### Table 1: Fatigue life at clamped end based on nonlinear response.

2003

"... In PAGE 7: ... The higher stress ranges contribute most to the accumulated fatigue damage, and the Dirlik approximation compares very well with the rainflow stress range PDF in this regime. The fatigue life calculated at these three locations using the rainflow and Dirlik stress range PDFs are shown in Table1... ..."

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### Table 1. Empirical Studies of IT Diffusion

1992

"... In PAGE 12: ...ndividuals in organizations or organizations as a whole. Similarly to Cooper and Zmud (1990, p. 123) information technology is defined here as any system, product or process whose underlying technology base is composed of computer or communications software or hardware. Figure 2 below maps the eighteen studies to the IT Diffusion Framework; Table1 provides a high-level summary of each study. [INSERT FIGURE 2 THEN TABLE 1 ABOUT HERE] The four subsections below use the IT Diffusion Framework as a device to structure a discussion of major results and implications arising from the eighteen studies.... In PAGE 12: ...1 Individual Adoption of Type 1 Technologies Five studies examined individual adoption or use of Type 1 technologies. The technologies included a text editor, a wordprocessing package, spreadsheet software, graphics software, personal computers and an expert system (see Table1 ). These technologies qualify as independent-use technologies since they were intended to facilitate self- contained tasks performed by individual users.... ..."

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### Table 1 Idiosyncratic Income Process: Parameter Estimates

1997

"... In PAGE 11: ... After presenting our benchmark estimation results we discuss a number of modi cations intended to incor- porate a non-degenerate distribution of initial conditions and/or agent speci c xed e ects. Table1 , panel A reports parameter estimates obtained using GMM in conjunction with the moments in equations (11). Our point estimate of is 0.... In PAGE 12: ... We estimated the parameters of our time series process using a GMM estimator analogous to that outlined in equations (11). The results for the rst-di erenced data, which handles what we view as the most important omission | xed e ects | are reported in Table1 , panel B. We see that the the conditional variances are qualitatively very similar to those from panel A, whereas the estimates of are, not surprisingly, somewhat smaller at .... In PAGE 13: ... The solid-dotted graph in Figure 3 reports the age-dependent cross-sectional variance of log of idiosyncratic earnings, yit, which would apply in a life cycle economy with no aggregate shocks and a large number of agents of each generation, where each agent derives their earnings from the process (9). Population moments are evaluated at the point estimates from Table1 , panel A. When estimating this process we controlled for some characteristics, in particular education.... In PAGE 13: ... We x the ratio of the transitory to the permanent standard deviation at 1.44 (corresponding to Table1 , panel A). We then choose the remaining three parameters, , and to match the cross-sectional standard deviation of the young (0.... In PAGE 14: ...5 Benchmark processes We have chosen to explore the implications of two di erent processes for log of indi- vidual earnings: 1. Based on our GMM estimates from Table1 we set = 0:9345, 2 = 0:061, and 2 = 0:0172. When estimating this process we controlled for some character- istics, in particular education.... ..."

### Table 5: Nonlinear Least Squares Results

"... In PAGE 1: ... In addition, an F-test indicated that the hypothesis that the two rates are the same could not be rejected at conventional significance levels. The 1,775 observations in Table5 represent all 1981 through 1987 vintage passenger cars owned by RTECS respondents in July of 1988 for which complete data were available. Model year 1988 new cars are considered separately from the older vehicles in the household stock because an F-test indicated that the two samples could not be pooled.... In PAGE 8: ... If however, there is no relationship between life cycle fuel expenditures and vehicle price, the capitalization rate would be zero. Based on the regression estimates in Table5 for the sample of pre-1988 vehicles in household holdings, the estimated mean willingness-to-pay for a one dollar change in life cycle operating costs, is $ 0.39.... In PAGE 11: ...8 million--l6 percent higher-- indicating that excluding a separate measurement for nonfatal injuries causes the fatality valuation to reflect the value of nonfatal injuries. The third regression result in Table5 demonstrates the importance of including controls for the driver characteristics in fatal accidents. The mortality risk measure used in the model does not represent a pure measure of automobile-specific risk because driver characteristics are not excised from the rates.... In PAGE 11: ... As defined in section II, these controls measure the proportion of fatal accidents occurring in each make/model/year vehicle that reflect the characteristic in question. The first column in Table5 indicates that the proportion of drivers who are young, those who are older, and those wearing seat belts were all statistically significant at the 0.05 level, and alcohol involvement was significant at the 0.... ..."

