guidelines for developing baseline studies

GUIDELINES FOR DEVELOPING BASELINE STUDIES

EXPERIENCES FROM CARE NEPAL

CARE Nepal

May 1998 Jopie Duijnhouwer

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TABLE OF CONTENTS

1. Introduction.........................................................................................4 2. Overall framework ...............................................................................4 3. Why are we collecting baseline information? ........................................5

3.1. Baseline design principles..............................................................6 4. What kind of information has to be collected?......................................8

4.1. Review of the logframe ..................................................................9 4.2. From indicators to information needs ..........................................10 4.3. Collection of general information.................................................11

5. How to collect this information?.........................................................12 5.1. Information collection methods ...................................................12

5.1.1. Review of secondary information ...........................................12 5.1.2. Participatory methods............................................................13 5.1.3. Household survey ..................................................................14 5.1.4. In-depth interviews ...............................................................16

5.2. Linking information needs with methods .....................................16 5.2.1. Putting the pieces together....................................................18 5.2.2. Developing formats ...............................................................21

6. How to analyze this information? .......................................................21 6.1. Consolidation of the data.............................................................21 6.2. Analysis of data from PRA exercises ............................................22 6.3. Analysis of household survey data ...............................................23

Design of a baseline study

1. Introduction In the last two years, CARE Nepal has significantly increased its experience in designing and conducting project-wide baseline studies. This was not the first experience of CARE Nepal in this field, as baseline studies were done as early as 1991 in Bajura. One baseline study focused on health1, the other on home gardening2. After these studies other baseline studies were conducted, but the data were not always analyzed and reports on these studies were not available. In 1995 the Primary Health Care / Population section conducted a comprehensive study in Bajura, Solukhumbu and Mahottari districts3. The recent series of baseline studies started in 1997. The first baseline study was conducted in Bardia (May / June 1997). Since then three other project-wide baseline studies have been conducted in Mahottari (August - September 1997), Bajura (December 1997 - February 1998) and Jajarkot (March - April 1998). Another baseline study for Syangja district is planned for the coming months. These studies have increased CARE Nepal’s knowledge and experience in doing baselines. With this report CARE Nepal wants to consolidate its knowledge and experience on designing, conducting and analyzing baseline studies. Furthermore, this report can serve as guideline to individuals developing new studies. However, it should not be considered as a recipe and the ideas suggested here should be used in a flexible way.

2. Overall framework During the design of a base ine study a number of questions should be answered in a systematic way: 1. Why are we collecting baseline information?

Discusses the reasons why baseline information is collected and to a certain extent which type of information will be collected and the most appropriate method to do this;

1 R. Rajlawat, 1991. PHC Base Line Survey Report. RABNP No. 19. 2 A.R. Giuliano et al., 1992. Home Gardening Baseline Survey Bajura and Mahottari Districts Nepal. 3 Valley Research Group, 1995. CARE / Nepal Family planning Survey in Bajura, Mahottari and Solukhumbu.

2. What kind of information has to be collected? This section elaborates the method used by CARE Nepal of transforming project logframes into defined information needs;

3. How to collect this information? Discussion on the choice of the methodology to be used for information collection, and also the design of the formats to be used during the field work;

4. How to analyze this information? Consolidation and analysis of the data is complex, although it can be simplified if sufficient preparations are taken during the study design.

These issues are closely related. While identifying information needs it is essential to think about the possible methods of data collection and about the inputs required for the proposed methods. A number of these questions (#2 and # 3) can be answered during the design process (either during a workshop with Country Office and project staff or by an individual or small group), but only after some other issues are dealt with (#1).

3. Why are we collecting baseline information? There are good reasons to do a baseline study: most importantly, it allows organizations to measure their progress in achieving their objectives and most donors will demand it. This also makes it possible to learn from both successes and failures. Currently, CARE Nepal is collecting baseline information before new projects are started or enter a new phase and before projects substantially extend their working area. In practice it is not always possible to start information gathering before the project starts, in which case the baseline study is done as soon as possible after the start of activities. The objectives of the baseline studies done so far can be summarized as follows: 1. To gather baseline information related to the objectives and indicators

of the project document, so as to be able to measure progress and also to verify targets and indicators.

2. To deepen the understanding of the problems and opportunities of communities living in the study area;

3. To gain a better understanding of the working area which can lead to refining the planned interventions;

4. To establish working relations with the stakeholders in the working area.

3.1. Baseline design principles After the decision has been made to do a baseline study, certain issues have to be dealt with before the actual design starts. These issues follow: > the scope of the study. In the past many organizations have conducted large scale baseline studies, which covered a large number of variables. Many of these studies are large scale household surveys with huge questionnaires. This type of study can produce a wealth of information, but their scope makes the design, implementation and analysis much more complex and external support will often be necessary. A disadvantage of a very broad study is that a substantial chunk of the information collected may not be relevant for the project. > the focus of the study. This issue is related to the previous one. It is important to remember that the quantity of interesting information that could be collected is almost unlimited, but the quantity that can be collected and analyzed definitely has its limits. Therefore it is necessary to define prior to the study what kind of information should be collected. One of the guidelines that can be used is the logframe which shows which indicators the project wants to achieve. Information directly related to these indicators is necessary to assess whether our project interventions are successful or not (e.g. during mid-term or final evaluations). However additional information can improve the quality of project interventions: it is important to know that most of the adult men in Bajura migrate during four months in winter. It can also produce information to test assumptions made in the logframe, e.g. on women’s workload. > study team composition Another important consideration which has be dealt with beforehand is who will design conduct the study and analyze the information. This can done either by external consultants or by CARE staff (or a combination of consultants and staff). The recent series of baseline studies was done by project and CO staff and with minimal external support. Involving project and CO staff in the process of designing, implementing and analyzing has advantages. It offers an excellent opportunity to increase the insight of staff in the project objectives as well as in the local situation. This is especially the case when the studies include a large number of PRA exercises, which usually yield much qualitative information about the working area and its

population. If the baseline is limited to a household survey, hiring external enumerators would probably be a better option. The study will also benefit from the participation of staff, because they may understand well the project area, both in knowledge of the area and in a better understanding of the local customs and language1. Doing the baseline study with project and CO staff has also certain disadvantages: people who have lived for a long time in the study area may be biased, although this is unlikely at the moment of the baseline. Furthermore the studies are time-consuming and may interfere with regular project implementation. However, the financial possibilities will often decide whether a study can by done by external consultants or should be done as much as possible by CARE staff. > study methodology The choice for a specific type of study methodology (basically Participatory Rural Appraisal (PRA) tools versus household questionnaire) is linked with the objectives of the study, the nature of the logframe (quantitative versus qualitative indicators) and with the study team composition. During the Bardia baseline development workshop the participants compared the characteristics of the two methodologies (see Table 1). The design principles used for the series of studies done so far in CARE Nepal can be summarized as follows:

1. the baseline study is based on information needs derived from indicators in the logframe;

2. additional information is collected if directly relevant to project interventions;

3. a mix of participatory methods and a household questionnaire is used to obtain both quantitative and qualitative data2;

4. the scope of the study is such that data collection analysis and reporting can be done by CARE Nepal staff;

5. obtain reliable data using a method that can be easily replicated; 6. the costs of the baseline study should be reasonable.

