Do laws influence the cost of real estate brokerage services? A state fixed effects approach

A FTC-DOJ study argues that state laws and regulations may inhibit the unbundling of real estate brokerage services in response to new technology. Our data show that 18 states have changed laws in ways that promote unbundling since 2000. We model brokerage costs as measured by number of agents in a state-level annual panel vector autoregressive framework, a novel way of analyzing wasteful competition. Our findings support a positive relationship between brokerage costs and lagged house price and transactions. We find that change in full-service brokers responds negatively (by well over two percentage points per year) to legal changes facilitating unbundling

The transaction cost economics theory of the family firm: family-based human asset specificity and the bifurcation bias

We develop a transaction cost economics theory of the family firm, building upon the concepts of family-based asset specificity, bounded rationality, and bounded reliability. We argue that the prosperity and survival of family firms depend on the absence of a dysfunctional bifurcation bias. The bifurcation bias is an expression of bounded reliability, reflected in the de facto asymmetric treatment of family vs. nonfamily assets (especially human assets). We propose that absence of bifurcation bias is critical to fostering reliability in family business functioning. Our study ends the unproductive divide between the agency and stewardship perspectives of the family firm, which offer conflicting accounts of this firm type's functioning. We show that the predictions of the agency and stewardship perspectives can be usefully reconciled when focusing on how family firms address the bifurcation bias or fail to do so.

Margin squeeze: an above cost predatory pricing approach

We provide a new legal perspective for the antitrust analysis of margin squeeze conducts. Building on recent economic analysis, we explain why margin squeeze conducts should solely be evaluated under adjusted predatory pricing standards. The adjustment corresponds to an increase in the cost benchmark used in the predatory pricing test by including opportunity costs due to missed upstream sales. This can reduce both the risks of false-positives and false-negatives in margin squeeze cases. We justify this approach by explaining why classic arguments against above-cost predatory pricing typically do not hold in vertical structures where margin squeezes take place and by presenting case law evidence supporting this adjustment. Our approach can help to reconcile the divergent US and EU antitrust stances on margin squeeze.

The effects of corporate and country sustainability characteristics on the cost of debt: an international investigation

We investigate the relationship between corporate and country sustainability on the cost of bank loans. We look into 470 loan agreements signed between 2005 and 2012 with borrowers based in 28 different countries across the world and operating in all major industries. Our principal findings reveal that country sustainability, relating to both social and environmental frameworks, has a statistically and economically impactful effect on direct financing of economic activity. An increase of one unit in a country's sustainability score is associated with an average decrease in the cost of debt by 64 basis points. Our international analysis shows that the environmental dimension of a country's institutional framework is approximately twice as impactful as the social dimension, when it comes to determining the cost of corporate loans. On the other hand, we find no conclusive evidence that firm-level sustainability influences the interest rates charged to borrowing firms by banks. Our main findings survive a battery of robustness tests and additional analyses concerning subsamples, alternative sustainability metrics and the effects of financial crisis.

Simulating the impact on health of internalising the cost of carbon in food prices combined with a tax on sugar-sweetened beverages

Rising greenhouse gas emissions (GHGEs) have implications for health and up to 30 % of emissions globally are thought to arise from agriculture. Synergies exist between diets low in GHGEs and health however some foods have the opposite relationship, such as sugar production being a relatively low source of GHGEs. In order to address this and to further characterise a healthy sustainable diet, we model the effect on UK non-communicable disease mortality and GHGEs of internalising the social cost of carbon into the price of food alongside a 20 % tax on sugar sweetened beverages (SSBs). Developing previously published work, we simulate four tax scenarios: (A) a GHGEs tax of £2.86/tonne of CO2 equivalents (tCO2e)/100 g product on all products with emissions greater than the mean across all food groups (0.36 kgCO2e/100 g); (B) scenario A but with subsidies on foods with emissions lower than 0.36 kgCO2e/100 g such that the effect is revenue neutral; (C) scenario A but with a 20 % sales tax on SSBs; (D) scenario B but with a 20 % sales tax on SSBs. An almost ideal demand system is used to estimate price elasticities and a comparative risk assessment model is used to estimate changes to non-communicable disease mortality. We estimate that scenario A would lead to 300 deaths delayed or averted, 18,900 ktCO2e fewer GHGEs, and £3.0 billion tax revenue; scenario B, 90 deaths delayed or averted and 17,100 ktCO2e fewer GHGEs; scenario C, 1,200 deaths delayed or averted, 18,500 ktCO2e fewer GHGEs, and £3.4 billion revenue; and scenario D, 2,000 deaths delayed or averted and 16,500 ktCO2e fewer GHGEs. Deaths averted are mainly due to increased fibre and reduced fat consumption; a SSB tax reduces SSB and sugar consumption. Incorporating the social cost of carbon into the price of food has the potential to improve health, reduce GHGEs, and raise revenue. The simple addition of a tax on SSBs can mitigate negative health consequences arising from sugar being low in GHGEs. Further conflicts remain, including increased consumption of unhealthy foods such as cakes and nutrients such as salt.

