Modules



The module 5 corresponds to the Fiscal, Financial and Economic Analysis (FFEA) of LAPs which contains elements of the three main modules.

Module 5: Fiscal Financial and Economic Analysis (FFEA)

The F-CBA at household level

As shown in the flow diagram, the cause-effect chain explaining the generation of additional financial revenue or flows for beneficiaries of RCT processes is long, and it is difficult to isolate the effect of the project on obtaining these impacts. In this case the increase in property value, as mentioned for the economic CBA, cannot be used because it does not represent a financial flow for the beneficiaries.

If conditions existed for carrying out the F-CBA at household level, a survey would need to be applied to a representative sample of households to establish the baseline (ex ante) and then another survey in the ex post phase. Using the quasi-experimental evaluation method (see module 4) or the double difference method, the net revenue obtained by beneficiary households due to the effect of the project would be estimated.

To do this, the following would be compared:

  • First difference: the difference in revenue for beneficiary households, before and after RCT processes;
  • Second difference: the difference in revenue for a comparable control group of households (which were not beneficiaries but were also in a situation of insecure tenure) ex ante and ex post.

Example

Example

Very simply and as an example, how to evaluate a possible increase in revenue for households which received a title through the RCT processes of the LAP is demonstrated.

- To carry out this evaluation, surveys were set up ex ante (baseline) and ex post, at the end of the project.
- Random sampling was performed considering a treatment group representing households which received a rural title in the LAP, in an area without access to irrigation, and a control group whose members were in the same situation but without access to the project benefits. Further details on setting up a sample are available in the Guide to carrying out a household survey (see module 4).
- At baseline, the group of beneficiary households had an average revenue of USD 600 per hectare and per year, while the control group had a revenue of USD 780 per hectare.
- At the survey carried out at the end of the project, the control group had an average revenue per hectare of USD 810, while for the treatment group it was USD 740.
- By applying the double difference statistical method, the treatment group was found to have obtained on average an incremental revenue of USD110/ha compared with the control group.

The following graph shows how to use the results of a household survey on revenue.


Graph: Evaluation of variations in revenue attributable to the LAP using the double difference method

Graph: Evaluation of variations in revenue attributable to the LAP using the double difference method

A

Treatment group in ex ante situation

Average revenue of the sample of households which were eligible to benefit from RCT processes (RCT or treatment group in ex ante situation)

B

Treatment group in ex post situation

Average revenue of the sample of households which benefited from RCT processes at the end of the project (treatment group in ex post situation)

C

Control group in ex ante situation

Average revenue of the sample of households with similar characteristics to the group eligible to benefit but which will not receive the benefits (control group ex ante situation)

D

Control group in ex post situation

Average revenue of the sample of households with similar characteristics to the group eligible to benefit from RCT processes (ex ante situation)

E

Counterfactual scenario applied to the treatment group

Projection of the increase in revenue in relation to the control group applied to the treatment group. This is the reference that allows determination of the difference in revenue that can be attributed to the project

DD

Difference in revenue attribuable to the project

This is the difference in revenue in the treatment group that can be attributable to the project, because the comparison is made between households with and without LAP support

More simply, the projection of the net differential revenue of households attributable to the project would then be used to calculate the IRR and NPV.

For further information on this type of evaluation, also see the Guide to the evaluation of impacts at family level and the World Bank’s Guide to the evaluation of impacts on property rights1

Difficulties measuring incremental revenue flows

However, and as explained in Module 4, in practice the measurement of the increase in net revenue at household level is complex and not always reliable because:

  • The cause-effect chain which connects the strengthening of tenure rights to the generation of revenue is long and may require a longer period than the project cycle and/or special conditions that mean that some families can realize benefits while others cannot (because their properties are better located, because the household members have greater experience in business, etc.);
  • The measurement of family revenue, in particular in a rural setting, is a complex exercise because members may have different sources that are subject to change from year to year due to production cycles and also to migrations;
  • In an ex ante situation, it may be difficult to obtain the necessary information to find out who will be potential beneficiaries of RCT processes (because there is often no legal diagnosis of tenure) and thus to be able to set up a sample that will really be representative of the set of households that are LAP beneficiaries.

For this reason and as mentioned in Module 4, it is advisable to carry out an evaluation at household level with an experimental or quasi-experimental type design, which reliably collects intermediate indicators useful for measuring changes in line with the causal chain of RCT processes:

  • Access to funding sources (in particular mortgage loans where land is used as collateral)
  • Access to public services and infrastructure
  • The perception of security of tenure
  • The perception of increased property value

A further alternative given the complexity of applying surveys at household level and using quasi-experimental or experimental methods can be the creation of case studies.
Though usually limited by the number of observations, case studies can generate qualitative measurements useful for understanding the phenomena contributing to or generating obstacles to households having access to the benefits of RCT processes. This type of evaluation is particularly recommended when LAPs are midway through their implementation.

Notes

1 Conning, J.& Deb, P. (2007).