Tag: drainage for plants in pots

It is evident that there is less year-to-year variation in the national mean of temperature than precipitation

By using a panel of county level data and including county and state by year fixed effects, we rely on across county variation in county-specific deviations in weather within states. This means that our estimates are identified from comparisons of counties that had positive weather shocks with ones that had negative weather shocks, within the same state. Put in another way, this approach non-parametrically adjusts for all factors that are common across counties within a state by year, such as crop price levels. If production in individual counties affects the overall price level, which would be the case if a few counties determine crop prices, or there are segmented local markets for agricultural outputs, then this identification strategy will not be able to hold prices constant. The assumption that our approach fully adjusts for price differences seems reasonable for most agricultural products for at least two reasons. First, production of the most important crops is spread out across the country and not concentrated in a small number of counties. For example, McLean County, Illinois and Whitman County, Washington are the largest producers of corn and wheat, respectively, but they only account for 0.58% and 1.39% of total production of these crops in the US. Second, our results are robust to adjusting for price changes in a number of different ways. In particular, the qualitative findings are similar whether we control for shocks with year or state by year fixed effects.6 Returning to equation , consider the second term, which is the change in profits due to the weather-induced change in quantities. We would like to obtain an estimate of this term based on long run variation in climate, since this is the essence of climate change. Instead, our approach exploits short run variation in weather. Since farmers have a more circumscribed set of available responses to weather shocks than to changes in climate, it seems reasonable to assume that Short Run > Long Run. 7 For example, farmers may be able to change a limited set of inputs in response to weather shocks. But in response to climate change,plastic pots for planting they can change their crop mix and even convert their land to non-agricultural uses .

Consequently, our method to measure the impact of climate change is likely to be downward biased relative to the preferred long run effect. In summary, the use of weather shocks to estimate the costs of climate change may provide an appealing alternative to the traditional production function and hedonic approaches. Its appeal is that it provides a means to control for time invariant confounders, while also allowing for farmers’ short run behavioral responses to climate change. Its weakness is that it is likely to produce downward biased estimates of the long run effect of climate change.Agricultural Production. The data on agricultural production come from the 1978, 1982, 1987, 1992, and 1997 Censuses of Agriculture. The Census has been conducted roughly every 5 years since 1925. The operators of all farms and ranches from which $1,000 or more of agricultural products are produced and sold, or normally would have been sold, during the census year, are required to respond to the census forms. For confidentiality reasons, counties are the finest geographic unit of observation in these data. In much of the subsequent regression analysis, county-level agricultural profits are the dependent variable. This is calculated as the sum of the Censuses’ “Net Cash Returns from Agricultural Sales for the Farm Unit” across all farms in a county. This variable is the difference between the market value of agricultural products sold and total production expenses. This variable was not collected in 1978 or 1982, so the 1987, 1992, and 1997 data are the basis for our analysis. The revenues component measures the gross market value before taxes of all agricultural products sold or removed from the farm, regardless of who received the payment. Importantly, it does not include income from participation in federal farm programs, labor earnings off the farm , or income from non-farm sources. Thus, it is a measure of the revenue produced with the land. Total production expenses are the measure of costs. It includes expenditures by landowners, contractors, and partners in the operation of the farm business.

