### Table 8: Selection corrected maximum likelihood estimates of self-employment income in 1996 conditional on surviving since 1994

1999

"... In PAGE 19: ... Unfortunately the sample sizes do not allow for this kind of detailed analysis.20 Self-employment income Table8 displays the estimates of the determinants of self-employment income in 1996 (used as a proxy for enterprise growth) given self-employment in 1994 (equation 21).21 Again, neither the receipt of a windfall payment nor the type of windfall payment have a significant effect on income.... In PAGE 20: ... Burke et al (1997), for example, find that the size of any inheritance received has no impact on self-employment income.23 Other notable effects emerge from Table8 . Men have higher self-employment income than women, and unsurprisingly the income received in 1996 is positively related to that received in 1994.... ..."

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### Table 4. Maximum likelihood estimation of all alphas.

"... In PAGE 10: ...robability of obtaining the sample actually observed (Judge et al., 1988, p. 222).The estimated parameters s apos; and , s apos; , 0 j i b b b ) ) ) are the usual ones for a Cobb-Douglas technology, and i a apos;s and j a apos;s are the translation parameters for this particular case. Results of maximum likelihood joint estimation, are presented in Table4 . The last two columns of the table highlights the differences with the estimates presented in Table 4.... ..."

### Table 2. Fit Results for Rival Models by Student Groupa

### Table 1 Maximum Likelihood Estimates for Country Pairs

"... In PAGE 14: ... Estimates appear robust to a variety of starting values. Table1 presents the ma ximum likelihood estimates for our model and the country pairs a) US and Canada, b) US and France, c) US and Germany, d) US and Italy, e) US and Japan, and f) US and UK, respectively. The most important thing to notice about these estimates is that, for every country pair, the adjustment of prices to a transitory shock is much faster than the adjustment of the exchange rate.... In PAGE 16: ... Of course, we should be careful about interpreting the estimates of k too literally since they are not significant. The remaining estimates in Table1 are of the long-run inflation rates in each country and the normalizing initial values for the unobserved equilibrium prices and exchange rate. It is encouraging to note that the estimates for all of the parameters associated with US prices only (i.... In PAGE 38: ... Table1 (Continued) Parameter US/Canada US/France US/Germany US/Italy US/Japan US/UK g -0.286 5.... ..."

### Table 3. Maximum Likelihood Estimates of Specification (2)

2006

"... In PAGE 19: ... In this section, both ML and conventional GMM estimates of the specification are presented. Table3 displays the ML estimates for the specification in equa- tion (2), using either the output gap or real marginal cost as the driving variable.20 For this estimation, the sample is constrained to the Greenspan era, 1987:Q3 to the end of the sample.... ..."

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### Table 9 Quasi-Maximum Likelihood Estimates

"... In PAGE 25: ... Clearly, the measurement errors associated with the log absolute returns masks the persistence in volatility. Estimation of the One-Factor Stochastic Volatility Model With the Log Range as Volatility Proxy We report estimates of the one-factor stochastic volatility model described by equations (4)-(5) for the five currencies in the left panel of Table9 . For now, we focus on the estimates obtained using our preferred volatility proxy, the log range.... In PAGE 26: ... The misspecification of the one-factor model can be seen in another way. To obtain the estimates in Table9 , we set the standard deviation of the measurement equation disturbances to 0.29, per the results in Table 1.... In PAGE 26: .... Consider, for example, the British pound. When we set the standard deviation of the measurement errors to 0.29, we obtain , as recorded in Table9 , but when D apos;0 . 66 we estimate the standard deviation of the measurement errors along with the other parameters, we obtain and an estimate of the standard deviation of 0.... In PAGE 27: ... The difference is that ours is a truly two-factor stochastic volatility model, whereas theirs is a one-factor GARCH(2,2) model decomposed tautologically into a component structure. When we estimate the above two-factor stochastic volatility model, the results of which we report in the right panel of Table9 , we obtain a persistent and a transient factor. Each factor is responsible for about half the long-run (unconditional) variance of log volatility, but the transient factor responsible for much more of the short-run variance.... In PAGE 29: ... This is approximately true. Estimation With the Log Absolute Return as Volatility Proxy: Comparison and Reconciliation At first sight, the estimates of the one-factor model based on the log absolute return, in the left panel of Table9 , and the corresponding residual diagnostics, in the left panel of Table 10, show no evidence of model misspecification. 21 In particular, the single factor that emerges resembles closely the persistent factor of our two-factor model, instead of the variance-weighted average of the two factors.... ..."

