Risk Assessment Steeplechase: Hurdles to Becoming a Target Market

Framed in a quadrant model, the data sources that analysts use to predict the performance of core property types for the major metropolitan areas in the United States are reviewed. The hypothesis is that forecasters rely on information from the economic base, the property inventory and financial performance quadrants to generate forecasts. For each core property type, analysts are rather homogeneous in grouping metropolitan areas from best to worst. However, the property type determines what sets of economic, social, inventory and market information are used. The only consistent forecast factor used across all property types appears to be economic growth.

The Information Precision of CBD Office Vacancy Rates

Consistent with the rational expectations information model (REIM), the difference among reported area CBD office vacancy rates is proportional to the level of vacancy, inversely proportional to the size of the inventory, and significantly higher when both a national vendor and a local agent make simultaneous reports. Underlying volatility in the market and the cost and difficulty of acquiring information are the principal causes of the information variance. The difficulties and ambiguities in obtaining information are reviewed and the Diamond REIM model is tested using encountered published vacancy rates for central business districts for the period 1985-1989.

Texas Business Review, January 1978

An Economic Profile of the Texas Apparel Industry; Public Employee Unionization and Texas: A Critical Public Issue; Construction Activity in Texas SMSAs; Texas Companies: Sources of InformationBureau of Business Researc

Texas Business Review, March 1978

Recent Texas Growth Patterns; Regional Patterns of Industrial Growth in the Planning Regions of Texas; The Relocation Misconceptions: Manufacturing Change in Houston and Dallas-Ft. Worth; Construction Activity in Texas: A Boom in 1977Bureau of Business Researc

Texas Business Review, October 1978

The Consumer Price Index: An Improved Measure of Inflation; Consumer Economics in Education; Austin: Rapid Growth in the Hill Country; Bryan-College Station: An Education CenterBureau of Business Researc

Time to Peak Glucose and Peak C-Peptide During the Progression to Type 1 Diabetes in the Diabetes Prevention Trial and TrialNet Cohorts

OBJECTIVE To assess the progression of type 1 diabetes using time to peak glucose or C-peptide during oral glucose tolerance tests (OGTTs) in autoantibody-positive relatives of people with type 1 diabetes. RESEARCH DESIGN AND METHODS We examined 2-h OGTTs of participants in the Diabetes Prevention Trial Type 1 (DPT-1) and TrialNet Pathway to Prevention (PTP) studies. We included 706 DPT-1 participants (mean ± SD age, 13.84 ± 9.53 years; BMI Z-score, 0.33 ± 1.07; 56.1% male) and 3,720 PTP participants (age, 16.01 ± 12.33 years; BMI Z-score, 0.66 ± 1.3; 49.7% male). Log-rank testing and Cox regression analyses with adjustments (age, sex, race, BMI Z-score, HOMA-insulin resistance, and peak glucose/C-peptide levels, respectively) were performed. RESULTS In each of DPT-1 and PTP, higher 5-year diabetes progression risk was seen in those with time to peak glucose >30 min and time to peak C-peptide >60 min (P < 0.001 for all groups), before and after adjustments. In models examining strength of association with diabetes development, associations were greater for time to peak C-peptide versus peak C-peptide value (DPT-1: χ2 = 25.76 vs. χ2 = 8.62; PTP: χ2 = 149.19 vs. χ2 = 79.98; all P < 0.001). Changes in the percentage of individuals with delayed glucose and/or C-peptide peaks were noted over time. CONCLUSIONS In two independent at-risk populations, we show that those with delayed OGTT peak times for glucose or C-peptide are at higher risk of diabetes development within 5 years, independent of peak levels. Moreover, time to peak C-peptide appears more predictive than the peak level, suggesting its potential use as a specific biomarker for diabetes progression