An analysis of factors affecting the profits of new firms in Spain: Evidence from the food industry

Using the logistic model, this article investigates the influence of financial factors on gaining profits for new firms in the Spanish food industry. Specifically, the firms founded separately during the crisis period and during the postcrisis period are observed for their first three years. The findings suggest that indebtedness (for both periods), previous profitability (for the postcrisis period) and accounts payable (for the crisis period) were most frequently statistically significant in the logistic model. Hence, for new firms, controlling debt burden, accumulating internally generated funds and using payables to establish business relationships can help to gain profits. Firm size and asset rotation were significant in the first year (especially during the postcrisis period), with a positive relationship to profits. Given that the food industry is highly competitive, enlarging firm size to reach efficiencies of scale and using a low-price strategy with high asset rotation to obtain market share are effective marketing strategies for new firms. This article contributes to the empirical studies about the financial effects on new firms' profits in the food industry; it can also help potential entrepreneurs make better decisions about starting new businesses and help to manage new firms better in different macroeconomic environments.

Interplay between environmental, social and governance coordinates and the financial performance of agricultural companies

On the complex framing of the agricultural fields, related to the corporate social responsibility (CSR), the general objective of this paper is to assess the impacts of environmental, social and governance (ESG) credentials of CSR and human capital features on the financial performance of agricultural companies. The data consists of a sample of 412 public companies from the Thomson Reuters Eikon database, with data for 2020, operating in 17 agricultural areas with headquarters allocated around the world. The methodological endeavor embeds two econometric procedures, multifactorial models of robust regression and structural equation modelling (SEM). The research results bring new evidence to underline the risks related to the sustainability of the financial performance of agricultural companies and the decisive role played by the ESG dimensions to counteract these risks, particularly by the environmental pillar, along with CSR specific strategies and human capital characteristics (management board and employees). We propose several strategies for companies operating in agricultural fields in order to enhance profitability by CSR measures.

Has the euro been fattening the European pig meat trade?

The introduction of the euro is one of the great achievements of the European integration process. We ask whether the creation of the euro led to a significant increase in pig meat trade in the eurozone. The pig meat industry is the most important in the European meat sector, and the EU is the world's second-biggest producer of pork and the leading supplier of pig meat to the global market. No study has yet been conducted in this respect for this sector. Our results suggest that pig meat trade was encouraged between countries sharing the euro, although the impact of EU single market was still greater. Trade creation was also observed, increasing pig meat exports from eurozone to non-eurozone countries. Also, non-eurozone EU exporters suffer from a diversion effect that benefits eurozone exporters.

Are soft commodities markets affected by the Halloween effect?

Within the last three decades commodity markets, including soft commodities markets, have become more and more like financial markets. As a result, prices of commodities may exhibit similar patterns or anomalies as those observed in the behaviour of different financial assets. Their existence may cast doubts on the competitiveness and efficiency of commodity markets. It motivates us to conduct the research presented in this paper, aimed at examining the Halloween effect in the markets of basic soft commodities (cocoa, coffee, cotton, frozen concentrated orange juice, rubber and sugar) from 1999 to 2020. This long-time span ensures the credibility of results. Apart from performing the two-sample t-test and the rank-sum Wilcoxon test, we additionally investigate the autoregressive conditional heteroskedasticity (ARCH) effect. Its presence in our data allows us to estimate generalised autoregressive conditional heteroskedasticity [GARCH (1, 1)] models with dummies representing the Halloween effect. We also investigate the impact of the January effect on the Halloween effect. Results reveal the significant Halloween effect for cotton (driven by the January effect) and the significant reverse Halloween effect for sugar. It brings implications useful to the main actors in the market. They may apply trading strategies generating satisfactory profits or providing hedging against unfavourable changes in soft commodities prices.

Factors affecting competition in olive oil exports: Panel data analysis of selected countries. Case study

Recently, the growing interest in healthy and organic nutrition has led to an increase in both the consumption and production of olive oil. The fact that olive and olive oil production is mostly concentrated in the countries with a coastline on the Mediterranean has rendered their olive oil exports important in meeting the increasing demand for olive oil. For the exporting countries, this has raised the issues of having a large share in the international olive oil market and increasing their competitiveness. The importance of increasing competitiveness, especially for countries that generate income from agricultural production, is the driving force for conducting this study. The aim of the study was to determine the factors affecting the comparative advantages of the leading olive oil-exporting countries. In this context, the olive oil production, consumption and unit export prices of Turkey, Spain, Italy, Portugal, Greece and Tunisia for the 2000–2019 period were tested with a panel data analysis method to ascertain whether these variables have any significant effect on the revealed comparative advantage (RCA) index. According to the findings, olive oil production affects the RCA index positively, whereas olive oil consumption affects it negatively in a statistically significant way.

