Exhibits

The Finnish American Heritage Center at Finlandia University recently installed three exhibits. They include a photographic exhibit titled “Rural Reflections: Finnish American Buildings and Landscapes in Michigan’s Copper Country”; a historic photography exhibit named “People, Place and Time: Michigan’s Copper Country Through the Lens of J.W. Nara”; and a pair of lithographs acquired by the National Park Service which were on either side of the Italian Hall stage the night of the infamous Christmas Eve tragedy 100 years ago. The “Rural Reflections” exhibit documents the built environment that Finnish immigrants and their descendants created in Michigan's Copper Country from the 1880s through the 1930s. Although much of this heritage has been lost with the passage of time, the district yet holds one of the largest concentrations of rural Finnish buildings and cultural landscapes in North America. The Nara exhibit, funded in part by descendants Robert and Ruth Nara of Bootjack Michigan, works from historical photographs held at the Michigan Tech Archives. Interpretive panels highlight the people, places, and times that J.W. Nara experienced during his lifetime and include material on urban life, farming, and the 1913 Michigan copper miners’ strike. The lithographs are a recent and unique acquisition for the Keweenaw National Historical Park, and will be on protected display at the FAHC. One of the panels shows the Italian royal family and was produced in 1908, while the other, produced in 1905, is of the five founders of the modern Italian state. For more information about the exhibits at the Finnish American Heritage Center, call (906) 487-7302.

Survey data book and standards for operation and maintenance of physical plant in colleges and universities /

143, 147, omitted in numbering.

Annual housing survey:

Each year consists of separate reports on 20 selected areas.

Survey of public school classroom shortages in the fall of 1959 in borrowed-up districts; [report,

Reproduced from type-written copy.

Survey report on school building program for the Junction City schools, Junction City, Kansas,

Mode of access: Internet.

Survey of Dixon parks, Dixon Illinois /

Cover title: Survey of historic parks of Dixon, Illinois.

The effects on students' self-efficacy beliefs regarding their comprehension of American literature when aesthetic reading and reader response strategy are implemented

High-stakes testing and accountability have infiltrated the education system in the United States; the top priority for all teachers must be student progress on standardized tests. This has resulted in the predominance of reading for test-taking, (efferent reading), in the English, language arts, and reading classrooms. Authentic uses of print activities, like aesthetic reading, that encourage students to engage individually with a text, have been pushed aside. ^ During a 3-week time period, regular level, English 3/American literature students in a Title I magnet high school, participated in this quasi-experimental study (N = 62). It measured the effects of an intervention of reading American literature texts aesthetically and writing aesthetically-evoked reader responses on students' self-efficacy beliefs regarding their comprehension of American literature. One trained teacher and the researcher participated in the study: student participants were pre- and post- tested using the Confidence in Reading American Literature Survey which examined their self-efficacy beliefs regarding their comprehension of American literature. Several statistical analyses were performed. The results of the linear regression analyses partially supported a positive relationship between aesthetically-evoked reader responses and students' self-efficacy beliefs regarding their comprehension of American literature. Additionally, the results of the 2 (sex) x 2 (treatment) ANCOVAs conducted to test group differences in self-efficacy beliefs regarding the comprehension of American literature between treatment and control groups indicated a main effect for treatment (but not sex; nor was there a significant sex x treatment interaction), suggesting the treatment was partially effective in increasing students' self-efficacy beliefs. Seven of the twelve ANCOVAs indicated a statistically significant increase in the treatment group's adjusted group mean self-efficacy belief scores as a result of being exposed to the intervention. In six of these seven analyses, increases in self-efficacy beliefs occurred in tasks that required three or more higher-order levels of thinking/learning. The results are discussed in terms of theoretical, empirical and practical significance. Future research is recommended to extend the intervention beyond the narrow confines of a Title I magnet school to settings where the intervention could be tested longitudinally, e. g., honors and gifted students, elementary and middle schools.^

The Effects on Students' Self-Efficacy Beliefs Regarding Their Comprehension of American Literature When Aesthetic Reading and Reader Response Strategy are Implemented

