Objectives
The general objective of this research is twofold, first to determine the way in which markets, assets, indigenous knowledge, life cycle, access to resources, information and forecasts, and institutions cluster groups with distinct household production strategies in the Altiplano to adjust to climatic variability; and second, to identify the groups that use or would use climatic and weather information in their production decisions and the net returns of using improved forecasts.

Specific Objectives
I. Develop a methodology to:
1. Identify the role of climatic risk in decisions affecting the choice of economic activities, levels of production and levels of consumption at the household level.
2. Measure the impact of El Niño event of 1997-1998 in a peasant community of the Central Altiplano using a similar approach to that developed by Valdivia and Jetté (1996).
3. Evaluate the information flows, networks, transactions costs, and mechanisms that rural communities have to access climatic and weather information.
4. Based on the results from objective #3, assist in identifying the type of climatic information delivery systems best suited for Andean agriculture.

II. Test this methodology in a second community of the Altiplano region of the Andes.
1. Develop a baseline in a selected community of the Peruvian Altiplano where data on production and climate from previous years is available.
2. Test the methods of data collection and analysis developed in the Bolivian Altiplano in Southern Peru to validate our approach for identifying strategies under climatic risk.
3. To identify current information delivery paths and the factors that are necessary to improve decisions with forecasting.

Hypotheses
1. Access to resources, stage in the life cycle (age and labor), livestock assets, quality of resources,   and off farm employment are significant variables in developing distinct economic portfolios.
2. Access to resources, assets, life cycle, networks and experience with climatic information are predictors of use of forecasts.
3. High transactions costs preclude farmers and households from accessing climate information.
4. Farmer and household diversification strategies minimize climatic risk and result in lower net     income returns (following Rosenzweig and Binswanger, 1992).
5. Climatic information will be used only if risk reducing technologies are available.

Methods

Research Setting
We will work in two research sites one in the Province of Aroma in the Central Bolivian Altiplano and the other in Puno in Southern Peru. These sites were chosen because detailed production data exists on them for the early part of this decade. Our first proposed research site is the Community of San José Llanga in the Province of Aroma, Central Bolivian Altiplano. It is characterized by a high degree of abiotic perturbations-- periodic droughts, frequent frosts, occasional floods and seasonal wind erosion (Washington-Allen, 1993). Mean annual precipitation between 1943 and 1990 is about 400 millimeters, with a coefficient of variation exceeding 30 %.

Potential sites in Puno are two peasant communities, Santa María in Ilave, and the community of Apopata in Santa Rosa de Juli. The first is a crop livestock community near Titicaca Lake at an altitude between 3,827 and 3,931 masl. The second community, mostly of alpaca producers is located between 4,070 and 5,300 masl. These communities participated in the PISA project, a research program on agricultural systems funded by IDRC. CIRNMA our collaborating institution in Puno grew from this research program. Historical and in-depth information is available for sample selection (Arguelles and Estrada, 1991).

Household strategies in the Andean region

Framework for analysis
A household production systems and economic portfolio (Valdivia et al. 1996; Valdivia and Jette, 1995 and 1997). Data collection will be undertaken on a sample of households at selected sites in Bolivia and Peru. Criteria for selection include belonging to an area where climatic perturbations occur, where both crops and livestock are produced and are sensitive to climatic perturbations. Variability is required with respect to market linkages and transactions costs, and communal relations, and agroecological characteristics. We will build on the household approach for cluster analysis designed in previous research on economic strategies in Bolivia (Valdivia and Jetté, 1996).

Data collection
Two stages are part of the data collection process: In order to identify networks, climate and weather perceptions in production decisions and their timing related to each of the agricultural activities, and to measure transactions costs, farmer group meetings will take place in each identified community. Following these participatory rural appraisals, sections on these topics will be added to the original structured questionnaire about: crop variety information, spatial diversification and staggered planting by crop, traditional sources of information for production decisions, networks, costs of accessing information. Data will be collected from a random sample with replacement (Deaton, 1995), as was done for the original two samples in Bolivia. We will interview the same households in San José Llanga to evaluate the changing strategies and the impact of climatic events in changing the portfolio composition.

