such variation to country, sector and year variations in institutions. Even more simply, the immediate temptation is to test this prediction implicitly by examining the rank ordering of firm turnover and productivity dynamics across countries and to match that rank ordering up with priors about the rank ordering of market structure and institutions across countries.

However, further reflections suggest that the predictions regarding distortions in market structure and institutions are in fact not so clear. The reason is that distortions may affect the reallocation dynamics on different margins in a variety of ways. For example, artificially high barriers to entry will lead to reduced firm turnover and to a less efficient allocation of resources. But given the high barrier to entry (and in turn the implied ability of marginal incumbents to increase survival probabilities), the average productivity of entrants will rise while the average productivity of incumbents and exiting businesses will fall. Similar predictions apply to policies that subsidize incumbents and/or restrict exit in some fashion. The point is that institutional distortions might yield a larger gap in productivity between entering and exiting businesses.

Alternatively, some types of distortions in market structure and institutions might make the entry and exit process less rational (i.e., less driven by market fundamentals but more by random factors). Such randomness may be associated with either a higher or lower pace of churning. Pure randomness would, in principle, increase the pace of churning but the random factors might be correlated with other factors (e.g., firm size) and thus the impact would be to distort the relationship between churning and such factors with less clear predictions on the overall pace of churning. In any event, such randomness would imply less systematic differences between entering, exiting and incumbent businesses – in the extreme when all entry and exit is random there should be no differences between entering, exiting and incumbent businesses.

Another related problem is that a business climate that encourages more market experimentation might have a larger long run contribution but a smaller short run contribution from the creative destruction process. That is, the greater market experimentation may be associated with more risk and uncertainty in the short run so that it is only after the trial and error process of the experimentation has worked its way out (through learning and selection effects) that the productivity payoff is realized. Thus, a business climate that encourages market experimentation might have a lower short run contribution from entry and exit but a higher long run contribution from entry and exit.

In short, the gap between the productivity of entering and exiting businesses is not by itself sufficient to gauge the contribution or efficiency of the creative destruction process. In addition, different types of distortions might be acting simultaneously in a country. It might be that different policies act to subsidize incumbents (preferential treatment for incumbents), other policies artificially increase the barriers to entry (poorly functioning financial markets and/or regulatory barriers), while other policies make exit more random for some types of businesses (e.g., poorly functioning financial markets for young and small businesses). As such, there might be too little churning on some dimensions and too much on others, the gap between entering and exiting businesses might be too large on some margins and too small on others.

All of these remarks suggest the need for both caution and creativity in using the firm demographic and productivity dynamic statistics that we analyze below. On the one hand, even this brief discussion makes clear that simple cross country comparisons on specific dimensions may be misleading or inadequate. On the other hand, this discussion suggests that creativity needs to be used to examine the connection between the churning and productivity dynamics along multiple dimensions. In like fashion, this discussion helps make clear why it is likely important to exploit variation beyond simple country variation but instead exploit variation on 6