Most studies about the labor market impact of immigration limit their analysis tothe adult native population. This paper shows that teen employment is significantlymore responsive than adult employment to immigration, and that growth in low-skilledimmigration appears to be an important cause of recent declines in teen employmentrates. Using variation in immigrant shares across metropolitan areas between 1980and 2000, I show that the impact of immigration on youth employment is at leasttwice as large as the impact on adults, and that immigration aects school enrollmentdecisions and the type of jobs held by native youth. These eects are strongest for blackyouth and youth from poorer and less educated families. The estimates suggest that a10 percentage point increase in the immigrant share of a city's low-skilled populationreduces the teen employment rate by 5 percentage points, implying that up to halfof the fall in teen employment between 1990 and 2005 can be explained by increasedimmigration.

I measure the rates at which newly eligible voters, deaths of eligible voters, and newly naturalized citizens change the composition of the American electorate across the decennial censuses of 1950-2000.I then examine the consequences of the physical replacement of the electorate for party identification, voting turnout, and culturally grounded political and social attitudes.

Data from the NIPA and from the Decennial Census of Housing show that the household expenditure share on housing is remarkably constant over time and across U.S. metropolitan areas (MSA). Consistent with this fact, we consider a basic frictionless model in which identical households have Cobb-Douglas preferences for consumption and housing. Households choose an MSA in which to live, and MSAs differ in the income residents receive and in quality of life. In equilibrium, given our estimate of the expenditure share on housing at 0.24, and holding quality of life constant, the model predicts that the difference in log rental prices of two MSAs must equal 4.2 times the difference in log per-capita income. The model provides an exact methodology to estimate MSA-level quality of life. Like TFP in macroeconomics, differences across MSAs in quality of life enable us to reconcile observed wages and rents with the predictions of the theory. We find that quality of life is significantly negatively correlated with population.

The rapid transformation of the American South in the wake of the Civil War offered one of the most propitious institutional circumstances for the formation of an entrepreneurial middle class. Despite claims to the contrary by social historians and postbellum boosters, Census microdata reveal however that the numbers of the petite bourgeoisie actually declined in the Lower South between 1860 and 1900. Drawing on structural, institutional, and Marxist accounts of class formation, this paper probes why the middle class did not expand more vigorously in response to the demise of the Old Southern system of chattel slavery. Empirical analyses suggest that the new South erected greater barriers to middle class entrepreneurship among Northerners, foreign immigrants, and emancipated blacks than those in evidence during the antebellum period. Nevertheless, those individuals who did gain entry into the entrepreneurial class enjoyed a more clearly defined relationship to productive assets and greater material wealth than any other major social faction in postbellum Southern society. Paralleling earlier institutional studies of organizations, the paper underscores the importance of myth and ceremony--over mere numerical prevalence--in the making of an entrepreneurial class.

Data from the NIPA and from the Decennial Census of Housing show that the house-hold expenditure share on housing is remarkably constant over time and across U.S. metropolitanareas (MSA). Consistent with this fact, we consider a basic frictionless model in which identicalhouseholds have Cobb-Douglas preferences for consumption and housing. Households choose anMSA in which to live, and MSAs differ in the income residents receive and in quality of life, whichis a multiplicative factor in the utility function. Like TFP in macroeconomics, differences acrossMSAs in quality of life enable us to reconcile observed wages and rents with the predictions of thetheory. In equilibrium, given our estimate of the expenditure share on housing at 0.24, and holdingquality of life constant, the difference in log rental prices of two MSAs must equal 4.2 times the dif-ference in log per-capita income. The model provides an exact methodology to estimate MSA-levelquality of life. We find that quality of life is significantly negatively correlated with population.

