Manager From To Sector Country Client Type
Per Kirkemann 29.08.2011 14.10.2011 Transport Tanzania Danida  

 

Road TanzThe current Study analyses the economy-wide macroeconomic impact of decisions made by the Tanzanian Roads Fund Board (RFB). More specifically, the current Study has the dual purpose of analysing the macroeconomic consequences of: 1) changes in the overall RFB budget allocation; and 2) changes in the existing 70/30 percent allocation formula between national and LGA roads. The assessment methodology relies on a macroeconomic Computable General Equilibrium (CGE) model. The CGE model is used to assess eight road agency budget scenarios, which were established in the previous "Study on Criteria for Roads Fund Allocation to Different Classes of Roads in Tanzania, October 2011".

SSATP's RONET road transport model was used to establish eight road agency budget scenarios: Optimal+2/+1, Optimal, Optimal-1/-2/-3, Do Minimum, and Do Nothing. The key challenge is to choose the budget scenario, which provides an appropriate road quality standard at an affordable level and/or identify the road quality standard with the largest macroeconomic benefits. It is always desirable to choose a higher road quality standard. For example, policymakers may decide to increase the road agency budget, and thereby adopt a higher road quality standard than today (for example by allowing RFB to adopt RONET's Optimal-1 standard instead of the current standard which resembles Optimal-2). The adoption of a higher road quality standard would reduce driving costs for road users, but at the expense of increased roadwork costs for road agencies.The net impact of the reduced user costs and increased agency costs determines whether such change results in a positive or negative macroeconomic impact.


The current Study shows that the decision criterion for choosing the preferred scenario matters. This has implications for the recommended RFB budget allocation and the recommended allocation formula between national and LGA roads. The previous study recommended the 'Optimal' Scenario on the basis of the standard RONET decision criterion (minimum sector-wide society costs), while the current study recommends RONETs Optimal-1 Scenario (or an intermediate scenario between Optimal and Optimal-1) since this is economically optimal based on a standard investment decision criterion (i.e. the economic return is greater than opportunity cost).


The current Study adds another important dimension to the previous "Study on Criteria for Roads Fund Allocation to Different Classes of Roads in Tanzania". While the previous RONET Study focused on measuring sector-wide impacts, the current CGE Study focuses on economy-wide impacts. This is important since better roads tend to benefit not only road users, but also adjacent communities along the roads. Better roads make it cheaper to transport goods and persons around, and this creates additional income elsewhere. For example, better roads may increase rural accessibility and thereby allow smallholders to get better prices for their crops. The economy-wide CGE model allows for capturing these kinds of effects.

Furthermore, the CGE model allowed for computation of macroeconomic indicators such as society income (GDP) and poverty indicators. These are crucial indicators for policymakers (e.g. for informing the poverty and growth strategy). If the current RFB budget were to be continued, this would allow RFB to fund the implementation of RONETs Optimal-2 Scenario. Maintaining this road quality standard increases GDP by 3.4% (NPV over 20 years) and reduces monetary poverty by 11% (compared with the Do Nothing Scenario). If instead RFB's budget were increased to fund RONETs Optimal-1 or Optimal Scenario, this would raise GDP by 4.5%-4.8% and reduce monetary poverty by 14%-15%. These two scenarios give rise to the largest macroeconomic impacts and would therefore be preferred if additional funding was freely available or available on acceptable terms.

The problem is that funds may not be available on acceptable terms. This is because GoT has an opportunity cost of funds, which is determined by alternative investment opportunities. Our calculations suggest that a marginal increase in RFB's budget to fund RONETs Optimal-1 Scenario would result in a long-term economic rate of return of 20% p.a., while a marginal increase in RFB's budget to fund RONETs Optimal Scenario would only yield a long-term economic rate of return of 12% p.a. Since GoT's opportunity cost may well be in-between these economic returns, it is highly likely that RONETs Optimal-1 Scenario, or an intermediate strategy in-between Optimal and Optimal-1, would be preferred according to the investment decision criterion. Hence, RONET's Optimal-1 Scenario is more economically optimal than the Optimal Scenario.

Interestingly, the politically feasible road agency budget (including historical GoT funding of rehabilitation tasks, and the proposed expansion of the RFB revenue base for maintenance and spot improvements) lies in-between the funding requirements for RONET's Optimal Scenario and Optimal-1 Scenario. While RFB's proposed expansion of its revenue base up to USD 320mn per year will not be sufficient to meet the funding requirements for RONETs Optimal Scenario, this funding level will be between the Optimal Scenario and the Optimal-1 Scenario. This is so even though RFB proposes to introduce spot improvements as a substitute for planned rehabilitation – something which may ensure accessibility in the short term, but which is also likely to be inefficient and costly in the long-term.

In sum, if the opportunity cost of Tanzanian investment funds lies in the range of 12%-20% p.a. (which is highly likely), it would be economically optimal for the Tanzanian policymakers to follow RFB's recommendation in order to expand their revenue base to USD 320 million and allow RFB to undertake rehabilitation-related tasks, and at the same time to task them with maintaining a road quality standard in-between the Optimal Scenario and Optimal-1 Scenario. The expanded scale and scope of RFB operations has the potential to ensure predictable and sustainable maintenance, and it may have the added benefit of acting as a catalyst for donor commitments to fund the much-needed rehabilitation of the road network.

As the Ideal Situation budget covers the Optimal Scenario's maintenance budget and compensate partly for the lack of rehabilitation through spot improvements, a LGA funding share of about 35%+ in the medium-term as well as in the long-term would be a feasible solution. A smaller budget than the Ideal Situation budget would increase the funding share for LGA roads. If in the long-term, RFB were mandated to take the full responsibility for rehabilitation tasks – provided that the corresponding funding would be made available – or funding were provided from the consolidated budget to cover planned rehabilitation costs, the analyses suggest to adopt 35%+ in the medium-term, which could then be stabilized at around 31%-33% in the long-term.

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