Self-employment at the Macro-LevelDrivers, Inhibitors and Fluctuations

Resumen

This thesis consists of six self-contained essays structured as follows. Chapter 2 can be considered as an introduction to the techniques used on the analysis of self-employment time series, where we analyze the business cycle dynamics in the European Union (EU28) during recent decades and analyze possible changes in cyclical linkages among countries introduced after the Great Recession based on the similarities in their cyclical features and synchronization. We apply a methodology for detecting turning points in GDP time series, then date expansions and recessions of every country, which allows us to analyze the length, depth and shape for different cycles, in addition to the synchronization. Chapter 3 explores and checks whether the self-employed sector is responding in the same way as entrepreneurship in previous economic recovery episodes by analysing the case of the UK. By using the business confidence index and the unemployment rate as indicators, we provided evidence on i) turning points dating of self-employment rate time series to establish a selfemployment cycle; ii) the characteristics of the cycle phases; iii) an analysis of the synchronization between the selfemployment cycle and the cycles of unemployment and business confidence; and iv) a nonlinear causality analysis between these sets of variables. our empirical analysis shows that self-employment rate development is not caused by labour market evolution; rather, it is now caused by the business climate, that is, confidence in the economy. Chapter 3 reports evidence of unit roots and estimates an unobserved components model for testing the existence of hysteresis in the self-employment rate in the United Kingdom. Defining hysteresis in terms of the interdependent evolution of a nonstationary natural rate and a stationary cyclical component, thereby distinguishing hysteresis from natural rate shocks, the results provide robust evidence of hysteresis in entrepreneurship. This implies that economic and/or non-economic shocks have cyclical and permanent effects on rates of entrepreneurship. Chapter 5 re-evaluates the relationship between stages of economic development and entrepreneurship, at the macro level. To circumvent problems related to model uncertainty we use Bayesian Model Averaging to evaluate the robustness of determinants of self-employment in a dataset of 117 countries, investigating the existence of heterogeneity allowing interactions between GDP, as focus variable, and a set of 20 potential entrepreneurship determinants. Our empirical analysis then shows that the variation of self-employment rates across countries are mainly determined by variations in the unemployment, the stage of economic development and the variations in labor market frictions. When interactions are taken into account, results confirm that there is a differential effect of labor market frictions in countries with different levels of income. Frictions in labor market may encourage becoming self-employed in richer countries. Chapter 6 revisits the issue on the determinants of entrepreneurship/self-employment at the macro-level focusing on the effects of the greater or lesser employment protection legislation (EPL, henceforth) stringency in conjunction with compliance/enforcement. We use time series of cross-national macro data of entrepreneurship, from a sample of 28 OECD countries and apply a Bayesian Model Averaging approach as a way to circumvent problems related to the choice of the best predictors and considering the interaction between institutions and enforcement/flexibility. We find empirical support of our main hypothesis according to which employment protection legislation can either boost or contract the self-employment rate depending on the degree of practical compliance with employment legislation. Chapter 7 provides an empirical categorization of economies in terms of productive entrepreneurship by using a compendium of cross-national data by using a panel of 120 countries during 1991-2019. Using a Bayesian approach for clustering time series, we provide evidence of the existence of three clusters of countries defined in terms of the productivity of its selfemployment sectors and the economic and institutional factors which lead the transitions between groups. These groups might be identified with three major groups of countries usually considered in the entrepreneurship literature: factor-, efficiency-, and innovation-driven countries.