Generational Accounting and Immigration in the United States

In recent years, the renewed strength of immigration to the United States has sparked a debate about the economic effects of immigration. A central issue in this debate has been the fiscal impact of immigrants. Most research in this area has adopted a static, cross-section approach in assessing the net impact of immigrants on the economy's fiscal position. However, a dynamic approach is important because of the age dependency of many government tax and expenditure programs, and necessary to take the descendents of immigrants into account. This paper reconsiders the fiscal impact of immigrants over time, using the technique of generational accounting. We may summarize our results with three findings: 1. Because new immigrants represent a larger fraction of future generations than of present ones, shifting the burden onto future generations also shifts it, relatively, onto new immigrants. Thus, if the entire fiscal imbalance currently estimated for the United States is placed on future generations, then the presence of new immigrants reduces the burden borne by natives. 2. When a policy of fiscal responsibility' is followed, whether there is a fiscal gain from immigration depends on the extent to which government purchases rise with the immigrant population. 3. The impact of immigration on fiscal balance is extremely small relative to the size of the overall imbalance itself. Thus, immigration should be viewed neither as a major source of the existing imbalance, nor as a potential solution to it.

Implementation on Landsat Data of a Simple Cloud Mask Algorithm Developed for MODIS Land Bands

This letter assesses the performance on Landsat-7 images of a modified version of a cloud masking algorithm originally developed for clear-sky compositing of Moderate Resolution Imaging Spectroradiometer (MODIS) images at northern mid-latitudes. While data from recent Landsat missions include measurements at thermal wavelengths, and such measurements are also planned for the next mission, thermal tests are not included in the suggested algorithm in its present form to maintain greater versatility and ease of use. To evaluate the masking algorithm we take advantage of the availability of manual (visual) cloud masks developed at USGS for the collection of Landsat scenes used here. As part of our evaluation we also include the Automated Cloud Cover Assesment (ACCA) algorithm that includes thermal tests and is used operationally by the Landsat-7 mission to provide scene cloud fractions, but no cloud masks. We show that the suggested algorithm can perform about as well as ACCA both in terms of scene cloud fraction and pixel-level cloud identification. Specifically, we find that the algorithm gives an error of 1.3% for the scene cloud fraction of 156 scenes, and a root mean square error of 7.2%, while it agrees with the manual mask for 93% of the pixels, figures very similar to those from ACCA (1.2%, 7.1%, 93.7%)

Radiative Impacts of Cloud Heterogeneity and Overlap in an Atmospheric General Circulation Model

The radiative impacts of introducing horizontal heterogeneity of layer cloud condensate, and vertical overlap of condensate and cloud fraction are examined with the aid of a new radiation package operating in the GEOS-5 Atmospheric General Circulation Model. The impacts are examined in terms of diagnostic top-of-the-atmosphere shortwave (SW) and longwave (LW) cloud radiative effect (CRE) calculations for a range of assumptions and parameter specifications about the overlap. The investigation is conducted for two distinct cloud schemes, the one that comes with the standard GEOS-5 distribution, and another which has been recently used experimentally for its enhanced GEOS-5 distribution, and another which has been recently used experimentally for its enhanced cloud microphysical capabilities; both are coupled to a cloud generator allowing arbitrary cloud overlap specification. We find that cloud overlap radiative impacts are significantly stronger for the operational cloud scheme for which a change of cloud fraction overlap from maximum-random to generalized results to global changes of SW and LW CRE of approximately 4 Watts per square meter, and zonal changes of up to approximately 10 Watts per square meter. This is because of fewer occurrences compared to the other scheme of large layer cloud fractions and of multi-layer situations with large numbers of atmospheric being simultaneously cloudy, conditions that make overlap details more important. The impact on CRE of the details of condensate distribution overlap is much weaker. Once generalized overlap is adopted, both cloud schemes are only modestly sensitive to the exact values of the overlap parameters. We also find that if one of the CRE components is overestimated and the other underestimated, both cannot be driven towards observed values by adjustments to cloud condensate heterogeneity and overlap alone

