"... In PAGE 20: ... In this paper, I use the UC model to calculate a continuous slowdown in capital productivity, as opposed to one-time events. Table4 provides parameter estimates and Figure 6 and 7 plot the estimated trend and cyclical component. The estimates indicate that the model is well- determined.... ..."

"... In PAGE 13: ....2. The German Output Gap Calculated from Quarterly GDP I now turn to an analysis of the quarterly output gap. Details of the results of fitting the UC model for quarterly German GDP are shown in Table3 . Signal extraction carried out using the Kalman filter and smoothing algorithms leads to the various components in Figure 3 to 5.... ..."

"... In PAGE 17: ... While the differences between the farm and the non-farm sectors come up fairly clearly, there is much that needs to be explored further within the vastly heterogeneous non-farm sector. Table2 moves one step forward in that direction and informs us of the educational background of workers engaged in the nine broad sectors of the Indian economy. As in Table 1, here too, a three-layered educational classification of workers (non-iterate, semi-educated and educated) is adopted.... In PAGE 17: ... Again, the picture relates to the aggregate of workers; male-female and rural-urban differences are not considered. Table2 throws up many interesting insights about the non-farm sectors. First, the proportion of non-literate workers has witnessed a varying degree of decline, first between 1983 and 1993-94, and then between 1993-94 and 2004-05, in each sector of the Indian economy, including agriculture.... In PAGE 122: ... Here, we use FDI as the dependent variable and the seven variables (GDP, Openness, Debt/ GDP ratio, Foreign Exchange Reserves, REER, DTSER/Export and Infra/GDP) as the independent predictor variables. Table2 depicts the summary results of multiple regression model and F ratios were found significant at one per cent level in all the five models, which implies the existence of linear relationship between the independent variables and foreign direct investment (FDI) inflows in India. Hence, there is a strong evidence of a linear relationship between FDI and economic variables.... In PAGE 124: ...997 0.000 Predictors:(constant) GDP, openness, DEBT/GDP, FOREX, REER, 1 DTSER/ Export, Infrastructure Predictors:(constant) GDP, openness, DEBT/GDP, FOREX, REER, 2 Infrastructure 3 Predictors:(constant) GDP, openness, FOREX, REER, Infrastructure 4 Predictors:(constant) GDP, FOREX, REER, Infrastructure 5 Predictors:(constant) GDP, FOREX, REER 6 Dependent Variable: FDI Inflows in India Table2 offers that the values of Adjusted Coefficient of determination (R2) and R2 without adjustment are above 0.... ..."

"... In PAGE 17: ... While the differences between the farm and the non-farm sectors come up fairly clearly, there is much that needs to be explored further within the vastly heterogeneous non-farm sector. Table2 moves one step forward in that direction and informs us of the educational background of workers engaged in the nine broad sectors of the Indian economy. As in Table 1, here too, a three-layered educational classification of workers (non-iterate, semi-educated and educated) is adopted.... In PAGE 17: ... Again, the picture relates to the aggregate of workers; male-female and rural-urban differences are not considered. Table2 throws up many interesting insights about the non-farm sectors. First, the proportion of non-literate workers has witnessed a varying degree of decline, first between 1983 and 1993-94, and then between 1993-94 and 2004-05, in each sector of the Indian economy, including agriculture.... In PAGE 122: ... Here, we use FDI as the dependent variable and the seven variables (GDP, Openness, Debt/ GDP ratio, Foreign Exchange Reserves, REER, DTSER/Export and Infra/GDP) as the independent predictor variables. Table2 depicts the summary results of multiple regression model and F ratios were found significant at one per cent level in all the five models, which implies the existence of linear relationship between the independent variables and foreign direct investment (FDI) inflows in India. Hence, there is a strong evidence of a linear relationship between FDI and economic variables.... In PAGE 124: ...997 0.000 Predictors:(constant) GDP, openness, DEBT/GDP, FOREX, REER, 1 DTSER/ Export, Infrastructure Predictors:(constant) GDP, openness, DEBT/GDP, FOREX, REER, 2 Infrastructure 3 Predictors:(constant) GDP, openness, FOREX, REER, Infrastructure 4 Predictors:(constant) GDP, FOREX, REER, Infrastructure 5 Predictors:(constant) GDP, FOREX, REER 6 Dependent Variable: FDI Inflows in India Table2 offers that the values of Adjusted Coefficient of determination (R2) and R2 without adjustment are above 0.... ..."

"... In PAGE 4: ... Over the past two decades various software packages featuring stochastic methods have been developed and applied to numerous problems of academic and engineering interest. A list of existing packages has been compiled in Table1 . Of course great heterogeneity exists in the arena of the available software tools: the differences range from the width of applicability to the setting in which the software is developed, i.... In PAGE 5: ...arty packages. Some can handle both. This aspect has been included in the compilation of existing structural-reliability packages (cf. Table1 ). This highlights an important issue for any user of the engineering practice: the possibility and necessity of interaction with external software tools.... In PAGE 5: ... 3.5 CURRENT TRENDS For the purpose of this paper, a list of software packages capable of structural reliability and stochastic uncertainty analysis has been compiled in Table1 . Based on this list, a few trends can be observed with respect to the development of software capable of dealing with uncertainty.... ..."

"... In PAGE 9: ... Given these ( ; ) pairs, I calculate the welfare cost of uctuations. Table3 reports the amount consumption would have to be increased in all dates and states, in percentage terms, to make consumers indi erent between a deterministic consumption process and what we actually observe. In computing these costs, I assume that preferences are described by the parameter values in Table 2.... ..."

"... In PAGE 3: .... Trends and Non-homogeneity in U.S. real GDP The evidence against the stochastic trend view is reflected in the test statistics shown in Table1 for the annual U.S.... In PAGE 5: ... Therefore, in contrast to the Dickey-Fuller test, there does not exist a set of results which guarantees that inference based on the Leybourne-McCabe test is asymptotically unaffected by data-based lag selection. Results of these tests are reported in Table1 for the full Maddison sample and the sub-period 1909-1970 studied by Nelson and Plosser. The lag length is chosen alternatively by GS and Schwarz apos; (1978) information criteria (SIC).... In PAGE 12: ... Rejection rates differ sharply depending on which lag selection method is used. GS generally chooses a much larger value of k than does SIC, reflecting the contrast we saw in Table1 . It also appears that the particular pattern of real GDP during the period 1930-45 as opposed to the random outcomes of the AR(2) process do matter; the tendency to stronger rejection of the unit root in the longer sample being more apparent for the fixed pattern.... ..."

"... In PAGE 15: ... This filtering, however, although resulting in stationarity, does not entirely remove the stochastic trend, since the innovations of the random walk are a component of the first differenced series (see equation 6). The matrix of correlation coefficients is given in Table6 . There is a strong positive correlation among all the European countries, except the UK, and zero or negative correlations between any pair of European and non-European countries.... ..."