The Ricardian approach is a popular hedonic method for analyzing climate change impacts on agriculture. The approach typically relies on a cross-sectional regression of farmland asset prices on fixed climate variables, making it particularly vulnerable to omitted variables. I conduct a long-spanning Ricardian analysis of farmland prices in the eastern United States (1950–2012) and find a convergence of evidence indicating that large estimates of climate change damages for recent cross-sections (>1970s), also found in the literature, can be explained by the growing influence of omitted factors extraneous to the agricultural sector. I propose and evaluate a simple strategy to circumvent such nonfarm influences in the form of a Ricardian model based on cash rents (2009–2016), which better reflect agricultural profitability and do not capitalize expected land use changes. The new damage estimates on nonirrigated cropland and pasture rents are more optimistic and cannot be distinguished from zero. However, estimates remain imprecise under extreme climate change scenarios pointing to a cautionary long-term outlook for United States agriculture. The findings are robust to multiple checks and alternative explanations.

Debate over the implementation of food assistance programs and the role of in-kind food aid has intensified in recent years. Within that context, we study a randomized control trial of rural communities in Yemen. From 2011 to 2012, poor households in half of the communities received assistance in the form of in-kind food (wheat flour and oil), and households in the other half received an equal valued cash transfer. On average, those that received cash exhibited greater dietary diversity, with differences driven largely by increases in consumption of protein-rich foods like meat and fish. However, food households consumed, on average, approximately 150 more calories per person per day than cash recipients, due largely to higher wheat flour and oil consumption. Modality type did not significantly affect non-food consumption, including usage of qat, a mildly narcotic leaf consumed widely in Yemen, and cash cost less to deliver than food.

Understanding the determinants of agricultural productivity requires accurate measurement of crop output and yield. In smallholder production systems across low- and middle-income countries, crop yields have traditionally been assessed based on farmer-reported production and land areas in household/farm surveys, occasionally by objective crop cuts for a sub-section of a farmer’s plot, and rarely using full-plot harvests. In parallel, satellite data continue to improve in terms of spatial, temporal, and spectral resolution needed to discern performance on smallholder plots. This study evaluates ground- and satellite-based approaches to estimating crop yields and yield responsiveness to inputs, using data on maize from Eastern Uganda. Using unique, simultaneous ground data on yields based on farmer reporting, sub-plot crop cutting, and full-plot harvests across hundreds of smallholder plots, we document large discrepancies among the ground-based measures, particularly among yields based on farmer-reporting versus sub-plot or full-plot crop cutting. Compared to yield measures based on either farmer-reporting or sub-plot crop cutting, satellite-based yield measures explain as much or more variation in yields based on (gold-standard) full-plot crop cuts. Further, estimates of the association between maize yield and various production factors (e.g., fertilizer, soil quality) are similar across crop cut- and satellite-based yield measures, with the use of the latter at times leading to more significant results due to larger sample sizes. Overall, the results suggest a substantial role for satellite-based yield estimation in measuring and understanding agricultural productivity in the developing world.

Grant, C.W. and Mann, J.M. Applied Economics for Agribusiness. John Wiley and Sons 2018.

Cash transfersimpact evaluationlabor supplylivelihoodsproductive impactsrisk managementsub-Saharan Africa

Price discovery is the incorporation of information to prices through the actions of traders. Previous studies in financial markets have found evidence that informed traders may submit limit orders instead of market orders as part of their trading strategies. If so, the steps of limit order book (LOB) beyond the best bid and best ask spread (BAS) may contain valuable information and contribute to price discovery of the underlying asset. This is the first attempt to examine the informativeness of the LOB beyond the BAS for agricultural commodities. We reconstruct the LOB using market depth data and use three information share approaches to test to what extent the steps of LOB beyond the BAS contribute to price discovery. This is done for five major agricultural commodities, namely live cattle, lean hogs, corn, wheat, and soybeans, as well as the E-mini Standard and Poor's 500 Index (S&P 500) futures contracts. The results show that the steps of the LOB beyond the BAS contribute by over 27% to price discovery of futures contracts. Across agricultural commodities, the steps of the LOB beyond the BAS have more information for grains than meats. Moreover, beyond the BAS, the steps closer to the top of the book contain more information for livestock and E-mini S&P 500. For grains, the steps farther from the BAS are as informative as the steps closer to the BAS. These findings suggest that informed traders in futures electronic markets actively use limit orders with price steps beyond the BAS.