High-stakes testing and accountability have infiltrated the education system in the United States; the top priority for all teachers must be student progress on standardized tests. This has resulted in the predominance of reading for test-taking, (efferent reading), in the English, language arts, and reading classrooms. Authentic uses of print activities, like aesthetic reading, that encourage students to engage individually with a text, have been pushed aside. During a 3-week time period, regular level, English 3/American literature students in a Title I magnet high school, participated in this quasi-experimental study (N = 62). It measured the effects of an intervention of reading American literature texts aesthetically and writing aesthetically-evoked reader responses on students’ self-efficacy beliefs regarding their comprehension of American literature. One trained teacher and the researcher participated in the study: student participants were pre- and post- tested using the Confidence in Reading American Literature Survey which examined their self-efficacy beliefs regarding their comprehension of American literature. Several statistical analyses were performed. The results of the linear regression analyses partially supported a positive relationship between aesthetically-evoked reader responses and students’ self-efficacy beliefs regarding their comprehension of American literature. Additionally, the results of the 2 (sex) x 2 (treatment) ANCOVAs conducted to test group differences in self-efficacy beliefs regarding the comprehension of American literature between treatment and control groups indicated a main effect for treatment (but not sex; nor was there a significant sex x treatment interaction), suggesting the treatment was partially effective in increasing students’ self-efficacy beliefs. Seven of the twelve ANCOVAs indicated a statistically significant increase in the treatment group’s adjusted group mean self-efficacy belief scores as a result of being exposed to the intervention. In six of these seven analyses, increases in self-efficacy beliefs occurred in tasks that required three or more higher-order levels of thinking/learning. The results are discussed in terms of theoretical, empirical and practical significance. Future research is recommended to extend the intervention beyond the narrow confines of a Title I magnet school to settings where the intervention could be tested longitudinally, e. g., honors and gifted students, elementary and middle schools.

Studying the Causes and Consequences of Internal Labor Migration Using Survey and Administrative Data Sources

This dissertation comprises three chapters. The first chapter motivates the use of a novel data set combining survey and administrative sources for the study of internal labor migration. By following a sample of individuals from the American Community Survey (ACS) across their employment outcomes over time according to the Longitudinal Employer-Household Dynamics (LEHD) database, I construct a measure of geographic labor mobility that allows me to exploit information about individuals prior to their move. This enables me to explore aspects of the migration decision, such as homeownership and employment status, in ways that have not previously been possible. In the second chapter, I use this data set to test the theory that falling home prices affect a worker’s propensity to take a job in a different metropolitan area from where he is currently located. Employing a within-CBSA and time estimation that compares homeowners to renters in their propensities to relocate for jobs, I find that homeowners who have experienced declines in the nominal value of their homes are approximately 12% less likely than average to take a new job in a location outside of the metropolitan area where they currently reside. This evidence is consistent with the hypothesis that housing lock-in has contributed to the decline in labor mobility of homeowners during the recent housing bust. The third chapter focuses on a sample of unemployed workers in the same data set, in order to compare the unemployment durations of those who find subsequent employment by relocating to a new metropolitan area, versus those who find employment in their original location. Using an instrumental variables strategy to address the endogeneity of the migration decision, I find that out-migrating for a new job significantly reduces the time to re-employment. These results stand in contrast to OLS estimates, which suggest that those who move have longer unemployment durations. This implies that those who migrate for jobs in the data may be particularly disadvantaged in their ability to find employment, and thus have strong short-term incentives to relocate.

Inference in differences-in-differences with few treated groups and heteroskedasticity

Differences-in-Differences (DID) is one of the most widely used identification strategies in applied economics. However, how to draw inferences in DID models when there are few treated groups remains an open question. We show that the usual inference methods used in DID models might not perform well when there are few treated groups and errors are heteroskedastic. In particular, we show that when there is variation in the number of observations per group, inference methods designed to work when there are few treated groups tend to (under-) over-reject the null hypothesis when the treated groups are (large) small relative to the control groups. This happens because larger groups tend to have lower variance, generating heteroskedasticity in the group x time aggregate DID model. We provide evidence from Monte Carlo simulations and from placebo DID regressions with the American Community Survey (ACS) and the Current Population Survey (CPS) datasets to show that this problem is relevant even in datasets with large numbers of observations per group. We then derive an alternative inference method that provides accurate hypothesis testing in situations where there are few treated groups (or even just one) and many control groups in the presence of heteroskedasticity. Our method assumes that we can model the heteroskedasticity of a linear combination of the errors. We show that this assumption can be satisfied without imposing strong assumptions on the errors in common DID applications. With many pre-treatment periods, we show that this assumption can be relaxed. Instead, we provide an alternative inference method that relies on strict stationarity and ergodicity of the time series. Finally, we consider two recent alternatives to DID when there are many pre-treatment periods. We extend our inference methods to linear factor models when there are few treated groups. We also derive conditions under which a permutation test for the synthetic control estimator proposed by Abadie et al. (2010) is robust to heteroskedasticity and propose a modification on the test statistic that provided a better heteroskedasticity correction in our simulations.

