English: number or % of targeted [specify: households / businesses] that increased their income from [specify the activity] as a result of the provided assistance
French: nombre ou % de [spécifier: ménages/ entreprises] ciblé(e)s ayant augmenté leur revenu tiré de [spécifier l’activité] grâce à l’assistance fournie
Portuguese: número ou % de [especifique: famílias / empresas] -alvo que aumentaram sua receita de [especifique a atividade] como resultado da assistência prestada
Czech: počet či % cílových [určete: domácností / obchodníků], které si díky poskytnuté podpoře zvýšily příjem z [určete aktivitu]
What is its purpose?
The indicator assesses the number or proportion of target households (or businesses) which - thanks to the provided assistance - increased their income from a specific income-generating activity. This is a common indicator of income-generating interventions. It can be amended to measure whether the increase reached a pre-defined minimum level (for example, “at least by 20%”).
How to Collect and Analyse the Required Data
Collect the following data by conducting individual interviews with a representative sample of the target group members:
RECOMMENDED SURVEY QUESTION (Q) AND POSSIBLE ANSWERS (A)
Introduction: In this survey, we are asking people about the income they generate from [specify the income generating activity]. People often openly share with us both their successes and failures. I would like to ask you to respond to the following question as honestly as the other respondents did. There are no right or wrong answer, we just want to understand your true experience. All the information you tell me will be treated in a confidential way.
Q1: As a result of [specify the provided assistance], would you say that your financial income from [specify the supported activity] has increased, decreased, or remained the same?
3) remained the same
4) does not know / does not want to say
If you want to measure whether the income has changed by a certain pre-defined level (e.g. increased by at least 20%), proceed with the following steps (proceed only if the previous answer is “increased”).
If the respondent is well-educated and finds it easy to work with percentages:
Q1: Now, I would like you to compare the income you earned from [specify the livelihoods activity] before you received the assistance with the income you earn now. How big is the difference?
1) approximately ____ %
2) is not able or willing to say
If the respondent is illiterate:
Use participatory methods to estimate the change in the family income. For example, using 10 stones representing the household's income from the supported activity before the support and asking the respondent to add or remove some stones depending on to what extent their income from the supported activity has increased or decreased. When you analyze the data, each added stone represents a 10% increase in the respondent’s income from the supported activity (100% divided by 10 stones = 10%). If you use this method, ensure that the data collectors are able to explain to the respondents the meaning and the value of the stones. Test this method in your target area before you use it.
To calculate the indicator’s value, use the following guidance:
1) If you want to measure the proportion of respondents who increased their income (irrespective of by how much): Divide the number of respondents who increased their income by the total number of respondents (exclude those who could not or did not want to respond). Multiply the result by 100 to convert it to a percentage.
2) If you want to measure the proportion of respondents who increased their income above the pre-defined level: Divide the number of respondents who increased the income above the pre-defined level by the total number of respondents (exclude those who could not or did not want to respond). Multiply the result by 100 to convert it to a percentage.
Disaggregate the data by the type of the supported livelihood activity and other relevant criteria.
1) In the case the intervention supports people in establishing new livelihoods activities, you will have to change the indicator to “number or % of targeted [specify: households / businesses] that increased their household income as a result of the provided assistance” – i.e. instead of asking people about the changes in their income from a specific activity, you will enquire about changes in the overall household income (in the case you work with illiterate respondents, the 10 stones will represent the total household income before the intervention).
2) One of the important benefits of participatory methods (e.g. use of stones) is the way in which the information can be visually displayed and discussed, which helps with the triangulation of the data, and improves its accuracy. Where possible, try to involve various household members in this exercise (e.g. both the husband and the wife), so that they can help verify (and amend) the approximate income changes that are being suggested.
3) The ’10 stone method’ can also be utilised to provide insights into proportional changes in total household income (to better understand broader household economy trends that may be occurring, and to know if an increase in income from one activity, has resulted in a decline from other activities). For this type of assessment, the household is provided with 10 stones and asked to show where the proportion of their total income came from before the intervention commenced (broad categories can be used, e.g. livestock, crops, off-farm income etc), and now, so that some analysis can be done on the changes and proportions of overall household income
4) Since income measurement is prone to many complications and biases, the indicator does not aim to measure the exact changes in the respondent’s income. That is why it assesses only approximate changes, focusing primarily on whether the pre-defined minimum increase was achieved or not.
5) When setting the indicator’s target value, be realistic – even 20% increase can be a very good achievement.
6) If the supported income generation activities are prone to seasonal differences in the levels of generated income (e.g. as is the case with agriculture), ensure that the baseline and endline data is collected at the same time of year.