The text in the article “Policy Shocks and Market-Based Regulations: Evidence from the Renewable Fuel Standard” described all sample quantile (SQ) tests as two-sided hypothesis tests whereas the authors' Stata code implemented one-sided tests. While none of the authors' point estimates change, several of their significance levels do when the code is corrected. The conclusions remain the same. Updated tables are included below and updated code is available on Gabriel Lade’s website. The authors regret this error, and thank Arthur R. Wardle from Utah State University for bringing the error to their attention.

Agricultural economists frequently employ hurdle models to estimate the determinants of truncated outcomes such as market participation and adoption. A pervasive belief is that restrictions can be placed on hurdle models to test whether the decisions made in the underlying data-generating process occurred sequentially or simultaneously. This article argues against the ability to draw this conclusion and further submits there is a negative correlation between failing to reject these restrictions and sample size. Evidence to support both proposals comes from data collected in a natural setting, as well as simulated data with a known data-generating mechanism.

We utilize human resources data from The Ohio State University to assess the gender wage gap. We find a persistent gap of 11% among regular, tenure-track faculty after accounting for fiscal year, race, clinical appointments, experience, and department. While the presence of a statistically significant gender wage gap is robust, the magnitude of the gap varies substantially depending on how the sample of interest is defined. In assessing gender wage gaps, researchers and universities must be attentive to issues of attrition and classification. Transparency regarding how estimates are affected by sample exclusions and variable definitions will yield insight into possible sources of gender bias.

The impact of risk management on farm productivity is still being debated. Using survey data from French and Hungarian farms, we estimate the impacts of different risk management strategies and portfolios under varying levels of risk on total factor productivity. Results from a multinomial endogenous switching regression model show that the impacts can be positive or negative, depending on the risk management strategies adopted, the structure of the farming system, and the probability of risks. The choice of risk management strategies influences the farm’s production costs and the allocation of resources. More complex risk management portfolios tend to have larger negative productivity impacts due to higher costs and the larger amount of resources subtracted from the production activity. Our results have important implications for risk management policies.

The “right to food” has been formally implemented in some countries and, in other contexts, it is used as an exhortation for governments or other entities to take actions to reduce food insecurity. Central to any comprehensive set of policies to reduce food insecurity are food assistance programs directed towards vulnerable households. One example of such a food assistance program is in the United States, the Supplemental Nutrition Assistance Program (SNAP, formerly known as the Food Stamp Program). I begin by discussing one measure of a right to food, namely, to be free from food insecurity and then turn to a consideration the role of SNAP in meeting this goal. To do so, I cover five components that would seem to be essential to any definition of a right to food and how SNAP does and does not meet these components.

This paper explores the interplay between the biophysical and economic geographies of climate change impacts on agriculture. It does so by bridging the extensive literature on climate impacts on yields and physical productivity in global crop production, with the literature on the role of adaptation through international trade in determining the consequences of climate change impacts. Unlike previous work in this area, instead of using a specific crop model or a set of models, we employ a statistical meta-analysis that encompasses all studies available to the IPCC-AR5 report. This permits us to isolate specific elements of the spatially heterogeneous biophysical geography of climate impacts, including the role of initial temperature, differential patterns of warming, and varying crop responses to warming across the globe. We combine these climate impact estimates with the Global Trade Analysis Project model of global trade in order to estimate the national welfare changes that are decomposed into three components: the direct (biophysical impact) contribution to welfare, the terms of trade effect, and the allocative efficiency effect. We find that when we remove the spatial variation in climate impacts, the terms of trade impacts are cut in half. Given the inherent heterogeneity of climate impacts in agriculture, this points to the important role of trade in distributing the associated welfare impacts. When we allow the biophysical impacts to vary across the empirically estimated uncertainty range taken from the meta-analysis, we find that the welfare consequences are highly asymmetric, with much larger losses at the low end of the yield distribution. This interaction between the magnitude and heterogeneity of biophysical climate shocks and their welfare effects highlight the need for detailed representation of both in projecting climate change impacts.

