Industrial organisation with development spending -The Nation

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In Pakistan or for that matter in any developing country, one of the failings that are often pointed out is the failure to achieve transparency and efficiency in government spending (optimal results against the funds being spent). There has been a lot of talk of private-public partnerships (PPP) and how this can transform results and delivery, but such initiatives on a wider scale have not really gained much ground, because either the bureaucracy lacked the will to let go of its control and interest or simply because there are just not enough interested local companies with the right capacity and an inherently accountable corporate governance structure that can be entrusted with large government spending(s)—After all theoretically, it is the tax payers’ money; Right? Anyway, it is rather ironic that it is in fact in the developed countries that this subject is gaining a lot of ground where the endeavour is to either form a credible PPP to achieve the desired efficiencies in development work or to bring private sector workings to the public sector, meaning combining private sector’s industrial organisation with government’s development spending. A noteworthy example could be the work and teachings of Professor Jim Levinsohn at Yale. While surely the opportunities in somehow pairing the two fields can be huge, however, combining industrial organisation and development can never be easy. For one the very approach to industrial organisation (IO) and development spending (DS) hold a different set of beliefs. IO tends to be very empirically driven with a huge reliance on micro data from all facets, plant, product, consumer, market, competitive countries etc, whereas, in DS the optimal way points to the rise of Randomnistas (Proponents of randomised trials as the optimal form of research) who rely primarily on the random assignment of units (e.g. people, schools, villages, etc.) to the intervention or control groups; in another word: RCT. A randomised controlled trial (RCT) is an experimental form of impact evaluation in which the population receiving the program or policy intervention is chosen at random from the eligible population, and a control group is also chosen at random from the same eligible population. It tests the extent to which specific, planned impacts are being achieved. The distinguishing feature of an RCT is the random assignment of units (e.g. people, schools, villages, etc.) to the intervention or control groups. One of its strengths is that it provides a very powerful response to questions of causality, helping evaluators and programme implementers to know that what is being achieved is as a result of the intervention and not anything else.

Now some of the data in both disciplines may be the same or perhaps even be overlapping in many cases, but essentially modern analysts opine that over time, the bigger problem is that the two fields have each gone overboard in terms of partiality towards a particular methodological bent. In DS, the RCT has become an obsession and on the other hand in IO the very methodologically driven ways often foray into policy-irrelevant questions. Although, of late, researchers and academics are starting to step back from ever more structural approaches to ever less ordinary questions and are instead finally starting to re-examine some interesting issues; and this naturally gives hope. But there is still a long way to go to bridge this divide and ultimately it is this very rigidness that governments need to overcome, if they truly want to reap the benefits of formulating successful PPPs or in optimally incorporating industrial organisation efficiencies in development spending.

So, what is the way forward? Professor Levinsohn believes that going forward one of the real avenues for productive work is in using RCTs to nail down key behavioural parameters that can then be used in a more structural approach to investigate interesting policy issues. This represents the sort of melding, which can be both very interesting and productive. The challenges to achieving this though remain quite a few, especially in the developing countries—as touched upon earlier—since in most of them there just are not that many bigger and reliable firms that can be tapped. But then again, on the flip side, this also presents a huge opportunity for governments who are willing, to first comprehend and understand the concept, and thereafter to in-turn be able to drive entry of incumbent firms in the development sector by helping them prepare in a way where they can become that desired bridge in linking IO with DS in an economy. In this sense, the opportunity in developing countries far outweighs the one in developed countries and can be a fantastic case to unleash inter-sector synergies that also lead to healthy cum enhanced competition in a country’s economic setting. To conclude: in order to see the whole thing through it will be important that governments, such as Pakistan, do not rely on simply using off-the-shelf methodologies in IO or DS, but instead do their own due diligence suited to the local ground realities in order to find the most appropriate route in linking the two domains, and the one that better fits a country’s own peculiar needs.

A word of caution being to not deliberate too much on a project, once a decision has been reached, because needless small field-experiments or unnecessarily extended governance cum oversight structures only cause delays and confusion; often resulting in missing the moment of opportunity. The writer has always recommended ideally a 5 members apex board for the sake of clarity and speed. We here in Pakistan so far have not really seen any serious thinking or efforts in this regard and one can only hope that in the coming days a few key ministries (finance, industries and planning) can proactively combine to meaningfully engage credible corporate captains to see how work on linking industrial organisation with development spending can be taken forward in national interest.