Importantly, it covers all variable costs . It also includes measures of interest paid on debts and the amount spent on repair and maintenance of buildings, motor vehicles, and farm equipment used for farm business. The primary limitation of this measure of expenditures is that it does not account for the rental rate of the portion of the capital stock that is not secured by a loan so it is only a partial measure of farms’ cost of capital. Just as with the revenue variable, the measure of expenses is limited to those that are incurred in the operation of the farm so, for example, any expenses associated with contract work for other farms is excluded.Data on production expenses were not collected before 1987. The Census data also contain some other variables that are used for the subsequent analysis. In particular, there are variables for most of the sub-categories of expenditures . These variables are used to measure the extent of adaptation to annual changes in temperature and precipitation. The data also separately report the number of acres devoted to crops, pasture, and grazing. Finally, we utilize the variable on the value of land and buildings to replicate the hedonic approach. This variable is available in all five Censuses. Soil Quality Data. No study of agricultural land values would be complete without data on soil quality and we rely on the National Resource Inventory for our measures of these variables. The NRI is a massive survey of soil samples and land characteristics from roughly 800,000 sites that is conducted in Census years. We follow the convention in the literature and use the measures of susceptibility to floods, soil erosion , slope length, sand content, clay content, irrigation, and permeability as determinants of land prices and agricultural profits. We create county-level measures by taking weighted averages from the sites that are used for agriculture, where the weight is the amount of land the sample represents in the county. Since the composition of the land devoted to agriculture varies within counties across Censuses, we use these variables as covariates. Although these data provide a rich portrait of soil quality, we suspect that they are not comprehensive. It is this possibility of omitted measures of soil quality and other determinants of profits that motivate our approach.

Climate Data. The climate and weather data are derived from the Parameter-elevation Regressions on Independent Slopes Model .This model generates estimates of precipitation and temperature at 4 x 4 kilometers grid cells for the entire US. The data that are used to derive these estimates are from the more than 20,000 weather stations in the National Climatic Data Center’s Summary of the Month Cooperative Files. The PRISM model is used by NASA,drainage for plants in pots the Weather Channel, and almost all other professional weather services. It is regarded as one of the most reliable interpolation procedures for climatic data on a small scale. This model and data are used to develop month by year measures of precipitation and temperature for the agricultural land in each county for the 1970 – 1997 period. This was accomplished by overlaying a map of land uses on the PRISM predictions for each grid cell and then by taking the simple average across all agricultural land grid cells.To replicate the previous literature’s application of the hedonic approach, we calculated the climate normals as the simple average of each county’s annual monthly temperature and precipitation estimates between 1970 and two years before the relevant Census year. Furthermore, we follow the convention in the literature and include the January, April, July, and October estimates in our specifications so there is a single measure of weather from each season. Table 1 reports county-level summary statistics from the three data sources for 1978, 1982, 1987, 1992, and 1997. The sample is limited to the 2,860 counties in our primary sample.Over the period, the number of farms per county declined from approximately 765 to 625. The total number of acres devoted to farming declined by roughly 8%. At the same time, the acreage devoted to cropland was roughly constant implying that the decline was due to reduced land for livestock, dairy, and poultry farming. The mean average value of land and buildings per acre in the Census years ranged between $1,258 and $1,814 in this period, with the highest average occurring in 1978. The second panel details annual financial information about farms. We focus on 1987-97, since complete data is only available for these years. During this period the mean county-level sale of agricultural products increased from $60 to $67 million. The share of revenue from crop products increased from 43.5% to 50.2% in this period. Farm production expenses grew from $48 million to $51 million. Based on the “net cash returns from agricultural sales” variable, which is our measure of profits, the mean county profit from farming operations was $11.8 million, $11.5 million, and $14.6 million or $38, $38, and $50 per acre in 1987, 1992, and 1997, respectively. The third panel lists the means of the available measures of soil quality, which are key determinants of lands’ productivity in agriculture. These variables are essentially unchanged across years since soil and land types at a given site are generally time-invariant. The small time-series variation in these variables is due to changes in the composition of land that is used for farming.

