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New England raised and Oregon-based, I'm a twenty-something editor with a penchant for gear. Upon receiving a degree from the University of Massachusetts, I packed my car on a whim and made for the west coast. Like a rebel without a cause, I drove until I found myself in Oregon, a place where towering pines and peaks looked nothing like the old forests back home. It's here that I began my career as a freelance writer, contributing gear-related stories to REI Co-op, Backpacker, GearJunkie, Field Mag and others. Years later, I began working as a copywriter for Backcountry.com before jumping headfirst into the world of product journalism where I find myself today.
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We define "comp distance" as the average distance in miles between the subject property and the comps listed on the appraisal report. It is calculated as , where n refers to the number of comps. Exhibit 7 shows that the average comp distance is much smaller when the property is in a Black or Latino tract than in a White tract. For example, the average distance for properties in a Latino tract is 0.73 miles, compared to 1.40 miles in a White tract, resulting in a negative gap of 0.67 miles. On a relative basis, this negative gap is 48% (0.67/1.40). We also sort the data into urban, suburban, and rural subsets to check whether the overall pattern in Exhibit 7 persists. We find that the patterns are consistent in both urban and suburban areas.
The "comp variance" metric is defined as , where the "Highest (Lowest) Comp" refers to the highest (lowest) sales price of the comps. It measures the difference between the highest and the lowest sales price of the comps expressed as a percentage of the contract price. The higher the metric (the higher the percent), the larger the variance. Given the heterogeneity of minority neighborhoods (Lee, 2018), we want to examine whether there is more variation in the sales prices within comps used in appraisals for properties in minority tracts than in White tracts.
The data used in this exercise are from Freddie Mac's mortgages funded from January 1993 to June 2021 for the purchase of owner-occupied properties. We include properties that were sold at least twice during that period and excluded properties where subsequent sales occurred within 36 months. The final data set we analyze has 2,965,495 observations and 36.3% of these are of transaction pairs that span mixed racial/ethnic groups. Also, of the 72,568 census tracts covered by our sample about 86% have transaction pairs that span mixed racial/ethnic groups.
A challenge in this exercise is to properly account for unobserved changes in housing quality over time and housing quality differences across race and ethnicity. To address this, we implement a repeat-sales approach that controls for unobserved housing quality to better isolate racial and ethnic differences in sales prices for comparable homes. We estimate the following equation:15 where is the sale price for buyer i purchasing property j in the census tract n at time t; is a vector of indicators for the race and ethnicity of the buyer at time t (White being the base category); is a house-specific fixed effect that controls for changes in house quality over time, and ensures that house price changes are computed for the same properties using the first and second transaction prices; denotes a set of fixed effects per census tract over time and allows us to control for tract-level house price changes during the same period; and measures the average premium (or discount) paid by Black and Latino buyers relative to White buyers.
11 Conditions for t-statistics to be valid are as follows: MIN N1*P1, N1*(1-P1)>=10 and MIN N2*P2, N2*(1-P2)>=10 where N1 =Number of appraisals in Black tracts, P1=Percent of appraisals that have a value lower than the contract price in Black tracts, N2=Number of appraisals in White tracts, P2=Percent of appraisals that have a value lower than the contract price in White tracts.
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A realtime listing of the sensors in your Mac, including temperatures, hard drive temperatures (where supported), fans, CPU frequency, GPU frequency (Intel GPUs only), voltages, current and power. Fan speeds can be controlled, and even switched based on temperatures, active GPU and battery state. 2ff7e9595c
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