Dietary predictors of serum total carotene in low-income women living in Sao Paulo, south-east Brazil

Objective Dietary intake and nutritional status of antioxidant vitamins have been reported to protect against some cancers The objective of the present study was to assess the correlations between serum levels of carotenoids (including beta-, alpha- and gamma-carotene), lycopene, retinol, alpha- and gamma-tocopherols, and dietary intakes estimated by an FFQ, among low-income women in the Brazilian Investigation into Nutrition and Cervical Cancer Prevention (BRINCA) study. Design Cross-sectional study of data for 918 women aged 21-65 years participating in the BRINCA study in Sao Paulo city. Multiple linear regression models were used with serum nutrient levels as the dependent variable and dietary intake levels as the independent variable, adjusted for confounding factors. Results In energy-adjusted analyses, the intakes of dark green and deep yellow vegetables and fruits (partial R(2) = 4.8%), total fruits and juices (partial R(2) = 1.8%), vegetables and fruits (partial R(2) = 1.8%), carrots (partial R(2) = 1.4%) and citrus fruits and juices only (partial R(2) = 0.8%) were positively correlated only with serum total carotene levels, after adjusting for serum total cholesterol concentration, age, hospital attended, smoking status. BMI and presence of cervical lesions Multiple-adjusted serum levels of carotenoids were positively correlated with intake quartiles of dark green and deep yellow vegetables and fruits and total fruits and juices independent of smoking status. Conclusions The intake of specific fruits and vegetables was an independent predictor of serum total carotene levels in low-income women living in Sao Paulo

Poly-bagging predictors for classification modelling for credit scoring

Credit scoring modelling comprises one of the leading formal tools for supporting the granting of credit. Its core objective consists of the generation of a score by means of which potential clients can be listed in the order of the probability of default. A critical factor is whether a credit scoring model is accurate enough in order to provide correct classification of the client as a good or bad payer. In this context the concept of bootstraping aggregating (bagging) arises. The basic idea is to generate multiple classifiers by obtaining the predicted values from the fitted models to several replicated datasets and then combining them into a single predictive classification in order to improve the classification accuracy. In this paper we propose a new bagging-type variant procedure, which we call poly-bagging, consisting of combining predictors over a succession of resamplings. The study is derived by credit scoring modelling. The proposed poly-bagging procedure was applied to some different artificial datasets and to a real granting of credit dataset up to three successions of resamplings. We observed better classification accuracy for the two-bagged and the three-bagged models for all considered setups. These results lead to a strong indication that the poly-bagging approach may promote improvement on the modelling performance measures, while keeping a flexible and straightforward bagging-type structure easy to implement. (C) 2011 Elsevier Ltd. All rights reserved.

U-curve: A branch-and-bound optimization algorithm for U-shaped cost functions on Boolean lattices applied to the feature selection problem

This paper presents the formulation of a combinatorial optimization problem with the following characteristics: (i) the search space is the power set of a finite set structured as a Boolean lattice; (ii) the cost function forms a U-shaped curve when applied to any lattice chain. This formulation applies for feature selection in the context of pattern recognition. The known approaches for this problem are branch-and-bound algorithms and heuristics that explore partially the search space. Branch-and-bound algorithms are equivalent to the full search, while heuristics are not. This paper presents a branch-and-bound algorithm that differs from the others known by exploring the lattice structure and the U-shaped chain curves of the search space. The main contribution of this paper is the architecture of this algorithm that is based on the representation and exploration of the search space by new lattice properties proven here. Several experiments, with well known public data, indicate the superiority of the proposed method to the sequential floating forward selection (SFFS), which is a popular heuristic that gives good results in very short computational time. In all experiments, the proposed method got better or equal results in similar or even smaller computational time. (C) 2009 Elsevier Ltd. All rights reserved.

