The Effects of Intermarriage on the Earnings of Female Immigrants in the United States

This paper investigates the effects of intermarriage on the earnings of female immigrants in the United States. The main empirical question asked is whether immigrant females married to US-born spouses have higher earnings than those of immigrant females married to other immigrants. Using 1970 and 1870 samples of IPUMS data, I estimate an earnings equation through OLS. I also correct for the labor force selection bias using the Heckman procedure. I finally take into account the endogeneity of intermarriage and apply a twostage least squares (2SLS) estimation procedure. I find that there is a positive marriage premium among immigrant females in the United States but a negative intermarriage premium for exogamously married females compared to endogamously married females. My results show that the longer the immigrant stays in the host country, the higher her wages, which is evidence for the assimilation effect over time. I find some evidence for a negative labor force selection bias among immigrant females. In other words, higher human capital women may select themselves out of the labor force, while lower human capital women are working for wages. Among those who are in the labor force, however, married females earn more than singles. I also conclude that being an immigrant from an English-speaking country does not have any impact on wages. Both premiums become statistically insignificant in difference from zero when 2SLS is used as an estimation procedure

UK households' carbon footprint: a comparison of the association between household characteristics and emissions from home energy, transport and other goods and services

Does the association between household characteristics and household CO2 emissions differ for different areas such as home energy, transport, indirect and total emissions in the UK? Specific types of households might be more likely to have high emissions in some areas than in others and thus be affected differently by climate mitigation policies that target these areas.Using the Living Costs and Food Survey and Expenditure and Food Survey for the years 2006 to 2009, this paper compares how household characteristics like income, household size, rural/urban location and education level differ in their association with home energy, transport, indirect and total emissions. We find that the association between household characteristics and emissions differs considerably across these areas, particularly for income, education, the presence of children, female headed, workless and rural households. We also test the implicit assumption in the literature that the association between household characteristics and CO2 emission is constant across the CO2 emission distribution using quantile regressions and compare results for poor and rich households. The analysis considers policy implications of these findings throughout

Expenditure as proxy for UK household emissions? Comparing three estimation methods

Due to a lack of emissions data at the household level, studies examining the relationship between UK household CO2 emissions and household characteristics currently rely on expenditure surveys to estimate emissions. There are several possible methods available for doing so but so far there is no discussion in the literature about the advantages and disadvantages related to these options. Such a comparison is relevant because studies in this area often draw policy-relevant conclusions.To address this gap, this paper compares three different methods of estimation to discuss two questions: first, is it at all necessary to convert household expenditure into emissions, given that household expenditure and emissions are strongly correlated, and does research that takes this approach add anything to the insights that already exist in the extensive literature on the determinants of household expenditure? Second, if we assume that it is necessary to convert household expenditure into emissions, are more detailed (and time-consuming) methods of doing so superior to less detailed approaches? The analysis is based on expenditure data from the UK Living Costs and Food Survey 2008-9 and its predecessor the Expenditure and Food Survey 2006-7

Correlation plenoptic imaging

Plenoptic imaging is a promising optical modality that simultaneously captures the location and the propagation direction of light in order to enable three-dimensional imaging in a single shot. However, in classical imaging systems, the maximum spatial and angular resolutions are fundamentally linked; thereby, the maximum achievable depth of field is inversely proportional to the spatial resolution. We propose to take advantage of the second-order correlation properties of light to overcome this fundamental limitation. In this paper, we demonstrate that the momentum/position correlation of chaotic light leads to the enhanced refocusing power of correlation plenoptic imaging with respect to standard plenoptic imaging.Comment: 6 pages, 3 figure

Signal-to-noise properties of correlation plenoptic imaging with chaotic light

Correlation Plenoptic Imaging (CPI) is a novel imaging technique, that exploits the correlations between the intensity fluctuations of light to perform the typical tasks of plenoptic imaging (namely, refocusing out-of-focus parts of the scene, extending the depth of field, and performing 3D reconstruction), without entailing a loss of spatial resolution. Here, we consider two different CPI schemes based on chaotic light, both employing ghost imaging: the first one to image the object, the second one to image the focusing element. We characterize their noise properties in terms of the signal-to-noise ratio (SNR) and compare their performances. We find that the SNR can be significantly higher and easier to control in the second CPI scheme, involving standard imaging of the object; under adequate conditions, this scheme enables reducing by one order of magnitude the number of frames for achieving the same SNR.Comment: 12 pages, 3 figure

Exploring plenoptic properties of correlation imaging with chaotic light

In a setup illuminated by chaotic light, we consider different schemes that enable to perform imaging by measuring second-order intensity correlations. The most relevant feature of the proposed protocols is the ability to perform plenoptic imaging, namely to reconstruct the geometrical path of light propagating in the system, by imaging both the object and the focusing element. This property allows to encode, in a single data acquisition, both multi-perspective images of the scene and light distribution in different planes between the scene and the focusing element. We unveil the plenoptic property of three different setups, explore their refocusing potentialities and discuss their practical applications.Comment: 9 pages, 4 figure

Correlation Plenoptic Imaging With Entangled Photons

Plenoptic imaging is a novel optical technique for three-dimensional imaging in a single shot. It is enabled by the simultaneous measurement of both the location and the propagation direction of light in a given scene. In the standard approach, the maximum spatial and angular resolutions are inversely proportional, and so are the resolution and the maximum achievable depth of focus of the 3D image. We have recently proposed a method to overcome such fundamental limits by combining plenoptic imaging with an intriguing correlation remote-imaging technique: ghost imaging. Here, we theoretically demonstrate that correlation plenoptic imaging can be effectively achieved by exploiting the position-momentum entanglement characterizing spontaneous parametric down-conversion (SPDC) photon pairs. As a proof-of-principle demonstration, we shall show that correlation plenoptic imaging with entangled photons may enable the refocusing of an out-of-focus image at the same depth of focus of a standard plenoptic device, but without sacrificing diffraction-limited image resolution.Comment: 12 pages, 5 figure

Perceiving education from Facebook profile pictures

Our upbringing and education influence not only how we present and distinguish ourselves in the social world but also how we perceive others. We apply this central sociological idea to the social media context. We conduct a large-scale online study to investigate whether observers can correctly guess the education of others from their Facebook profile pictures. Using the binomial test and cross-classified mixed-effects models, we show that observers can assess the education of depicted persons better than chance, especially when they share the same educational background and have experience with the social media. We also find that posting pictures of outdoor activities is a strong signal of having higher education, while professional photographs can obscure education signals. The findings expand our knowledge of social interaction and self-expression online and offer new insights for understanding social influence on social media