One or many European models of agriculture? How heterogeneity influences income creation among farms in the European Union

Agricultural structures are quite heterogeneous across the European Union (EU), and it is likely that the underlying technology also differs across regions. In this article, we claim that the heterogeneity of agriculture across the EU affects the process of income creation (i.e. the relative importance of the factors of farm income differ for different agricultural models). A panel of farms representative for 125 regions reporting to the EU Farm Accountancy Data Network (FADN) during the period from 2007 to 2018 is used. In this article, those regions are grouped into three clusters. A system generalised method of moments (GMM) panel estimator is applied to each cluster. The results showed that total factor productivity (TFP), relative prices and agricultural subsidies make different contributions to farm net value added (FNVA). In particular, the income growth of farms in regions dominated by large farms seems to react more to marginal changes of the explanatory variables.

The butterfly effect in the price of agricultural products: A multidimensional spatial-temporal association mining

With the advent of the era of big data, data mining methods show their powerful information mining ability in various fields, seeking the association information hidden in the data, which is convenient for people to make scientific decisions. This paper analyses the butterfly effect in the agricultural product industry chain from the perspective of producer and consumer by using multidimensional time and space theory and proposes a new price forecasting method. We consider that the price change of agricultural products is not only affected by the balance of market supply and demand but also by the factors of time and space. Taking the pig industry chain of Sichuan Province as an example, this paper explores and excavates the data from 2010 to 2020 in the time dimension. Interestingly, we found that the price changes in pork in the market are generally highly correlated with the prices of slaughtered pigs, piglets a few weeks ago and the prices of multiple feed a few months ago. Based on the precise time-space factors, we improved the price forecasting model, greatly improved the accuracy of price prediction, and proved the effectiveness of multidimensional spatiotemporal association mining. The research in this paper is helpful to establish a brand-new agricultural product price prediction theory, which is of great significance to the development of the agricultural economy and global poverty alleviation.

Crude oil futures to manage the price risk of natural rubber: Empirical evidence from India

The trading of natural rubber derivatives in the Indian commodity exchanges was banned several times in the past. Hence, in India, the derivatives on natural rubber are not traded actively and regularly. We have examined the possibility of a forecast model and a cross hedge tool for the natural rubber price by using crude oil futures in India. Results of the Johansen cointegration test proved that there is no cointegration equation in the model; hence, there is no scope to develop long-run models or error correction models. We have developed a vector autoregressive [VAR(2)] model to forecast the rubber price, and we examined the possibility of a cross hedge for natural rubber further by using the Pearson correlation coefficient and Granger causality test. We have extended our research to a structural VAR analysis to examine the effect of crude futures and exchange rate shocks on the natural rubber price. Our results showed that there is a short-term relationship between the crude oil futures price, the exchange rates of the US dollar to the Indian rupee, the Malaysian ringgit to the Indian rupee and the Thai baht to the Indian rupee; and the natural rubber price in India. The effort of policymakers to cause the Indian rupee to appreciate against the Thai baht and Malaysian ringgit may increase the natural rubber price in India. Natural rubber traders, growers and consumers can use crude futures to hedge the price risk. The Indian Rubber Board can suggest the VAR(2) model to predict the short-run price for natural rubber.

Agricultural production trends towards carbon neutrality in response to the EU 2030 Green Deal: Economic and environmental analysis in horticulture

The European Green Deal to tackle climate change sets emission reduction targets for 2050. Particular attention has been paid to the agricultural sector, where there is a strong need to reduce carbon emissions and re-establish the natural carbon cycles. The concept of carbon neutrality is emerging in a scenario where it is necessary to reduce carbon dioxide (CO₂) emissions from cultivation to near zero. The quantification of carbon emissions was carried out by the carbon footprint (CF) of conventional, organic and zero residue potato cultivation in Sicily. In order to provide farmers and consumers with answers regarding the most sustainable cultivation regime, the results showed that the organic and zero residue methods have the best results in terms of emissions; the latter instead revealed the positive results in economic terms. It becomes a new model to follow in the pursuit of sustainability as it is based on the reduction of synthesis inputs and is free from the constraints imposed by organic production standards.

Technical efficiency of the food and drink industry and its determinants

This study focuses on evaluating the technical efficiency (TE) of food and drink companies in the Czech Republic and on finding its determinants. The analysis is based on the data of 597 firms and uses the stochastic frontier method. We have identified the key players in the market and the less effective groups of processors. Foreign-owned companies have a strong position because of a better economy, but the results showed that their efficiency is comparable with that of Czech-owned companies. The results helped confirm that the size of the company influences its TE. The lowest efficiency was observed in small companies. TE also differed among branches of the food industry. The highest efficiency was in the bakery and milk industries, and the lowest efficiency was in fruit and vegetable processing. Subsidised firms reached a significantly higher efficiency. With respect to economic results, there is still a need to improve competitiveness through investments.