1 This is not always the case; because field staff is regularly transfered, they will not all understand local languages or dialects in the beginning. 2 There are arguments to split the baseline study in two parts and to start with a household survey. The results from this survey could then be used to design the qualitative / participatory component, with mostly participatory tools, more focused on “why” issues, problems and opportunities identified during the household survey.

Table 1. Comparison of participative methods and household questionnaire.

participatory methods structured survey questionnaire

flexible / dynamic ; can give information on trends and in-depth information on the causes of the observed trends

static; gives detailed information about one particular point in time

listen to the population top-down high level of participation from community during analysis

community is less involved; they are producers of information

produces qualitative information produces quantitative information does not produce statistically generalizable data; can ‘infer’ only

can be solidly documented; reliability of data can be assessed; generalizable

more emphasis on building rapport with population

rapport is less important; people may feel uncomfortable being asked many questions

can involve both men and women if well-done

can be intimidating for women, especially in very traditional areas

4. What kind of information has to be collected? After choices have been made on the design principles, the logframe indicators have to be translated to information needs. Most of the indicators taken in consideration will be effect and impact level indicators. Output indicators are considered to be services delivered by the project and prior to project interventions these will be zero. There may be some exceptions, e.g. when a project aims at improving existing services. In this case it is necessary to collect information about the current level of services and the perception of the population on the quantity and quality of these services. In addition to this, assumptions at all levels should also be included in the baseline study1.

1 Including information needs regarding assumptions is limited to those which can be measured / assessed at district level, e.g. the availability of market channels for the distribution of improved seeds. Whether the macro-economic situation is stable or not, will not be a part of the baseline study.

Note that this step will be started by CARE after a choice has been made to involve CARE staff as much as possible in design and implementation. When it is decided that the baseline study will be designed, implemented and analyzed by external consultants, the initiative for the rest of the design process will be on the shoulders of these consultants, who can use any of the next steps or propose their own methodology under guidance from CARE and using the parameters of the Terms of Reference.

For Mahottari and Jajarkot the design of the baseline study was done during a workshop with the study team members.This workshop covered the following topics: 1. analysis of the logframe and identification of terms in the logframe

that have to be clarified or defined; 2. identifying information needs based on the project logframe; 3. orientation on the use of different study methods; 4. linking information needs with the most appropriate study methods; 5. sampling methods and sample size; 6. develop work plans for the field study based on the study methods

identified under point 4; 7. develop formats for data collection.

4.1. Review of the logframe The first step of the workshop is a thorough review of the project logframe. All objectives and indicators have to be clear to all the participants of the workshop. Terms, which are ambiguous, unclear and which have not yet been defined in the project document, have to be defined first1. The quality of the effect and output indicators is important in completing this step. If the terms used are well-defined and specific, it is in most cases not difficult to identify the information needed.

1 see for example J.J. Duijnhouwer, 1997. Baseline study for Bardia Buffer Zone Development Project, where a large number of terms used in the Bardia logframe are discussed.

This box illustrates the importance of well-defined terms when defining information needs. In the Bardia logframe indicator 3a is: 3a) 25% of the households owning land and engaged in farming activities within the core project area perform any or a combination of the farm practices promoted by the project by the end of phase I. However, “farm practices promoted by the project” were not defined, which made it impossible to identify the information needs. So, as a first step, the intended practices were specified and only then the information needs could be defined. In the Bajura logframe the indicator on kitchen gardening is more precise: 1a) 40% HHs produce at least 6 different types of vegetables in their kitchen garden over a year and some vegetables exist for at least 6 months per year. Based on this indicator it is relatively easy to identify the information needs: • how many households have kitchen gardens; • what is the variety of vegetables cultivated (in households with

kitchen gardens; • during which months do they actually produce vegetables.

4.2. From indicators to information needs If the indicators are formulated in a clear and unambiguous way and if the terms used are clear for everybody, then the transformation of indicators in information needs should be rather straightforward (an example of this

Table 2. Indicators and information needs for Intermediate Goal # 4 of ajarkot Poverty Reduction Project. J

4) Diversified and increased sources of income. indicators information needs 4a) increased number & value

of (active) sources of income in the project area.

4b) changes in participants

self- perceptions in income. 4c) changed consumption

patterns (as a proxy for income)

> existing sources of income > the range of income generated through these sources of income > market opportunities for (forest) products and traditional skills > perceived change in household socio-economic status > purchase of cooking oil, masala, soap, hair oil, toothpaste during the last three months and year

exercise is given in Table 2). It is important to realize that there are is a lot of information that could be collected. To collect information for the first indicator (4a) a full-fledged socio-economic household survey could be done, which tries to measure all the sources of income, expenditure etc. However, this is not in line the design principles which state that design, field work, analysis and report writing will be done by the available CARE staff. Sometimes it is not easy to come up with information needs, either caused by the phrasing of the indicators (see e.g. indicator 4b) or by technical problems related to collect data. However, indicator 4c gives more problems (see 5.2 for a discussion on proxy indicators). It is, for example, difficult to measure the productivity of crops in many areas, because the correct measurement of the production requires a huge study with complex sampling techniques which measures the production in farmers’ fields during harvest over an extended period of time. Because of the complexity of this type of research the productivity of crops is estimated by asking households about the production of their crops during the last season. An additional question which compares the production of last year with the average production of the five previous years can give a good idea about the production of most of the crops (cross-checking with data collected on food self-sufficiency may give further indications about the reliability of the data).

4.3. Collection of general information Data on the indicators mentioned in the logframe provide a basis for the comparison of the situation at the start of the project and the end of project. However, there is information of a more general nature which is important to gather during a baseline study. Some of this information may be available from secondary sources or from the situational analysis in which case there is no need to gather additional information. Other important general information may not be available and it may be necessary to include these issues in the baseline study. Land tenure is not a variable that CARE projects are trying or able to influence, but it is very important to know what percentage of the population owns land and what percentage is landless. Project interventions which require land (kitchen gardening, agroforestry, tree plantation on private land, improved varieties, etc.) will not be profitable for landless families. Other information like seasonal migration is relevant for project interventions. If this information has not been collected during the situational analysis, or if more in-depth information is required, it can be

included as part of the baseline study. Village histories and well-being ranking increase our knowledge about the population living in the project area. But again, many things are interesting and more-or-less relevant for the project. It is important to limit the collection of information to a minimum, without omitting essential information. In the Jajarkot baseline study the area planted with and the production of improved varieties was initially included in the study design. However, the logframe does not refer to it and as other questions regarding productivity were already included, it was left out from the final version.