Notably, the only measure of salinity is from 1982, so we use this measure for all years. The final panels report the mean of the 8 primary weather variables for each year across counties. The precipitation variables are measured in inches and the temperature variables are reported in Fahrenheit degrees. On average, July is the wettest month and October is the driest. The average precipitation in these months in the five census years is 3.9 inches and 2.0 inches, respectively.Table 2 explores the magnitude of the deviations between counties’ yearly weather realizations and their long run averages. We calculate the long run average variables as the simple average of all yearly county-level measurements from 1970 through two years before the examined year. Each row reports information on the deviation between the relevant year by month’s realization of temperature or precipitation and the corresponding long run average. The first column presents the yearly average deviation for the temperature and precipitation variables across the 2,860 counties in our balanced panel. The remaining columns report the proportion of counties with deviations at least as large as the one reported in the column heading. For example, consider the January 1987 row. The entries indicate that 73% of counties had a mean January 1987 temperature that was at least 1 degree above or below their long run average January temperature . Analogously in October 1997, precipitation was 10% above or below the long run average in 95% of all counties. Our baseline estimates of the effect of climate change follow the convention in the literature and assume a uniform five degree Fahrenheit increase in temperature and eight percent increase in precipitation associated with a doubling of atmospheric concentrations of greenhouse gases .It would be ideal if a meaningful fraction of the observations have deviations from long run averages as large as 5 degrees and 8% of mean precipitation. If this is the case, our predicted economic impacts will be identified from the data, rather than by extrapolation due to functional form assumptions. In both the temperature and precipitation panels, it is clear that deviations of the magnitudes predicted by the climate change models occur in the data. It is evident that for all four months there will be little difficulty identifying the 8% change in precipitation. However in the cases of temperature, deviations as large as +/- 5 degree occur less frequently, especially in July. Consequently, the effects of the predicted temperature changes in these months will be identified from a small number of observations and functional form assumptions will play a larger role than is ideal.

Consolidation reduced the number of input suppliers available to growers

Events were gradually righting a badly tossed sector when the 1987–1992 drought appeared on the horizon to ultimately affect all California agriculture. This was yet another severe shock to the system. In particular, the west side of the San Joaquin Valley was pummeled by a nexus of water issues, e.g., reduced water supplies, inadequate off-farm drainage, and rising water tables, extending through the decade of the 1990s. Selenium toxicity in the Kesterson Wildlife Refuge was a harbinger of future environmental challenges. The 1990s Two additional early-decade shocks would impact agriculture in the 1990s. A four-year recession softened domestic demands and affected capital markets. The CVPIA in 1992 abruptly changed the political economy of federal water availabilities, curtailing water deliveries south of the Delta. Farms on the west side of the San Joaquin Valley were impacted financially as water became at once more expensive and scarcer because of both drought and regulatory change or, as some saw it, because of a combination of natural and regulatory droughts. Financially leveraged farms again faced foreclosure pressure. Lending institutions this time were quicker to secure and dispose of foreclosed assets. Quick disposal depressed the land market and the value of collateral assets to the chagrin of marginally solvent producers and firms. Weakening of Japanese and Asian economies again affected U.S. commodity exports. However, California’s specialty-crop exports were impacted to a lesser extent, and nut crops and grapes in particular enjoyed more favorable markets and prices. Large investments again appeared for perennial crops from investors and from growers seeking to broaden production portfolios to include higher-grossing crops.

Ample farmland was still available for these higher and better uses relative to production of field crops,drainage for plants in pots which was still plagued by the low prices of the early 1990s. By mid-decade, export markets were again strong, including those for basic field-crop commodities. In the main, prices strengthened for the products of California’s agricultural sector through 1996–97, with variations from commodity to commodity . Low interest rates continued to feed investments in permanent plantings. Producers of basic commodities enjoyed high export demand when new federal farm legislation was put in place in 1996. In the first year of the farm program, producers enjoyed healthy market prices and decoupled farm-program payments, but shortly thereafter economic fortunes again reversed. Within a couple of years, world economies again softened and farm prices were low across a wide spectrum of both basic and specialty commodities—and the domestic economy also faltered. An ex post doubling of federal program payments sought to shore up basic commodity producers. Acreage remained in production despite low prices. The ups and downs of the 1990s were also marked by significant structural change. Brand-name fruit and vegetable processors closed processing facilities. Other processing outlets disappeared. The bankruptcy of Tri Valley Growers in 1999 had a disastrous effect on producers already at the margin.Increased buyer concentration in fresh produce squeezed out many grower/shippers, placing more reliance on large firms capable of supplying customer needs on a year-round basis. With widespread and rapid changes in the competitive environment, product prices fell while production costs continued to rise, further squeezing production agriculture.