The existence of detailed production data from two previous years in Bolivia, and baseline data from Peru will permit us to gather more detailed information on the use of climatic data than would otherwise be possible. The data gathered in previous research, combined with the data gathered with the research proposed here provides a rich data set to study farmer decisions throughout this decade.

Strategies
Cluster analysis (Valdivia and Jetté, 1996; Aldenderfer and Blashfield, 1984) using the variables identified in previous analysis (Valdivia and Jetté, 1996), will be performed to identify current strategies and the consistency comparing the results to previous clusters (Do households persist in their initial group?). Previous analysis (Valdivia, forthcoming) showed the permanence of households in identified groups, by age and adult equivalent labor units first, and then by access to resources, by their quality, as well as total net income.

Comparisons between years will be performed with Discriminant Analysis (pair wise comparisons) and Canonical Analysis (more than two groups for three points in time) (Pedhazur, 1997; Aldrich and Nelson,1984). Income change between 1993 and 1995 was analyzed through regression analysis (Valdivia, forthcoming). Regression analysis to explain income change from one rainfall and frost year to another will be explained by factors believed to affect income: diversity index, assets, stage in the life cycle, and quality of resources. This analysis will be repeated to compare the effect of climate change with 1998 -1999. Other multivariate techniques will be used to analyze differences between clusters/groups (strategies) on variables hypothesized to affect or be affected by year (climate). Three production years with different rainfall patterns will be analyzed in Bolivia, and two in Peru.

Diversification and the portfolios
Diversification indices developed for production in 1993 and 1995 (Valdivia et al., 1996) will be revised to include climatic and weather risk (drought and frost) based on historical data and the simulation models. This index will include a measure of risk to each economic activity, in order for the index to reflect not evenness in spread of income, but also the amount of risk attached to each portfolio. This will allow us to test Rosenzweig and Binswanger hypothesis. We will measure the degree of covariance between economic activities in each portfolio to determine which ones are more risky (Rosenzweig and Binswanger, 1992; Reardon et al., 1992).

Impact of networks and social capital on risk management strategies
The household surveys will provide initial data on the structure and strength of networks. Questions will be adapted for use in Bolivia from the "core discussion network items" on the General Social Survey (Marsden, 1987; National Opinion Research Center, 1991). These items will be used to identify the weak and strong tie networks of farmers and correlated with response to climatic variation. Using cluster analysis, a typology of farmers will be developed and set of farmers will be identified for case studies in the year following the household survey. Measures of social capital and transactions costs will be constructed from the data to evaluate their effect on probability of using information.

Impacts of climatic events on household strategies
Evaluate if the risk reducing strategies without climatic information yield lower income than those with forecasts.

Models to predict outcome in crops and livestock with yields based on climatic forecasts
Experimentation in the real world, although absolutely necessary is in some circumstances an expensive and time consuming process with severe problems in controlling variables exogenous to the experiments (Dent, 1993). In computer modeling, by contrast, experimentation is easy, cheap and speedy, at least once a suitable model has been developed (Pandey and Hardaker, 1995). A word of caution is important at this level; modeling is only an analytical tool and not an end in itself. It is also worth mentioning that models are at best simple representations of reality thus they only should be seen as decision support tools (Quiroz et al., 1998).

A valid model is useful for evaluating scenarios that are difficult to be tested in the real world. This is especially true when assessing the long-term consequences of different management practices or the possible impact of climate change. In such cases, comprehensive models are extremely valuable for formulating and testing hypotheses that otherwise require many years of data.

In this project models of crop growth and livestock models developed and/or adapted to adequately simulate production in the Altiplano will be used to evaluate different production scenarios (see Arce et al., 1994; Quiroz et al., 1994;Tsuji et al., 1994).

