### Table 8: Cross-Section estimates (N 19) Ranking of models

### Table 11: Cross-Section estimates Model diagnostics

### Table 3 Cross-Section Estimates of Saving Equations Dependent Variable: GNS/GNP

"... In PAGE 21: ...orrelated with real per capita income (the corresponding correlation coefficients exceed .88). It will be useful to keep in mind these features of the data for the discussion of the empirical results below. Table3 shows estimation results using the basic equation for a variety of samples. As a benchmark, the first column reports parameter estimates using a specification excluding income distribution indicators.... In PAGE 22: ...49, which overwhelmningly rejects the null at the I percent level. Columns 2-4 in Table3 augment the specification in the first column using the Gini coefficient as income distribution indicator in different country samples. The sign pattern of the parameter estimates in the first six rows remains unchanged, and the full-sample estimates in column 2 are virtually identical to those in column 1.... In PAGE 22: ... Apart from a general loss of precision, the estimation results are otherwise very sumilar to those obtained usmg the Gini coefficient, as should be expected in view of the very high correlation reported above between the two income distribution indicators. Columns 8 and 9 of Table3 show the results of excluding from the sample the group of take-off developing countries, which some might argue are apos;exceptional apos; from the viewpoint of saving (and also growth). For both the full and LDC samples in columns 8 and 9, the main consequence is that the estimated coefficient on growth loses all significance, a finding similar to that reported by Carroll and Weil (1994) when excluding from their sample the East-Asian apos;tigers apos;.... In PAGE 23: ... The first two columns estimate our basic specification on the full and LDC sample, respectively. As can be seen, the main difference with the estimation results in Table3 is the loss of significance of income growth as a saving determinant. For the full sample, the parameter estimate on the Gini coefficient is very similar to that reported by Sahota ( 1993), but falls far short of statistical significance.... ..."

### Table 4 Cross-Section Estimates of Saving Equations Dependent Variable: GNSIGNP

"... In PAGE 23: ...stimates are biased, although the direction of the bias is not known in general (e.g., Maddala 1983). Next we check the robustness of our main result -- that income inequality does not affect aggregate saving -- by estimating altemative specifications that have been used in previous studies. Table4 presents the results using the full sample. The first two columns explore possible non-linear effects of income distribution, interacting the Gini coefficient with real per capita income and adding a quadratic term, respectively.... In PAGE 23: ...681, far below conventional significance levels). The last two columns in Table4 investigate alternative inequality indicators: column 5 uses the income share of the middle class, and column 6 adds to this the ratio of income shares of the top 20 and bottom 40 percent of the population. In neither case do we find any significant effects on saving.... ..."

### Table 9: Cross-section estimates (N =19) Number of times the rank is:

### Table 12: Cross-Section estimates (N=17) Model diagnostics: Bischoff model

### Table 6 Cross-Section Estimates of Saving Equations Dependent Variable: GDS/GDP

### Table 1: Cross-sectional parameters, as well as the prior and posterior estimates of , , , and .

1999

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### Table 5: Per cent of repeated housing problems or evictions

"... In PAGE 9: ... We are most interested in the dynamics of arrears and evictions, as little evidence is available on this subject. In Table5 we list the distribution of repeated housing problems for the 25% of households who report at least one incidence of problems. About 30% of households who experience housing finance difficulties have problems only once, 24% twice, and 30% say in 4 or more interviews that they have problems paying for their housing.... In PAGE 10: ... If rho is zero, then the panel-variance level component is unimportant and the panel estimator is not different from a cross-sectional (or pooled) estimation. As seen in Table5 the number of repeated evictions is low. The estimation of a random-effects... ..."

### Table 8 provides the pooled time series cross sectional estimates fo r each country. Note

"... In PAGE 36: ... On the other hand, the results indicate that larger firms have lower dividend yields, while firms with more variable returns on assets (business risk proxy) have higher dividend yields; these two results are significant and contradict hypotheses 6 and 2, respectively. Table8 also indicates that firms with more tangible assets tend to have lower dividend yields, which contradicts hypothesis 8. The US control model off ers some good and bad news for our hypotheses, and our eight emerging markets offer similar conclusions.... ..."