We report new estimates of beekeeper costs and revenues, which include major activities undertaken by beekeepers, including honey producers and pollinators. We use our cost estimates, recent government surveys and other United States Department of Agriculture information to characterize supply functions for (1) pollination services to crops that bloom in the late winter (dominated by almonds), (2) pollination services to crops that bloom in the spring and summer, and (3) honey produced in the United States. The positions and shapes of these supply functions are crucial to understanding how the honeybee industry will respond to changes in demand for pollination services and other market conditions, including shifts in honey demand, honey import supply, and forage availability affected by climate change.

The decline of European honey bees (Apis mellifera) has been a prominent part of supporting pollinator conservation among the public and conservation efforts, even while honey bees are not native to North America and may compete for resources with native insect pollinators. However, little is known about what distinguishes support for native insect pollinators, including solitary bees, the majority of native bees, which provides use and non-use values distinct from honey bees even though some natives have faced even more precipitous die-offs. Using data collected from the general public and beekeepers in Louisiana, we adopt a contingent valuation method to investigate the value of conserving solitary bees. Results suggest modest to moderate positive willingness to pay for solitary bee conservation, and possibly higher willingness to pay among honey beekeepers versus the general public. Significant heterogeneity exists between the general public and beekeepers in terms of their knowledge and attitudes of honey bees and other pollinators.

Over the last two decades, the number of honey bee colonies performing pollination services for the California almond industry has grown steadily and now equals a substantial share of all colonies in the United States. Most US beekeeping operations have not expanded their colony numbers at the current levels of almond pollination fees. Thus, as almond acreage has increased, the marginal supplier of colonies has moved further away from California, increasing interstate shipments. We provide a conceptual representation of the supply and demand of U.S. colonies for almond pollination, and utilize the relatively inelastic demand for colonies to explore spatial elasticities of supply. We combine colony shipment data from 2007 to 2018 provided by the California Department of Food and Agriculture with projected prices from the California State Beekeeper’s Association pollination fee survey. We use a geographically weighted regression to estimate supply elasticities for each state, and provide supporting regional estimates. The eastern United States, where beekeepers have hesitated to participate in almond pollination due to relatively high transportation costs and the potential for local honey production at the time of almond bloom, have some of the highest price elasticities of supply. This suggests that beekeepers in areas with low transportation and/or opportunity costs have supplied all available colonies, and increases in almond pollination fees have had little effect. We estimate that Florida, Georgia, and Texas had the largest number of colonies that did not participate in almond pollination in 2017, so further increases in supply are likely to come from those states.

Child dietary diversity is poor in much of rural Africa and developing Asia, prompting significant efforts to leverage agriculture to improve diets. However, growing recognition that even very poor rural households rely on markets to satisfy their demand for nutrient-rich non-staple foods warrants a much better understanding of how rural markets vary in their diversity, competitiveness, frequency and food affordability, and how such characteristics are associated with diets. This article addresses these questions using data from rural Ethiopia. Deploying a novel market survey in conjunction with an information-rich household survey, we find that children in proximity to markets that sell more non-staple food groups have more diverse diets. However, the association is small in absolute terms; moving from three non-staple food groups in the market to six is associated with an increase in the number of non-staple food groups consumed by ∼0.27 and the likelihood of consumption of any non-staple food group by 10 percentage points. These associations are similar in magnitude to those describing the relationship between dietary diversity and household production diversity; moreover, for some food groups, notably dairy, we find that household and community production of that food is especially important. These modest associations may reflect several specific features of our sample which is situated in very poor, food-insecure localities where even the relatively better off are poor in absolute terms and where, by international standards, relative prices for non-staple foods are very high.

We introduce a model that incorporates two important elements to estimating welfare gains from groundwater management: stochasticity and a spatial stock externality. We estimate welfare gains resulting from optimal management under uncertainty as well as a gradual stock externality that produces the dynamics of a large aquifer being slowly exhausted. This groundwater model imposes an important aspect of a depletable natural resource without the extreme assumption of complete exhaustion that is necessary in a traditional single cell (bathtub) model of groundwater extraction. Using dynamic programming, we incorporate and compare stochasticity for both an independent and identically distributed as well as a Markov chain process for annual rainfall. We find that the spatial depletion of the aquifer is significant to welfare gains for a parameterization of a section of the Ogallala Aquifer in Kansas, ranging from 2.9% to 3.01%, which is larger than those found previously over the region. Surprisingly, the inclusion of stochasticity in rainfall increases welfare gains only slightly.

