# **Box 2: The Methodology and Lessons Learned**

The approach in Section IV is based on the **framework of “growth diagnostics”** developed by Haussman, Rodrik and Velasco (2005). It seeks to explain some key features of the economy by going through the decision tree on the right. Are firms constrained by finance or by low returns? If finance, is it because of local or international access issues? Etc.

|**Low private investment & innovation**<br>**Low return to economic activity**<br>**High cost of finance**<br>**Coordination**<br>**externalities**<br>**Information**<br>**externalities (self**<br>**discovery)**<br>**Low appropriability**<br>**Market**<br>**failures**<br>**Low social**<br>**returns**<br>**Government**<br>**failures**<br>**Macro risks**<br>**(financial, monetary;**<br>**fiscal; instability)**<br>**Micro risks**<br>**(property rights;**<br>**corruption; taxes)**<br>**Bad**<br>**infrastructure**<br>**Low**<br>**human**<br>**capital**<br>**Bad**<br>**international**<br>**finance**<br>**Bad local**<br>**finance**<br>**Poor**<br>**intermediation**<br>**Low domestic**<br>**savings**<br>**Bad**<br>**geography**|
|---|

As noted in Haussman, Klinger and Wagner (2007), this requires detective work to navigate the decision tree. Here is a list of some of the key ingredients used in this paper:  _Comparisons across countries_ are instructive, especially if the level of development is factored in (see for instance Figure 7). Comparing with countries under a sustainable path of development, as identified by the Growth Commission is also very instructive (e.g. Figure 5).

 The general principle that existing firms should be making _efforts to overcome the most binding constraints_ is also insightful. In particular, coupled with a political economy analysis, this approach generated a good understanding of the growth of the garment sector compared to other sectors (Box 1). The political economy aspect is critical since a lot of these efforts are likely to be related to rents. Firm-level data was also useful to understand these efforts to overcome binding constraints – with, however, the usual caveats with respect to perception data from firms.

 _Simple economic analysis_ generates also useful insights. In particular the diagnostic on the scarcity of finance is difficult. But the predicted correlation between interest rates and investment rates (e.g. a negative correlation would suggest that the equilibrium is moving along the demand curve, i.e. being constrained by the supply of credit) helped diagnosed this branch of the decision tree (Figure 10).

 Diagnosing the market failures side of the decision tree has proven hard. In our case, significant analysis on _the product space of exports and value-chains_ generated important insights (e.g. limited self-discovery; collective action failures) to make the case that this was indeed an important constraint.

What are the **lessons learned** from the exercise?

First the exercise confirms the value of the _discipline_ of looking at binding constraints. It is easy in a poorcapacity, weak-governance environment like Cambodia to make a case that everything is a constraint. Yet, this view is at odds with the record of growth of the past decade. And this view would also not be operational – given Government’s own capacity constraints.

Looking for one or few binding constraints is however _politically counterintuitive_ . First, in the Cambodian, Buddhist context, there is a view that everything should be improved at the same time, a theme that echoes that of a “balanced growth” path. Second, given the uncertainties (conclusions are often based on signals or hints, rather than being firm), the rapid changes of the economy, and the time it will take to address constraints that might emerge only in the future (e.g. skills), it would be unwise to “put all one’s eggs in the same basket”. This suggests a process-oriented diagnostic, that enables adjustments over time. Third, whether within Government or a multi-sector organization like the World Bank, radical prioritization at the expense of a some sector or issue is challenging.

Another lesson is the value of looking at _sectoral constraints_ (see for instance on agriculture in Box 3). This is first useful to assess whether the economy-wide diagnostic is robust enough. It might also help to further prioritize the analysis, to focus on constraints that are more binding to pre-identified “priority sectors” or to sectors that are consistent with the country’s comparative advantage: while it might be desirable to not identify such sectors, it might be a pragmatic way to prioritize policies (provided the identified sectors are not defying the country’s comparative advantage, see Lin, 2008).

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