Firm size and the predictive ability of quarterly earnings data

We present evidence on inter-firm differences in the predictive ability of quarterly earnings data for a sample of 109 New York Stock Exchange firms. The sample consisted of large, medium, and small firms after deletion of nonseasonal and volatile growth and inconsistent strata membership firms. Although the structure of the best fitting time-series models was constant across firm-size strata, we did find significant differences in the autoregressive parameters of the Foster and Brown and Rozeff ARIMA models across firm-size strata. One-step-ahead quarterly earnings forecasts were generated by a set of best fitting time-series models. A repeated measure multivariate analysis of variance design indicated that predictive ability differed on the basis of size at the .012 level. Tests also indicated that largeand medium-size firms generated one-step-ahead forecasts that were significantly more accurate than smaller firms at the .05 level. We obtained similar predictive findings on the significance of the size-effect in a supplementary analysis of the nonseasonal and volatile growth and inconsistent strata membership firms. T HE time-series properties and predictive ability of quarterly earnings data have long been topics of interest to financial accounting researchers. The focus of early work in time-series research was on the development of parsimonious models for quarterly earnings such as those popularized by Foster [1977], Griffin [1977], Watts [1975], and Brown and Rozeff [1979]. Motivation for such time-series work has been the notion that a general form seasonal model, identified from cross-sectionally derived average sample autocorrelation functions (SACFs), is sufficiently robust to represent the quarterly earnings data of firms without resorting to more complex, firm-specific alternatives. However, more recent work by Lorek and Bathke [1984] provides evidence that the quarterly earnings of certain firms behave in a nonseasonal manner systematically different from that suggested by the parsimonious models.1 This raises the issue of whether systematic differ' All three parsimonious models contain either seasonal differencing and/or seasonal moving average