Suchergebnisse

The authors estimate the relationship between trees and three crime aggregates (all crime, violent crime, and property crime) and two individual crimes (burglary and vandalism) in Portland, Oregon. During the study period (2005-2007), 431 crimes were reported at the 2,813 single-family homes in our sample. In general, the authors find that trees in the public right of way are associated with lower crime rates. The relationship between crime and trees on a house's lot is mixed. Smaller, view-obstructing trees are associated with increased crime, whereas larger trees are associated with reduced crime. The authors speculate that trees may reduce crime by signaling to potential criminals that a house is better cared for and, therefore, subject to more effective authority than a comparable house with fewer trees.

We assess exchange rate pass-through (ERPT) for U.S. and Canadian prices for oriented strand board (OSB), a structural wood panel product used extensively in U.S. residential construction. Because of its prominence in construction and international trade, OSB markets are likely sensitive to general economic conditions. In keeping with recent research, we examine regime-specific ERPT effects; we use a smooth transition vector error correction model. We also consider ERPT asymmetries associated with a measure of general macroeconomic activity. Our results indicate that during expansionary periods ERPT is modest, but during downturns, ERPT effects are larger. ; USDA-USFS [SRS 09-CA-11330143-023] ; This research has been supported by USDA-USFS Cooperative Agreement No. SRS 09-CA-11330143-023. We appreciate the helpful comments provided by an anonymous referee and by seminar participants at the International Conference of Agricultural Economists in Vancouver, Canada, August 2018. Authors names appear in alphabetical order - senior authorship is shared. ; Public domain authored by a U.S. government employee

This study evaluated the hypothesis that urban-tree planting increases neighborhood gentrification in Portland, Oregon. We defined gentrification as an increase in the median sales price of single-family homes in a Census tract compared to other tracts in the city after accounting for differences in the housing stock such as house size and number of bathrooms. We used tree-planting data from the non-profit Friends of Trees, who have planted 57,985 yard and street trees in Portland (1990–2019). We estimated a mixed model of gentrification (30 years and 141 tracts) including random intercepts at the tract level and a first-order auto-regressive residual structure. Tract-level house prices and tree planting may be codetermined. Therefore, to address potential endogeneity of tree planting in statistical modeling, we lagged the number of trees planted by at least one year. We found that the number of trees planted in a tract was significantly associated with a higher tract-level median sales price, although it took at least six years for this relationship to emerge. Specifically, each tree was associated with a $131 (95% CI: $53-$210; p-value=0.001) increase in tract-level median sales price six years after planting. The magnitude of the association between the number of trees planted and median sales price generally increased as the time lag lengthened. After twelve years, each tree was associated with a $265 (95% CI: $151-$379; p-value<0.001) increase in tract-level median sales price. Tree planting was not merely a proxy for existing tree cover, as the percent of tract covered in tree canopy was independently associated with an increase in median sales price. Specifically, each 1-percentage point increase in tree-canopy cover was associated with a $882 (95% CI: $226-$1,538; p-value=0.008) increase in median sales price. In conclusion, tree planting is associated with neighborhood-level gentrification, although the magnitude of the association is modest.

This book provides the background theory behind two types of trade models rooted in economic theory and mathematical programming, and two econometric/statistical models. It shows the reader how to construct their own models to analyse policy questions in forestry and other sectors.