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The efficiency of the Tokyo housing market
We take advantage of annual micro data sets which we have compiled from individual listings in the widely-circulated real estate advertisement magazine. A data set compiled from the "properties for investment" section lists both asking (purchase) prices and rents for the same property. With this data, the price-rent ratio is directly observable and expected capital gains before tax and commissions are found to be just less than 90 percent in ten years. The "repeatedly-listed properties for investment" data set, a subset of the first data set, contains only those units in the same buildings after a one-year interval. In this data set, price, rent, and ex post capital gains are all observable. They are used to show that ex post returns on housing investment in the last four years were actually rather modest. The data set for "housing for purchase" and the data set for "housing for rent" data sections were separately used for hedonic regressions, from which we constructed the hedonic price index and the hedonic rent index. Those regressions show the effects of various determinants for housing prices and rents. The time (year) dummy variables in the hedonic regressions give that estimate of increases in prices and rents in the last eleven years in Tokyo. According to these estimates, prices increased 85 to 90 percent over the 1981-92 period, while rents increased about 65 percent during the same period. The price-(annual) rent ratio rents appears to have fluctuated around a constant ratio between 17 and 32. Finally, the weak-form efficiency of excess returns on housing is rejected. However, the conclusion is tentative considering the small sample of our data
Predicting complete loss to follow-up after a health-education program: number of absences and face-to-face contact with a researcher
<p>Abstract</p> <p>Background</p> <p>Research on health-education programs requires longitudinal data. Loss to follow-up can lead to imprecision and bias, and <it>complete </it>loss to follow-up is particularly damaging. If that loss is predictable, then efforts to prevent it can be focused on those program participants who are at the highest risk. We identified predictors of complete loss to follow-up in a longitudinal cohort study.</p> <p>Methods</p> <p>Data were collected over 1 year in a study of adults with chronic illnesses who were in a program to learn self-management skills. Following baseline measurements, the program had one group-discussion session each week for six weeks. Follow-up questionnaires were sent 3, 6, and 12 months after the baseline measurement. A person was classified as completely lost to follow-up if none of those three follow-up questionnaires had been returned by two months after the last one was sent.</p> <p>We tested two hypotheses: that complete loss to follow-up was directly associated with the number of absences from the program sessions, and that it was less common among people who had had face-to-face contact with one of the researchers. We also tested predictors of data loss identified previously and examined associations with specific diagnoses.</p> <p>Using the unpaired t-test, the U test, Fisher's exact test, and logistic regression, we identified good predictors of complete loss to follow-up.</p> <p>Results</p> <p>The prevalence of complete loss to follow-up was 12.2% (50/409). Complete loss to follow-up was directly related to the number of absences (odds ratio; 95% confidence interval: 1.78; 1.49-2.12), and it was inversely related to age (0.97; 0.95-0.99). Complete loss to follow-up was less common among people who had met one of the researchers (0.51; 0.28-0.95) and among those with connective tissue disease (0.29; 0.09-0.98). For the multivariate logistic model the area under the ROC curve was 0.77.</p> <p>Conclusions</p> <p>Complete loss to follow-up after this health-education program can be predicted to some extent from data that are easy to collect (age, number of absences, and diagnosis). Also, face-to-face contact with a researcher deserves further study as a way of increasing participation in follow-up, and health-education programs should include it.</p