Data from the NIPA and from the Decennial Census of Housing show that the householdexpenditure share on housing is remarkably constant over time and across metropolitan areas,despite sizeable changes to real rental prices and variation in income. Consistent with this fact,we consider a basic frictionless model in which identical households have Cobb-Douglas preferencesfor consumption and housing. Households choose an MSA in which to live, and MSAs differ inthe income residents receive and in amenities. Equilibrium in the model satisfies the followingproperties: (1) MSA-level per-capita income and rental prices increase at the same rate only whenper-capita housing is held constant; (2) per-capita housing will not be constant when per-capitaincomes increase at different rates across MSAs; (3) this income dispersion leads to disproportionaterent dispersion, that is, given our estimate of the expenditure share on housing of 0.25, and holdingamenities constant, the difference in log rental prices of two MSAs must equal 4 times the differencein log per-capita income; (4) the difference in log rental prices in any two MSAs is independentof the local housing supply in either MSA. The model provides an exact methodology to quantifychanges to the MSA-level total stock of housing and MSA-level amenities, much in the same waythat neoclassical growth theory provides a framework to identify changes to TFP given estimatesof capital and labor inputs. We find that in the past 24 years, the per-capita and total stock ofhousing has increased in almost every MSA we consider, and changes to per-capita income andamenities have been nearly perfectly negatively correlated across MSAs. The model raises issueswith regard to existing studies of the relationship of house prices, income, and local amenities.

We use a difference-in-difference-in-difference estimator to compare changes in labor force participation, weeks, and hours of work associated with nofault divorce laws, allowing for differential responses for married women with and without children. Although other research has found that the labor supply of women in general does not respond to no-fault divorce laws, we find that no-fault divorce laws are associated with increases in the labor supply of married mothers relative to married nonmothers, even after controlling for changes in female labor supply in states without no-fault divorce laws and for property division rules associated with the laws.

The importance of going to college has increased in the context of global competition and continuing stratification in society. Many strides have been made in encouraging students and parents to believe in the value of higher education, but the process of preparing for and applying to college is not easy. It requires making a variety of complex choices that range from pursuing a challenging academic curriculum to developing an understanding of college financing. Middle school is a crucial stage at which students and their parents must begin to make these choices. Studies have shown that almost all parents hope that their children will be able to attend college, but many parents do not have the necessary information to help their children make the important early choices that will help them prepare to fulfill their college dreams. Worse still, it is often the parents who most need the information and who find it difficult to obtain, leaving their children at risk of not properly preparing for college. College access programs often attempt to fill in the lack of college knowledge, particularly for disadvantaged students. However, these programs traditionally target at-risk groups in the later years of high school. Research suggests that targeted efforts at this stage may be too late for college planning. In addition, many programs do not bring parents and other family members into discussions about planning for college and thus help them understand their role in guiding their children through the college preparation process. To explore these issues, the Institute for Higher Education Policy (IHEP) commissioned a nationwide survey to ask parents of middle school students about the steps they have taken to start planning for college. The findings from this survey may be grouped into four key choice points on the pathway to college: (1) aspirations; (2) college knowledge and planning; (3) academic preparation; and (4) financial preparation. Working toward greater involvement by parents in early college planning will require a comprehensive approach that combines outreach efforts, curricular changes, increased program support, and other activities. It will also require participation at all levels, including students and families, high schools, colleges, state and local governments, the federal government, and the private sector. Appended are: (1) Survey Instrument for the "IHEP Survey of Middle School Parents"; and (2) List of Kids to College Partners. (Contains 14 figures, 3 tables and 18 footnotes.)

This paper proposes a theory of educational attainment differences across U.S. metropolitan areas. The theory is motivated by the finding that employment in business services predicts more than 70% of the observed cross-city variation in education. In the model, agglomeration economies in the production of business services, which are complementary with skilled labor, account for cross-city variation in education. The theory makes a number of testable predictions which find strong support in U.S. data.