The rise in drug overdose deaths in the United States since the turn of the millennium has been extraordinary. A popular narrative paints a picture whereby opioid overdoses among white, male, less-educated, rural workers have been caused by reduced economic opportunities borne by such people. In this article, we causally test the validity of this theory by using Bartik-type variables to explore the relationship between local economic conditions and county opioid overdose death rates. We add to the literature by exploring how both employment and wage growth in different types of industries are related to opioid overdose deaths for the population as a whole, as well as for rural (vs. urban), male (vs. female) and white (vs. black) populations. We find mixed evidence. Our results confirm that wage and employment growth in industries more likely to employ low-skill workers are important protective factors for rural, white males. However, we also find evidence that economic improvements in low-skill industries are just as important in protecting blacks and women against opioid overdoses, and for workers in metro counties. We also find evidence that employment growth in high-paying industries has led to increases in opioid overdoes rates.

The obesity epidemic and excessive consumption of sugar-sweetened beverages have led to proposals of economics-based interventions to promote healthy eating in the United States. Targeted food and beverage taxes and subsidies are prominent examples of such potential intervention strategies. This paper examines the differential effects of taxing sugar-sweetened beverages by calories and by ounces on beverage demand. To properly measure the extent of substitution and complementarity between beverage products, we developed a fully modified distance metric model of differentiated product demand that endogenizes the cross-price effects. We illustrated the proposed methodology in a linear approximate almost ideal demand system, although other flexible demand systems can also be used. In the empirical application using supermarket scanner data, the product-level demand model consists of 178 beverage products with combined market share of over 90%. The novel demand model outperformed the conventional distance metric model in non-nested model comparison tests and in terms of the economic significance of model predictions. In the fully modified model, a calorie-based beverage tax was estimated to cost $1.40 less in compensating variation than an ounce-based tax per 3,500 beverage calories reduced. This difference in welfare cost estimates between two tax strategies is more than three times as much as the difference estimated by the conventional distance metric model. If applied to products purchased from all sources, a 0.04-cent per kcal tax on sugar-sweetened beverages is predicted to reduce annual per capita beverage intake by 5,800 kcal.

Nearly 15% of all U.S. households and 40% of near-poor households were food insecure in 2009. The Supplemental Nutrition Assistance Program (SNAP) is the cornerstone of federal food assistance programs and serves as the first line of defense against food-related hardship. This paper measures the effectiveness of SNAP in reducing food insecurity using an instrumental variables approach to control for selection. Our results suggest that receipt of SNAP benefits reduces the likelihood of being food insecure by roughly 30% and reduces the likelihood of being very food insecure by 20%.

A censored Exact Affine Stone Index incomplete demand system is estimated for 23 packaged foods and beverages and a numéraire good. Instrumental variables are used to control for endogenous prices. A half-cent per ounce increase in sugar-sweetened beverage prices is predicted to reduce total calories from the 23 foods and beverages but increase sodium and fat intakes as a result of product substitution. The predicted decline in calories is larger for low-income households than for high-income households, although welfare loss is also higher for low-income households. Neglecting price endogeneity or estimating a conditional demand model significantly overestimates the calorie reduction.

This article presents a statistical model of agricultural yield data based on a set of hierarchical Bayesian models that allows joint modeling of temporal and spatial autocorrelation. This method captures a comprehensive range of the various uncertainties involved in predicting crop insurance premium rates as opposed to the more traditional ad hoc, two-stage methods that are typically based on independent estimation and prediction. A panel data set of county-average yield data was analyzed for 290 counties in the State of Paraná (Brazil) for the period of 1990 through 2002. Posterior predictive criteria are used to evaluate different model specifications. This article provides substantial improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations where data are limited.

We construct panel price indexes using retail scanner data that allow comparisons of consumption cost across space and time. Two types of panel indexes are examined: the rolling-window panel extensions of the multilateral Cave-Christensen-Diewert (CCD) index with the Törnqvist index as its elements, and of the multilateral Gini-Eltetö-Köves-Szulc (GEKS) index using the Fisher ideal index as its elements. The rolling window method maintains the nonrevisability of published index numbers while it allows index numbers for new periods and locations be calculated and the basket of items be updated. Meanwhile, the multilateral structure of price comparison eliminates significant downward drift in standard chained indexes. Using county-level bilateral and panel indexes based on retail beverage scanner data, we experimentally adjust for purchasing parity the portion of Supplemental Nutrition Assistance Program (SNAP) benefits that participants spend on beverages. Accounting for temporal and spatial cost differences causes over 2% of SNAP allotment spent on beverages be reallocated, or approximately a 5% change in allotment on average for a county. About 90% of the relocated SNAP fund is to adjust for spatial differences in food cost. We also compare SNAP allotments implied by the retail scanner data indexes with those implied by indexes based on the USDA Quarterly Food-at-Home Price Database (QFAHPD). The treatment of unit values and product quality may have contributed to the significant differences observed between the retail scanner data indexes and the QFAHPD indexes.

