Employers use OSHA form 300 to record each incident, including the employees name, job title, date, brief description of the incident, days absent, and other pertinent data. Employers sum the numbers within categories each year. The BLS, Office of Safety, Health, and Working Conditions, surveys roughly 250,000 firms and state and local government agencies, collecting annual OSHA form 300 summaries and compiling them into SOII. Based on these data, the BLS Safety Office publishes annual estimates for numbers of non-fatal injuries and illnesses, employment, and incidence rates within detailed industries including crop and animal farms. Our data on injuries and illnesses are drawn directly from SOII. Our employment data are drawn from QCEW. Incidence rates are for full-time equivalent workers. The Safety Office estimates FTE workers using numbers of injuries and illnesses from SOII, employment from QCEW , annual work hours from SOII, and a formula that defines full-time employment as 2,000 work hours per year.QCEW employment data “are derived from the quarterly tax reports submitted to State workforce agencies by employers, subject to State unemployment insurance laws” as well as federal agencies. QCEW does not explicitly exclude farms with <11 employees. Nevertheless, some state laws do not require farms with <10 employees to provide unemployment insurance ,maceta de 30 litros and these small farms may not be included in QCEW counts.
The state with the largest farm worker employment, California, requires UI, even for small farms. QCEW nevertheless recognizes that limitations to its ability to capture all employment within agriculture. QCEW estimates it misses 0.2 million employees in all agricultural industries combined and captures 1.2 million, suggesting it misses 14.3% of farm workers. In 2011, for crop farms in SOII, the estimate for number of injuries and illnesses was 19,700; the employment estimate was 413,800; the case rate was 5.5 cases per 100 FTE. For animal farms, the corresponding numbers were 12,400 injury or illness cases, 163,600 employed, and 6.7 cases per 100 FTE. The 2011 QCEW numbers for employment were 531,245 for crop and 230,610 for animal farms. Our first methodological adjustment was to increase the SOII injury and illness cases estimates in proportion to the difference in the SOII and QCEW employment estimates. For crops, the SOII estimate of 413,800 employed persons must be multiplied by 1.2838 to bring it up to the QCEW estimate of 531,245 employed persons. If we similarly inflate the number of SOII-reported injury and illness cases, the result is 25,291 cases. The same procedure was applied to animal farms and yielded 17,479 cases.The second methodological adjustment pertains to the QCEW underestimate of employment in agriculture.
The QCEW is likely to underestimate the number of employees in all industries, but especially in agriculture. In all industries, employers have an incentive to underreport numbers of employees because greater numbers will result in higher total payments for both unemployment and workers’ compensation insurance. This incentive is especially strong in agriculture because significant numbers of workers are undocumented — roughly 53% in crop farms. It is likely that undocumented workers are much less likely than documented workers to apply for unemployment compensation. In addition, our estimate of the under count is likely affected by varying UI statutes across states. Legal requirements on employers are not as strict for farms compared to other industries. In most states, UI only applies to farms with 10+ employees. BLS recognizes that there are limitations for the QCEW in measuring agricultural employment: “the QCEW program does provide partial information on agricultural industries… “. We therefore sought to adjust upward the QCEW estimates to reflect employment under counting. We could not find QCEW under counting estimates in agriculture in scientific journals. We used alternative QCEW data that estimated 0.2 million out of a total of 1.4 million were omitted from published QCEW tables. These data suggested that the QCEW estimates on which we rely missed 14.29% . This indicates that the observed figure should be multiplied by 1.1667 to yield the adjusted figure of 1.4 million employees. This adjustment used data from the BLS’s Current Population Survey provided by Steven Hipple. We calculated an adjustment factor for expected number of cases based on the fraction of the CPS participants. This fraction is divided by .
For CPS crop workers, of the total 966,000 participants, 634,000 are salary and wage workers; thus our adjustment factor is 966,000/634,000 = 1.5237. Our crop estimate from above that accounted for employees on farms with <11 employees as well as the QCEW underestimate of all agricultural workers was multiplied by 1.5237 and yielded 44,959 cases. This 44,959 estimate relied on the assumption that the case rate for farm owners and family members was the same as for wage and salary workers. A corresponding adjustment factor for animal production cases was also applied. Employers and employees may deliberately or carelessly not report an injury or illness.We refer to this as a behavioral rather than an institutional cause. Incentives for under reporting for employers may include a desire to reduce workers’ compensation insurance premiums, whereas employees may fear that reporting an injury may jeopardize their employment or may not be aware that they should report an injury. The extent of willful and negligent reporting is unknown, although there are estimates. An earlier review of the literature suggested an 11% to 59% rate for the SOII and a 28% to 75% rate for occupational conditions eligible for workers’ compensation coverage. More recent studies, described below, have generated estimates within these ranges. According to Boden and Ozonoffs analysis of six states, the SOII missed 27% – 57% due to willful and negligent under reporting. For Michigan, Rosenman et al estimated that the SOII missed 67.6%. Bonauto et al analyzed data from ten states and found 23% to 53% of cases were missed by the workers compensation system. Lakdawalla, Reville, and Seabury estimated workers compensation missed from 39% to 74% in their most recent years of analysis.