### Table 5: Nonlinear Least Scruares Results

"... In PAGE 1: ... In addition, an F-test indicated that the hypothesis that the two rates are the same could not be rejected at conventional significance levels. The 1,775 observations in Table5 represent all 1981 through 1987 vintage passenger cars owned by RTECS respondents in July of 1988 for which complete data were available. Model year 1988 new cars are considered separately from the older vehicles in the household stock because an F-test indicated that the two samples could not be pooled.... In PAGE 8: ... If however, there is no relationship between life cycle fuel expenditures and vehicle price, the capitalization rate would be zero. Based on the regression estimates in Table5 for the sample of pre-1988 vehicles in household holdings, the estimated mean willingness-to-pay for a one dollar change in life cycle operating costs, is $ 0.39.... In PAGE 11: ...8 million--l6 percent higher-- indicating that excluding a separate measurement for nonfatal injuries causes the fatality valuation to reflect the value of nonfatal injuries. The third regression result in Table5 demonstrates the importance of including controls for the driver characteristics in fatal accidents. The mortality risk measure used in the model does not represent a pure measure of automobile-specific risk because driver characteristics are not excised from the rates.... In PAGE 11: ... As defined in section II, these controls measure the proportion of fatal accidents occurring in each make/model/year vehicle that reflect the characteristic in question. The first column in Table5 indicates that the proportion of drivers who are young, those who are older, and those wearing seat belts were all statistically significant at the 0.05 level, and alcohol involvement was significant at the 0.... ..."

### Table 2 Nonlinear models.

1998

"... In PAGE 16: ... Much of the emphasis will be on the choice of bandwidth and the new aspects brought in by using local polynomial approximation. A power experiment on a wide class of nonlinear models listed in Table2 has been conducted in Section 6.3.... In PAGE 18: ...Table2 , however, where M1(x) is approximately quadratic (see Figure 1), as can be expected the best result is achieved with T = 2 and h = 1. For the ^ L(V1)-tests the size tends to be too low.... In PAGE 18: ... If no corrections are made for this e ect, it will lead to conservative tests. Figure 5 shows the power of the ^ L(V )-tests for model la) of Table2 , and we see the same general trend as for the ^ L(M)-tests; the optimal h increases with T and the derivative. Here ^ L1(V1) also has some power for h = 1 because the variance is constant, not only linear, under the null hypothesis.... In PAGE 18: ... Here ^ L1(V1) also has some power for h = 1 because the variance is constant, not only linear, under the null hypothesis. ^ L0(V1) is much more robust than ^ L0(M1), and this is the case for the other models listed in Table2 as well. 6.... In PAGE 18: ... In particular when we have a nonlinear model, we do of course not want h = 1 to be chosen when T = 0 or T = 1, but with a small autocorrelation, this may well happen for T = 0. In fact h = 1 was chosen in 136 of 500 realizations of model lc) of Table2 which is clearly nonlinear (cf. Figure 1).... In PAGE 19: ... 6.3 A power experiment for a wide set of models We have performed a power experiment for the models listed in Table2 , where t N(0; 0:62) in model ld) - lf), t N(0; 0:72) in lg) - lj) and t N(0; 1) in the other models. Models la) - lj), aa) - ag) and Aa) - Ag) are discussed in Luukkonen et al.... In PAGE 36: ...Figure 1-2: Plots of ^ M1(x) (Figure 1) and ^ V1(e) (Figure 2) for the models listed in Table2 with n = 100 000. The kernel estimator with bandwidth h = 0:2 is used and each plot consists of two realizations.... In PAGE 36: ... The possible values for h is given at the vertical axes. Figure 7: The gure is based on 500 realizations of the models in Table2 . It shows the power of ^ LT (M1) with h cross-validated and n = 100, 250 and 204 for models la) - li), aa) - ag) and Aa) - Ag), respectively.... In PAGE 36: ...ower achieved in Hjellvik and Tj stheim (1995). The nominal size is 0.05. Figure 8: The gure is based on 500 realizations of the models in Table2 and shows the power of ^ LT (V1) with h cross-validated and n = 100, 250 and 204 for models la), aa) - ag) and Aa) - Ag), respectively.... In PAGE 37: ....05 for the standard normal distribution has been used. The model is Xt = t, the bandwidth is h = n?1=9 and the number of realizations are 500. Table2 : Various nonlinear models. Models la) - lj), aa) - ag) and Aa) - Ag) are discussed in Luukkonen et al.... ..."

