Data on 376 farms were acquired from a direct mail questionnaire containing 31 questions. These farms were on a production testing program and employed one or more full time workers who spent 50% or more of their time with the herd. Characteristics on workers, farms, and working conditions were obtained. The average worker was 38.6 years, had 6.8 years of schooling, and 5.9 years of dairy experience prior to their last employment.. About 80% of the workers were married and had 3.6 children. Reasons why workers left dairy farms and where they go for employment were compiled on 262 workers. The average dairy farm had a herd of 69 cows, and 1.9 hired workers. Seventy-eight percent of the farms had loose housing, 71% pipeline milkers, 55% mechanical manure handling, and 32% mechanical silage feeding. Average working conditions on these farms were: starting hour, 5:00 am.; hour per day, 9.75; days off per month, 3; wages per month, $230.48, and benefits per month, $81.65. Farms that provided incentives, 37%; annual leave, 63% and advancement opportunities, 94%. / M.S.

Financial records from 63 farms on Virginia Agribusiness Management Association and 72 farms on North Carolina Farm Business Records Program from 1978 to 1981 were combined with annual Dairy Herd Improvement (DHI) records to determine relationships among management practices and farm profit between and within dairy herds. Herd effects were the largest source of variation (>45%) for most financial variables whereas year effects were smaller (<10%). Regressions within herds and years accounted for .7 to 8.5% and residual effects 8.6 to 56.8% of variation in financial measures. DHI variables had large components of variance due to herds (>40%), but year effects were not significant. Correlations between financial and production variables were estimated overall and after removing herd and year effects. Many differences in magnitude existed between levels of correlation. Standardizing herd management and year differences reduced relationships between financial and production variables. Time-series cross-sectional regression analyses to identify production variables predictive of net cash income, receipts, and expenses found nine production variables to be significant within herd and year in one or more equations. While not significant in all equations, year average milk and quadratic year average milk were the most important production variables influencing financial variables, as measured by standard partial regression coefficients. Results varied among production levels with a 1 kg increase in year average milk increasing net cash income $.25 per cow and total receipts $.20 per cow while decreasing total expenses $.05 per cow at low levels of production. At high levels of production, further increases in year average milk increased total receipts $.26 per cow and total expenses $.34 per cow with a net negative effect on net cash income of $.10 per cow. Differences among herds and years are responsible for most variation in financial variables. Relationships among financial and production variables within herds need to be considered when making management recommendations to dairymen. / M.S.