Economic Efficiency and Growth: Evidence from Brazil, China, and India

We compare economic efficiencies in Brazil, India, and China, where economic efficiency measures the gap between potential and actual output for a given input combination and technological factor. We use stochastic production frontier models to measure the contributions of factors of production and technology to growth and estimate non-positive error terms that capture production inefficiencies in each country. The results suggest that China and India had relatively inefficient production in the early 1980s but have since improved production efficiency substantially. In the same period, production efficiency in Brazil has declined somewhat from relatively high initial levels and the gap between production efficiency between these countries has narrowed substantially, supporting more rapid growth in China and India relative to Brazil.growth, trade, production

Economic efficiency and growth: Evidence from Brazil, China and India

We compare economic efficiencies in Brazil, India, and China, where economic efficiency measures the gap between potential and actual output for a given input combination and technological factor. We use stochastic production frontier models to measure the contributions of factors of production and technology to growth and estimate non-positive error terms that capture production inefficiencies in each country. The results suggest that China and India had relatively inefficient production in the early 1980s but have since improved production efficiency substantially. In the same period, production efficiency in Brazil has declined somewhat from relatively high initial levels and the gap between production efficiency between these countries has narrowed substantially, supporting more rapid growth in China and India relative to Brazil

Forecasting state income tax receipts : a time series approach

Includes bibliographical references (p. 15-16)

Time Series Analysis and Indicators of Economic Activity (Forecasting)

182 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1985.Some of the problems involved in identification of time series models and forecasting variables of interest are considered. A theoretical/empirical comparison of various information criteria of interest is provided and it is concluded that Hannan and Kavalieris criterion is the most appropriate criterion to be used for model selection. Appropriate time series models for forecasting state income tax receipts are identified by employing information criteria and Box-Cox transformation. Furthermore, bivariate time series models with the index of leading indicators as the input variable are used to forecast a coincident indicator of interest. The weights assigned to the elements of the index of leading indicators are found by constructing and minimizing the variance of forecast error function for several steps ahead forecasting.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD