Dongling Chen

Fundamental Similarities in Consumer Behaviour

Diversities and similarities in international consumption patterns are highlighted. A large body of data is used to identify cross-country consumption differences and to understand these in terms of the familiar utility-maximizing framework, in which observed differences in prices and incomes play the key role. Taken as a whole, the results reveal a surprising degree of similarity in international consumption patterns and support the idea that tastes are constant, at least with respect to broad commodity groups.

Forecasting steel demand in China

Abstract Chinese steel demand will grow from 60 million tons in the late 1980s to 100 million tons by the year 2000. The Chinese steel market will then rank equal with markets in Japan, the USA and the European Community. Chinese steel demand is predicted to stay below the level of 1988 until 1992. After a strong recovery in 1992-93, steel demand will then grow at 5% per annum in the second half of the 1990s. These forecasts are generated by a vector autoregressive model of the Chinese economy. The VAR models the joint serial correlation between output, price level, money stock, investment and steel.

Affluence and Food: A Simple Way to Infer Incomes

Accurate and timely measures of cross-country real incomes are still a rarity. As the share of expenditure devoted to food is readily available, we use of Engel’s law in reciprocal form to measure affluence. Analysis of real income data for the OECD countries indicates that this approach is viable. To recognise the role of uncertainty in the analysis, we present the results in the form of stochastic cross-country income comparisons.

The matrix approach to evaluating demand equations

As there is a plethora of demand models, which one should be used to estimate income and price elasticities? The paper sheds light on this important practical problem by developing a matrix approach to simulating (MAS) demand equations to analyse their performance under idealized circumstances. Artificial data on the dependent variable are generated by one model, and these are then used for the estimation of another model. As an illustrative application, using four popular models, a 4 × 4 matrix is generated which gives all pair-wise comparisons. The performance of the models is then evaluated on the basis of the quality of the income and own-price elasticity estimates.