5. How to collect this information? After completion the list of the information needs based on the logframe the next step is to identify the most appropriate way to collect this information. For our purposes three broad methods of information collection should be considered:

1. review of available documents and literature; 2. participatory tools; 3. household survey; 4. in-depth interviews with stakeholders.

5.1. Information collection methods

5.1.1. Review of secondary information The first option is of course the easiest one, but quantitative and qualitative studies of most of the project areas are lacking. Information can be obtained from the district headquarters, line agencies and Central Bureau of Statistics. Most often the data obtained from these sources do not give specific enough information on the working area of the projects. Furthermore the quality of the information from secondary sources is sometimes questionable. However, it is always worthwhile to investigate if other organizations have been active in the working area and if they did proper baseline studies or other research oriented studies. In the case of Bardia several studies were available for the project working area and although these studies were geographically most often only partly overlapping, they provided a lot of useful information. The information obtained from the available documents was analyzed and compared in a literature review study which took place before the design of the baseline study. No further information was collected during the baseline study when the information from different sources on a specific topics was consistent. However, if data

were inconsistent or unlikely, additional information was collected to cross-check.

5.1.2. Participatory methods Currently, participatory methods are very popular in data collection. During the baseline studies extensive use was made of these methods such as village histories, social and natural resource mapping, well-being ranking, seasonal calendars, trend lines and Venn diagrams1. For certain types of information it is the only method available to collect information. This is the case for village histories or Venn diagrams. Other data can be collected in different ways, but using participatory methods is far easier and cheaper than other methods. However, the method most suitable is in most cases determined by the type of information required. For example, a seasonal calendar of workload can be done in participatory way, but could also be done by daily or weekly structured interviews with a large number of women. The latter method is much more cumbersome and probably not much more reliable than simply asking people about the comparative workload in different months. On the other hand, asking information about family planning in focus groups may be much less reliable than information obtained during household interviews. Participatory tools are easy to handle for most of the CARE staff, who all had training on PRA techniques, and many of them have extensive practical experience. It is also much more interesting for the participants, who can at the same time visualize and observe and reflect on their own situation. It gives field staff also an excellent opportunity to learn about the people’s perception of situations and changes over time. It also offers the opportunity to establish rapport between staff and the community and it demonstrates to the participants that project staff respect and value their perspective and knowledge. However, the problem with some (not all) participatory methods is the reliability of the data. The data obtained through participatory methods are more subjective and based on the perception of people, living in a specific area in a specific period. Most of the information is relative and can not be compared across different areas. For example, our informants in Bardia, who are living in clearings in the forest, described a strongly negative trend for the availability of firewood, which was comparable to the trend line produced in Mahottari. For study team members the situation was not comparable, because in Bardia piles of dry wood were

1 For a description of the experiences with these tools in baseline studies, see Annex 1.

used to protect the fields against wildlife, whereas people in certain clusters in Mahottari district used no wood at all and relied completely on dungcakes. Although the trends in these two districts may be comparable, the situation can not be compared in absolute terms. There is a general exception to the rule that data from participatory methods are more subjective. A lot of ‘hard’ information can be obtained from social mapping, like the exact composition of the village, the number of landless households or households which are involved in seasonal migration, the number of water points, toilets, kitchen gardens, etc.

5.1.2.1. Sampling issues for participatory methods Sampling for participatory methods has specific problems, related to the type of information generated by the method. In the case of quantitative information like the number of households with kitchen gardens or toilets, each of the households can be treated as a separate yes/no answer. If a field check shows that the information provided by the participants in the social mapping exercise is accurate, then each of the households can be treated as a separate datapoint. However, in other cases (Venn diagams or seasonal calendars) the information from the participatory exercises will provide quantative information, but will produce only one or two datapoints per cluster. Although the information obtained through these methods is not ‘hard’, it is necessary to cover a reasonable number of clusters to get some idea about patterns. Information from earlier clusters should be checked later during the discussion other groups. There is no scientific rule about how many clusters or wards to sample for these participatory exercises. During the recent series of baseline studies at least 12-18 clusters were covered representing 20-25 % of the total number of clusters in the project area. The larger the number of clusters the better the information, but in remote districts in Nepal the logistical consequences of increasing the number of clusters are considerable. A third group of exercises produces basically qualitative information. It is not possible to give fixed rules for the number of samples for this type of execises. It is again important to cover a reasonable number of clusters to be able to distinguish patterns and ensure representation of different (caste) groups. However, if cropping patterns are found to be identical in most of the clusters, it is not necessary to repeat these over and over and it may be more interesting to discuss other topics related to agriculture, like changes in cropping pattern over the years or eventual differences

between different socio-economic groups in the community. If new information keeps coming up it is important to continue For these qualitative exercises it is even more important to assess the variation between different castes, socio-economic strata, men and women. Different groups make different use of natural resources, men may be involved in seasonal migration with cattle, whereas women and children are herding cattle around the village or cut fodder and hay in the dry season. Low caste blacksmiths use the forest to produce charcoal, etc. It is worthwhile to discuss certain topics with other groups instead of repeating the questions with the same type of focus groups (unless there are interesting differences between the different focus groups). Another issue in using participatory methods is the composition of the groups of participants. In general separate exercises with men and women should be done if the outcome of these exercises is expected to be different. In the case of village histories, trend lines and social maps can be done with mixed groups of men and women. For seasonal calendars of workload, natural resource mapping and most of the semi- structured interviews it is necessary to work with separate groups of men and women. Other exercises, like Venn diagrams and well-being ranking can be done with separate groups, but it depends on the time available whether this can be realized or not.

5.1.3. Household survey A household survey, if properly designed and implemented, is the best method to collect statistically valid information that can be generalized to the whole project area. The data obtained in this way can be compared with other periods and is therefore a good way to compare the situation at the start of a project with end of project situation. Household surveys have also certain disadvantages: they require qualified staff to design, conduct and analyze the findings and the jargon and sophisticated software used for data analysis give these surveys a superior appearance which is not always justified. The reliability of the data collected with a household survey can be determined beforehand and it is possible to determine the sample size depending on the desired reliability. For a detailed discussion of some of the statistical issues of sample surveys, see Annex 2.

