### Table 3: Standardized parameter estimates.

2007

"... In PAGE 15: ....2. Linguistic style differences between complaint emails and other email types This Section explores if linguistic style differences exist between a complaint email and another email type. Table3 shows the standardized parameter estimates of the linguistic style variables kept during the stepwise logistic regression whereby one tries to predict whether the received email involves a complaint or not using only the linguistic style variables as described in Table 1. INSERT TABLE 3 OVER HERE Table 3 clearly indicates that the more words (WC), the more articles (Article) and the less prepositions (Preps) are found in an email; the more likely, the email is classified as a complaint.... In PAGE 15: ... Table 3 shows the standardized parameter estimates of the linguistic style variables kept during the stepwise logistic regression whereby one tries to predict whether the received email involves a complaint or not using only the linguistic style variables as described in Table 1. INSERT TABLE 3 OVER HERE Table3 clearly indicates that the more words (WC), the more articles (Article) and the less prepositions (Preps) are found in an email; the more likely, the email is classified as a complaint. In contrast to other types of emails (e.... ..."

### Table 5: Parameter Estimates

in Tiebout Sorting and Discrete Choices: A New Explanation for Socioeconomic Differences in the . . .

2000

"... In PAGE 29: ... For the specification of the model presented in this section, I use the average housing, air quality, climate, and urban density variables for the three closest communities to the community in question. The parameter estimates for the full model are presented in Table5 . Before examining these estimates, it is important to clarify how one should read them.... In PAGE 29: ... In this way, the coefficients that multiply the choice characteristics in the utility function of a black household exactly like the baseline group in every way except race would combine the baseline parameter estimates of first column with the race- black parameter estimates of the second column. The last four rows of Table5 show the estimates of the inclusive value (s) parameters, which determine households substitution patterns between choices within versus across branches in the decision tree depicted in Figure 2. Values close to one imply that the household substitution patterns are substantially different, while values close to zero reduce the nested framework of Figure 2 to the multinomial logit framework.... In PAGE 29: ... Values close to one imply that the household substitution patterns are substantially different, while values close to zero reduce the nested framework of Figure 2 to the multinomial logit framework. A quick examination of Table5 reveals that the precision of my estimation with a sample of 5,000 households is quite good, with a majority of the would-be t-statistics residing in the 2 to 5 range. I now present the primary analysis of this paper, which attempts to distinguish the underlying forces that drive the observed differences in the consumption of public school quality by households with different characteristics and endowments.... In PAGE 47: ...Table5 (cont): Parameter Estimates Baseline Race Race Education Income Black Hispanic HS degree $40k or less or less Tenure Characteristics: Rental Unit 0.020 0.... ..."

### Table 5 (cont): Parameter Estimates

in Tiebout Sorting and Discrete Choices: A New Explanation for Socioeconomic Differences in the . . .

2000

"... In PAGE 29: ... For the specification of the model presented in this section, I use the average housing, air quality, climate, and urban density variables for the three closest communities to the community in question. The parameter estimates for the full model are presented in Table5 . Before examining these estimates, it is important to clarify how one should read them.... In PAGE 29: ... In this way, the coefficients that multiply the choice characteristics in the utility function of a black household exactly like the baseline group in every way except race would combine the baseline parameter estimates of first column with the race- black parameter estimates of the second column. The last four rows of Table5 show the estimates of the inclusive value (s) parameters, which determine households substitution patterns between choices within versus across branches in the decision tree depicted in Figure 2. Values close to one imply that the household substitution patterns are substantially different, while values close to zero reduce the nested framework of Figure 2 to the multinomial logit framework.... In PAGE 29: ... Values close to one imply that the household substitution patterns are substantially different, while values close to zero reduce the nested framework of Figure 2 to the multinomial logit framework. A quick examination of Table5 reveals that the precision of my estimation with a sample of 5,000 households is quite good, with a majority of the would-be t-statistics residing in the 2 to 5 range. I now present the primary analysis of this paper, which attempts to distinguish the underlying forces that drive the observed differences in the consumption of public school quality by households with different characteristics and endowments.... In PAGE 46: ...Table5 : Parameter Estimates Baseline Race Race Education Income Black Hispanic HS degree $40k or less or less Community Characteristics: Commuting distance 0.033 0.... ..."

### Table 1 parameter Estimates from Univariate Models

1987

### Table 3: Parameter estimates and bootstrap results of reduced-form model point

2005

### Table 4: Tax Parameters

2007

"... In PAGE 18: ... We calculate income by normalizing average income in each income bracket by the mean household income in 2000. Table4 shows the estimates of the coefficients for married and single households. Given these estimates, we specify the tax functions in the benchmark model as T M(income) = [0.... ..."

### Table 5 ARMD trial

2007

"... In PAGE 20: ... This finding is mildly confirmed by the random-intercept model, when the data as observed are used. The results for the random-effects models are given in Table5 . We observe the usual relationship between the marginal parameters of Table 4 and their random-effects counterparts.... ..."

### Table 2 Comparison of Models Based on Equation (3.1)

2001

Cited by 6

### Table 1 Parameter Estimate Parameter Estimate

2000

"... In PAGE 5: ... Through a likelihood function of a logit specification, both the precision parameters and the proportion of each type of behavior in the population, a t, were determined. The parameters used for predictions of initial-period play in this paper (see Table1 ) are based on out-of-sample estimation of 20 different one- shot games in HS99. Given the 12 estimated parameters in Table 1, this model of initial play defines a probability distribution over the pure strategies, which is the derived estimate of the probability distribution from which the empirical sample was drawn.... In PAGE 5: ... The parameters used for predictions of initial-period play in this paper (see Table 1) are based on out-of-sample estimation of 20 different one- shot games in HS99. Given the 12 estimated parameters in Table1 , this model of initial play defines a probability distribution over the pure strategies, which is the derived estimate of the probability distribution from which the empirical sample was drawn. Hence, this estimated probability distribution can be used to forecast initial play out-of-sample.... ..."

### Table 2 Parameter Estimates

2000

"... In PAGE 15: ...The estimated parameters are shown in Table2 . We find that they are estimated with fairly good precision.... ..."