The huge influx of immigrants coming to the United States from every corner of the globe has helped propel the issue of immigration high up on the national agenda. Most of the attention has focused on the legal side of the issue, especially with Congress set to tackle comprehensive immigration reform this year. In contrast, relatively little attention has focused on the side of the nation’s immigration story that represents the future: children. This Research Brief draws on new results of Census 2000 data to take a closer look at children in immigrant families, that is, children with at least one foreign-born parent. For example, the brief reports that children in newcomer families are driving the nation’s racial and ethnic transformation. Moreover, these children constitute a very diverse group in terms of their national origin, as well as the places that they now call home. Children in newcomer families also have strong ties to their adopted country; four out of five are American citizens and three out of four are fluent in English. At the same time, children of immigrants are less likely to be enrolled in preschool programs, putting them at a disadvantage when it comes to the cognitive aspects of school readiness and English-language fluency. In particular, this brief highlights the proportion, dispersion, national origins, language, and early education of children in newcomer families, both for the United States as a whole and in various states. (Results for each state can be accessed at http://www.childtrends.org/Files//Child_Trends2007_04_01_TBL_ChildrenInImmigrantFamilies.pdf. This research brief and the results for each state, as well as more detailed data for the United States, individual states, and other local areas, can be accessed at http://www.albany.edu/csda/children.)

The United States is growing increasingly diverse, so it is important that economists understand the macroeconomic consequences of diversity within the US economy. International analyses often argue that heterogeneity reduces macroeconomic productivity by engendering corruption, political instability, and social turmoil. However, other studies claim that diversity improves creative decision making and augments productivity. This paper exploits differences in diversity across regions of the United States from 1980 to 2000 to determine whether racial heterogeneity creates macroeconomic gains or losses for states and cities. Fixed effects analysis indicates that diversity enhances the productivity of cities. Evidence at the state-level is more ambiguous, as significant results only appear in random effects specifications.

Many workers with low levels of educational attainment immigrated to the United States in recent decades. Large inflows of less-educated immigrants would reduce wages paid to comparably-educated native-born workers if the two groups compete for similar jobs. In a simple model exploiting comparative advantage, however, we show that if less-educated foreign and native-born workers specialize in performing complementary tasks, immigration will cause natives to reallocate their task supply, thereby reducing downward wage pressure. Using individual data on the task intensity of occupations across US states from 1960-2000, we then demonstrate that foreign-born workers specialize in occupations that require manual tasks such as cleaning, cooking, and building. Immigration causes natives -- who have a better understanding of local networks, rules, customs, and language -- to pursue jobs requiring interactive tasks such as coordinating, organizing, and communicating. Simulations show that this increased specialization mitigated negative wage consequences of immigration for less-educated native-born workers, especially in states with large immigration flows.

Skyline and top-k queries are two popular operations for preference retrieval. In practice, applications that require these operations usually provide numerous candidate attributes, whereas, depending on their interests, users may issue queries regarding different subsets of the dimensions. The existing algorithms are inadequate for subspace skyline/top-k search because they have at least one of the following defects: 1) They require scanning the entire database at least once, 2) they are optimized for one subspace but incur significant overhead for other subspaces, or 3) they demand expensive maintenance cost or space consumption. In this paper, we propose a technique SUBSKY, which settles both types of queries by using purely relational technologies. The core of SUBSKY is a transformation that converts multidimensional data to one-dimensional (1D) values. These values are indexed by a simple B-tree, which allows us to answer subspace queries by accessing a fraction of the database. SUBSKY entails low maintenance overhead, which equals the cost of updating a traditional B-tree. Extensive experiments with real data confirm that our technique outperforms alternative solutions significantly in both efficiency and scalability.

We are at the beginning of the multicore era. Computers will have increasingly many cores (processors), but there is still no good programming framework for these architectures, and thus no simple and unified way for machine learning to take advantage of the potential speed up. In this paper, we develop a broadly applicable parallel programming method, one that is easily applied to many different learning algorithms. Our work is in distinct contrast to the tradition in machine learning of designing (often ingenious) ways to speed up a single algorithm at a time. Specifically, we show that algorithms that fit the Statistical Query model [15] can be written in a certain "summation form," which allows them to be easily par-allelized on multicore computers. We adapt Google's map-reduce [7] paradigm to demonstrate this parallel speed up technique on a variety of learning algorithms including locally weighted linear regression (LWLR), k-means, logistic regression (LR), naive Bayes (NB), SVM, ICA, PCA, gaussian discriminant analysis (GDA), EM, and backpropagation (NN). Our experimental results show basically linear speedup with an increasing number of processors.