Comparing US gross domestic product to the sum of measured payments to labor and imputed rental payments to capital results in a large and volatile residual or “factorless” income. We analyze three common strategies of allocating and interpreting factorless income, specifically that it arises from economic profits (case Π), unmeasured capital (case K), or deviations of the rental rate of capital from standard measures based on bond returns (case R). We are skeptical of case Π because it reveals a tight negative relationship between real interest rates and economic profits, leads to large fluctuations in inferred factor-augmenting technologies, and results in profits that have risen since the early 1980s but that remain lower today than in the 1960s and 1970s. Case K shows how unmeasured capital plausibly accounts for all factorless income in recent decades, but its value in the 1960s would have to be more than half of the capital stock, which we find less plausible. We view case R as most promising as it leads to more stable factor shares and technology growth than the other cases, though we acknowledge that it requires an explanation for the pattern of deviations from common measures of the rental rate. Using a model with multiple sectors and types of capital, we show that our assessment of the drivers of changes in output, factor shares, and functional inequality depends critically on the interpretation of factorless income.

中文翻译：

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无因素收入的会计处理

将美国国内生产总值与对劳动力的可衡量支付和对资本的推算租金支付的总和进行比较，会导致大量且不稳定的剩余收入或“无因素”收入。我们分析了分配和解释无因素收入的三种常见策略，特别是它来自经济利润（案例 Π）、未衡量的资本（案例 K）或资本租金率与基于债券回报的标准衡量标准的偏差（案例 R） . 我们对案例 Π 持怀疑态度，因为它揭示了实际利率与经济利润之间的紧密负相关关系，导致推断因子增强技术的大幅波动，并导致利润自 1980 年代初以来有所上升，但今天仍低于1960 年代和 1970 年代。案例 K 显示了近几十年来未计量的资本如何合理地解释了所有无因素收入，但它在 1960 年代的价值必须超过资本存量的一半，我们认为这不太可信。我们认为案例 R 最有希望，因为它比其他案例带来更稳定的要素份额和技术增长，尽管我们承认它需要对与租金率常用衡量标准的偏差模式进行解释。使用具有多个部门和资本类型的模型，我们表明我们对产出、要素份额和功能不平等变化的驱动因素的评估在很大程度上取决于对无要素收入的解释。我们认为案例 R 最有希望，因为它比其他案例带来更稳定的要素份额和技术增长，尽管我们承认它需要对与租金率常用衡量标准的偏差模式进行解释。使用具有多个部门和资本类型的模型，我们表明我们对产出、要素份额和功能不平等变化的驱动因素的评估在很大程度上取决于对无要素收入的解释。我们认为案例 R 最有希望，因为它比其他案例带来更稳定的要素份额和技术增长，尽管我们承认它需要解释与租金率常用衡量标准的偏差模式。使用具有多个部门和资本类型的模型，我们表明我们对产出、要素份额和功能不平等变化的驱动因素的评估在很大程度上取决于对无要素收入的解释。