Which School Attributes Matter? The Influence of School District Performance and Demographic Composition on Property Values

Increasing levels of segregation in American schools raises the question: do home buyers pay for test scores or demographic composition? This paper uses Connecticut panel data spanning eleven years from 1994 to 2004 to ascertain the relationship between property values and explanatory variables that include school district performance and demographic attributes, such as racial and ethnic composition of the student body. Town and census tract fixed effects are included to control for neighborhood unobservables. The effect of changes in school district attributes is also examined over a decade long time frame in order to focus on the effect of long run changes, which are more likely to be capitalized into prices. The study finds strong evidence that increases in percent Hispanic has a negative effect on housing prices in Connecticut, but mixed evidence concerning the impact of test scores on property values. Evidence is also found to suggest that student test scores have increased in importance for explaining housing prices in recent years while the importance of percent Hispanic has declined. Finally, the study finds that estimates of property tax capitalization increase substantially when the analysis focuses on long run changes.

Performance Evaluation of the New Connecticut Leading Employment Index Using Lead Profiles and BVAR Models

Dua and Miller (1996) created leading and coincident employment indexes for the state of Connecticut, following Moore's (1981) work at the national level. The performance of the Dua-Miller indexes following the recession of the early 1990s fell short of expectations. This paper performs two tasks. First, it describes the process of revising the Connecticut Coincident and Leading Employment Indexes. Second, it analyzes the statistical properties and performance of the new indexes by comparing the lead profiles of the new and old indexes as well as their out-of-sample forecasting performance, using the Bayesian Vector Autoregressive (BVAR) method. The new indexes show improved performance in dating employment cycle chronologies. The lead profile test demonstrates that superiority in a rigorous, non-parametric statistic fashion. The mixed evidence on the BVAR forecasting experiments illustrates the truth in the Granger and Newbold (1986) caution that leading indexes properly predict cycle turning points and do not necessarily provide accurate forecasts except at turning points, a view that our results support.

The Relationship of Student Demographics to 10th Grade MCAS Test Anxiety

The intensification of consequential testing situations is associated with an increase in anxiety among American students (Casbarro, 2005). Test anxiety can have negative effects on student test performance (Everson, Millsap, & Rodriguez, 1991). If test anxiety has the potential to decrease students’ test scores, it becomes a factor that can threaten the validity of any inferences drawn between test scores and student progress (Cizek & Burg, 2006). There are several factors that relate closely to test anxiety (Cizek & Burg, 2006). Variables of key influence include gender, socioeconomic status, and teacher-manifested anxiety (Hembree, 1988). Another influence upon test anxiety is students’ participation in academic support programs to prepare them for exit examinations. The purpose of this study was to examine the relationship between 10th grade high school student gender, socioeconomic status, perceived teacher anxiety, and student preparedness with levels of the Massachusetts Comprehensive Assessment System (MCAS) test anxiety. It appears that few studies have examined levels of high school test anxiety in regards to this specific high-stakes MCAS exit exam required for high school graduation. A two-phase sequential mixed-methods research design was used to survey (N=156) 10th grade students represented by a sampling of (n=80) students with low socioeconomic status and (n=76) students with high socioeconomic status regarding their levels of test anxiety in relation to upcoming MCAS testing. A multiple regression analysis was used to measure the relationship between the predictor variables (gender, socioeconomic status, perceived teacher anxiety, and student preparedness) with the criterion variable of student test anxiety using the Test Anxiety Inventory (TAI). Personal interviews with (n=20) volunteer students provided rich explanations of students’ academic self-efficacy, their perceptions of their performance on the upcoming MCAS exam, and their use of strategies to reduce their levels of test anxiety. Personal interviews with (n=12) volunteer school administrators and teachers provided descriptions of their perceptions of how test anxiety affected their students’ performance. A major quantitative finding of this study was that the variables of student socioeconomic status and student ratings of teacher anxiety accounted for the variance in students’ levels of surveyed test anxiety (R2 = .06, p = .033, small to medium effect size). These results indicate that different student populations vary in their readiness skills to successfully participate in consequential testing situations. Consequently, high-test anxious students would require emotional preparation as well as academic preparation when confronting high-stakes testing. The results have the potential to re-shape the format of schools’ MCAS test preparation efforts.