TITLE:
Application of Non-Linear Cobb-Douglas Production Function with Autocorrelation Problem to Selected Manufacturing Industries in Bangladesh
AUTHORS:
Md. Moyazzem Hossain, Tapati Basak, Ajit Kumar Majumder
KEYWORDS:
Cobb-Douglas Production Function; Autocorrelation; Manufacturing Industry; Bangladesh
JOURNAL NAME:
Open Journal of Statistics,
Vol.3 No.3,
June
18,
2013
ABSTRACT:
In developing counties, efficiency of
economic development has been determined by the analysis of industrial production. An examination of the characteristic
of industrial sector is an essential aspect of growth studies. The growth of a country can be measured by Gross Domestic Product
(GDP). GDP is substantially affected by the industrial output. Industrial
gross output is mainly a function of capital and labor input. If the effect of
labor and capital input to output is at a satisfactory level in an industry or
in a group of industries, then industrial investment will increase. As a
result, the number of industries will increase, which will directly affect GDP
and also will decrease the unemployment rate. This is why, industrial
input-output relationship is so important for any industry as well as for the
overall industrial sector of a country. To forecast the production of a firm is
necessary to identify the appropriate model. MD. M. Hossain et al. [1]
have shown that Cobb-Douglas production function with additive errors was more
suitable for some selected manufacturing industries in Bangladesh. The main
purpose of this paper is to detect the autocorrelation problem of Cobb-Douglas
production model with additive errors. The result shows that autocorrelation is
presented in some manufacturing industries. Finally, this paper removes the autocorrelation
problem and re-estimates the parameters of the Cobb- Douglas production function with additive errors.