Social capital, government expenditures, and growth

We present a tractable stochastic endogenous growth model that explains how social capital influences economic development. In our model, social capital increases citizens' awareness of government activity. Hence, it alleviates the electoral incentives to under- invest in education, whose returns are delayed and less visible to voters. In equilibrium, higher social capital raises the average output growth rate and reduces its volatility by increasing public investment in education while making its returns higher and less variable. Our theory also predicts that a more unequal distribution of social capital reduces public education expenditures. We provide suggestive cross-country evidence consistent with these predictions.Social Capital, Education Expenditures, Economic Growth, Elections, Government Expenditures, Imperfect Information

"The Flea Catcher" portrait: does it image pre-eclampsia or hypothyroidism?

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Clusters of Entrepreneurship

Employment growth is strongly predicted by smaller average establishment size, both across cities and across industries within cities, but there is little consensus on why this relationship exists. Traditional economic explanations emphasize factors that reduce entry costs or raise entrepreneurial returns, thereby increasing net returns and attracting entrepreneurs. A second class of theories hypothesizes that some places are endowed with a greater supply of entrepreneurship. Evidence on sales per worker does not support the higher returns for entrepreneurship rationale. Our evidence suggests that entrepreneurship is higher when fixed costs are lower and when there are more entrepreneurial people.Entrepreneurship, Industrial Organization, Chinitz, Agglomeration, Clusters, Cities.

Centralization and Accountability: Theory and Evidence from the Clean Air Act.

This paper studies fi scal federalism when voter information varies across regions. We develop a model of political agency with heterogeneously informed voters. Rent-seeking politicians provide public goods to win the votes of the informed. As a result, rent extraction is lower in regions with higher information. In equilibrium, electoral discipline has decreasing returns. Thus, political centralization efficiently reduces aggregate rent extraction. The model predicts that a region' s benefi ts from centralization are decreasing in its residents' information. We test this prediction using panel data on pollutant emissions across U.S. states. The 1970 Clean Air Act centralized environmental policy at the federal level. In line with our theory, we fi nd that centralization induced a differential decrease in pollution for uninformed relative to informed states

A general framework for implicit and explicit debiasing of distributional word vector spaces

Distributional word vectors have recently been shown to encode many of the human biases, most notably gender and racial biases, and models for attenuating such biases have consequently been proposed. However, existing models and studies (1) operate on under-specified and mutually differing bias definitions, (2) are tailored for a particular bias (e.g., gender bias) and (3) have been evaluated inconsistently and non-rigorously. In this work, we introduce a general framework for debiasing word embeddings. We operationalize the definition of a bias by discerning two types of bias specification: explicit and implicit. We then propose three debiasing models that operate on explicit or implicit bias specifications and that can be composed towards more robust debiasing. Finally, we devise a full-fledged evaluation framework in which we couple existing bias metrics with newly proposed ones. Experimental findings across three embedding methods suggest that the proposed debiasing models are robust and widely applicable: they often completely remove the bias both implicitly and explicitly without degradation of semantic information encoded in any of the input distributional spaces. Moreover, we successfully transfer debiasing models, by means of cross-lingual embedding spaces, and remove or attenuate biases in distributional word vector spaces of languages that lack readily available bias specifications

Thermal Physics and Glaucoma II: Preliminary Evidences for a Thermophysical Design of a Possible Visible-Light-Photons Therapy

Recently, a non-equilibrium thermodynamic approach has been developed in order to model the fundamental role of the membrane electric potential in the cell behaviour. A related new viewpoint is introduced, with a design of a photobiomodulation treatment in order to restore part of the visual field. Here, a first step in experimental evidence of the validity of the thermodynamic approach is developed. This result represents the starting point for future experimental improvements for light stimulation in order to improve the quality of life of the patients. The future possible therapy will be in addition to the pharmacological treatments

A Thermodynamic Approach to the Metaboloepigenetics of Cancer

We present a novel thermodynamic approach to the epigenomics of cancer metabolism. Here, any change in a cancer cell’s membrane electric potential is completely irreversible, and as such, cells must consume metabolites to reverse the potential whenever required to maintain cell activity, a process driven by ion fluxes. Moreover, the link between cell proliferation and the membrane’s electric potential is for the first time analytically proven using a thermodynamic approach, highlighting how its control is related to inflow and outflow of ions; consequently, a close interaction between environment and cell activity emerges. Lastly, we illustrate the concept by evaluating the Fe2+-flux in the presence of carcinogenesis-promoting mutations of the TET1/2/3 gene family