Great Plains Project Historical Demography, Agricultural Census, and Economics (The Whole Kitchen Sink) Myron Gutmann Agricultural Landscapes in Transition Planning Workshop Tempe, December 2-4, 2002

Great Plains Project Research supported by Grant R01 HD33554 from the National Institute of Child Health and Human Development

Great Plains Project A Primer on Historical Data for Coupled Human-Natural Systems Aggregate Data (zip code?/county/state) –Population –Agriculture –Other Economic Activities –Weather/Climate Individual Level Population Data –Extent & Nature –Geographical Limitations

Great Plains Project Some data history: Population Census (since 1790) Good questions beginning 1850 (family census prior to 1850) Good tabulations by County for all years Digital data files exist for all years, complete (all tables) for Tabulated questions vary from year to year, excellent on population size and urban/rural, good on distribution by age, sex, origin, etc./best County Net Migration begins with decade

Great Plains Project Data history: Census of Agriculture since early 1800s Decennial , every five years present Good data begin 1880 (land use acreage), even better in 1925 Tabulations by county for all years Some digital data for most years, but coverage is sometimes scant (next slide)

Great Plains Project Agricultural Census Availability YearsGreat Plains All U.S All (decades) MuchVery Limited ( by late 2003) (mid-decades) MuchNone MuchSome All

Great Plains Project Other Useful Data Other economic censuses: manufacturing, trade, government-tabulated by county County business patterns since 1950s – employment Crop Reporting data (generally since 1950s) on areas, production, yields VEMAP weather history data since 1890s – ½ degree grid can be summarized to other geographies

Great Plains Project Individual-Level Census Data Public-Use Micro Data Samples (PUMS) allow individual- and family-level analysis –Tiny: 1900, 1910 (bigger samples coming) –1%: , 1920, (1930 later) –5%: Big limitation is geography: –Counties to 1930 –State Economic Areas/County Groups/PUMAs –State only in 1960

Great Plains Project Other Kinds of Useful Data Annual Data Points –Commodity Prices Historically significant spatial data –Soils Non-systematic data: –Aerial photographs since 1930s –State Censuses of Agriculture & Population (often mid- decade, from 1860s to 1930s) CSU Summaries of Agricultural Practices by MLRA for 20 th Century (For Century Model Use)

Great Plains Project Analytic Approaches to Quantitative Historical Data Descriptive/Cartographic Approaches –Draw maps –Tables/Graphs of Change –Simple comparisons Statistical Approaches –Space-time regressions with tests for autocorrelation –Time-series (Granger) causality tests Model-based approaches –Merging actual data with Model runs

Great Plains Project An Example: Do Urbanization and Suburbanization Lead to Loss of Land from Agriculture?

Great Plains Project Land Not in Farms, Million Acres Percent of Farmland Farm land use peaked in 1964; then it declined until 1982

Great Plains Project Land Not in Farms Key Dependent Variable DEFINITION: Difference Between County Area and Reported Land in Farms Unit of Analysis: 450 Counties in Great Plains Area Study Measurement problems exist

Great Plains Project Urban Encroachment Model Predominant Explanation Key Components –Counties Begin by Being Rural –Population Grows Over Time –Cities & Suburbs Consume Farmland An Alternative: Recreational Encroachment The question: does land use change vary in different kinds of counties?

Great Plains Project Land Transformation by Category Conclusion: Loss of farmland in and near urban areas, but also in rural areas. Why?

Great Plains Project Farm Abandonment/Agricultural Change Model Urban Encroachment does not fit well in very rural counties, so an alternate hypothesis is needed Key Components –Agricultural Economy Changes Over Time –Profitability Issues Lead to Marginal Land Being Taken Out of Production Less Often Examined than the Urban Encroachment model

Great Plains Project Which Model Works? A Multivariate Approach Pooled time series models, OLS Regression Independent Variables mostly measure change between agricultural censuses Split models –urban (about 20% of counties) –rural (about 80% of counties) Correction for Spatial Autocorrelation

Great Plains Project Parameter Estimates for the Pooled Data Fixed Effects Model: Similarities Same effects in different contexts

Great Plains Project Different Effects in different contexts Parameter Estimates for the Pooled Data Fixed Effects Model: Differences

Great Plains Project Descriptive Conclusions Decline of farmland in rural areas suggests other models that work independently of but simultaneously with urban effects. The conversion of land in farms in the Great Plains prior to 1992 mostly took place in the 1970s data still need to be analyzed. Public debate about the conversion of land away from agriculture has focused on urban sprawl as an explanation. A large amount of land has gone out of agriculture in counties with no urban places at all.

Great Plains Project Multivariate Results Nearly the same predictors are significant in both urban and rural areas. Some processes are linked to the conversion of land out of farms: changes in the size and number of farms, & more concentrated ownership. Land use: Numbers of cattle decline as land shifts away from farms, while increased cropland can be associated with decreases in total farmland. More population promotes conversion of farmland to other uses in urban contexts, while less is associated with loss of farmland in rural areas.

Great Plains Project Beyond the Data: What Drives Agricultural Land Use Change We always start with population density But what are the lags? And how does feedback work? Going further: what’s the role of other kinds of economic and social change? What’s local and what’s broader?

Great Plains Project Land and Life Cycle Are life cycle conditions (crucial to farm- level decision making) visible at higher levels of observation? We know rural America is aging. Do age composition and community life cycle alter land use? How can we see it if it is?

Great Plains Project Born to Farming? Farms are multigenerational, farm experience is crucial to entry. Few people from outside farm life enter the profession. Where does lifetime personal history fit in? As communities age, what are the implications for stewardship?

Great Plains Project Provocative Ideas & Questions about Demographic Drivers How do we go beyond population density? How do we incorporate local, national, global processes with the experiences of individuals? How do we fit the non-replacement of farmers into our models? What really matters? Land? People? History?

Great Plains Project Practical Questions about Data How much more digital data? How should the data be disseminated? How should analysis be done? How much interest in modeling? When are the data needed? When should we have the first workshop?

Great Plains Project The end