Inference in differences-in-differences with few treated groups and heteroskedasticity

Differences-in-Differences (DID) is one of the most widely used identification strategies in applied economics. However, how to draw inferences in DID models when there are few treated groups remains an open question. We show that the usual inference methods used in DID models might not perform well when there are few treated groups and errors are heteroskedastic. In particular, we show that when there is variation in the number of observations per group, inference methods designed to work when there are few treated groups tend to (under-) over-reject the null hypothesis when the treated groups are (large) small relative to the control groups. This happens because larger groups tend to have lower variance, generating heteroskedasticity in the group x time aggregate DID model. We provide evidence from Monte Carlo simulations and from placebo DID regressions with the American Community Survey (ACS) and the Current Population Survey (CPS) datasets to show that this problem is relevant even in datasets with large numbers of observations per group. We then derive an alternative inference method that provides accurate hypothesis testing in situations where there are few treated groups (or even just one) and many control groups in the presence of heteroskedasticity. Our method assumes that we know how the heteroskedasticity is generated, which is the case when it is generated by variation in the number of observations per group. With many pre-treatment periods, we show that this assumption can be relaxed. Instead, we provide an alternative application of our method that relies on assumptions about stationarity and convergence of the moments of the time series. Finally, we consider two recent alternatives to DID when there are many pre-treatment groups. We extend our inference method to linear factor models when there are few treated groups. We also propose a permutation test for the synthetic control estimator that provided a better heteroskedasticity correction in our simulations than the test suggested by Abadie et al. (2010).

Escândalos políticos e o clima econômico dos países sul-americanos: evidências baseadas na confiança de especialistas

Qual o impacto dos escândalos políticos sobre o clima econômico dos países sul-americanos? O presente trabalho busca responder essa pergunta ao avaliar a confiança de especialistas na economia de sete países sul-americanos durante a ocorrência de escândalos políticos em um recorte temporal de 10 anos (de 2005 até 2014). Entendemos os escândalos políticos como sendo eventos noticiados pela mídia envolvendo os presidentes das repúblicas sul-americanas em episódios de corrupção ou abuso de poder. Já o clima econômico é medido a partir da avaliação da economia por especialistas regularmente consultados pela Sondagem Econômica da América Latina, uma pesquisa que gera a construção do Índice de Clima Econômico da América Latina. Evidências apontam a influência de determinantes políticos sobre a avaliação econômica realizada pelo público geral. Poucos estudos exploram o processo de formação da confiança econômica de especialistas. Utilizamos o modelo de regressão em painel para verificar a correlação entre escândalos políticos e o Índice de Clima Econômico. Nenhuma correlação pôde ser verificada quando adotamos um modelo relacionado à economia internacional. Surpreendentemente, encontramos uma correlação significante e positiva quando adicionamos variáveis econômicas domésticas à análise. Acreditamos que futuras contribuições para o tema devam levar em conta a importância do papel das instituições como elemento fundamental na confiança de especialistas.

Subutilización de las capacidades de los profesionales mexicanos de las ciencias y la tecnología y su vínculo con la migración a los Estados Unidos

Incluye bibliografía

The Use of Factor Analysis in the Development of Hand Sizes for Glove Design

Factor analysis was used to develop a more detailed description of the human hand to be used in the creation of glove sizes; currently gloves sizes are small, medium, and large. The created glove sizes provide glove designers with the ability to create a glove design that can provide fit to the majority of hand variations in both the male and female populations. The research used the American National Survey (ANSUR) data that was collected in 1988. This data contains eighty-six length, width, height, and circumference measurements of the human hand for one thousand male subjects and thirteen hundred female subjects. Eliminating redundant measurements reduced the data to forty-six essential measurements. Factor analysis grouped the variables to form three factors. The factors were used to generate hand sizes by using percentiles along each factor axis. Two different sizing systems were created. The first system contains 125 sizes for male and female. The second system contains 7 sizes for males and 14 sizes for females. The sizing systems were compared to another hand sizing system that was created using the ANSUR database indicating that the systems created using factor analysis provide better fit.

Racial Differences in Homeownership: The Effect of Residential Location

The rate of homeownership among African-American households is considerably lower than white households in American urban areas. This paper examines whether racial differneces in residential location outcomes are among the factors that contribute to the large racial differences in homeownership rates in major US metropolitan areas. Based on the 1985 metropolitan sample of the American Housing Survey for Philadelphia, the paper does not find any evidence that existing racial differences in residential location in Philadelphia decrease the homeownership rate among African Americans. Rather, the empirical evidence suggests that African-American residential location outcomes are associated with lower than expected racial differences in homeownership. Therefore, after controlling for neighborhood, racial differences in homeownership are larger than originally believed, and the ability of racial differences in endowments to explain hoeownership differences is more limited.