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In this vein, it is essential to acknowledge the critical role played by SMEs on entrepreneurship, innovation, employment and economic growth.

This allocation strategy holds particular significance when the business density in European countries is integrated by small and medium-sized enterprises (SMEs) that contribute 66.5% of employment and 57.8% of the gross added value generated by the private sector (Foray et al., 2012). In Europe, a good example is the allocation of public resources on mechanisms for stabilizing the economy, kick-starting growth, and tackling systemic risks. Several authors have recognized that we currently were embroiled in uncertain times (Soros, 2008 Stiglitz, 2010). "Machine Learning: An Applied Econometric Approach.The current social and economic scenarios have generated several challenges for any organization located across the globe. We hope to make them conceptually easier to use by providing a crisper understanding of how these algorithms work, where they excel, and where they can stumble-and thus where they can be most usefully applied.

This also raises the risk that the algorithms are applied naively or their output is misinterpreted. Machine learning algorithms are now technically easy to use: you can download convenient packages in R or Python. So applying machine learning to economics requires finding relevant tasks. Specifically, machine learning revolves around the problem of prediction, while many economic applications revolve around parameter estimation. Machine learning not only provides new tools, it solves a different problem. This similarity to econometrics raises questions: How do these new empirical tools fit with what we know? As empirical economists, how can we use them? We present a way of thinking about machine learning that gives it its own place in the econometric toolbox. Face recognition algorithms use a large dataset of photos labeled as having a face or not to estimate a function that predicts the presence y of a face from pixels x. Machines are increasingly doing "intelligent" things.