5.1.4. In-depth interviews Sometimes in-depth interviews with key informants can give valuable qualitative information, which link the perception of change of the interviewees with the causes for these changes. In-depth interviews asking about changes in socio-economic situation can reveal the causes behind the changes that take place in the life of ordinary people. Sometimes, when a specific person is very important for the project (like the Park Warden in Bardia) only in-depth interviews with the Park Warden and/or other officials will reveal changes in attitude towards communities close to the Park.

5.2. Linking information needs with methods The comparison of the different methods in section Table 1 shows that none of the above-mentioned methods is superior in all aspects. All have their advantages and disadvantages and for each of the indicators mentioned it will be necessary to reflect on which will be the most appropriate method(s) for data collection. Sometimes it may even be necessary to use two different methods for one indicator: e.g. use a household survey to gather data on the production of foodgrains combined with a participatory technique to investigate the change over time in foodgrain production. In general the choice for a specific information collecting method will depend on: • the type of information required; • the time and human resources allotted to the study team; • the desired level of precision; • the time requirements of the different methods; • the possibilities of combining data gathering of different variables in

one tool. Table 3 gives an elaboration of Table 2 and includes columns for the data collection method and a plan of analysis. This table shows that for each of the indicators different methods are used to collect the information. The existing sources of income were measured in different ways: • focus group interviews with men were used to get an idea about the

variety of sources of income, the importance of these sources of income and changes over time (trends). These interviews also indicate whether sources of income are open to everybody or limited to specific groups or castes;

• during natural resource mapping information is obtained on the importance of Non Timber Forest Products (NTFPs) in a cluster;

• quantitative information was obtained through a household survey, which asked every sampled household whether they earn money through different livelihood strategies. Through this survey it is possible to assess how many people are involved in which activities and what is the approximate amount of money earned through these activities.

In this case the focus group interviews and natural resource mapping give qualitative information on the sources of income, and the household survey complements this. It allows comparison or triangulation between the different methods. If a certain source of income is mentioned during

Table 3. Indicators, information needs and information collection methods for Intermediate Goal #4 of Jajarkot Poverty Reduction Project.

4) Diversified and increased sources of income. indicator information need data collection

method plan of analysis

4a) increased number & value of (active) sources of income in the project area.

4b) changes in

participants self- perceptions in income.

4c) changed

consumption patterns (as a proxy for income).

4a) > existing sources of income in the district > the estimated income generated through these sources of income 4b) > market opportunities for (forest) products and traditional skills > reported income 4c) > purchase of cooking oil, masala, soap, hair oil, toothpaste during the last three months and year > school attendance of children

4a)> natural resource mapping > semi structured interviews > household survey 4b) > focus group interviews with men and women > household survey 4c) > household survey > household survey

4a) > maps; description of FUGs; > synthesis of management of natural resources > tabulation of sources of income per category, cluster or caste 4b) >inventory of opportunities and problems > average income per household per source of income 4c) > tabulation of expenditure patterns for households in different socio-economic categories > literacy rates (boys/ girls) in relation to caste and socio-economic status

the focus group interviews but which does not come back during household surveys additional attention should be given to this subject by cross-checking with other key informants. Another method which could have been used to add information is ranking of the importance of the different sources of income. However, the household survey already provides this information and adding extra methods does not seem necessary in this case. Indicator 4c is an interesting example of the use of a proxy indicator. Objective 4 aims at increasing both the diversity as well as the value of the sources of income. It is for several reasons very difficult to measure income, and to avoid all the technical problems related to measuring income a proxy is chosen. A proxy measures the change indirectly, so the change in income is not measured, but rather the change in household expenditures. Buying more things more frequently indicates that the family income has gone up and that is felt to be sufficient for our purpose. The selection of the items mentioned in Table 3 is based on the importance of these products and the socio-economical situation of the project area. Most products are “luxury” products, which means that people will buy these products after they have bought the necessary food. It is assumed that an increase in income will lead to an increase in the use of these “luxury” products. The list used in this example is based on previous experiences with measuring changes in household expenditures in remote areas of Nepal.

5.2.1. Putting the pieces together After the list of necessary information is completed and the most appropriate data collection methods are selected it is time to put the pieces together. The individual methods have to be combined in a overall study methodology, which may include a review of secondary data, PRA tools, as well as a household survey. The most important issues to be dealt with are: • the sequence of the different methods to be used

It is best to start with exercises (after introducing the study team members, the objectives of the project and the study) which create good rapport and which involve a large group of people. Village histories and social mapping are most suitable for these purposes. An example of a typical workplan for a cluster or ward is presented in Annex 3.

• the time and staff available for the study Project staff have their own on-going activities according to their workplan. A baseline study should not take too much of their time. In the recent baseline studies project staff were involved in field work for four to five weeks.

• the number, location and variation of the population in the wards or clusters covered during the study In many districts the variation between clusters and wards is large, especially if their is a distinct cluster-wise segregation of castes or ethnic groups.

• the time spent in each cluster or ward This issue is linked to the previous two: increasing the number of days per cluster means a reduction in the number of clusters that can be covered. Reducing the number of days per cluster means that less information can be gathered! The number of clusters covered until now has varied from 12 (Bajura and Mahottari) to 18 (Bardia);

• size and composition of the study team All studies were done with two teams of three to four persons (with the exception of Mahottari). Doing the baseline study with a smaller number of people has definite advantages, because the team members have the opportunity to learn from their experiences and because it is much easier to coordinate the study and check the formats. Preferably, each of the study teams should include at least one woman (although two is better) and each team should include people with different professional backgrounds so that they can adequately explore the varied themes covered in the baseline study.

During this part of the design it may be necessary to make changes in the information needs as defined in earlier stages, because it may not be possible to use all the different methods. Not only is there a limit to what the study team members can do, but the villagers also get tired if they have to participate in many different exercises. Overburdening villagers or team members will reduce the quality of the information. Examples of a cluster-wise study plan with an overview of methods plus the expected outcome is added as Annex 4. The timing of the field work is also important, although the experience has shown that external factors (e.g. pressure from donors or start of

project activities) often play a decisive role in the timing of the studies. Planting and harvesting time of rice should be avoided at all times, because this is the season with the highest labor peak for farmer families and it will be difficult to meet people. Although the timing of the studies in Bajura (December / January) and Bardia (May / June) was not very good (seasonal migration in Bajura and a heat wave in Bardia), it did not have a negative impact on the participation of the population. The best season is between November, after Tihar until April, except that at this time it may be difficult to meet migrating men.

