Existing literature on housing prices is predominantly in a linear framework, and an important question that has not been addressed is whether housing prices exhibit nonlinearity. We examine Smooth Transition Autoregressive (STAR) model based nonlinear properties of housing prices over the 1969–2004 period for the entire US and the four regions. Our main findings are (1) housing price for the entire US and all regions except for the Midwest show non-linearity, (2) the dynamic properties implied by the nonlinear estimation explain the typical patterns that have characterized each housing market, and (3) results of Granger causality tests look more plausible in the nonlinear framework where we find stronger evidence of Granger causality from housing price to employment and also from mortgage rates to housing price. Copyright Springer Science+Business Media, LLC 2009Housing market, STAR, Granger causality, Dynamic property, R10, R21, C12, C13, C32, G10,
We examine improvements in financial knowledge for 8th-grade participants in our financial fitness camp, part of our multifaceted financial literacy program. Eighty-three students enrolled in the camp, and 59 had individual development accounts (IDA). We address several issues raised in the literature by focusing on low-income, predominantly Hispanic students, varying the treatment intensity, comparing outcomes for students in our IDA program with those who are not, addressing the potential endogeneity of IDA participation, and testing for selection bias. Financial knowledge increased by approximately 12 percentage points from camp participation. Standardized Language Arts scores, rather than treatment intensity or IDA participation, most affected gains in financial knowledge. There was no evidence of selection bias. Parents with high “present bias” were less likely to enroll their students in the camp, implying that integrating financial literacy education in the regular school curriculum will better serve students in such families.
This paper employs a vector autoregressive (VAR) methodology to examine the role of oil price shocks, defense shocks, national, and local shocks in explaining fluctuations in non-farm employment in a sample of ten states/MSAs in the US in the period 1969–2000. These include a sample of energy rich states and a sample of presumed beneficiaries of defense spending. Existing literature provides mixed evidence on the effects of defense shocks and oil shocks or does not focus on individual states. Results of this paper indicate that oil shocks and defense shocks have more pronounced effects at the local level than they do at the national level. An increase in the price of oil has a fairly large and for the most part statistically significant positive impact on the energy rich states and has a negative and statistically significant impact in the case of the Detroit-Flint MSA. When defense shocks occur they have a sizable impact on local economies that are beneficiaries of defense spending, even though their importance over the whole sample is not always significant. A key policy implication that emerges is that macroeconomic policy at the aggregate level may not be sufficient to uniformly stabilize regional economies that face oil, defense, and local shocks. Furthermore, to the extent that some of these states are linked more to their own local economies rather than to the US economy, they would have to rely more on local stabilization policies when faced with adverse local shocks. Copyright Springer-Verlag Berlin Heidelberg 2003JEL classification: R1,
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.