Performance of balanced two-stage empirical predictors of realized cluster latent values from finite populations: A simulation study

Predictors of random effects are usually based on the popular mixed effects (ME) model developed under the assumption that the sample is obtained from a conceptual infinite population; such predictors are employed even when the actual population is finite. Two alternatives that incorporate the finite nature of the population are obtained from the superpopulation model proposed by Scott and Smith (1969. Estimation in multi-stage surveys. J. Amer. Statist. Assoc. 64, 830-840) or from the finite population mixed model recently proposed by Stanek and Singer (2004. Predicting random effects from finite population clustered samples with response error. J. Amer. Statist. Assoc. 99, 1119-1130). Predictors derived under the latter model with the additional assumptions that all variance components are known and that within-cluster variances are equal have smaller mean squared error (MSE) than the competitors based on either the ME or Scott and Smith`s models. As population variances are rarely known, we propose method of moment estimators to obtain empirical predictors and conduct a simulation study to evaluate their performance. The results suggest that the finite population mixed model empirical predictor is more stable than its competitors since, in terms of MSE, it is either the best or the second best and when second best, its performance lies within acceptable limits. When both cluster and unit intra-class correlation coefficients are very high (e.g., 0.95 or more), the performance of the empirical predictors derived under the three models is similar. (c) 2007 Elsevier B.V. All rights reserved.

Low cost selective sensor for carbonyl compounds in air based on a novel conductive poly(p-xylylene) derivative

A novel poly(p-xylylene), PPX, derivative bearing phenyl side groups was electrochemically synthesized in 85% yield. The polymer, poly(2-phenyl-p-xylylene) (PPPX), presented a major fraction (88%) soluble in common organic solvents. It showed to be thermally resistant up to 140 degrees C. UV-VIS analysis revealed an Egap of similar to 3.0 eV. Gas sensors made from thin films of CSA doped PPPX deposited on interdigitated electrodes exhibited significant changes in electrical conductance upon exposure to five carbonyl compounds: acetaldehyde, propionaldehyde. benzaldehyde, acetone and butanone. Three-dimensional plots of relative response vs. time of half-response vs. time of half-recovery showed good discrimination between the five carbonyl Compounds tested. (C) 2008 Elsevier B.V. All rights reserved.

Efficient and low cost devices for solar energy conversion: Efficiency and stability of some natural-dye-sensitized solar cells

Dye-sensitized solar cells, named by us Dye-Cells, are one of the most promising devices for solar energy conversion due to their reduced production cost and low environmental impact, especially those sensitized by natural dyes. The efficiency and stability of devices based on natural sensitizers such as mulberry (Morus alba Lam), blueberry (Vaccinium myrtillus Lam), and jaboticaba`s skin (Mirtus cauliflora Mart) were investigated. Dye-Cells prepared with aqueous mulberry extract presented the highest P(max) value (1.6 mW cm(-2)) with J(sc) = 6.14 mA cm(-2) and V(oc) = 0.49 V, Photoelectrochemical parameters of 16 cm(2) active area devices sensitized by mulberry dye were constant for 14 weeks of continuous evaluation. Moreover, the cell remained stable even after 36 weeks with a fairly good efficiency. Therefore, mulberry dye opens up a perspective of commercial feasibility for inexpensive and environmentally friendly Dye-Cells. (C) 2009 Elsevier B.V. All rights reserved.

A Cost Model for the Effect of Setup Time Reduction in Stainless Steel Strip Production

Setup time reduction facilitate the flexibility needed for just-in-time production. An integrated steel mill with meltshop, continuous caster and hot rolling mill is often operated as decoupled processes. Setup time reduction provides the flexibility needed to reduce buffering, shorten lead times and create an integrated process flow. The interdependency of setup times, process flexibility and integration were analysed through system dynamics simulation. The results showed significant reductions of energy consumption and tied capital. It was concluded that setup time reduction in the hot strip mill can aid process integration and hence improve production economy while reducing environmental impact.