Earlier the author, together with his collegue, developed a growth model of the Canadian economy (9) which concentrated on the Gross Domestic Product (GDP) side, and from this earlier experience it was found desirable to incorporate not only the GDP side but also the gross national expenditure...

The main objective of this model is to analyse the simultaneous determination of market share and advertising expenditure under dynamic conditions. The authors' empirical analysis is applied to the case of the Eisai Company within the Japanese pharmaceutical industry from 1959 to 1969. Although...

Earlier the first author built an oligopolistic model of the American automobile firms, demonstrating the possibility of econometric model building at the firm level. In the present paper, on the basis of detailed corporate data, we advance this effort further using a more elaborate behavioral...

The present paper is an attempt to extend Chetty's work. It derives a suboptimal adaptive control model for the demand for investment and labor by using invariant imbedding equations.

Advertising expenditures may well be regarded as a form of investment. Using this concept, Nerlove and Arrow examined an optimal advertising policy for the firm which maximizes present valued cash flow. In this paper the Nerlove-Arrow model is applied by use of the usual stock adjustment formula...

Since Timbergen's pioneering study published in 1939, various econometric models have been built in many countries in the world. The rate of production of econometric models has been increasing, particularly over the last decade. This trend is a product of the following developments: (i)...

We develop a new Markov Chain Monte Carlo procedure for a time series regression model truncated by upper and lower bounds. The regression error term is assumed to follow an ARMA--GARCH process. We use a convergence diagnostics with a simultaneous test of mean and covariance stationarity and...

This study proposes a Bayesian semiparametric binary response model using Markov chain Monte Carlo algorithms since this Bayesian algorithm works when the maximum likelihood estimation fails. Implementing graphic processing unit computing improves the computation time because of its efficiency...

We compare Bayesian and sample theory model specification criteria. For the Bayesian criteria we use the deviance information criterion and the cumulative density of the mean squared errors of forecast. For the sample theory criterion we use the conditional Kolmogorov test. We use Markov chain...