DEMAND EQUATIONS FOR SELECTED SOUTH AFRICAN AGRICULTURAL COMMODITIES
ABSTRACT A set of demand equations for 18 South African agricultural products, representing three demand systems (red meats, fruits and vegetables), were estimated from monthly data for the period December 1982 to February 1988. Data were deflated with a commodity price index and natural logarithmic partial adjustment equations were estimated with two-stage least squares to determine demand parameters for each product. Theoretically expected results were obtained and, owing to variability in seasonal data, results were generally highly significant. Beef is confirmed as the dominant commodity in the red meat market, having cross-price flexibilities with mutton and pork of 0,30 and 0,20, respectively. All goods other than pumpkins are shown to be normal and fruits and vegetables (having many substitutes) are shown to be demand elastic. All products are normal goods, with the exception of pumpkins (income flexibility of −0,74), which are inferior. Apples and pineapples were found to be the dominant fruits an...
ECONOMETRIC ESTIMATION OF THE DEMAND FOR MEAT IN SOUTH AFRICA
In this study the demand relations for meat in South Africa are estimated and interpreted. Two demand model specifications, namely the Rotterdam and Linearized Almost Ideal Demand System (LA/AIDS), were estimated and tested in order to determine which model provide the best fit for South African meat data. Tests for separability included an F and Likelihood ratio version. Both tests rejected the null hypothesis of weak separability between meat, eggs and milk as protein sources, indicating that the demand model for meat products should be estimated separately from eggs and milk. Consequently, separability tests between the four meat products fail to reject the null hypothesis, confirming that the four meat products should be modelled together. According to the Hausman exogeneity test, the expenditure term is exogenous. As a result, a Restricted Seemingly Unrelated Regression (RSUR) was used to estimate both models. Annual time series data from 1970 to 2000 were used. Both models were estimated in first differenced format, whereafter the estimated parameters were used to calculate compensated, uncompensated and expenditure elasticities. In a non-nested test, the Saragan's and Vuong's likelihood criterion, selected the LA/AIDS model. In terms of expected sign and statistical significance of the elasticities, the LA/AIDS also proved to be more suitable for South African meat data. Although the magnitudes of most own price and cross-price elasticities were significantly lower than previous estimates of demand relations for meat in South Africa, several reasons, including estimation techniques and time gaps, were offered as explanations for these differences. The uncompensated own price elasticity for beef (-0.7504) is the largest in absolute terms, followed by mutton (-0.4678), pork (-0.36972) and chicken (-0.3502). In terms of the compensated own price elasticities, which contain only the pure price effect, pork (-0.30592) was the most elastic, followed by mutton (-0.27713), chicken (-0.1939) and beef (-0.16111). The expenditure elasticities of beef (1.243) and mutton (1.181) are greater than one, indicating that beef and mutton are luxury goods in South Africa. The expenditure elasticity for beef is the most elastic; indicating that South African consumers as a whole, will increase their beef consumption as the total expenditure on meat products increase.
Automatic classification of TV news articles based on telop character recognition
The purpose of this study is to develop a multimedia database system for TV news video data. TV news video data consist of speech, characters and images. In this study, telop characters are recognized and given to the news articles as indices for classification. At first, telop frames which include telop characters are detected and then the telop characters are extracted and recognized. Through morphological analysis of the recognized telop characters, keywords are extracted which consist of more than two characters. Their keywords are used as indices to classify the TV news articles. We carried out experiments for 30 days of NHK 5 minutes news and obtained 95.4% telop character extraction rate, 81.4% character recognition rate and 83.8% article classification rate. We improved the article classification rate by 43.4% through character recognition improvement from 44.1% to 81.4%.