Thesis (M.B.A.)--University of Hong Kong, 1985.

Thesis (Ph.D.)--University of Tulsa, 1989. / Bibliography: leaves 33-36.

This dissertation proposes to develop a functional specification of the cost function which can be used to discriminate among the alternative flexible functional forms and to analyze productivity growth. The problem of choosing among alternative functional forms is tackled by developing a nested representation which takes as special cases several well known forms. Productivity growth is analyzed by considering input price effects, non-neutral scale effects and biased technical change. Total factor productivity (TFP) is used as an index of technical change. Traditionally, the rate of TFP growth has been computed, assuming constant returns to scale, as the residual of the rate of growth of real output minus the rate of growth of aggregate real input. The parametric approach to productivity analysis adopted here allows estimation of the TFP growth rate without requiring constant returns to scale. The stochastic specification of the model incorporates errors arising out of imperfect cost minimizing behaviour. The resulting likelihood function is continuous in all the parameters. A four input version of the model has been used to estimate the total U.S. Manufacturing Technology, 1947-71. The inputs are capital, labour, energy and other intermediate materials. The parameters of the model have been estimated by utilizing the maximum likelihood method. The main hypotheses tested are neutrality of technical change and homotheticity. This investigation suggests that total U.S. Manufacturing, 1947-71 may be characterized by non-neutral scale effects and biased technical change. The scale effects have been capital, labour and energy saving while technical progress has been capital and energy using and labour neutral. The elasticity results indicate that capital and labour are substitutes as are labour and energy while capital and energy are complements. Capital and energy are more own price elastic than labour. Scale economies seem to have contributed considerably to productivi growth in total U.S. Manufacturing, 1947-71. The contribution of total factor productivity is, however, uncertain and perhaps small. / Arts, Faculty of / Vancouver School of Economics / Unknown

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Thesis (M. Soc. Sc.)--University of Hong Kong, 1986.

Thesis (M.Soc.Sc.)--University of Hong Kong, 1986. / Also available in print.

Thesis (Ph. D.)--University of Michigan, 1985. / Includes bibliographical references (leaves 108-117).

Thesis (Ph. D.)--University of California, Berkeley, 1989. / Includes bibliographical references (leaves 219-235).

Wong Tin-Ip. / Thesis (M.Phil.)--Chinese University of Hong Kong. / Bibliography: l. [98-100]

This dissertation contains three essays on Macroeconomics. Detailed micro-level data is used in all three essays. The first chapter studies wealth inequality problems. More specif- ically, it focuses on capital return inequality among university endowments. It combines university-level data on endowment size, capital returns, and portfolio allocations into a unified dataset. Using panel data regression, I show a strong impact of size on investment return. Everything else the same, the biggest endowment has a capital return 8 percent higher than the smallest endowment. However, after adjusting for risk using Sharpe ratios, the strong positive correlation turns negligible or even negative. This result suggests that the higher return of bigger endowments can be attributed to risk compensation rather than to an informational premium. The second and the third chapters employ firm-level data to study macroeconomic pro- ductivity. The second chapter documents the sectoral growth paths of measured total factor productivity (TFP) in southern Europe during the boom that proceeded the great contraction (1996 to 2007). Using both aggregate and firm-level panel data, I show that TFP in sectors that displayed fast expansion, such as construction, dropped significantly, while in non- expanding sectors, such as manufacturing, it stayed stable. I evaluate the relevance of two alternative explanations of this phenomenon: capital misallocation (the increase in capital was directed to less productive firms) and labor quality mismeasurement (lower quality of incoming labor was not fully captured in the TFP calculation). I find that the misalloca- tion channel is almost negligible. Moreover, worker-firm matched data shows that labor quality did deteriorate in the expanding sectors but not in the others, giving credence to the labor-quality mismeasurement hypothesis. A model featuring both the misallocation and the mismeasurement channels and calibrated to match the micro-level productivity distri- bution and labor quality distribution predicts that the drop in true TFP was small if labor quality is measured properly. The third chapter documents the total factor productivity growth path in China from 1998 to 2015 using both the aggregate and the firm-level data. We find that measured TFP growth is positive from 1998 to 2011, before turning flat and even negative. A care- ful comparison between state-owned enterprises (SOEs) and private firms reveals that the slowing down of TFP growth of SOEs is the major contributor to the TFP growth reversal of the whole manufacturing sector. The reversal is not due to changes in the composition of production in different sub-sectors, but mostly due to changes within existing firms.