We apply a generalized structural equation model approach to the estimation of the relationship between R&D, innovation and productivity that focuses on the potentially crucial heterogeneity across sectors. The model accounts for selectivity and handles the endogeneity of this relationship in a recursive framework which allows for feedback effects from productivity to future R&D investment. Our approach enables the estimation of the different equations as one system, allowing the coefficients to differ across sectors, and also permits us to take crossequation correlation of the errors into account. Employing a panel of Swedish manufacturing and service firms observed in three consecutive Community Innovation Surveys in the period 2008-2012, our fullinformation maximum likelihood estimates show that many key channels of influence among the model's components vary meaningfully in their statistical significance and magnitude across six different sectors based on the OECD classification on technological and knowledge intensity. These results cast doubt on earlier research which does not allow for sectoral heterogeneity.

Using data from approximately 8,300, primarily small, exporting rms in Sweden observed over the business cycle period 1997-2007, we examine the relationship between innovation and nancial factors in a regression that include changes in cash holdings, cash ow and debt issues. Our nonlinear econometric approach with interaction variables between recession period, technology intensity and nance suggests that innovative rms in high-tech sectors tend to oset the eect of a negative nancial shock by exploiting internal cash resources. No corresponding link between innovation and nancial factors is found for medium and low technology exporters.

We assess the impact of the location of genuinely new ventures and spinoffs on these firms' survival, productivity and growth. The study distinguishes between four different categories of locations: metro cities, metro regions, urban areas, and rural areas. Using a unique database covering more than 23,000 new entrants between 2000 and 2004 in Sweden and observing them for 5 years, several conclusions may be drawn from our study. First, there is a substantial difference in ex-post entry performance between the manufacturing and service sectors. Second, the proposed superiority of start-ups by ex-employees depends on the performance measures and the sector. Third, knowledge and technology intensity of the industry matter for the viability of the new firms.

This paper studies firms′ capability to recombine internal and local knowledge. It measures the outcome in terms of total productivity growth. Using Swedish data on commuting time for face-to-face contacts across all 290 municipalities, we employ a time-sensitive approach for calculating localized knowledge within a municipality and and its close neighbors. Internal knowledge is captured by register data on firms' innovation intensity. The two sources of knowledge are modeled in a production function setting by discrete composite variables with different combinations of input factors. Applying the model on Swedish firm level panel data, we find strong evidence of differences in the capacity to benefit from external knowledge among persistent innovators, temporary innovators and non-innovators. The results are consistent regardless of whether innovation efforts are measured in terms of the frequency of patent applications or the level of R&D investment.

Researchers have established a relationship between greater education and training and higher earnings but it is difficult to infer that the former causes the latter if those with higher earnings tend to engage in more education and training. The present study attempts to control for ability and family background to see if stronger inferences can be made about education and training as the independent variable. The study focuses upon advanced vocational education and training (AVET) in Sweden. This is post‐secondary school education for individuals who are 20 years of age or older. The aim of this article is to estimate the effects of AVET on earnings by controlling for selection bias. We used various approaches such as instrumental variables, Hausman–Taylor estimates, fixed effects estimates and propensity score matching to achieve this aim. A panel, or longitudinal, data set for eight different labor markets in Sweden for the period 1996–2008 was used. The results indicate that earnings from AVET are higher than the return on investment in comprehensive education. The average effect on income is estimated to be in the range of 3–8 percent.