5.2.1.1.Timetable After the completion of the study methodology for each of the clusters, a timetable can be made for the baseline study. This should include the following elements: 1. training / orientation of study team members

Until now three-day trainings have been given in the project area 2. field testing of the methodology

Although it is very important to test the methodology before starting the baseline study, it was in the past not possible to do field testing because of time constraints. This lack of testing was overcome by a very intensive support to both of the teams during the field work in the first clusters. After the completion of all the methods the experiences were reviewed by all team members and adaptations were made if necessary.

3. travel In remote areas the distances between VDCs and even between clusters within one VDC can be considerable and it is therefore important to include sufficient time for traveling.

4. cleaning, arranging and correcting notes and formats Often notes are made during discussions with individuals or groups; at times it is not always possible to make notes. Therefore the formats have to be reviewed, completed or cleaned by the team members if necessary during the field work. The team coordinator should check if all formats are completed and if no exercises have been forgotten. This also takes time and has to be included somewhere.

5. rest and recreation The circumstances during the field work are often demanding and the

team members need time to rest, wash their clothes, and get charged again.

The time table for the baseline study in Bajura is added as Annex 5 and the estimated time requirement for different levels of staff is presented in Annex 6.

5.2.2. Developing formats The process often described as collecting information is in fact often a process of losing information. The loss of information will be greatest for participatory methods as the participants may discuss a large number of topics in a semi-structured way. While noting down the contents of these discussions a lot of information is lost and this becomes only worse when the data from all wards or clusters are compiled. It is therefore essential to develop strong formats to prevent the loss of data which are considered most relevant. For household surveys good formats are also essential, to avoid ambiguities in the questions and to make later analysis easier. A set of formats used during the Bajura baseline study is added as Annex 7. During the baseline studies done so far, Access software (a database program developed by Microsoft) was used to design formats for the household survey. This program is programmer- and especially user-friendly. The formats used for data entry in the computer can be identical to those used by the study team members used in the field, which simplifies data entry in the computer.

6. How to analyze this information?

6.1. Consolidation of the data After completion of the field work the data have to be collected and entered in the computer. This is often a tedious job which includes checking all the formats and entering the data. Data can be entered in Word (e.g. focus group interviews, village histories and most other PRA tools), Excel or Access. Access is better for data management, but few staff are used to working with this software. It has the advantage that it is very flexible and can store large chunks of text as

well as figures and pre-defined categories. Especially the latter characteristic is very valuable for large surveys1. A certain level of quality control in data entry is possible by comparing some ( e.g. 5 %) of the original forms with the data as entered in the computer. If mistakes are often observed in a few specific variables it may be worthwhile to check them on a larger scale and correct all entries. Access has advantages in data entry, because the formats used in the field can be identical to those used for data entry in the computer. Information entered in Access can transferred with one push on the (right) button to transfer it to Excel for (statistical) analysis.

6.2. Analysis of data from PRA exercises The analysis of the results from many of PRA methods is tricky. In the case of village histories it will be limited to a qualitative analysis, in which the common characteristics of the village histories are brought together. Some of the village histories contain many distinct historical events, like migration streams, floods, epidemics, etc. (e.g. Bardia), whereas others almost mythical in nature (Mahottari and Bajura). Social maps and natural resource maps contain often a large variety of information. Some of this information can easily be analyzed, like the number of households, the number of toilets, water points, etc. Other information is much more qualitative, like the use of the natural resources and the quality of the water sources. The analysis of the first type of information can be done with the use of a spreadsheet (Excel), while common sense is the most essential ingredient for the analysis of the qualitative information. The results of seasonal calendars can be transformed in quantitative data. However, the number of observations for these participatory methods is much smaller: one per cluster compared to 25 observations per cluster for the household survey. The results from the seasonal calendars can be averaged over a number of clusters, because the timeframe used (months) is the same for all clusters (analysis stops at making averages and comparing the averages from different months).

1 Excel treats Chettri, Chetri and Chhetri as three distinct categories. This kind of different spellings and typing mistakes can be avoided by creating pre-defined lists.

This is not the case for trendlines. The participants in trend lines often use time references which are different in many clusters. This makes it much more difficult to calculate averages for several clusters. In practice it is often possible to find a number of clusters with a comparable time scale and these can be used to calculate averages. The same holds for the results of wealth ranking. Participants in certain clusters distinguish four categories, whereas others may distinguish three or five categories. In these cases it is necessary to elaborate the characteristics of the categories mentioned for the most common classification (often in four categories). This standard list can then be compared with the characteristics of the categories of the other classifications. The analysis of the data from the Venn diagrams is more complicated. In certain wards the participants in this exercise may mention only four organizations, whereas other wards may mention nine or ten organizations. To make the data from different wards comparable a formula has been developed to ‘normalize’ the results. The process used is as follows: the ranking of an organization as given by the participants during the Venn diagrams was transformed in a score. The formula used for this transformation is 10/n * (n+1-r), with n the total number of organizations mentioned in a specific ward and r the rank of the organization in the ranking1. If the participants in one ward mention four organizations and rank these as 1, 2, 3 and 4, these organizations get a ‘rating’ of 10, 7.5, 5 and 2.5 points respectively. In the analysis of the Venn diagrams both the number of wards which mention a specific organization as well as the average ‘normalized’ score of this organization can be mentioned.

6.3. Analysis of household survey data Many different methods are available for the analysis of the data from household surveys. Interested people can use e.g. G.W. Snedecor and G.W. Cochran, Statistical Methods as a reference. For a baseline the analytical part of the study is limited. The report should include averages of the most relevant variables plus their standard deviation or confidence limits. The pivot table feature in Excel is a great help in the analysis of data and produces cross tabulations of averages, sums, standard deviations, etc.

1 In this ranking, one is the most important organization, two the second most important organization, etc.

The average number of trees per cluster can be replaced the total number of trees for each category in the well-being ranking within ten seconds (as long as the data are in one table of course).

