While using detailed firm-level data from the private business sector, this study identifies two empirical puzzles: (i) returns-to-scale (RTS) parameter estimates rise at higher levels of data aggregation and (ii) estimates from the firm level suggest decreasing returns to scale. The analysis shows that, although consistent with rising estimates, neither entry/exit nor the Basu-Fernald [Returns to scale in U.S. production: estimates and implications. Journal of Political Economy 105, 249-283) aggregation-bias effect drives this result. Rather, rising and too low RTS estimates seem to reflect a mixture of random errors in factor inputs at the firm level. It turns out, in fact, that a 7.5-10 percent error in labor (hours worked) can explain both puzzles.