Method to assess impact using a household portfolio approach
The set of strategies identified from the cluster analysis for each year will be the baseline used to compare with the net returns obtained with the models under same climatic and weather events. We will calculate the net economic returns of the household economic portfolio, including in-kind production for consumption, in each of the identified strategies, three in the case of Bolivia and two in the case of Peru. Sensitivity analysis will assist us in comparing the farmer strategy, with one that assumes a range of precision in forecast (Mjelde et al. 1996) as an approach to measure the potential impact of accessing climate and weather forecasts. The objective will be to determine which strategies (portfolio of economic activities, which included no-farming) perform better under climatic risk and why. The three years of data from Bolivia will show household strategies under three different rainfall and frost events. It will allow us to compare and identify the groups that are most vulnerable to climatic risk, and will allow us to evaluate the impact of current access to climatic and weather information. We will know from the study of networks, social capital and transactions costs which groups of farmers, identified by the strategies, are able to use information. This evaluation model will be developed through the end of year two, and will measure actual household decisions reflected in their portfolio of economic activities. A similar model will be constructed for the Peru site with the data gathered in year two. We expect the conditions that facilitate access to weather and climate information to differ because of distance to market, different crop and livestock mix, local conditions, government policies, and markets.

Plan of Work: Summary of Yearly Activities and Outputs

Year One
Convene an advisory and expert panel committee for interdisciplinary research:
Valdivia and Gilles (MU), Quiroz and Hijmans (CIP), Valdivia and Reinoso (CIRNMA), Lagos (Instituto Geofisico del Peru, weather forecasts), Jetté (UNDP), and a representative from SINSAAT (National System of Food Security and Early Warning System in Bolivia), and a representative from PROINPA will be the core members of this committee. Members from the National Agrarian University La Molina will be invited to participate in the second and third year. The purpose of this group is to review current instruments of data collection to capture more crop information, as well as indicators of knowledge on climate. The panel will also discuss integration of the approaches in social sciences, biological sciences and climate forecast feasibility in to the development of the models. The panel will assist with the diffusion of information to existing networks.

J. Gilles, C. Valdivia, C. Jetté and a member of PROINPA will conduct participatory rural appraisal meetings with farmers in the community to identify use of climate and weather information by farmers in San José Llanga building on preliminary studies conducted in 1995. Gather information on their perceived need of climate information and current coping mechanisms.

Prepare instruments for data collection with R. Espejo and field test in the first community to capture production year 1998-1999, as well as ask recall questions on El Niño 97-98 year; field test and apply a survey to 45 households (contingent on resources we could expand this to 45 farms in another location form which previous information exists). Identify strategies in 1998-1999 through cluster analysis, and evaluate the current degree of climatic risk in each group at CIP. Identify institutions, organization and networks at the household level for case study analysis in year two. The principal investigator will spend four weeks in Bolivia on the development of instruments, the participatory rural appraisal, and the field testing of the instruments. She will spend four weeks at the International Potato Center, working with R. Quiroz on the modeling of household strategies with the biological information. The co-investigator will set up the research questions for the study of networks and social capital. If resources allow, we will start identifying the second site in Peru on year one.

Year Two
Expert panel meets to review priorities for year in light of findings year 1, advise on the qualitative research in Bolivia, review instruments proposed for data collection in Peru. Assess initial household strategies in the second community with baseline information if an initial survey is conducted at the end of year 1 in Peru. Otherwise apply the household survey to the selected community in Peru identified in year one. Based on the crop choices, model yields based on potential forecasts of drought and frost in Peru and Bolivia. Develop case studies to identify and evaluate transactions costs, the role of social capital, current networks and sources of information on climate and weather; understand how these impact on decisions. We will study the groups of farmers and varieties of crops that may be chosen to improve performance in terms of productivity under stress (from on-going research conducted by CIRNMA and PROINPA) to reduce risk.

Process and evaluate the data with CIRNMA experts using the same cluster approach to identify groups households with similar strategies to determine the consistency of the framework. We expect a graduate student at the masters level from the Social Sciences Unit, MU to conduct field research in Bolivia on year two. We will apply to the Brown Fellowship for graduate international experiences provided by the College of Agriculture Food and Natural Resources (CAFNR), to cover travel and research costs. The co-investigator will spend at least three weeks in Bolivia on case studies to gather information about social capital and networks, in order to develop measurable indicators. He will spend one week in the second community, in Peru. The investigator will spend three weeks of field research in Peru in the identified community, and three weeks in Bolivia on the case studies, and two weeks at CIP on data analysis. At the end of the year, R. Quiroz will spend two weeks in the U.S. to evaluate the results of Peru's questionnaire. Outputs from the Bolivia research will be completed at the end of year two regarding both the quantitative analysis of the strategies, as well as the qualitative study on factors that may enhance or facilitate use of climatic information in Bolivia.