LIST OF ANNEXES

Annex 1. Description of the PRA tools used during the baseline studies. 26

Annex 2. Sampling for a household questionnaire. 29

Annex 3. Cluster-wise work plan for a baseline study in one cluster. 32

Annex 4. The expected output of the tools used during the baseline study. 33

Annex 5. Time frame used for the baseline study in Bajura. 36

Annex 6. Estimated time requirements for different levels of staff involved in a baseline study. 37

Annex 7. The formats used for the Jajarkot baseline study. 38

Annex 1. Description of the PRA tools used during the baseline studies. This overview gives a list of the different participatory methods used in the baseline studies. It does not go into the details of the tools, which can be found in many documents, but focuses on the possibilities and experiences with these tools during the baseline studies. For more information on the tools see for example: • Theis and H.M Grady, 1991. Participatory Rural Appraisal for

Community Development. • CARE Nepal, 1997. Participatory Rural Appraisal for Community

Development. A training manual based on experiences in Nepal. Village histories After an introduction in the village during which the objectives of the project as well as the baseline study are explained, the study teams often started with a village history. During these village histories a group of people (including at least a few old men and women) are asked to relate the story of their village, the most important events which took place. If important events are known from other places (e.g. drought, flooding, migration) probing can be used to assess the influence of these events on this village. Mapping After village histories social maps or resource maps from the area are the most logical steps. Initially social maps were made first, followed by resource maps, but in many cases the team prefer to do these exercises simultaneously, using the outlines of the natural or social resources map to construct the second one. Natural resource maps give an overview of a larger area, indicating neighboring clusters, government forests, park boundaries etc. Certain clusters (Bardia and Mahottari) were big (up to 400 households) and composed of several sub-clusters. It is not possible to work with such large numbers in participatory exercises, and therefore a choice was made to select a part of the cluster or a sub-cluster for detailed study. This can be done based on a social map. In general the number of households in the samples varied from 35 to 120. The natural resource map was used to delineate the part of the cluster that was studied more in detail during the later exercises. Social mapping was used to identify all the households in the (sub) cluster, to identify the major characteristics of the clusters, drinking water, schools, etc. The social maps can also used to indicate landless and/or migrating households, etc. This information combined with the

names of the household heads gave a complete overview of the demographic situation of the cluster. Participants during the social mapping showed a strong tendency to expand the area covered in the map, because those who were living in areas not covered by the map were afraid they would also be excluded in the future from project activities. During social mapping people were also asked about the existing traditional organizations within the communities and the NGOs active in these clusters. Well-being ranking Small groups of people (mostly composed of two women and two men) are asked to rank the households in their cluster. The list of households was generated during the social mapping. In general well-being gives very interesting results. The informants in most clusters distinguished four to five different categories of well-being. After the ranking the people were asked to analyze the choices they had made by trying to describe the characteristics of the different categories. The results from the well-being ranking were often used in the analysis of the quantitative data. This proved to be very fruitful and in general there was a strong relation between the results from the well-being ranking and the household survey. This shows that well-being ranking is an effective method to get an indication about the socio-economic well-being in an area. Trend lines Trend lines describe the changes over time in the availability of resources (firewood, fodder or cattle) or production. This exercise can be combined with e.g. natural resource mapping or semi-structured interviews.Trend lines showed often negative trends, with the exception of trend lines on food production in a few Terai clusters. There seems to be a tendency to glorify the past and it is questionable whether these negative trends are real or perceived. Seasonal calendars Seasonal calendars are used to get information on changes in the availability of food, fodder and firewood during the year. As mentioned under trend lines, it was easy to combine these exercises with related exercises like natural resources mapping or semi- structured interviews. Contrary to the trendlines, the seasonal calendars seem to be quite accurate and are strongly related with the cropping pattern. Seasonal calendars were made by separate groups of men and women. Semi Structured Interviews Semi Structured Interviews (SSIs) are interview during which the interviewer limits the questions to a specific topic. Normally the interviewer has a list of key questions, but follows the stream of issues brought up during the discussion. SSIs can be combined with any of the

other tools described above and are often complementary. The more visual exercises describe a given situation, whereas the SSIs explains the reasons behind it. Where trendlines or seasonal calendars clarify changes over time, the SSIs can help to understand why these changes take place. Venn diagrams produce a graphic overview of the important institutions in a cluster; the complementary SSI can clarify the reasons behind the assessment made by the population. Often SSIs are done with a specific group of people, who are supposed to be in comparable situation and face the same problems (focus group interviews). Interviews with government organizations and NGOs Apart from the fieldwork in the villages, interviews were held with key stakeholders who are active in the buffer zone. These include park authorities, iNGOs and local NGOs as well as governmental organizations.

Annex 2. Sampling for a household questionnaire. Sampling method and sample size are complex issues, and in this annex I want to touch only a few aspects of this field. Those who are interested in the details should refer to handbooks. Sampling methods Normally samples are used for household surveys, as it is in most cases impossible and unnecessary to cover the whole population during a survey. However, there are many ways to select a sample. The basic method is simple randomized sampling, in which a given number of households are selected from the total population from the study area. This means that a list of al households from the study area (which may included 10-16 wards) is needed plus a method for random selection. In this way no sampling bias occurs, but the disadvantage is that the selected households are not clustered and that visiting all households may take a lot of time, especially in remote areas. A second option is stratified random sampling. If it is known that large differences exist between certain groups or areas, stratification may be used. The strata are chosen in such a way that the variance within the groups is as small as possible. For example, VDCs can be used as different strata or ethnic groups. The sample size for each of the strata can best be chosen in such a way that it is proportionate to the actual shares of the strata in the population. This allows easy calculations of population averages without complex weighing factors. Multistage random sampling uses the same techniques as mentioned above. In this case two different levels of sampling units are defined. In the baseline studies done so far the primary sampling unit was in most cases the cluster or ward. To avoid extensive travelling, two clusters or wards were randomly selected from the nine wards in the studied VDCs. The second sampling unit are the households within the clusters / wards selected in the first step. Random selection can again be used for the selection of the households. This is a case of two-stage random sampling. Sample size The size of the sample i a complex topic. It depends among others on: 1� the type of variables measured; The standard deviation of a specific variable has a large influence on the

sample size. The formula used to calculate the sample size

n= t SEL

0.952

2

* (for variables with a normal distribution and 95 %

confidence limits). with SE standard error or standard deviation n sample size L allowable error t0.95 a constant, to be used forsamples larger than 60 and 95 %

confidence limits. This constant is approximately 4.0 for 95 %, 2.7 at 90 %, and 6.6 for 99 % confidence limits

There is a large differences between the SE of different variables. The

standard error of the weight of paperclips is small compared to the weight of CARE staff. Four measurements of small size paperclips will probably enough come up with a good estimate of the average small size paperclip with an allowable error of 10 %. However, it may be necessary to weigh 40 staff members to have the same estimate for the average weight of the CARE staff.

Most often the SE of variables are unknown (this is not always the case,

for health related variables SE are often known), and the best alternative is to use the SE of variables used in previous studies. The situation is slightly different for the binominal distributed variables, or in simple terms the yes/no answers. In this case the formula to measure the sample size is:

n t pL

=0.95

2

* * q

with: p the probability that a certain event occurs q the probability that a certain event does not occur (p+q =1) In this case no standard deviation is necessary to establish the sample

size and if we take the worst-case scenario of p=0.5 (which implies that q=0.5), the formula becomes: n

L L= =

4 05 05 22 2

* . * . .

