The United States' ability to compete in many international markets has been based on competitive advantage in high-technology products. Until recently, these industries had a favorable trade balance but in 1987, it slipped to deficit of $0.6 billion. Management of research and development programs is one of the most important elements in remaining competitive. Therefore, this research study of 291 high-technology firms was undertaken to determine if: (1) a positive relationship exists between the amount of investment in research and development (R&D) and a firms success in sales, net income, or market share, (2) excessive investment in R&D would decrease profitability, (3) there exists a "critical mass" of R&D spending for a firm to remain competitive. The results of this study indicates that while R&D is an important factor in high-technology industries, it is not the driving force in the success of a firm. Successful management requires a more systemic approach which considers many factors including research and development. There was no evidence found that excessive investment decreases profits and no indication that a "critical mass" of R&D was required for a high-technology firm. This study found lag times from R&D investment to the time of impact on sales, net income and market share. The lag times did not have significant correlations in most cases but appeared to be in agreement with the opinions of industry experts surveyed in field interviews. It was also found that the leading high-technology firms budget R&D by a percent of sales or prior years budget method. This approach may be very detrimental to effective management of research programs since it may reduce funding for at a time when it should be increased in order to develop new products and technologies. The results indicate that start-up firms can compete effectively with mature firms. Leading start-up companies generally spend more as a percent of sales on R&D than mature firms but appear to be as effective in managing their research effort. The results of this study has implications for stakeholders of high-technology industries in understanding some important elements in the management of successful R&D programs.

In this thesis, I apply the sophisticated tools made available by the econometrics of panel data and treatment models to a range of different issues. In the first Chapter, an ECM model is used to test on the existence of financing constraints in firms’ investment and R&D, taken a proxy for the efficiency of market institutions and governance rules in different countries. In the second chapter we test an agency model linking pay-performance contracts of CEOS to the financial situation of a firm by using a UK panel data. In the third chapter I use a sophisticated treatment model to evaluate the effectiveness of Italian public subsidies to R&D. Finally, in the fourth chapter I try to evaluate the efficiency of Italian regional systems of public healthcare by controlling for socio-economic factors and quality of healthcare in a composite model using panel data estimation and efficient frontier techniques.<p>The first Chapter analyzes the investment behavior of a sample of R&D intensive firms which are quoted on the stock market from USA, UK and Japan for the period 1990-1998. By using an error correction model we test the elasticity of investment and R&D to cash flow in these countries to see by which measure different market institutions and corporate governance rules affects the cost of external financing. Contrary to previous studies, we find significant differences in the sensitivity to cash flow of the two types of investment, with R&D expenditure being much less sensitive than ordinary investment. This is not surprising given the more long-term nature of R&D expenditures. For what concerns the comparison between the different systems/countries, the USA stock markets confirms as the most efficient market providing outside financing at a much lower cost compared to other markets, especially for young, smaller firms.<p>The second Chapter is a joint work with Biagio Speciale. It uses the data on a panel of quoted UK firms over the period 1995–2002 to study the effects of financial leverage on managerial compensation. The change in the investors’ expectations that caused the recent collapse of the stock market tech bubble is a perfect example of natural experiment that has been used as a source of plausibly exogenous variation in the firm’s debt. The estimates show that pay-for-performance sensitivity is increasing in financial leverage, with the exception of the 10% most levered firms, giving rise at the end to a non-linear (inverted U-shape) relationship between the two variables. The chapter includes also a theoretical model accounting for this relationship where an higher leverage increases both the expected returns and the expected variance of investment returns: the first effect (determining increased pay-performance sensitivity) prevails for low leverage values and the second effect (determining decreased pay-performance sensitivity) prevails for high leverage values.<p>The third Chapter undertakes an empirical estimation of the additionality of public funding on both the propensity to initiate R&D activity and the intensity of R&D spending of Italian enterprises for the period 1998-2000, using data from the Third Community Innovation Survey and from firms' financial accounts. The chosen methodology (Endogenous Switching Type II-Tobit) takes into account the possibility that decisions about both starting an R&D activity (sample selection effect) and applying for/obtaining public funding (essential heterogeneity) are influenced by private knowledge of enterprises' idiosyncratic propensities in R&D spending. The present analysis shows that both these effects are indeed important and that they contribute to explain most of the additionality found with less sophisticated models.<p>The fourth Chapter investigates the underlying causes of variability of public health expenditure per capita (SSPC henceforth) between Italian regions. A fixed-effect panel data estimate on the SSPC (for the period 1997-2006) is used in the first part of the paper to account for regional differences in terms of physical, demographic, socio-economic characteristics and in terms of other variables that affect demand and supply of health services. In the second part, we take the ‘adjusted’ SSPC and proceed to estimate an "efficient production function" of the quality of health services through Data Envelopment Analysis. This procedure allows us to separate the share of expenditure used for the improvement of the quality from the one that can be traced only to an inefficient use of financial resources. A comparison of regional SSPC after factoring out the socio-economic factors and the quality of healthcare shows that big differences still remain and are even exacerbated, signalling big pockets of inefficiency and correspondingly a huge potential for cost savings. Finally, a preliminary analysis shows a positive correlation between the efficiency of regional public spending in healthcare and the level of social capital. / Doctorat en Sciences économiques et de gestion / info:eu-repo/semantics/nonPublished