### Table 9 Quasi-Maximum Likelihood Estimates

"... In PAGE 23: ... Clearly, the measurement errors associated with the log absolute returns masks the persistence in volatility. Estimation of the One-Factor Stochastic Volatility Model With the Log Range as Volatility Proxy We report estimates of the one-factor stochastic volatility model described by equations (4)-(5) for the five currencies in the left panel of Table9 . For now, we focus on the estimates obtained using our preferred volatility proxy, the log range.... In PAGE 24: ... The misspecification of the one-factor model can be seen in another way. To obtain the estimates in Table9 , we set the standard deviation of the measurement equation disturbances to 0.29, per the results in Table 1.... In PAGE 24: .... Consider, for example, the British pound. When we set the standard deviation of the measurement errors to 0.29, we obtain , as recorded in Table9 , but when D apos;0 . 66 we estimate the standard deviation of the measurement errors along with the other parameters, we obtain and an estimate of the standard deviation of 0.... In PAGE 25: ... The difference is that ours is a truly two-factor stochastic volatility model, whereas theirs is a one-factor GARCH(2,2) model decomposed tautologically into a component structure. When we estimate the above two-factor stochastic volatility model, the results of which we report in the right panel of Table9 , we obtain a persistent and a transient factor. Each factor is responsible for about half the long-run (unconditional) variance of log volatility, but the transient factor responsible for much more of the short-run variance.... In PAGE 27: ... This is approximately true. Estimation With the Log Absolute Return as Volatility Proxy: Comparison and Reconciliation At first sight, the estimates of the one-factor model based on the log absolute return, in the left panel of Table9 , and the corresponding residual diagnostics, in the left panel of Table 10, show no evidence of model misspecification. 21 In particular, the single factor that emerges resembles closely the persistent factor of our two-factor model, instead of the variance-weighted average of the two factors.... ..."

### Table 3: Maximum Likelihood Estimation Results

"... In PAGE 14: ... (Philip Morris is a component stock of the index.) Table3 contains the estimation results for Philip Morris and the S amp;P500 index. For all cases, we keep the S amp;P500 parameters constant.... ..."

### Table 4. Manufacturer Discretion: Maximum Likelihood Estimates

"... In PAGE 19: ... On their own, the average price sold, the number of dealers in the network and the age of the network explain around 70% of the variation in the allocation of completion rights by these contracts. [ Note: Table4 here, with allocation of rights by MLE] The regressors are also economically significant. An increase in price of automobiles of one standard deviation (Pta- 1.... In PAGE 20: ...88) increases manufacturer discretion by 1 clause. The main observation that can be derived from using MLE methods to estimate the relation between decision rights and network characteristics as showed in Table4 is that the results of such a procedure are entirely consistent with those in Table 3. None of the 28 signs of the dependent variables is altered by the change in methods.... In PAGE 20: ... Our confidence in these results is increased by the analysis of the individual clause variation presented in Table 5. 13 The signs of the individual effects are overwhelmingly the ones that Table4 has led us to expect: of 60 possible signs (15 regressions times 4 independent variables), only 4 are different than in Tables 3 and 4 and all of those 4 are insignificantly different than 0. As in Tables 3 and 4, particularly robust appear the results on Car Price, Number of Dealers in the Network, and the Asia dummy.... ..."

### Table 9 Maximum likelihood estimation (MLE) of LTP.

1997

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