Despite the recognition of entrepreneurship as one of the main determinants of rural economic development, empirical research in this field is relatively sparse. Thus, there is little evidence on the role and function of rural entrepreneurs, the driving force behind the birth, survival and growth of rural enterprises. The present work aims at providing a contribution to filling this gap in knowledge. We present and analyse the results emerging from a questionnaire submitted to a sample of 123 rural entrepreneurs and businesses in a mountainous area of central Italy. In particular, we test for six hypotheses concerning the correlation between different factors, reflecting entrepreneur and business-specific characteristics, and the adoption of instruments of institutional assistance. Entrepreneur's and business's variables are related to (1) entrepreneurial human capital; (2) entrepreneur's local knowledge and social capital; (3) firm's size; (4) entrepreneur's age; (5) firm's age; and (6) busines's sector of activity. Empirical results largely support the importance of variables taken into consideration in explaining differences in the adoption of institutional assistance among businesses of the sample. In the light of our empirical findings, we also examine and propose potential policies for fostering entrepreneurship and the development of the rural region under study

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The nonlinearity of macroeconomic processes is becoming an increasingly important issue at both the theoretical and empirical levels. This trend holds for labor market variables as well. The reallocation theory of unemployment relies on nonlinearities. At the same time there is mounting empirical evidence of business cycles asymmetries. Thus the assumption of linearity/nonlinearity becomes crucial for the corroboration of labor market theories. This paper turns the microscope on the assumption of linearity and investigates the presence of asymmetries in aggregate and disaggregate labor market variables.The assumption of linearity is tested using five statistical tests for U.S. and Canadian unemployment rates and growth rates of the employment sectoral shares of construction, finance, manufacturing, and trade. An AR(p) model was used to remove any linear structure from the series. Evidence of nonlinearity is found for the sectoral shares with all five statistical tests in the U.S. case but not at the aggregate level. The results for Canada are not clear-cut. Evidence of unspecified nonlinearity is found in the unemployment rate and in the sectoral shares. Overall, important asymmetries are found in disaggregated labor market variables in the univariate setting. The linearity hypothesis was also examined in a multivariate framework. Evidence is provided that important asymmetries exist and a linear VAR cannot capture the dynamics of employment reallocation.

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This paper appraises the literature on the macroeconomic effects of job reallocations. We overview different methodological approaches to the problem of observational equivalence of aggregate and sectoral shocks and draw two main conclusions. First, the non-directional nature of reallocation shocks holds the key to the fundamental identification problem. The second conclusion is that sectoral reallocation of labor has been responsible for no less that 1/4 and no more that 2/3 of the variance of aggregate unemployment in postwar data. This wide range indicates that the importance of labor reallocation may change over time, being larger at particular historical junctures.

This article revisits the sectoral shifts hypothesis by examining unemployment fluctuations for 48 U.S. states over the period 1990:M01-2011:M12. We develop a panel approach that incorporates dynamics, parameter heterogeneity, aggregate factors, and cross-sectional dependence (CSD). Our findings provide support for a positive and significant effect of the employment dispersion index on unemployment. This outcome is robust under alternative specifications and measures of employment dispersion. The empirical evidence corroborates the presence and relevance of CSD and heterogeneity among states. The results show that, once unobserved common factors and cross-state heterogeneity are taken into account, labor reallocation has a significant effect on unemployment that is half the size of the estimate when cross-sectional dependence is not taken into account. (JEL E24, E32, J21, R23, C23)

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Some recent papers dealing with Milton Friedman's methodological framework (Boland, 1979; Frazer andmland, 1983; Hoover, 1984a, b) tend to overlook or just briefly mention a fundamental aspect of his approach: Friedman's adherence to the neeBayesian interpretation of probability theory. In this note I shall try to show that Friedman's probabilistic framework has deep implications for his notion of rationality and treatment of expectations and that disregarding this feature of his analytical toolkit leads to fictitious arguments which are factually wrong and misleading.It should be made clear from the outset that this paper is not an appraisal of the neeBayesian approach nor an attempt at interpreting recent developments in economic theory in neeBayesian terms. Its aim is to introduce a methodological clarification and to pinpoint its theoretical and epistemological implications. I FRIEDMAN AS A NEO-BAYESIANIn his JEL article, Hoover (1984a) set out similarities and differences between Friedman's monetarism and new classical macroeconomics and argued that new classical economists consider only situations of risk (in a Knightian sense) as relevant to economic analysis (Lucas, 1976, 19n) whereas Friedman "implicitly defends the importance of uncertainty". But whilst this distinction between risk and uncertainty may be consistent with some objectivistic interpretations of probability, such as those of Knight and 'Manuscript received 12.7.85; final version received 17.6.87. t I would like to thank Mike Artis, Massirno De Felice, Milton Friedman, Kevin Hoover, Arjo Klamcr, Stephen LeRoy, Ipazio V h , the participants of deparrmcntal seminan at Hull and Manchester Universities and three anonymous referees for comments and insights. I am also grateful to M o m Abramovik. Simon French. David Laidler and Doug White for suggestions and cntiasm on a previous version. Any errors an my responsibility only. financial support from the Consiglio Nazionale delle Riccrche is gratefully acknowledged.This pa r has been resented at The 3rd Valencia Meeting 00 Bayesian Statistics, Altca, Spain, L t h ~u n e , Pw.407