This study tests the hypothesis that fertility is affected differently by economic growth depending upon the specific sector (agriculture, manufacturing, heavy industry, and services) where growth occurred. The hypothesis is that fertility responses are not identical across sectors. The sample includes 51 World Bank member countries in varying stages of development. The econometric model pertains to 1965-88 and the percentage change in the total fertility rate (TFR). During the study period the average TFR declined by over 22%, but the extent of change varied by country and included, for instance, countries such as Ethiopia that experienced fertility increases from 5.8 to 6.5. Hong Kong's TFR declined by 66% from 4.7 to 1.6. Analysis included measures of changes in gross domestic product (GDP) for each of the four sectors and change in real per capita exports in agricultural commodities, resources, and manufactured products. Changes in educational status and changes in infant mortality were also included in some models. There were mixed results for the impact of total GDP. Sectoral analysis shows a positive, small significant impact on TFR from changes in the GDP per capita in agriculture (domestic and export products), and a negative, small significant impact from manufacturing growth. Heavy industry and services produced insignificant impact. In the model with only domestic consumption, results show a stronger coefficient and continued significance for agricultural productivity, agricultural exports, and manufacturing changes per capita. Manufacturing exports produced a negative, insignificant impact. The null hypothesis is rejected only in models comparing aggregate GDP in agriculture and manufacturing industries plus control variables (excluding heavy industry and services). Only secondary education was a negative, significant determinant of fertility. Infant mortality was insignificant when sectoral growth and education were included in the model. The evidence supports the thesis that growth depending on the sector leads to fertility decline, and economic growth has a negative effect on fertility if employment opportunities for women are improved.

This article discusses the impact of structural adjustment programs (SAPs) on women farmers in developing countries. SAPs aim to improve economic efficiency and promote more rapid economic growth. SAPs are introduced in two phases. The first phase involves short-term loans with the condition that the country adopt monetary restraints and currency devaluation measures. In the second phase, long-term loans are given with the provision that the country deregulate their economy and open up markets. The agricultural sector is affected by SAPs because of their importance in employment, income generation, and export earnings. SAPs result in lower farm commodity prices due to currency devaluations and in removal of subsidies, which results in market-sensitive pricing or higher food prices. The impact of SAPs on agriculture vary between countries. In Morocco and Algeria, agriculture expanded under SAPs. In Indonesia, Bolivia, Costa Rica, and Mexico, the agriculture stagnated or declined. Agricultural growth was slowest in Africa. SAPs were somewhat successful in increasing agricultural exports. Food production grew slowly in many adjusting countries. Blame for failures of SAPs has been placed on government failure to implement reforms properly and overly optimistic assumptions about the timing of productive gains. Little attention has focused on the constraints facing women farmers, who are a large proportion of farmers, particularly in sub-Saharan Africa. This article focuses on the issues of limited access to resources, credit, agricultural extension and information, land ownership, education, and time as constraints to women farmers. Women also must ensure household food security. For SAPs to work effectively, complementary policies must be implemented that reallocate available productive resources and new technologies to women and that deal with women's constraints.

The author analyzes the relationship between population and the environment, with a focus on "the role which environmental degradation and natural resources depletion may play in producing the...population pressure which lies behind such degradation and depletion especially in developing countries.... The principal conclusion of this analysis is that the possibilities for a stable equilibrium between human population and its environment are quite limited....I show that parental altruism toward their children can only make matters worse, if socially unchecked, by leading to an increase of the birthrate in every environmental state in comparison with that which would occur in its absence."