Contractual arrangements became increasingly critical to preserve shrinking margins. Some growers countered by integrating processing and marketing activities. Even though farm financial advisors had been more temperate regarding increasing debt loads, many growers and agribusiness firms experienced difficulty in continuing their farming operations.At the century’s end, California’s agricultural producers once again were seeking to stay upright while searching to reright their economic fortunes. The industry had witnessed significant change over the preceding three decades. The sector was more diverse in production and less dependent on field-crop and livestock production than in 1970. Contractual marketing arrangements for agricultural production were now the norm in this new, higher-valued production system, changing marketing channels and risk exposures of producers and contracting firms. Field crops, livestock, and livestock products contributed less than 20 percent to agricultural markets in 2000 whereas specialty crops now dominated—28 percent fruit and nut crops, 26 percent vegetables, and 11 percent nursery and greenhouse products. Dairy products alone contributed nearly 15 percent of the value of agricultural products sold in 2000. The sector was also more export-oriented. Despite a drop of 5 percent below peak levels in 1997, the value of California agricultural exports amounted to $6.6 billion in 2000. Agricultural commodities with ratios of farm quantity exported to farm quantity produced of 20 percent or more in 2000 included cotton lint ; almonds ; walnuts ; prunes ; dry beans ; grapefruit ; plums and rice ; apples, apricots, and onions ; oranges ; broccoli and fresh tomatoes ; dates and pistachios ; asparagus and cherries ; and cauliflower .

Competitive pressures increased for water resources throughout the state and for land in some areas, particularly in the northern San Joaquin and southern Sacramento Valleys. Environmental issues continued to command attention with more emphasis on in-stream water use, dairy-waste management, new chemical standards, water quality, and particulate matter concerns. With ample field-crop land and increased permanent plantings, values for open agricultural land for agricultural uses have remained relatively stable over the past decade. The major exceptions include varietal wine-grape vineyards in premium coastal areas, irrigated vegetable land on the south and central coast, and dependably watered, developable land in the San Joaquin Valley. The two dominant underlying forces affecting regional shifts in the location of agricultural production have been population growth and water-supply conditions. Rapid postwar and continuing urban and suburban population expansions forced relocation to interior valleys, first from the Los Angeles basin and later from the Central Coast and San Francisco Bay Area.A fuller appreciation of changes of the recent half century is the immediate precursor to an examination of the state of California agriculture as the industry enters the 21st Century. We first review the changing character of California agriculture from 1950 to 2000, focusing on major shifts in the structure of production , commodity composition, and geographic distribution. We then document the increasing importance of exports, followed by statistical information and financial indicators comparing California and aggregate national agriculture with respect to farm numbers, land in farms, farm real estate values, farm income, and selected financial ratios.Without doubt, the most significant structural changes of the half century were those that followed the addition of two major water projects that came online in this period. Together, the federal CVP and the California SWPT brought more than three million additional acres under irrigation. As shown in Figure 2, irrigated acreage grew from 4.3 million acres prior to WWII to 6.4 million at the start of the 1950s. Expansion, mostly from CVP supplies, increased irrigated acreage to 7.4 million in 1959 and subsequent increases, mostly from SWP deliveries, yielded 8.5 million acres in 1978. The most recent census indicated that there were 8.7 million acres of irrigated land in 1997.Expansion in irrigated production capacity plus rapid increases in productivity allowed California agriculture to experience very rapid growth in output at good prices until the early 1990s. Demand growth fueled by rising incomes and population growth kept California agriculture on a steep growth path. In constant 1996 dollars, the market value of agricultural products sold grew from $400 million in 1950 to nearly $27 billion in 1997 . The upward trend in the real value of agricultural production was tempered by short periods of decline—in the mid- 1970s and early 1980s and by economic recessions in the early 1990s and again at the end of that decade. However,30 litre pot within that overall picture of growth, there were significant changes in the composition of output, the importance of particular commodities, and the geographic location of production.The shares of the value of agricultural product sales coming from plant and animal products changed persistently over the past 50 years.