These two recent workers compensation studies therefore suggest a range from 23% to 74%. But if workers’ compensation systems are more complete than SOII, then the SOII likely missed more cases than previous estimates suggest. Following two earlier studies, we assumed an under reporting rate of 40%. Our sensitivity analysis allowed for a lower bound of 27% and an upper bound of 57% following Boden and Ozonoff. These might be low estimates given that such a high percentage of employees are undocumented. But our estimates assumed that undocumented workers would have reported cases at the same rate as BLS-SOII workers and the latter are likely to contain a high percentage of documented workers precisely because undocumented workers are less likely to report injuries and illnesses. We assumed, in other words,maceta plastico cuadrada that undocumented workers reported as frequently as documented workers before we took willful and negligent reporting into account. The 40% under reporting rate corresponded to a multiplication factor of 1/ = 1.667. For crop farms, the under reporting estimate was 1.667 × 44,959 = 74,932. The same factor was multiplied by the animal farm estimate.We also conducted a sensitivity analysis in which key assumptions were altered and new estimates were generated. These altered assumptions were included in five scenarios, each with one lower and one upper bound. The first scenario addressed the assumption that farms with <11 employees experienced the same case rate as farms with 11+ employees. This scenario used SOII data on 2011 case rates for farm establishments with 11–49 employees, 50–249 employees, 250–999 employees, 1000+ employees and all sizes combined. The SOII data display an inverted U-shape with establishments with the fewest and greatest number of employees with the lowest rates and establishments with 50–249 and 250–1000 employees with the highest rates. For the lower bound, we used the ratio of rates for establishments with employees 11–49 to the mean rate for all establishments. For crops this ratio was 4.8/5.5. The mean rate for all establishments was in the denominator because it corresponded to our assumption that farms with <11 employees had the same rate as farms with 11+ employees. For the upper bound, the ratio was the highest rate to the mean for all establishments. For crops, this ratio was 6.4/5.5. Because these adjustments were derived directly from injury and illness rates, they did not apply to the QCEW employment multiplication factors of 1.1238 and 1.4096 for crops and animal farms. For example, for the lower-bound for crops, we used 4.8/5.5 = 0.8727 or 87.27% of the original estimate for cases from farms with <11 employees. . The QCEW employment was 28.38% more than the SOII employment, so the 87.27% was applied to the 28.38% only and the adjustment factor was 1+0.2838×0.8727 = 1. 2477. The second scenario applied to the assumption that the QCEW missed 14.29% of worker employment and that the adjustment factor was 1/ or 1.1667. This 14.29% was drawn from the 2011 estimate of the QCEW employment under count. For the second scenario, we used QCEW estimates from 2010 and 2009.
In 2010, the estimate was 15.38% and an adjustment factor of 1.1818. In 2009, the estimate was 8.3% and used a multiplication factor of 1.0909. The third scenario involved the assumption that case rates were the same for farmers and family members as for employees. The preferred estimate above used employment data from the CPS; for example, for CPS crop workers, of the total 966,000 employment, 634,000 were salary and wage workers and the corresponding adjustment factor was 966,000/634,000 = 1.5237. Steven Hipple at the BLS provided us with standard errors and 90% confidence intervals for each CPS mean employment figure. Our interest, however, centered on the ratio of means . The standard error of a ratio requires information on the covariance between the numerator and denominator. But we do not have information on the covariance. We therefore applied 90% confidence intervals to numerators and denominators simultaneously. For example, for the upper bound for the ratio for crops, we added the upper limit to 966,000 and subtracted the lower limit from 634,000. For the upper bound for the ratio, we subtracted the upper limit from 966,000 and added the lower limit to 634,000. For the lower bound in crops, for example, the calculation was / = 1.3299 and 1.3299/1.5237 = 87.28% of the preferred estimate. . Our approach estimated the under count of nonfatal occupational injuries and illnesses on crop and animal farms utilizing data from the SOII, QCEW, CPS and assumptions from the literature. Whereas the SOII estimated 32,100 cases in 2011, we estimated 143,436, indicating that SOII missed 77.6%. A sensitivity analysis suggested the percent missed by SOII ranged from 61.5% to 88.3%. The reasons for this under count are straightforward, and, for the most part, readily acknowledged by BLS. We refer to these as institutional causes of the under count. First, the SOII explicitly excludes farms with < 11 employees, all self-employed farmers and family members. Second, SOII, QCEW, and CPS acknowledge data gathering problems from agriculture due to the transient nature of the work and the extent of employment accounted for by undocumented workers. These institutional causes account for nearly one-half of the under count. Third, there is considerable evidence that workers and employers in all industries under report cases due to willfulness and negligence. This third cause, which we label behavioral, accounts for a little over one-half of the under count. The QCEW is not the only data set with information on agricultural employment; the CPS and the Census of Agriculture also generate estimates. We preferred the QCEW because it serves as the basis for estimates in the SOII. It is nevertheless useful to compare employment estimates. The QCEW estimates 532,245 and 230,610 employees for crop and animal farms, respectively in 2011. In the Current Population Survey for 2011, for private sector employees, these numbers were 626,000 for crop farms and 447,000 for animal. Daniel Carroll recently analyzed Census of Agriculture data from 2007 and estimated 1,358,020 farm workers on crop farms and 434,953 on animal farms. But none of these estimates are for FTEs, and agriculture is well-known for transient and part-time work. Thus, each of these data sets, including the QCEW, have deficiencies. The CPS and Census of Agriculture data suggest an employment under count by the QCEW.