This article reviews the emerging trends in global food supply and demand up to 2020, and discusses policy challenges and obstacles to meeting this demand. Data were obtained from the International Food Policy Research Institute's International Model for Policy Analysis of Commodities and Trade (Rosegrant et al.). The country-specific data pertains to 37 countries and regions and 17 food commodities and prices in the world market. Cereal prices are expected to decline by about 11% by 2020; meat prices may decline by 6%. After 2010, cereal prices are expected to dramatically decline. Cereal demand will change with changes in income and urbanization. Maize and coarse grains will be replaced by wheat and rice. Life style changes may lead to a switch from rice to wheat. Growth in food consumption in developed countries will slow. A projected 82% of growth in global cereal consumption and almost 90% of increased global meat demand will occur in developing countries during 1993-2020. Asia alone will account for 48% of increased cereal consumption and 61% of increased meat consumption. 88% of food production growth will occur in developing countries through increased yields and 94% in developed countries. World trade in cereals will increase from an estimated 185 million metric tons annually to 328 million during 1993-2020. Food security for the poor and child malnutrition will remain unimproved. Yield growth is affected by agricultural research, fertilizer and energy use, land degradation, water scarcity, and bad policy. Water scarcity is the most limiting on yield growth. Malnutrition problems present multiple challenges.

A large and growing body of literature has examined how agricultural households cope with risk. Much of the work has focused on which types of households are better able to smooth consumption, testing whether households with more resources and greater access to income-smoothing institutions, such as credit markets or well-functioning labor markets exhibit greater consumption smoothing. However, income shocks may have different effects upon different individuals within households, and differences in individual ability to smooth income or consumption may have welfare consequences which go beyond foregone income. The development of collective household models challenges the assumption that individuals within households maximize a single utility function. The assumption of income pooling has also been rejected in a growing body of empirical research on intrahousehold resource allocation. However, research on risk-pooling within households and differences in individual abilities to smooth consumption is relatively new. Selected papers are discussed.

Ejidos are communal holding groups of redistributed land expropriated (generally without compensation) from large private landowners during Mexico's post-1910 land reform. The model in this study of the "ejidal" system's influence on fertility differs from DeVany and Sanchez in providing more current data and including the following more detailed variables: the land area of ejidos and the number of ejidos, the need for children, male income, female income share, and social security coverage. The data pertains to states rather than municipalities. DeVany and Sanchez found that the ejidal system encouraged fertility, because having more children helped an ejido family retain land rights, increased its chances of gaining additional productive land, and gave it increased political power. Children also provided a means of intergenerational transfer of resources. The estimation results of this study revealed that the total proportion of land held as ejidos had a positive, significant effect on fertility. The ratio of ejidos to total number of farms was negative and significant. There was support for the hypothesis that the impact of ejidos land holdings and area was diminished when ejidos were dominant in the state. Fertility declined with the increase in unpaid workers per hectare of land. Elasticity functions were small: 0.075 on ejidal land, -0.222 on ejidal farms, and -0.045 on workers. A positive significant demographic effect on fertility was illiteracy. Infant mortality and female income share each had a negative, significant effect on fertility. Insignificant variables were male income, social security coverage, and the dummy for northern states. There have been changes in the Mexican ejidal system. These changes and the availability of farm labor are expected to reduce urban and rural fertility differentials.

The relation between household income, food intake, and nutritional status in less developed countries is examined, and a framework that explicitly relates household behavior patterns with public policy options designed to improve the nutritional status of the rural and urban poor is presented. For rural areas, nutritional and health status depends largely upon the levels of private inputs provided by households. In turn, level depends upon income. Consequently, increasing income may also lead to improvements in nutrition and health status. Regrettably, post-World War II development strategy in most developing countries has undervalued the potential contribution of agricultural development to economic development. Domestic economic policies practiced thus far have most probably had serious negative effects upon the nutrition and heal status of the poorest segments of developing nations. Economic development policy reform is therefore called for as a measure to alleviate rural poverty in developing countries.

The author discusses the role of residential preferences and the search for a better quality of life as determinants of urban-rural migration in the United States

An analysis of the impact of migration to the United States on the sending community and on the labor market in the receiving country is presented based on a case study of Las Animas, Mexico. "As the community becomes increasingly involved in migration, tendencies can be identified regarding changing migration patterns, class differentiation among villagers, impact of migration on village economy, and the changing role of Mexican workers in California labor markets. Results indicate the importance of social networks in determining the outcome of migration; while migration is individually rational, it is a factor of stagnation for village economy, and it helps reproduce segmented California labor markets."