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### Table 2 summarizes the sampling distributions of the three estimators of the diffusion

"... In PAGE 20: ... If, however, the information about intraday volatility that is revealed by the range but not by absolute or squared returns is useful in the estimation of the model, the sampling properties of the range- based quasi-maximum likelihood estimator could well dominate the sampling properties of the exact maximum likelihood estimator for absolute returns. 14 Comparing the third row of each panel in Table2... In PAGE 21: ...bsolute return as volatility proxy. First, the range-based parameter estimates are more accurate. Second, even for the same parameters values, the approximate normality of the log range yields a more efficient volatility extraction. With this in mind, we summarize in the last two panels of Table2 (and in the last column of Figure 2) the sampling distributions of the average extraction error , which is 1 T j T t apos;1 ( ln Ft amp;ln Ft ) an estimator of the expected extraction error , and the average squared extraction E [ ln Ft amp;ln Ft ] error , which is an estimator of the expected squared extraction error 1 T j T t apos;1 ( ln Ft amp;ln... In PAGE 22: ... Now we discuss the results for a smaller sample size of T = 500 observations and a larger sample size of T = 5000 observations. We show the results for T = 500 in Table 3; they are qualitatively identical to those in Table2 . Quantitatively, however, the relative performance of the quasi-maximum likelihood estimator with the log absolute return as volatility proxy, which was already poor with T = 1000 observations, is much worse with T = 500 observations.... In PAGE 22: ... D We present the results for T = 5000 in Table 4. Qualitatively, they are again identical to the results in Table2 ; quantitatively, the comparative performance of the quasi-maximum likelihood estimator with the log absolute return as volatility proxy is improved in some respects,... ..."

### Table 2 summarizes the sampling distributions of the three estimators of the diffusion

"... In PAGE 18: ... If, however, the information about intraday volatility that is revealed by the range but not by absolute or squared returns is useful in the estimation of the model, the sampling properties of the range- based quasi-maximum likelihood estimator could well dominate the sampling properties of the exact maximum likelihood estimator for absolute returns. 14 Comparing the third row of each panel in Table2... In PAGE 19: ...bsolute return as volatility proxy. First, the range-based parameter estimates are more accurate. Second, even for the same parameters values, the approximate normality of the log range yields a more efficient volatility extraction. With this in mind, we summarize in the last two panels of Table2 (and in the last column of Figure 2) the sampling distributions of the average extraction error , which is 1 T j T t apos;1 ( ln Ft amp;ln Ft ) an estimator of the expected extraction error , and the average squared extraction E [ ln Ft amp;ln Ft ] error , which is an estimator of the expected squared extraction error 1 T j T t apos;1 ( ln Ft amp;ln... In PAGE 20: ... Now we discuss the results for a smaller sample size of T = 500 observations and a larger sample size of T = 5000 observations. We show the results for T = 500 in Table 3; they are qualitatively identical to those in Table2 . Quantitatively, however, the relative performance of the quasi-maximum likelihood estimator with the log absolute return as volatility proxy, which was already poor with T = 1000 observations, is much worse with T = 500 observations.... In PAGE 20: ... D We present the results for T = 5000 in Table 4. Qualitatively, they are again identical to the results in Table2 ; quantitatively, the comparative performance of the quasi-maximum likelihood estimator with the log absolute return as volatility proxy is improved in some respects,... ..."

### Table 10. Other Research on Internet Diffusion

2001

"... In PAGE 28: ... Rather than constraining or pre- scribing the use of any particular data, the GDI framework encourages researchers to consider any available sources. OTHER INTERNET DIFFUSION WORK We are now in a position to characterize other research work that has tried to measure the status of Internet diffusion in various countries ( Table10 ). These may be grouped into four categories: (1) studies grounded in traffic patterns and data collection from the Internet itself, (2) studies based on survey research and statistical samples, (3) estimates and derived indexes that are based on self- assessment or syntheses of other studies, and (4) quantitative modeling approaches.... In PAGE 28: ... These may be grouped into four categories: (1) studies grounded in traffic patterns and data collection from the Internet itself, (2) studies based on survey research and statistical samples, (3) estimates and derived indexes that are based on self- assessment or syntheses of other studies, and (4) quantitative modeling approaches. Table10 is a representative but not necessarily exhaustive list of these approaches and references where more information may be found about them. Press [1997b] presented one of the first survey articles about on-going measure- ment techniques.... ..."

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