This means that if the allowable error is put at 10 %, the sample size is 100. With an allowable error of 5 %, the sample size becomes 400.

Most household surveys measure both quantative as well as binominal

variables. Binominal variables require the largest sample size, and therefore the desired sample size depends basically on the binominal distributed variables.

2� the desired level of reliabillity; One of the most important factors in deciding on sample size is the desired level of reliability. The formula to calculate sample size contains the t0.95.However, if the desired level of reliability is put at 99 %, the t0.99.value has to be looked up in a table (this alue is 6.6). At 90 % reliability we find t0.90 or 2.7. Substituting both values in the formula will show the consequences of these changes.

3� sampling method All these formulas are based on simple randomized samples. If other

sampling methods are used correction factors have to be used to estimate the sample size. These correction factors are mostly based on experience and there are no statistical calculations available to determine these correction factors.

In the CARE M&E workshop the following correction factors were used:

stratified sampling 0.5-0.95 cluster sampling 1.5-3.0 4� resources available for the research. This adds of course the more pragmatic considerations to the discussion about the size of the sample.

Annex 3. Cluster-wise work plan for a baseline study in one cluster.

SSI on sources ofincom e

household questionnaire

village history

well being ranking

social m apping

resource m appingcom binedwith SSI

focus groupdiscussion onagriculture

venn diagram andSSI on localorganizations

day 3day 2day 1

Annex 4. The expected output of the tools used during the baseline study.

ACTIVITY EXPECTED OUTPUT

HOUSEHOLD

QUESTIONNAIRE

household questionnaire covering household composition, literacy, farming systems (300 households: 100 high caste; 100 Chetrri; 100 low aste households

ACTIVITY EXPECTED OUTPUT

a map, indicating important characteristics of a ward including clusters, forest, grazing land, up hill agricultural land, etc.

SSI on natural resources, focusing on land use and user rights of forests and grazing lands indicated on the resource map. Indicate also when these are used and who controls the use of these lands

RESOURCE MAPPING a combination of SSI and trend lines on

the availability of fodder, firewood and other forest products (if relevant)

a combination of SSI and seasonal calendars on the availability of fodder, firewood and other forest products (if relevant)

a Venn diagram with all relevant organizations and institutions

VENN

DIAGRAM

discussion on the importance of different types of organizations and institutions, with special emphasis on : * (l)NGOs *government services (schools health posts

Annex 5. Time frame used for the baseline study in Bajura.

DATE ACTIVITY 15th Dec Leave for Nepalgunj 16 th Dec Leave for Kolti 17th Dec Leave for Martadi 18th to 20th Dec Orientation of study team members 21st Dec Leave for Budhiganga VDC 22nd-24th Dec Field work of Budhiganga VDC in two wards by 2 teams 25 th Dec Return to Martadi 26th Dec Completion of forms and feed back 27th Dec Leave for Kolti 28th Dec Leave for Sapala and Rugin VDC 29th Dec - 3rd Jan

Field work of 2 wards in each VDC( Sapala and Rugin) by two teams

4th Jan Return to Kolti and completion of all forms 5th Jan Leave for Wai and Jukot VDC 5th - 11th Field work of 2 ward in each VDC (Wai and Juku) by two

teams 12th Jan Return to Kolti 13th Jan Completion of forms and rest 14th-16st Jan Field work of Bandhu VDC by two teams taking a ward each 17nd Jan Completion of forms and evaluation of the overall work by

both the teams 18rd- 21th See to all the entry of data in computer 22th Jan Return to Nepalgunj 23th Jan Return to Kathmandu

Kolti Area: Rugin ----6 hrs from Kolti

Wai-------3 hrs from Kolti Jukot------31/2 hrs from Kolti Sappata---- 7 hrs from Kolti Bandhu---- 2 hrs from Kolti

Martadi Area: Budhiganga-- 4hrs from Martadi

Annex 6. Estimated time requirements for different levels of staff involved in a baseline study. phase staff level time

requirements per person in days

total staff requirement in person days

design coordinator 7 7

logistics assistant 4 4

training coordinator 5 (incl. travel) 5

assistant 5 (incl. travel) 5

project staff (7)

8 28

fieldwork coordinator 3 3

assistant 30 30

project staff (7)

30 280

data entry secretary (3) 4 12

data analysis coordinator 10 10

assistant 10 10

report writing coordinator 25 25

Totals: coordinator: 50 person days assistant 49 person days secretary 12 person days project staff 308 person days

6.4. Annex 7. The formats used for the Jajarkot baseline study.

Annex 7. Overview of forms and interview guides used for this study. Form 1a. Village history. Form 1b. Information on village and local leaders (Mukhiya and/or Raja). Form 2. Compilation of households and well being ranking. Form 3. Traditional forms of community organizations. Form 3a. Description of the traditional organization of the community. Form 3b. Description of the traditional irrigation systems. Form 4a. Overview of community organizations present in cluster. Form 4b. Group description. Form 5a. Drinking water situation in the cluster. Form 5b. Availability of services (time needed for one way trip). Form 6. Characteristics of categories of well being ranking. Form 7a. Trend lines of livestock. Form 7b. Trend line of agricultural production. Form 8a. Seasonal calendar of the availability of fodder. Form 8b. Seasonal calendar of the availability of food. Form 9. Cropping patterns. Form 10a. Availability of different natural resources. Form 10b. Use of natural resources. Form 11. Seasonal calendar of agricultural activities. Form 12. Seasonal calendar of workload for men and women. Guidelines for semi structured interviews Household questionnaires for the Bajura baseline survey.

Bajura Baseline study form 1 number of participants

men: women:

date: filled in by: VDC: ward #: cluster:

form 1a village history

time event format 1b

information on village and local leaders (Mukhiya and/or Raja)


men: women:



men: women:

date: filled in by: VDC: ward #: cluster: form 2 compilation of households and well being ranking

SN name number of persons in the household

category ethnic group or caste


men: women:


form 3 traditional forms of community organizations Please describe the traditional forms of community organization in the cluster. > Is there a Mukhiya or other village leader? Is leadership changing? > Are there any community activities organized in recent times? Who takes the initiative? > How are these organized, who are the members of these organizations? Try to find out to what extent women and lower castes are included in different steps of activities (e.g. decision making; implemenetation of activities)? >What kind of activities do they undertake? What did they do last year? > Ask specifically about irrigation committees. How are they organized, how are caretakers selected? Do users have to pay for these services, etc. What is the total area irrigated under these committees? Who are members of these irrigation groups? > If there are any other constructions that indicate involvement of the community (traditional bridges; foot trails) try to find out about community organization involvement. Describe this kind of community organizations below. feel free to use Nepali if you feel more comfortable about this. format 3a description of the traditional organization of the community format 3b description of the traditional irrigation systems


men: women:


continue on the backside


men: women:

date: filled in by: VDC: ward #: cluster: How many community organizations are active in this cluster?