An Examination of the Nature of Global MODIS Cloud Regimes

We introduce global cloud regimes (previously also referred to as "weather states") derived from cloud retrievals that use measurements by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Aqua and Terra satellites. The regimes are obtained by applying clustering analysis on joint histograms of retrieved cloud top pressure and cloud optical thickness. By employing a compositing approach on data sets from satellites and other sources, we examine regime structural and thermodynamical characteristics. We establish that the MODIS cloud regimes tend to form in distinct dynamical and thermodynamical environments and have diverse profiles of cloud fraction and water content. When compositing radiative fluxes from the Clouds and the Earth's Radiant Energy System instrument and surface precipitation from the Global Precipitation Climatology Project, we find that regimes with a radiative warming effect on the atmosphere also produce the largest implied latent heat. Taken as a whole, the results of the study corroborate the usefulness of the cloud regime concept, reaffirm the fundamental nature of the regimes as appropriate building blocks for cloud system classification, clarify their association with standard cloud types, and underscore their distinct radiative and hydrological signatures

Performance of McRAS-AC in the GEOS-5 AGCM: aerosol-cloud-microphysics, precipitation, cloud radiative effects, and circulation

A revised version of the Microphysics of clouds with Relaxed Arakawa-Schubert and Aerosol-Cloud interaction scheme (McRAS-AC) including, among others, a new ice nucleation parameterization, is implemented in the GEOS-5 AGCM. Various fields from a 10-yr-long integration of the AGCM with McRAS-AC are compared with their counterparts from an integration of the baseline GEOS-5 AGCM, as well as satellite observations. Generally McRAS-AC simulations have smaller biases in cloud fields and cloud radiative effects over most of the regions of the Earth than the baseline GEOS-5 AGCM. Two systematic biases are identified in the McRAS-AC runs: one is underestimation of cloud particle numbers around 40° S–60° S, and one is overestimate of cloud water path during the Northern Hemisphere summer over the Gulf Stream and North Pacific. Sensitivity tests show that these biases potentially originate from biases in the aerosol input. The first bias is largely eliminated in a test run using 50% smaller radius of sea-salt aerosol particles, while the second bias is substantially reduced when interactive aerosol chemistry is turned on. The main weakness of McRAS-AC is the dearth of low-level marine stratus clouds, a probable outcome of lack of explicit dry-convection in the cloud scheme. Nevertheless, McRAS-AC largely simulates realistic clouds and their optical properties that can be improved further with better aerosol input. An assessment using the COSP simulator in a 1-yr integration provides additional perspectives for understanding cloud optical property differences between the baseline and McRAS-AC simulations and biases against satellite data. Overall, McRAS-AC physically couples aerosols, the microphysics and macrophysics of clouds, and their radiative effects and thereby has better potential to be a valuable tool for climate modeling research

The Precipitation Characteristics of ISCCP Tropical Weather States

We examine the daytime precipitation characteristics of the International Satellite Cloud Climatology Project (ISCCP) weather states in the extended tropics (35 deg S to 35 deg N) for a 10-year period. Our main precipitation data set is the TRMM Multisatellite Precipitation Analysis 3B42 data set, but Global Precipitation Climatology Project daily data are also used for comparison. We find that the most convective weather state (WS1), despite an occurrence frequency below 10%, is the most dominant state with regard to surface precipitation, producing both the largest mean precipitation rates when present and the largest percent contribution to the total precipitation of the tropical zone of our study; yet, even this weather state appears to not precipitate about half the time. WS1 exhibits a modest annual cycle of domain-average precipitation rate, but notable seasonal shifts in its geographic distribution. The precipitation rates of the other weather states tend to be stronger when occurring before or after WS1. The relative contribution of the various weather states to total precipitation is different between ocean and land, with WS1 producing more intense precipitation on average over ocean than land. The results of this study, in addition to advancing our understanding of the current state of tropical precipitation, can serve as a higher order diagnostic test on whether it is distributed realistically among different weather states in atmospheric models

MODIS Dynamical and Microphysical Regimes as Viewed by AIRS

No abstract availabl

How to Educate Entrepreneurs?

Entrepreneurship education has two purposes: To improve students’ entrepreneurial skills and to provide impetus to those suited to entrepreneurship while discouraging the rest. While entrepreneurship education helps students to make a vocational decision its effects may conflict for those not suited to entrepreneurship. This study shows that vocational and the skill formation effects of entrepreneurship education can be identified empirically by drawing on the Theory of Planned Behavior. This is embedded in a structural equation model which we estimate and test using a robust 2SLS estimator. We find that the attitudinal factors posited by the Theory of Planned Behavior are positively correlated with students’ entrepreneurial intentions. While conflicting effects of vocational and skill directed course content are observed in some individuals, overall these types of content are complements. This finding contradicts previous results in the literature. We reconcile the conflicting findings and discuss implications for the design of entrepreneurship courses