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One of the productions planning models economists have used for the past four decades is the production-smoothing model. The model's conclusion is simple: if cost functions are convex, under certain conditions, firm's production plans may show smaller variability than the firm's sales. This is a result of the first-order condition for cost minimization over the production-planning horizon. In a 1986 paper Blinder raised doubts regarding the ability of the production-smoothing model to explain the observed data. Some researchers (e.g. Ramey, Journal of Political Economy 99(2) (1991) 306) explained the inconsistency between the theory and the data by providing evidence that the cost functions are non-convex. In this paper, I point out that the shapes of the cost functions depend on the length of the time horizon under consideration. It is possible that while short-run cost functions are upward sloping, long-run cost functions may be downward sloping. Because the planning horizon for firms facing seasonal demand has been shown to be one seasonal cycle, the short-run cost function, whose shape determines the firm's production plan over the horizon, need to be estimated using single planning horizon data, i.e., a single seasonal cycle. Researchers who use long time series data are, in effect estimating long-run cost functions, the slopes of which may be non-positive. I show, further, that convexity of the production cost function is neither necessary nor sufficient condition for production smoothing to be an optimal plan. Keywords: Convexity; Cost function; Production smoothing

Analysis of the impact of temporal aggregation on inventory decisions such as adjustment policies shows that there exists a significant degree of correlation between the two variables compared. Using real as opposed to hypothetical data proves the above observation. Furthermore, the effect of aggregation has been observed to be negative, that is, it has a downward influence on adjustment speed.

The controversial production smoothing hypothesis, also known as the buffer stock motive of holding inventories, was evaluated using classical econometric and generalized variance bounds tests. Both testing methodologies yielded positive support for the hypothesis in the asphalt, glass container and Portland cement sectors. When the oil burner, beer and printing paper industries were considered, however, little positive evidence was provided by the classical econometric test for beer. The variance bounds test, meanwhile, rejected the hypothesis in the case of oil burners.

Three decision models were evaluated with regard to production and inventory in varying demand conditions. The models, production smoothing, dynamic cost production smoothing and buffer stock, were used in analyzing the asphalt, oil burner, glass container, printing paper, beer and portland cement industries. The production smoothing and buffer stock models were effective and showed significant smoothing in the asphalt, oil burner, glass container and cement industries. The dynamic cost production smoothing model was not as effective due to its relatively low explanatory capability.