form 4a overview of community organizations present in cluster name of

community organization

number of members

founded when by

activities / remarks

men women How many members do they have? How is the composition (men/women; castes)? (form 4b) Did they start spontaneously or were they encoouraged by outsiders to form community organizations? How often do they meet? Do they have a special executive committee? What are their most important activities? Do they have saving and or credit activities? What is their financial situation? How did they collect money? (fill in in format) How are their relations with other organizations (line agencies, DDC, VDC, NGOs?) What are their plans for future activities? form 4b group description group composition:

men women

total

Brahmin Thakuri Chettri lower caste other (...........)

started in: name: type of group: group fund: NRs used for: loans / group activities / not used / other activities undertaken until now: (use extra paper if necessary)


men: women:



men: women:

date: filled in by: VDC: ward #: cluster: form 4b group description group composition:

men women

total


started in: name: type of group: group fund: NRs used for: loans / group activities / not used / other activities undertaken until now: (use extra paper if necessary) group composition:

men women

total


form 4b group description started in: name: type of group: group fund: NRs used for: loans / group activities / not used / other activities undertaken until now: (use extra paper if necessary)


men: women:


Bajura Baseline study form 5

number of participants

men:

date: filled in by: VDC: ward #: women: cluster: form 5a drinking water situation in the cluster

source1 of drinking water

number of households using

this source

distance in time for most

users

all season? / accessible for all castes?

form 5b availability of services (time needed for one way trip) services distance

from cluster which services

delivered? remarks

primary school secondary school

health post agricultural office

veterinarian bank

sanitation cluster number of

toilets remarks

1 if several sources, are used please mention all



men:

date: filled in by: VDC: ward #: women: cluster:



men:

date: filled in by: VDC: ward #: women: cluster: form 6 characteristics of categories of well being ranking category A characteristics category B characteristics category C characteristics



men:

date: filled in by: VDC: ward #: women: cluster:



men:

date: filled in by: VDC: ward #: women: cluster: category D characteristics category E characteristics category F characteristics


number of participants date:

men: women:

filled in by: VDC: ward #: cluster: form 7a trend lines of livestock

0

20

40

60

80

100

explanation: form 7b trend line of agricultural production

0

20

40

60

80

100

explanation:



men:

date: filled in by: VDC: ward #: women: cluster: form 8a seasonal calendar of the availability of fodder

0

20

40

60

80

100

bais

jest

asha

shra

bhad

asoj

kart

mang

push

magh

fagu

chai

explanation: form 8b seasonal calendar of the availability of food

0

20

40

60

80

100

bais

jest

asha

shra

bhad

asoj

kart

mang

push

magh

fagu

chai


number of participants date: filled in by: men:

women: VDC: ward #: cluster:

CROPPING PATTERNS

Khet Land Baisak Jest Asar Shraw Bhadr Asoj Kartik Mangs Push Magh Fagun Chaitr Percentag

e

Bari Land Baisak Jest Asar Shraw Bhadr Asoj Kartik Mangs Push Magh Fagun Chaitr Percentag

e

other Baisak Jest Asar Shraw Bhadr Asoj Kartik Mangs Push Magh Fagun Chaitr Percentag

e


number of participants date: filled in by: men:

women: VDC: ward #: cluster:

Bajura Baseline study form: 10 date: filled in by: number of participants: men: women:

resource mapping VDC: ward #: cluster:

form 10 a availability of different natural resources type of natural

resource availability: abundant,

moderate, scarce? location (in same

cluster, ward, VDC?) ownership (private,

community, government?)

khet bari

forest grazing land

community land irigation water

form 10 b use of natural resources

who? Men,women, children?

where? cluster, ward, VDC?

time required for collection

who else uses the same resources?

who controls these resources?

drinking water firewood fodder herding animals xxxxxxxxx


form 11. seasonal calendar of agricultural activities VDC: ward #: custer:

crops /activities

bais jest asha shra bhad asoj kart mang push magh fagu chai may jun jul aug sep oct nov dec jan feb mar apr


form 12 seasonal calendar of workload of men and women VDC: ward #: cluster: 10

9

8

7

6

5

4

3

2

1

M W M W M W M W M W M W M W M W M W M W M W M W bais jest asha shra bhad asoj kart mang push magh fagu chai may jun jul aug sep oct nov dec jan feb mar apr

Bajura Baseline study date: filled in by: number of participants: men: women:

GUIDELINES FOR SEMI STRUCTURED INTERVIEWS

farming systems agricultural production !What are the different types of ownership? (Owned, rented, sharecropped, kamiya) ! What are the different types of land used by the population of the cluster? Khet, bari, pakho bari, patan, lekh, etc. !Is the land irrigated? All seasons/ reliability/ quality/ regularity of the irrigation system? !Cropping pattern: which crops are grown during the year; which crops are intercropped? !Is crop rotation practiced? !What are the major crops? !Is agricultural production consumed in the household or sold? Which products are sold? !Is the labor force from the own household large enough or do they hire laborers from elsewhere? livestock !Types of livestock. !Ownership of livestock !Stall feeding/ free grazing/ other forms of livestock husbandry; seasonal migration with the animals? !Products of livestock. Milk, ghiu, dung, meat, sales of animals. !Type of fodder used/origin of fodder/quantity and quality available throughout the year.

GUIDELINES FOR SEMI STRUCTURED INTERVIEW

NATURAL RESOURCES !What are the different types of natural resources/ forests/ gazing land/ pakho / pakho bari / lekh / patan/ etc.? (use information from resource mapping)

Bajura Baseline study date: filled in by: number of participants: men: women: ! Where do they use these natural resources for? agriculture? livestock? construction materials? collection of other products (honey, hunting, fish, fruits, medicinal herbs, edible roots) ! Who collects which products and when is this done? does it involve seasoanl migration? !Who controls the forest? government? private? community? ! Are any of these products sold? Which ones and where? ! Is there any (traditional) management system of the abovementioned natural resources? Is there any sign of over exploitation of certain products? Do people think that management is necessary (to avoid overexploitation)? INCOME GENERATION ! What are the most important sources of income (in cash as well as in kind)? Can they rank these sources of income according to importance? (Think about sale of livestock, agricultural labor, skilled labor in Jajarkot, migration to India, sale of agricultural production, etc.) ! Who is doing this type of IGA? Men/ women/ lower caste? ! Do women have their own sources of income?

design baseline studies 1

6.5.

guidelines for developing baseline studies

Documents