Entry, Exit, and Structural Change in Pennsylvania's Dairy Sector

Abstract

Data on the number of Pennsylvania dairy farms by size category are analyzed in a Markov chain setting to determine factors affecting entry, exit, expansion, and contraction within the sector. Milk prices, milk price volatility, land prices, policy, and cow productivity all impact structural change in Pennsylvania's dairy sector. Stochastic simulation analysis suggests that the number of dairy farms in Pennsylvania will likely fall by only 2.0 percent to 2.5 percent annually over the next 20 years, indicating that dairy farming in Pennsylvania is likely to be a significant enterprise for the state in the foreseeable future.

Agricultural Policies and Structural Change in French Dairy Farms: A Nonstationary Markov Model

“…Results indicate that increased average milk production per cow increases the exit movement of farms in size class 40–99 cows and has a marginal impact on the largest size class (>100 cows) (very low probability elasticities to remain stable or exit). This result is consistent with previous studies, such as Stokes (), Rahelizatovo and Gillespie () as well as Chavas and Magand (), which use this variable to investigate the effect of economies of size on structural change and found the impact to be rather positive. Zepeda () found, by contrast, that technical change had no measurable impact on farm size.…”

“…Stokes () shows that optimal herd size inherits the Markov property. Then, he demonstrates that the Markov chain model of dairy farm size is an appropriate methodology for examining structural change and its effect on farm size (for more details, see Stokes ). The Markov model relates the observed size class distributions by transition probabilities describing the probability to move from one size class to another size class over time and so‐called Markov Transition Probabilities Matrix (TPMs) (Huettel and Jongeneel ).…”

Structure and future development of the service sector in Bangladesh

“…Table 4 presents the average transition probability matrix, where standard deviations of the transition probabilities across seven regions and 3 time periods showed by the small italic numbers below the mean probability values. This transition probability matrix presents a typical pattern like other study on transition probability matrix (Zimmermann, Heckelei, 2012;Stokes, 2006), where the highest diagonal values of the matrix indicate the high probability to employ in the same sector like as previous time. In addition, the probability matrix also reveals lesser variability over time than region, which indicates changing sector's employment in different regions is much higher than they change it over time.…”

“…Table 1. Share of broad sectors to GDP and growth rate during the period of 1980-2014Sectors 1980-19811985-19861990-19911995-19962000-20012005-20062010-20112011-20132013-2014 Source: BER (2014). Table 2 presents the GDP contribution of different sub-sectors under service sector.…”

The effects of the Common Agricultural Policy on exit strategies and land re-allocation

“…In fact, the study demonstrates that larger farms with breeding stock, primary sheep and dairy cattle, are more likely to continue farming. Stokes (2006) uses a Markov chain model for farm size to study the determinants of structural change in Pennsylvania's dairy sector. The simulation analysis includes both the exit and the expansion possibility for farms.…”