As shown in Figure 4, crops made up 61 percent of sales in 1950 while livestock accounted for 39 percent.The shares remained relatively constant throughout the 1950s and 1960s with expansions both in crop production and livestock production . However, livestock shares then fell steadily so that in 2000 three-quarters of the value of California production came from plant production and only onequarter from livestock. The crop share in California was much higher than the U.S. average of roughly 50/50 and significantly different from European agriculture, where animal products generated approximately two-thirds of sales. Additionally, these broad trends hide significant changes that occurred within both the plant and livestock production categories. Figure 5 shows the shares of crop production made up by major crop categories: field crops ; fruits, nuts, and berries; vegetables and melons; and nursery and greenhouse products. Over 50 years, the field-crop share of total crop production fell steadily, dropping from 33 percent of value in 1950 to less than 10 percent in 2000. The share of intensive agricultural crops rose from 63 percent in 1950 to 77 percent of total crop products by 2000. Growth was most pronounced in nursery products . These latter trends no doubt reflected the shift in the preference of consumers with rising incomes toward fresh products, and phenomenal growth in urban populations. Shares also shifted significantly within the livestock sector. In 1950 poultry and poultry products made up about 23 percent of the value of production, dairy products constituted 26 percent, and meat animals represented 42 percent . Over the 50-year period, poultry’s share declined gradually to 16 percent. Cattle and calves increased very rapidly in the 1950s and 1960s as the large-scale feedlot boom hit California, rising to 49 percent of livestock value in 1970. Thereafter, the share of the beef industry steadily declined, approaching 20 percent of value in 2000. The value of dairy production approached 60 percent of total livestock production in 2000, doubling in importance from shares of 30 percent or less in the period 1950 to 1970. We attempt to explain some of the causes of these shifts in industry composition in the sections that follow.At the aggregate level, California agriculture seems to be fairly stable and growing rapidly ; but beneath the surface it is a caldron of perpetual change. Here, we look briefly at what commodities are important, followed in the next section by a discussion of where they are produced. Table 1 attempts to capture the dynamics of an ever changing commodity composition. Part A presents the top ten commodities in 1950 and what happened to their rankings over the next 50 years, and Part B presents the top ten commodities in 2000 and how their rankings changed over the past 50 years. Several trends stand out in Part B. Dairy has clearly supplanted beef as the number-one commodity and now holds a commanding lead over the second-ranked commodity, grapes. Cattle and calves, ranked first from 1950 to 1970, were ranked fifth in 2000. Field crops’ role in the top ten declined in relative importance. In 1950 four of the top ten were field crops —cotton , hay , barley , and potatoes . In 2000 only two field crops remained in the top ten —cotton and hay . Nursery products and flowers and foliage have come from relative insignificance to number three and number seven, respectively. Overall, products sensitive to rising incomes have grown in importance—grapes , nursery products, flowers, lettuce, strawberries, and almonds make up six of the top ten.The share of the total value of production accounted for by the top ten commodities has fallen, reflecting a much wider spectrum of high-valued commodities produced on California farms and ranches. The top ten commodities accounted for 66 percent of the total value of agricultural production in 1950 but only 61 percent in 2000.The majority of agricultural production takes place in just four of the eight agricultural production regions of California : Region 4 , Region 5 , Region 6 , and Region 8 .8 Major shifts of production among regions reflect progressively increasing demands for California products for both domestic and export markets, withdrawal of land from agricultural production because of population growth in temperate coastal areas , growth in higher-valued perennial and vegetable production displacing field-crop acreage in interior areas, and shifts within the Central Valley induced by surface-water deliveries.