CONTEXT

This article examines the process of the transformation of agricultural systems in post-communist Central and Eastern European (CEE) countries. It focuses on the survival of large agricultural firms, known as corporate farms, during periods of economic liberalization, privatization, land reform, and the restructuring of economies and the agricultural sector. The survival of corporate farms plays a significant role in driving structural changes within the farming sector and facilitating the transition from centrally planned to market-driven farming systems in the respective countries.

OBJECTIVE

The study investigates the factors correlated to the survival of corporate farms based on cross-country data analysis for 17 CEE countries. The survival of corporate farms can be correlated with a combination of farm-specific characteristics, sector-specific factors within the agricultural industry, country-specific natural and other resource endowments, and external factors related to a conducive economic environment.

METHODS

The study examines the viability of corporate farms by utilizing a comprehensive dataset encompassing 17 CEE countries between 2007 and 2019. The accelerated failure time model is employed to estimate the survival probabilities of these farms. The study uses the Nelson-Aalen estimator to calculate the cumulative hazard function and Kaplan-Meier survival function. Additionally, the baseline estimation of the two-level mixed-effects Weibull accelerated failure time model is utilized. Furthermore, estimations are conducted under various assumptions regarding sample restriction to ensure the robustness of the results.

RESULTS AND CONCLUSIONS

We find remarkable differences in corporate farm survival rates among 17 CEE countries. We document that legal format, ownership structure, and corporate finance indicators are highly relevant to corporate farm survival. Estimations reveal the non-linear correlation between corporate-farm size and age and their survival. We show that agricultural factor endowments and agricultural trade openness exhibit statistically significant and economically meaningful correlations with the survival probability of the sample farms.

SIGNIFICANCE

Farm-, sector- and country-specific factors play a crucial role in agri-food production, as well as regional and global food security. Diverse agricultural system structures may be associated with distinct farm attributes, various agricultural sector- and country-specific factors, and diverse allocations of agricultural resources. Better agricultural factor endowments and a conducive macroeconomic environment can foster comparative advantages and enhance corporate farm viability and survival. The findings of this study may be of significance to scholars and practitioners who are interested in comprehending the shifts in agricultural farm structures within agricultural systems.

The Earth’s climate is projected to warm significantly in the 21st century, and this will affect human societies in many ways. Since sleep is a basic human need and part of everyone’s life, the question of how temperature affects human sleep naturally arises. This paper examines the effect of daily mean temperature on sleep duration using nationally representative Hungarian time use surveys between 1976 and 2010. Compared to a day with an average temperature of 5–10 °C, colder temperatures do not influence sleep duration. However, as daily mean temperatures rise, sleep duration starts to strongly decline. The effect of a hot (>25 °C) day is −13.3 minutes, but if preceded by a few other hot days, the effect is even stronger, −24.7 minutes. The estimated sleep loss is especially large on weekends and public holidays, for older individuals, and men. Combining the estimated effects with temperature projections of twenty-four climate models shows that the warming climate will substantially decrease sleep duration. The projected impacts are especially large when taking into account the effects of heatwave days. This study also shows that different groups in society are likely to be affected in significantly different ways by a warming climate.