelope and stroma proteins remain remarkably stable. This is coincident with the disruption of the machinery for thylakoids and photosystem biogenesis (vesicular trafficking, provision of material for thylakoid biosynthesis, photosystems assembly) and the loss of the plastid division machinery. Altogether, the data provide new insights on the chromoplast differentiation process while enriching our knowledge of the plant plastid proteome