Heterogeneity in Production Structures and Efficiency: An Analysis of the Czech Food Processing Industry

Abstract

The present study analyses firm heterogeneity and sector‐specific technology. The theoretical model stands on the assumption of maximizing the return on capital and overcomes problems involved in simple profit maximization. The results show that a random parameter model with sector dummies and heteroscedasticity is the most appropriate model specification for distinguishing firm‐level and sector‐level efficiency and heterogeneity. The heterogeneity among firms as well as among sectors was found to be an important characteristic in Czech food processing. This holds for production technology as well as for technical efficiency. Moreover, the decomposition of total variance shows that intrasectoral differences in technologies are much more pronounced than the intersectoral differences. The differences in intrasector heterogeneity also suggest that the food processing industry will be subject to accelerated structural change in the coming years. Moreover, we found that on average the companies highly exploit their production possibilities. However, some companies cannot keep pace with competitors. Because leapfrogging does not appear to be present in selected industries (except for Milling), structural change is expected to occur in such a way that the most successful companies will strengthen their position.

Technical Efficiency in the European Dairy Industry: Can We Observe Systematic Failures in the Efficiency of Input Use?

“…High technical efficiency of the top 10% of food processors is a common feature for all countries in all analysed sectors. Similar findings were provided for Czechia byČechura and Hockmann [8] and Špička [11]. On the other hand, lower technical efficiency scores were estimated for the Czech food processing industry by Náglová and Šimpachová Petrová [7].…”

Productivity and Efficiency in European Milk Production: Can We Observe the Effects of Abolishing Milk Quotas?

“…According to Karagiannis et al [58], any IDF is concave in inputs and quasiconcave in outputs if the Hessian matrix of the second-order IDF's parameter derivative is negative-definite with respect to outputs and positive-definite with respect to inputs, at the point of approximation. AsČechura and Hockmann [59] noted, this is fulfilled on the sample mean if β jj + β j 2 − β j ≤ 0 for all j. Since all these conditions are met, the estimated input-distance functions seem to well approximate the production behaviour of farmers in selected European countries.…”

The impact of technical efficiency on firms’ value: The case of the halal food and beverage industry in selected countries

“…Those classified as current assets include cash and cash equivalents, receivables, short-term investments, inventory, and prepaid expenses. Previous research results showed that higher current assets owned by the company impact the level of technical efficiency of the company, which can be seen from the t-ratio: if it is higher than the p-value (5%), it means the current asset gives significant effect through firm efficiency [10,12,28,38,39,41,42].…”

“…In the measurement of TE, there are provisions for the input-output selection approach. This study uses a production approach, referring to the research of [38][39][40][41][42]. The selection of input variable in this study includes current assets, fixed assets, liabilities, and capital.…”

“…Other sources classified as capital are treasury stocks and other comprehensive profit accumulations. Capital has a positive effect on technical efficiency, where when capital increases, the company becomes more efficient, as can be seen through the t-ratio: if it is bigger than t-value (5%) the variable is extremely significant [10,28,38,40,42].…”