Year Three
The method for impact evaluation based on identified strategies according climate events (actual and simulated), will be applied to the strategies identified in the Peruvian community. We will use Logit analysis to identify the characteristics of farmers, their households, institutions and resources that explain use climatic information and forecasts in Peru. An interesting question is what has been the effect of El Niño on decision making. Some believe it to have decreased production in the region, because of a forecasted drought that did not occur (Woodman, 1998). We expect a second graduate student to conduct field research in the identified community in Peru on the institutions, transactions costs, networks and impediments to use climate information. We will follow the same approach of seeking funding for field research and travel for the student from the Brown Fellowship, CAFNR. Household portfolio economic evaluation as a result of simulated improved weather information will be conducted by the research group at CIP and in the US. Case studies in Peru will be completed on transactions costs and networks with graduate student. If possible we will apply the questionnaire in Peru one more time to obtain an additional point in time. Finally we will hold a conference at CIP to share the results of our research with scientific and policy community.

Relevance to the goal of the Climate and Global Change Program and the program priorities
The proposed research aims at identifying how climate, especially drought, affects the portfolio of economics activities, i.e. the production and market decisions of rural households, as they respond and adapt to climate variability. Our study will identify groups of the population that are in the best position to take advantage of climate and weather information, and understand the constraints they experience. This research also intends to evaluate, based on current production strategies, the potential impact of using the climate forecasts. Recommendations will be developed from the findings, to formulate policies intended to eliminate current constraints on the use of forecasts. Recommendation will also be developed on the type of weather and climate reports are useful to agricultural producers in this region. The announcement of El Niño Event of 1997-1998 and its effect on production will be studied in the region. Reinoso (personal communication, CIRNMA) mentioned conservative planting after the announcement of El Niño were taken that decreased production (Woodman, 1998).

Our research will shed light on how rural households and communities currently adjust to climatic variability, evaluate the outcome of current decisions identifying use of climate and weather information, and analyze the institutions that influence their decisions to identify how climate forecast information can be incorporated.

Benefits to the public and scientific community
We expect our research to advance the understanding of decision making under uncertain environments and non perfect functioning markets; we also hope to improve the evaluation methods by incorporating a household portfolio approach; integrate information generated from crop and livestock models with forecast predictions to the evaluation of rural household strategies. Contribute to the knowledge of the role of non market institutions, networks and organizations in the use of climatic information and weather forecasts. Contribute information to the community on the type of weather and climate forecasts that are useful to producers in the Altiplano region in the production of food crops such as potato and quinoa.

Linkages
CIRNMA, PNUD, PROINPA, and CIP are institutions working in the region and devoted to improving the living conditions of small holder producers and their families in the Andean Altiplano regions of Bolivia and Peru. As the letter of participation by PNUD indicates this institution is currently working in a project to strengthen the Bolivian National System to mitigate and manage disasters, and are at present conducting an assessment of the damages of El Niño phenomenon is the region. The International Potato Center is part of the Consortium for the Development of the Andean Region (CONDESAN),which is a network of institutions working on the development of this region. CIP is currently developing drought and frost models for different potato varieties (Hijmans et al.,1997) in the Andes, and the Department that R. Quiroz leads is working on integrating biological models to study land use management and sustainability in this eco-region. We are working with the International Potato Center. Researchers from CIP have submitted another proposal "Integrated Assessment of ENSO and Climate Change Impacts on the Andean Agriculture" (Charles Crissman, Principal Investigator, Roberto Quiroz co-investigator). Our research on the household approach, decisions and strategies, will inform the research at CIP, while our project will benefit by diffusion of the results of our research through the networks they would be strengthening in the region, and the work on climate models. Both PROINPA and CIRNMA are institutions that are committed to the development of their regions. Our collaborative research activities would strengthen both their and our research capacity. CIP has collaborative relations with both institutions. We have established collaboration with CIRNMA (see letter of collaboration) and are pursuing a similar relationship with PROINPA, as they are the institution that will be working at Patacamaya, site where the Instituto Boliviano de Tecnología Agropecuaria worked. The latter is going through reforms and will collaborate with PROINPA.

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