‘Not Even Wrong’
Chapter 3: Simulation studies, the aggregate production function and the accounting identity
‘Not Even Wrong’
In the previous chapter, it was shown why the existence of an underlying accounting identity is responsible for the good statistical fits of aggregate production functions, even though the latter in all probability do not theoretically exist. In this chapter, we consider some simulation studies that illustrate the problems associated with the estimation, and interpretation, of aggregate production functions. The advantage of simulation experiments is that they allow us to know precisely what the underlying technological structure of the economy is. If the Cobb–Douglas production function gives a good fit to the aggregated data when we know that either the underlying technology of the firms in no way resembles the Cobb–Douglas production function, or, if it does, the conditions for successful aggregation are (deliberately) violated, then this should at least give us reason to pause for thought. We start with a simulation exercise that we undertook to determine what precisely conventional regressions of production functions using value data are actually estimating. We also consider the extent to which we can be confident that estimates of total factor productivity (TFP) are approximating the rate of technical progress, or the rate of increase inefficiency of an economy.
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