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Using a database on innovation activities by Spanish firms, we perform an exploratory analysis on a frequently overlooked area of research: innovation investment decisions by small firms in rural areas where socioeconomic indicators are weak. We focus on two quite different sectors of interest there, agri-food and t-KIBS firms, to explore how the regional context influences the capacity and the nature of innovation. Following the TOE approach as a conceptual framework, we perform a multivariate statistical analysis based on MCA and PCA combined, to identify the most relevant factors among a list of 73 indicators in four broad domains, including innovation decisions as well as organizational, technological, and environmental determinants. The exploratory results obtained suggest an open field of research. Thus, we observe a distinctive behavior of marketing innovation by agri-food firms that is related to former ICT experience, whereas services innovation by t-KIBS would be related to the objective of entering new market niches. Some results confirm previous results for SMEs outside rural areas, such as financial constraints, lack of qualified personnel, and strong competition being relevant barriers to invest in R&D by t-KIBS firms. Contrariwise, we dispute the assertion that agri-food firms are primarily oriented toward product and process innovation: what comes together is product and organizational innovation. [ABSTRACT FROM AUTHOR]

The depopulation process of rural areas in Europe during the last decades is widespread. However, in many regions, this performance is largely an inheritance from past migration and the drag it causes in terms of an ageing population structure. Removing the inertial effects of past migration, we may find a much greater diversity in the current demographic dynamics of rural areas. We analyse the case of Galicia, a NUTS-2 region in Spain that represents a paradigmatic case of traditional emigration. We remove the drag from past migration to obtain the population performance of rural counties once the effects of that inertia were removed, and interpret the results. The analysis works as a descriptive tool: refined data help to identify which rural areas, however they continue to lose population, are being able to slow down or even revert the processes of depopulation inherited from the past. Finally, we explore possible explanations for such better performance, verifying that this is mainly related to key factors in regional planning and development such as the proximity to urban nodes and the quality of connections. [ABSTRACT FROM PUBLISHER]

We provide a dynamic model of banking competition, in which bounded rationality of some competitors explains how the credit cycle is intensified. We model the economic cycle following Tobias F. Rötheli (2012b), who argues that boundedly rational banks, in their Bayesian learning, overestimate the probability of success during booms and underestimate it during recessions. We obtain three main results. First, the model suggests that pessimism/underconfidence is not a powerful driver of credit cycles. Instead, it supports the conclusion that it is euphoria during large upswings that leads to the next crunch. Second, the dynamization of the model provides further insight into the way boundedly rational competition intensifies the credit cycle. Third, it additionally predicts that the effects of behavioral biases are more pervasive when the quality of the niche markets is lower. [ABSTRACT FROM PUBLISHER]